Sage Journals: Discover world-class research

Abstract

Introduction

In bipolar women who took lithium during pregnancy, several epidemiology studies have reported small increases in a rare fetal cardiac defect termed Ebstein’s anomaly.

Methods

Behavioral, environmental, and lifestyle-associated risk factors associated with bipolar disorder and health insurance status were determined from an Internet search. The search was conducted from October 1, 2023, through October 14, 2023. The search terms employed included the following: bipolar, bipolar disorder, mood disorders, pregnancy, congenital heart defects, Ebstein’s anomaly, diabetes, hypertension, Medicaid, Medicaid patients, alcohol use, cigarette smoking, marijuana, cocaine, methamphetamine, narcotics, nutrition, diet, obesity, body mass index, environment, environmental exposures, poverty, socioeconomic status, divorce, unemployment, and income. No quotes, special fields, truncations, etc., were used in the searches. No filters of any kind were used in the searches.

Results

Women who remain on lithium in the United States throughout their pregnancy are likely to be experiencing mania symptoms and/or suicidal ideation refractory to other drugs. Pregnant women administered the highest doses of lithium salts would be expected to have been insufficiently responsive to lower doses. Any small increases in the retrospectively determined risk of fetal cardiac anomalies in bipolar women taking lithium salts cannot be disentangled from potential developmental effects resulting from very high rates of cigarette smoking, poor diet, alcohol abuse, ingestion of illegal drugs like cocaine or opioids, marijuana smoking, obesity, and poverty.

Conclusions

The small risks in fetal cardiac abnormalities reported in the epidemiology literature do not establish a causal association for lithium salts and Ebstein’s anomaly.

Keywords

Lithium epidemiology alternative causation confounding Ebstein's anomaly

Introduction

Mood disorders include bipolar I, bipolar II, and cyclothymia (bipolar III). Bipolar I disorder is defined by manic episodes lasting for at least 7 days. Depressive episodes lasting at least 2 weeks also occur.¹ Bipolar II disorder is defined by depressive and hypomanic episodes, with the hypomanic episodes being less severe than the manic episodes experienced in bipolar I disorder.¹ However, the depressive cycles can sometimes last longer in bipolar II disorder such that bipolar II disorder is not a milder form of bipolar I disorder but rather a separate diagnosis.² Cyclothymic disorder or cyclothymia is defined by recurring hypomanic and depressive symptoms less intensive and persistent than those seen in hypomanic or depressive episodes.¹

In 1970, the US FDA approved lithium as a treatment for mania.³ FDA approval for use as a maintenance/prophylactic treatment for manic-depressive episodes followed in 1978. It was not until 25 years later in 1995 that a second drug was approved by the FDA as a treatment for mania, that is, the anticonvulsant agent valproic acid.⁴ Lithium has a narrow therapeutic window. Following oral administration, lithium is rapidly and completely absorbed from the gastrointestinal tract where it is first found in serum and then redistributes to various tissue compartments. Lithium is not metabolized and 95% of the dose is excreted in unchanged form via the kidneys.⁵

Lithium can be prescribed to treat an acute manic episode, to prevent the recurrence of a manic episode, and paradoxically to prevent recurrence of depression given that lithium is not effective in treating a current episode of depression.⁶ In adults, the usual lithium carbonate dose for acute mania in bipolar disorder is 1800 mg/day. This dose is achieved by either administering 600 mg orally 3 times per day, or by oral dosing with 900 mg extended-release formulation 2 times per day. For prophylactic long-term control, the usual oral dose is 900–1200 mg/day either by 300–600 mg regular release 2-3 times per day, or an extended-release formulation of 600 mg orally 2 times per day.⁷ Concerns regarding the potential kidney and thyroid side effects of lithium necessitate patient screening and monitoring. After starting lithium therapy, the target plasma level is between 0.8 and 1.2 mmol/L. Some patients that cannot tolerate the 0.8 level can sometimes be maintained successfully at 0.6 mmol/L. Levels should not exceed 1.2 mmol/L due to lithium side effects.^8,9

The US FDA currently approves lithium, atypical antipsychotics, and anticonvulsants for the treatment of bipolar disorder. The FDA-approved atypical antipsychotics include Aripiprazole (Abilify), Asenapine (Saphris), Cariprazine (Vraylar), Lurasidone (Latuda), Olanzapine (Zyprexa), Olanzapine/fluoxetine combination (Symbyax), Quetiapine (Seroquel), Risperidone (Risperdal), and Ziprasidone (Geodon). The FDA-approved anticonvulsants include Carbamazepine (Carbetrol, Epitol [TEVA], Equetro, Tegretol, Teril), Lamotrigine (Lamictal), and Divalproex sodium* or valproate (Depakote).¹⁰ Table 1 lists the FDA-approved drugs for bipolar disorder, the year the drug was approved, and the indications and usage.

Table 1.

FDA-approved drugs for bipolar disorder.

Drug	Year approved	Indications and usage
Lithium	1970	Lithium is a mood-stabilizing agent indicated as monotherapy for the treatment of bipolar I disorder
		Treatment of acute manic and mixed episodes in patients 7 years and older
		Maintenance treatment in patients 7 years and older
Anti-psychotics
Aripiprazole	2004	Maintenance monotherapy treatment of bipolar I disorder in adults
Asenapine	2015	Treatment of manic or mixed episodes of bipolar I disorder in adults and children aged 10–17 years
Cariprazine	2015	Acute treatment of manic or mixed episodes associated with bipolar I disorder in adults Treatment of depressive episodes associated with bipolar I disorder (bipolar depression) in adults
Lurasidone	2013	Treatment for depressive episode associated with bipolar I disorder (bipolar depression) in adults and pediatric patients (10 to 17 years) as monotherapy; depressive episode associated with bipolar I disorder (bipolar depression) In adults as adjunctive therapy with lithium or valproate
Olanzapine	2000	Acute treatment of manic or mixed episodes associated with bipolar I disorder and maintenance treatment of bipolar I disorder
Olanzapine/fluoxetine combination	2012	Treatment for the depressive phase of bipolar disorder
Quetiapine	2004	Quetiapine is FDA approved for schizophrenia, acute manic episodes, and adjunctive treatment for major depressive disorder
Risperidone	2003	Treats bipolar I acute manic or mixed episodes as monotherapy (in adults and children aged 10 and up), bipolar I acute manic or mixed episodes adjunctive with lithium or valproate (in adults)
Ziprasidone	2004	Acute treatment of manic or mixed episodes of bipolar disorder. Maintenance (long-term) treatment of bipolar disorder (when used with lithium or valproate)
Anticonvulsants
Carbamazepine	2004	Treatment for acute mania. Provides better protection against manic than depressive relapses for carbamazepine
Lamotrigine	2003	Not effective against acute mania. Maintenance treatment of bipolar disorder
Divalproex sodium* or valproate	1995	Treatment for acute mania and mixed episodes

Only about 10% of bipolar patients in the US are prescribed lithium in contrast with prescription rates as high as 50% in some European and Scandinavian countries.¹¹ Throughout the developed world prescriptions for lithium are declining most likely due to the availability of newer drugs for the treatment of bipolar disorder.¹² Two comparative superiorities underlie the selection of lithium salts from among the other approved drugs despite its potential side effects of weight gain, kidney toxicity, thyroid dysfunction, and reported risks in pregnancy, that is, treatment of mania and suicidal ideation.

The American College of Obstetricians and Gynecologists lists lithium as contraindicated for pregnancy and lactation.¹³ The United States Food and Drug Administration categorizes lithium as having positive evidence of risk for pregnancy and possible hazardous risk for lactation.¹⁴ While lithium carbonate is reserved for pregnant women with severe symptoms of bipolar disorder, or women who do not respond to other drugs, there are several options available to the treating psychiatrist. Lamotrigine is useful for prophylaxis of mania but does not treat acute mania.¹⁵ The atypical antipsychotics aripiprazole, olanzapine, quetiapine, and risperidone can treat acute mania and are considered safe during pregnancy.¹⁶ Atypical antipsychotics including olanzapine/fluoxetine combination, quetiapine, and lurasidone are efficacious against acute bipolar depression.¹⁷

The aim of the present study is to demonstrate that pregnant bipolar patients are a unique patient population experiencing numerous co-morbidities which have reported risk factors for congenital heart defects of the same or larger magnitude than the reported risks attributed to lithium. In addition, the weight-of-the-evidence garnered from epidemiology and animal toxicology studies strongly suggests that workers in an industrial environment, employing standard methods of industrial hygiene practice, are not at increased risk from lithium exposure in the workplace.

Putative developmental toxicity of lithium

Lithium is not teratogenic in rats

In late 2021, the European Chemicals Agency’s Risk Assessment Committee (ECHA RAC) concurred with French proposals to classify lithium carbonate, lithium hydroxide and lithium chloride as Category 1A reproductive toxicants.¹⁸ To assess the potential reproductive toxicity of lithium, a two-generation reproductive toxicity study and a prenatal developmental toxicity study in rats¹⁹ was initiated by the Lithium Consortium in the context of REACH regulation. The respective results are reported in detail by Van Deun et al. (2021).¹⁹ The prenatal developmental toxicity study was conducted under OECD TG 414 guideline and employed doses by oral gavage of 10, 30, and 90 mg Li carbonate/kg body weight/day (1.9, 5.7, and 17.1 mg Li+/kg body weight/day). The 90 mg/kg body weight/day dose resulted in signs of toxicity in association with peak plasma concentrations in the toxic range, that is, >1.0 mEq lithium/L. No developmental toxicity was observed in any of the pups from treated animals up to and including doses causing the lead systemic toxic effect (kidney toxicity). The two-generation study was carried out with a lower dosage regimen due to the longer duration of dosing and based on the results (kidney toxicity) of a dose range finding study. At 5, 15, and 45 mg Li carbonate/kg body weight/day (0.95, 2.85, and 8.55 mg Li+/kg body weight/day), no adverse effects were seen in any of the fertility parameters tested, including sperm parameters such as total motility, progressive motility, morphology of testicular and cauda epididymal sperm. In addition, no findings on male reproductive organs (e.g., weight changes or effects noted at macroscopic evaluation or at histopathology) were noted. There were also no adverse effects in the females, nor in the offspring, including no findings related to sex-ratio, litter size, pup weight, nor any other parameter tested in an OECD 416 study design for reproductive toxicity. It should be noted that kidney toxicity, that is, the most sensitive lithium effect, was seen for the highest test dose.

Rodents are an appropriate animal model for examining potential developmental effects of lithium administration as many other agents, actions, and pathophysiological states have been shown to induce fetal cardiac defects. Maternal nicotine exposure induces congenital heart defects (CHDs) in the offspring of mice.²⁰ Sodium valproate induces cardiac malformations in mice.²¹ Ochratoxin A causes heart defects in hamsters.²² Bisphenol A adversely impacts fetal rat heart gene expression related to development.²³ Bis-diamine induces Tetralogy of Fallot, truncus arteriosus, abnormal myocardial architecture, and anomalies of the aortic arch. in fetal rats.²⁴ Trichloroacetic acid is a cardiac teratogen in fetal rats.²⁵ Nitrofen induces neural-crest cardiac defects in fetal rats.²⁶ Nimustine hydrochloride causes cardiovascular anomalies in fetal rats.²⁷ In fetal rats during the periconception period, arsenic induces heart abnormalities.²⁸

There are many other examples of agents, actions, or conditions that can cause fetal cardiac defects in rats and other rodents. The ability of rodent models to induce fetal cardiac defects from a wide range of exposures including chronic hypoxia,²⁹ maternal diabetes,³⁰ cocaine,³¹ nicotine,²⁰ alcohol,³² anticonvulsants,²¹ and numerous chemicals, supports the relevance of the negative fetal developmental results reported for lithium by Van Deun et al. (2021).¹⁹

Epidemiology studies reporting developmental effects

Concerns regarding the developmental toxicity of lithium date back to the early 1970s. At that time, the International Register of Lithium Babies (IRLB) evaluated infants born to bipolar mothers prescribed lithium during the first trimester.^33,34 Based on only 2 cases, the IRLB suggested a risk for Ebstein’s anomaly of 400-fold, and 5.3-fold overall risk for cardiac defects. The IRLB continued to monitor cases and by 1979 had accumulated 225 babies born to bipolar women prescribed lithium.³⁵ The IRLB final report issued in 1979 described 18 infants with CHDs (8%) and six infants with Ebstein’s anomaly (3%).³⁶

Following the initially alarming IRLB report, a series of epidemiology studies and an influential meta-analysis conducted by Fornaro et al. (2020)⁵⁹ were conducted that reported much lower risks for Ebstein’s anomaly in infants born to women taking lithium in pregnancy.^35,37–60 The ECHA RAC considers the Patorno et al. (2017) study to be the most relevant study toward evaluating the risk of lithium administration to pregnant bipolar women.³⁵ Patorno et al. (2017) is a retrospective analysis of 1,325,563 pregnancies in women who were enrolled in Medicaid and who delivered a live-born infant between 2000 and 2010.³⁵ The primary endpoint was the risk of cardiac malformations among infants exposed to lithium during the first trimester as compared with unexposed infants. The secondary analysis compared infants exposed to lithium with infants exposed to the commonly prescribed mood stabilizer lamotrigine.

Lithium and Ebstein’s anomaly

The tricuspid valve is also known as the right atrioventricular valve. It is located on the right side of the heart between the right atrium and the right ventricle. The tricuspid valve directs blood from the right atrium to the right ventricle and prevents blood from flowing backwards between those two chambers. After the right atrium fills, the tricuspid valve opens, and lets blood flow into the right ventricle. Next, the right ventricle contracts to send blood to the lungs. The tricuspid valve closes tightly thereby preventing blood from flowing backwards into the right atrium.⁶¹

The tricuspid valve is constructed from three thin strong flaps of tissue called leaflets or cusps. The valve is positioned vertically. The leaflets are named via their orientation, i.e., anterior, posterior, and septal. Thin, strong cords called chordae tendineae connect the leaflets to the papillary muscles of the ventricle. The microanatomy of the leaflets consists of a layered microstructure comprising a hierarchical arrangement of collagen, elastin, proteoglycans, and various cell types.⁶²

Ebstein’s anomaly is a complex, congenital heart defect. The tricuspid valve and right side of the heart are malformed. Several other cardiac abnormalities can be found in association with Ebstein’s anomaly including atrial septal defect (hole in the wall separating the atria), conduction system abnormalities, patent foramen ovale (small hole between the atria), pulmonary stenosis (narrowing of the valve between the right ventricle and the pulmonary arteries), and ventricular septal defect (hole in the wall separating the ventricles). The severity of the abnormalities determines the treatment plan for a patient with Ebstein’s anomaly. Less severe tricuspid damage can be surgically repaired, with more severe damage requiring valve replacement. Any associated cardiac abnormalities are also repaired.⁶³ Ebstein’s anomaly is extremely rare presenting at a rate of approximately 1 case per 200,000 live births and representing less than 1% of CHDs.⁶⁴

Risk factors in medicaid beneficiaries and patients

Medicaid is a joint federal and state program. Federal law requires states to cover certain mandatory eligibility groups including low-income families, qualified pregnant women, qualified children, and individuals receiving Supplemental Security Income (SSI). [SSI is a federal program that provides monthly payments to the disabled or to older adults with little or no income.] Individual states can expand coverage to other groups such as those receiving home and community-based services, and certain children in foster care.⁶⁵

In 2023, TheraThink Mental Health Insurance Billing Service rated the reimbursement rates for psychiatrists by insurance type (Commercial, Medicare [federal medical insurance for the elderly], and Medicaid), psychiatric Current Procedural Technology (CPT) code rendered, and by each insurance company’s rate.⁶⁶ Medicaid was ranked in the lowest paying tier. In 2023, Medicaid paid psychiatrists at 81.0% of Medicare rates. The median percentage was even lower at 76%.⁶⁷ Medicaid does not allow patients to be billed for missed appointments (Texas Medical Association 2020) in contrast with privately insured patients.⁶⁸ The inadmissibility of billing for missed appointments is exacerbated by a higher-than-average number of missed visits, that is, “no shows,” seen in Medicaid populations.^69–71 Due to low reimbursement rates, many psychiatrists do not accept Medicaid patients with only 35% accepting Medicaid insurance in 2015.⁷²

Chapel et al. (2017) reviewed the prevalence of chronic diseases in adults covered by Medicaid.⁷³ Using nationally representative data on beneficiaries aged 18–64 years, 55.7%–62.1% had at least one chronic condition.^74–76 For all adults nationally, the percentage having at least one chronic condition is 50%, but the 50% number would be significantly lower if it did not include the greater than 17% of the US population 65 years and older (Statista Research Department 2023) who have much higher rates of chronic disease.^77–79 Medicaid covers some disabled persons, who on average have even worse health than the general low-income Medicaid population.^80,81 While inclusion of disabled Medicaid patients makes some contribution to the 55.7–62.1 percentage, the much more significant contribution is provided by poorer health in the overall Medicaid population as compared with persons at similar low-income levels not on Medicaid.^75,76 Medicaid beneficiaries have relatively high rates of cardiovascular disease and atherosclerotic manifestations,^75,82,83 hypertension,^{75,76,83–85} hyperlipidemia, and diabetes.^86–89

The high prevalence of chronic diseases in Medicaid patients is consistent with a high prevalence of lifestyle and behavior-related risk factors for chronic diseases. A higher percentage of Medicaid beneficiaries smoke cigarettes than privately insured individuals (25.3% vs 11.8%).⁹⁰ In a study on 328,578 patients who underwent surgery in Michigan, 43% of patients covered by Medicaid smoked as compared with 22.3% in the overall patient sample. After adjusting for clinical and demographic factors, the odds ratio for increased smoking in Medicaid patients as compared with privately insured patients was 2.75 (95% Confidence Interval 2.69–2.82).⁹¹ Obesity is more common among Medicaid beneficiaries. Mylona et al. (2020) studied 74,089 adults (18–65 years old) who visited a statewide health network in Rhode Island during 2017.⁹² The overall prevalence of obesity within the Rhode Island cohort was 38.88% with the prevalence of obesity varying significantly by ethnicity – 16.77% in Asians, 37.49% in whites, 44.23% in Hispanics, and 48.44% in Blacks. Medicaid beneficiaries were 27% more likely to have obesity than privately insured patients (Odds Ratio:1.27, 95% Confidence Interval 1.22–1.32). Medicaid beneficiaries with obesity had a higher prevalence of diabetes compared with the privately insured with obesity (10.58% vs 4.45%).⁹²

Marijuana use is more common among young Medicaid beneficiaries aged 25–34.⁹³ Opioid use is much higher in Medicaid beneficiaries than in the privately insured. Sullivan et al. (2016) studied 273,200 adults in the State of Washington covered by Medicaid who had a paid claim for an opioid prescription between April 1, 2006, and December 31, 2010.⁹⁴ Medicaid patients showed 6 times the number of fatal opioid overdoses as privately insured patients. In a study on 6,454,775 weighted hospitalizations with Cocaine Use Disorders in the United States from 1998 to 2014, Medicaid patients were disproportionately overrepresented.⁹⁵ Alcohol abuse is more common among Medicaid beneficiaries than among the privately insured. Suen et al. (2022) conducted a retrospective analysis of the National Hospital Ambulatory Medical Care Survey covering the period 2014-2018.⁹⁶ These authors reported that 9.3 million emergency room visits (9.4% of the total) were related to alcohol or drug abuse. Similarly, 1.4 million hospitalizations (11.9% of total admissions) were related to alcohol or drug abuse. Medicaid patients were overrepresented accounting for 33.1% of the alcohol abuse and 35% of the substance abuse emergency room visits.

In summary, Medicaid patients suffer from overall poor health with high rates of obesity, diabetes, hypertension, and cardiovascular disease. Medicaid patients smoke cigarettes and drink alcohol at elevated rates as compared with the general population. In addition, Medicaid patients smoke marijuana, take opioids, and ingest cocaine at comparatively higher rates. The net result is that Medicaid patients are not comparable to the general population. In a retrospective epidemiology study, adjustment for the large number of potential confounders extant in Medicaid populations is required to establish the risk of a therapeutic agent. Given the potential for a pregnant woman on Medicaid to underreport cigarette, alcohol, and drug use, identifying the relevant potential confounders would be highly problematic. A further complication is introduced by women on Medicaid suffering from high rates of depression with The Centers for Medicare & Medicaid Services’ Chronic Condition data reporting a prevalence rate of 22.6%.⁹⁷

Risk factors in bipolar patients

Chronic disease risk factors seen at elevated rates in bipolar patients overlap strongly with risk factors found at elevated rates in Medicaid beneficiaries but at even higher prevalence rates. Approximately 60%–70% of bipolar patients smoke tobacco as compared with 25%–30% in the general population.^98–100 The co-morbidity of alcohol use disorder and bipolar disorder is reportedly 45%,^101,102 and the odds ratio for alcohol use disorder in bipolar I disorder is higher than for bipolar II disorder (odds ratios of 3.5 and 2.6, respectively).¹⁰³ The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) (wave III, 2012–2013) reported rates and odds ratios for 12 months and lifetime prevalence of specific substance user disorders (SUD). The substances studied included amphetamine, cannabis, club drug, cocaine, hallucinogens, heroin, non-heroin opioids, sedatives or tranquilizers, and solvent or inhalant use disorders.¹⁰⁴ The total sample size was n = 36,309. Prevalence rates of 12-months and lifetime SUD were 3.9% and 9.9%, respectively. Bipolar I disorder individuals had a significantly increased 12-month SUD odds ratio of 1.5 (95% CI, 1.06–2.05) and lifetime SUD odds ratio of 1.4 (95% CI, 1.14–1.74). Bipolar disorder patients are at increased risk for developing eating disorders or disordered eating symptoms compared to the general population. The eating pathologies commonly associated with bipolar disorder are bingeing and/or purging symptomatology.¹⁰⁵ Higher divorce rates are consistently reported in association with bipolar disorder.¹⁰⁶ Bipolar disorder is associated with high rates of unemployment and job instability. The National Depressive and Manic-Depressive Association reported that approximately 60% of individuals with bipolar disorder are unemployed, including patients with college degrees. In addition, 88% of survey respondents with a bipolar diagnosis reported occupational difficulties.¹⁰⁷ Another large registry of patients with bipolar disorder reported a similar unemployment rate of about 60%.¹⁰⁸ A US national sample of respondents self-reporting a diagnosis of bipolar disorder reported a 40% reduction in paid employment.¹⁰⁹ Bipolar disorder (BD) is associated with obesity, being clinically overweight, and with abdominal obesity.¹¹⁰

Risk factors for congenital heart defects

The elevations in co-morbidities and lifestyle and behavior-related risk factors found in Medicaid beneficiaries and patients, and at even higher prevalence rates in bipolar patients, are also associated with an increased risk for CHDs (Table 2). In the United States, only 45% of mothers are within the normal weight range when becoming pregnant.¹¹¹ Obesity is an established risk factor for CHDs.^112–117 Maternal obesity and impaired glucose metabolism are clearly associated with an increased risk for CHDs. How obesity and altered glucose metabolism affect cardiac development is not well understood.¹¹⁸

Table 2.

Congenital heart defects risk factors in pregnant bipolar patients compared with lithium risk ratios from Paterno et al. (2017).³⁵

Paterno et al. 2017 16 CHD cases	≤600 mg/ 1.11 (95%CI 0.46-2.64)	601-900 mg/d 1.60 (95%CI 0.67-3.80)
Maternal risk factor	Study	Risk level
Cigarette smoking	Ng et al. 2014⁹⁸	60%–70% of bipolar patients smoke tobacco; 25%–30%
	Heffner et al. 2011⁹⁹	In the general population
	Lasser et al. 2000¹⁰⁰	Risk for septal defects
	Lee and lupo (2013)¹²¹	1.44 (1.16-1.79)^a
	Sullivan et al. 2015¹⁴⁰	“Maternal smoking was most strongly associated with pulmonary valve anomalies (aOR 1.48 [95% CI: 1.15-1.90]), pulmonary artery anomalies (aOR 1.71 [1.40-2.09]), and isolated atrial septal defects (aOR 1.22 [1.08-1.38]).”
Obesity	Waller et al. 2007¹¹⁷	OR 1.40 (1.24-1.59)
	Watkins et al. 2003¹¹²	OR 2.0 (1.2-3.4)
	Moore et al. 2000¹¹³	Prevalence went from 0.08 controls to 0.16 in obesity
	Mills et al. 2010¹¹⁴	OR 1.15 (1.07-1.23); p < .0001
	Madsen et al. 2013¹¹⁵	“Infants with CHD were more likely to have an obese mother (OR 1.22, 95% CI 1.15-1.30). The strength of association increased with increasing BMI (BMI 30-34.9: OR 1.16, 95% CI 1.07-1.25; BMI 35-39.9: OR 1.25, 95% CI 1.13-1.39; BMI > = 40: OR 1.49, 95% CI 1.32-1.69). The association was greatest for left and right ventricular outflow tract defects (OR 1.27, 95% CI 1.02-1.59 and OR 1.43, 95% CI 1.20-1.69, respectively). Hypoplastic left heart syndrome was markedly associated (OR 1.86, 95% CI 1.13-3.05).”
	Cedergren and Kallen 2003¹¹⁶	aOR = 1.23 (1.05 to 1.44) only ventricular septal defects and atrial septal defects reached statistical significance
Alcohol	Harvey et al. 2022¹¹⁹	45% of bipolar patients drink alcohol
		Overall risk (RR 1.33-1.84)
		Conotruncal defects (RR 1.62-2.11)
		Endocardial cushion defects (RR 2.71-3.59)
Opioids	Ramphul et al. 2020¹²²	OR ⁓ 3
	Interrante et al. 2017¹²³	aOR 1.8–2.3
	Sahramian et al. 2013¹²⁴	225 children with CHDs, 23.5% had parents addicted to opium as compared with 2.3% in control subjects
	Broussard et al. 2011¹²⁵	Conoventricular septal defects OR 2.7 (1.1-6.3) atrioventricular septal defects OR 2.0 (1.2-3.6) hypoplastic left heart syndrome OR 2.4 (1.4-4.1)
Cocaine	Lipshultz et al. 1991¹²⁷	RR 3.7 (1.4-9.4)
Marijuana	Williams et al. 2004¹²⁸	“A two-fold increase in risk of isolated simple ventricular-septal defects was identified for maternal self- and paternal proxy-reported cannabis use.”
Ecstasy	McElhatton et al. 1999¹²⁹	“Prospective follow-up of 136 babies exposed to ecstasy in utero indicated that the drug may be associated with a significantly increased risk of congenital defects (15·4% [95% CI 8·2–25·4]). Cardiovascular anomalies (26 per 1000 livebirths [3·0–9·0]) and musculoskeletal anomalies (38 per 1000 [8·0–109·0]) were predominant.”
Social deprivation	Peyvandi et al. 2020¹³⁰	OR 1.31 (1.21-1.41)
	Miao et al. 2021¹³¹	Rate ratio 1.20 (1.15-1.24)
	Zhang et al. (2022)¹³³	“…A higher household annual income (100,000-400,000 CNY: 0.47, 95% CI: 0.34-0.63; >400,000 CNY: 0.23, 95% CI: 0.15-0.36), higher maternal education level (13-16 years: 0.68, 95% CI: 0.50-0.93; ≥17 years: 0.87, 95% CI: 0.55-1.37), maternal folic acid (0.21, 95% CI: 0.16-0.27), and multivitamin supplementation (0.33, 95% CI: 0.26-0.42) were protective factors.”
Environmental exposures	Peyvandi et al. 2020¹³⁰	OR 1.23 (1.15-1.31)
Environmental exposures	Zhang et al. (2022)¹³³	Environmental pollution OR 1.61 (1.18-2.20)
Poor diet	Luo et al. 2022¹³⁴	“…Mothers reporting excessive intake of smoked foods (aOR = 2.44, 95%CI: 1.89-3.13), barbecued foods (aOR = 1.86, 95%CI: 1.39-2.48), fried foods (aOR = 1.93, 95%CI: 1.51-2.46), and pickled vegetables (aOR = 2.50, 95%CI: 1.92-3.25) were at a significantly higher risk of ventricular septal defects (VSD) in offspring, instead, mothers reporting regular intake of fresh fruits (aOR = 0.47, 95%CI: 0.36-0.62), fish and shrimp (aOR = 0.35, 95%CI: 0.28-0.44), fresh eggs, (aOR = 0.56, 95%CI: 0.45-0.71), beans (aOR = 0.68, 95%CI: 0.56-0.83), and milk products (aOR = 0.67, 95%CI: 0.56-0.80) were at a lower risk of VSD in offspring
	Yang et al. 2022¹³⁵	“Dietary quality was assessed by the Global Diet Quality Score (GDQS) and Mediterranean Diet Score (MDS). Logistic regression models were adopted to evaluate the associations of dietary quality scores with CHD. Pregnant women with higher scores of GDQS and MDS were at a lower risk of fetal CHD, and the adjusted ORs comparing the extreme quartiles were 0.26 (95%CI: 0.16–0.42; Ptrend < 0.001) and 0.53 (95%CI: 0.34–0.83; Ptrend = 0.007), respectively.”
	Botto et al. 2016¹³⁶	“For diet quality index of pregnancy, estimated risks reductions (Q4 vs. Q1) for conotruncal defects were 37% for tetralogy of fallot (OR 0.63, 95% CI 0.49 to 0.80) and 24% overall (OR 0.76, 95% CI 0.64 to 0.91); and for septal defects, 23% for atrial septal defects (OR 0.77, 95% CI 0.63 to 0.94) and 14% overall (OR 0.86, 95% CI 0.75 to 1.00).”
	Cao et al. 2021¹³⁷	“Compared with the control group, levels of triglyceride, apolipoprotein-A1, and apolipoprotein-B in early pregnancy were significantly higher in the CHD group. Multivariate analyses showed that triglyceride (odds ratio [OR] 2.46, 95% CI 1.62-3.73, p < .01), total/high-density lipoprotein cholesterol (OR 2.10, 95% CI 1.07-4.13, p = .03), and apolipoprotein-A1 (OR 2.73, 95% CI 1.16-6.40, p = .02) were positively associated with CHD risk in offspring.”

^aValues in parentheses are 95% Confidence Intervals.

OR – Odds Ratio.

aOR – Adjusted Odds Ratio.

RR – Relative Risk.

In a large California-based study, alcohol‐related diagnostic codes in pregnancy were associated with an increased risk of CHDs, most notably endocardial cushion and conotruncal defects.¹¹⁹ This was a retrospective analysis of hospital discharge records from the California Office of Statewide Health Planning and Development and linked birth certificate records restricted to singleton, live‐born infants from 2005 to 2017. Of the 5,820,961 births included, 16,953 had an alcohol‐related International Classification of Diseases, Ninth and Tenth Revisions (ICD‐9; ICD‐10) code during pregnancy. The maternal alcohol-related code was associated with an overall risk for CHDs (relative risk 1.33–1.84), conotruncal defects (relative risk 1.62–2.11), and endocardial cushion defects (relative risk 2.71–3.59).

Some studies have reported associations between cigarette smoking and increases in CHDs. Malik et al. (2008) reported that maternal smoking during pregnancy was associated with septal and right-sided obstructive defects.¹²⁰ Lee and Lupo (2013) conducted a meta-analysis based on 18,282 congenital heart defect cases and reported an overall relative risk of 1.11 (CI 1.02–1.21) for smoking during pregnancy and the risk of CHDs.¹²¹ Based on 2977 congenital heart defect cases, the relative risk for septal defects was 1.44 (95 % CI 1.16–1.79). Sullivan et al. (2015) reported that maternal smoking was associated with pulmonary valve anomalies (adjusted OR 1.48 [95% CI 1.15–1.90]), pulmonary artery anomalies (adjusted OR 1.71 [95% CI 1.40–2.09]), and isolated atrial septal defects (adjusted OR 1.22 [95% CI 1.08–1.38]).⁹⁴

Several studies have reported significant increases in CHDs in infants associated with opioid use in pregnancy. Ramphul et al. (2020) reported odds ratios of approximately 3 for prenatal opioid exposure and CHDs.¹²² Prenatal opioids were associated with tetralogy of Fallot, peri-membranous ventricular septal defect, and ventricular septal defect with atrial septal defect (adjusted OR 1.8–2.3).¹²³ In an Iranian cohort of 225 children with CHDs, 23.5% had parents addicted to opium as compared with only 2.3% in the control group. This difference was statistically significant, with the most common presentation being ventricular septal defect.¹²⁴ Broussard et al. (2011) examined the potential teratogenic effect of maternal opioid treatment from 1 month before pregnancy to the end of the first trimester.¹²⁵ Self-reported therapeutic use was reported by 2.6% of 17,449 case mothers and 2.0% of 6701 control mothers. Prescription opioid use was associated with several CHDs including conoventricular septal defects (OR 2.7 [95% CI 1.1–6.3]), atrioventricular septal defects (OR 2.0 [95% CI 1.2–3.6]), and hypoplastic left heart syndrome (OR 2.4 [95% CI 1.4–4.1]).

The association between birth defects and prenatal illicit drug use was examined in a Hawaiian population-based pregnancy outcome registry.¹²⁶ The cases included all infants and fetuses presenting with any of 54 selected birth defects delivered during 1986–2002. Compared to prenatal use rates among all deliveries, prenatal methamphetamine, cocaine, or marijuana use rates were calculated for each birth defect. Among normal deliveries, the prenatal use rate for methamphetamine was 0.52%, for cocaine 0.18%, and for marijuana 0.26%. There were 14 birth defects among methamphetamine users accounting for 26% of the total birth defects in the cohort. Thirteen birth defects were seen among cocaine users accounting for 24% of the total birth defects. Twenty-one birth defects were found in marijuana users accounting for 39% of the birth defects. The birth defects reported in methamphetamine, cocaine, and marijuana users affected the central nervous system, cardiovascular system, oral clefts, and limbs. Cocaine use in pregnancy has been associated with increased risks of CHDs. Animal models demonstrate adverse effects of cocaine on the developing heart.³¹ Lipshultz et al. (1991) reported a relative risk of 3.7 (95% CI 1.4-9.4) for cardiac anomalies in cocaine-positive infants.¹²⁷ There were 65 cardiac anomalies out of 100 live births in cocaine-positive infants. In infants not positive for cocaine, there were 18 cardiac anomalies out of 1000 live births. For self-reported maternal and paternal cannabis use, a two-fold increase in risk of isolated simple ventricular-septal defects was reported.¹²⁸ McElhatton et al. (1999) conducted a prospective follow-up of 136 babies exposed in utero to the recreational drug ecstasy.¹²⁹ Use of the drug was associated with an increased risk of all congenital defects (15.4% [95% CI 8.2–25.4]) with the risk of cardiovascular anomalies reported as 26 per 1000 livebirths.

In a large California-based study on 7698 infants with CHDs and 2,411,953 infant controls, social deprivation, and exposure to environmental pollutants were associated with CHDs.¹³⁰ The study considered infants born in California from 2007 to 2012. A social deprivation index and an environmental exposure index were constructed with quartiles. Quartile 1 was assigned to the most favorable group of infants, and quartile 4 was the least favorable. The overall incidence of CHDs in the entire cohort was 3.2 per 1000 live births. CHD was significantly more common in quartile 4 as compared with quartile 1. The social deprivation index was 0.35% versus 0.29%, OR 1.31 (95% CI 1.21–1.41). The environmental exposure index was 0.35% versus 0.29%, OR 1.23 (95% CI 1.15–1.31) after adjusting for maternal race, ethnicity, and age. In Ontario Canada, lower maternal neighborhood household income, poverty, lower educational level, and unemployment status had positive associations with CHDs.¹³¹ Children born in low socioeconomic areas of Ontario represented 23% of all births and had significantly higher rates of CHDs (rate ratio 1.20 [95 CI 1.15-1.24]). Agha et al. (2011) reported that free and universal access to healthcare does not eliminate the socioeconomic gap observed in the prevalence of CHD in Ontario.¹³² A similar association between low SES and CHD has been reported by Zhang et al. (2022).¹³³ They studied 44,578 subjects and found higher household income and higher maternal education level to be protective against CHD. In addition, several studies have reported that maternal diets high in saturated fats, pyrolysis products, and preservatives, and low in fiber, minerals, and vitamins are associated with an increased risk for CHD.^134–137

Differences among the low, medium, and high-dose groups in Patorno et al. (2017)

The proposal by the ECHA RAC to classify lithium carbonate, lithium hydroxide and lithium chloride, as Category 1A reproductive toxicants¹⁸ is heavily dependent upon the results of Patorno et al. (2017).³⁵ This large study was a retrospective analysis of 1,325,563 pregnancies in women who were enrolled in Medicaid and who delivered a live-born infant between 2000 and 2010. Lithium exposure in the first trimester occurred in 663 of the 1,325,563 pregnancies, that is, 0.05% of the total pregnancies. There were 16 cases of cardiac malformations reported in the 663 lithium-exposed pregnancies. Of the 16 total cases, the authors do not describe the distribution of cases among the three dose groups. However, the number of lithium-exposed pregnancies are given as 305 for ≤600 mgs per day, 235 for 601–900 mgs per day, and 123 for >900 mgs per day. The reported risk ratios were 1.11 (95% CI, 0.46- 2.64) for a daily dose of 600 mg or less, 1.60 (95% CI, 0.67–3.80) for 601 to 900 mg, and 3.22 (95% CI, 1.47–7.02) for more than 900 mg. An increased risk of lithium exposure was only seen in the >900 mg per day highest dose group. The distribution of cases suggests that there were less than 10 CHD cases in the statistically significant highest-dose group. From this result, the authors conclude that there is an increased risk for cardiac malformations in women exposed to lithium in the first trimester and a dose-response.

In Table S6 in the Supplement to Patorno et al. (2017), several important differences among the 3 dose levels of lithium carbonate confound the conclusion of a positive association between first trimester lithium exposure and cardiac malformations.³⁵ First, there is an increasing percentage of bipolar disorder diagnosis from the lowest to highest lithium dose groups, that is, 61.6%, 66.8%, and 74%, respectively. Concomitant with the increase in bipolar disorder diagnosis, is an increase in use of anti-psychotics in conjunction with lithium administration, that is, 41.3%, 46.8%, 58.5%. These data strongly suggest that the highest lithium dose group suffers from a higher degree of psychosis than the lower lithium dose groups. Since the therapeutic dose of lithium is close to the systemic toxic dose,^8,9 pregnant women on the >900 mg/day dose can be assumed to have not responded sufficiently at lower lithium doses as the psychiatrist would prescribe the lowest effective dose. The refractoriness of the highest lithium dose group is consistent with that group also being prescribed atypical antipsychotics to achieve symptomatic relief. Coadministration of >900 mg/day lithium carbonate and atypical antipsychotics indicates that the high lithium dose group is struggling with episodes of mania.

The risk factors seen in bipolar disorder that are also risk factors for CHDs are more pronounced in patients with more severe disease as manic episodes are associated with an enhanced sense of well-being, frenzied activity, and risk-taking behaviors.⁶ Patients receiving the highest dose levels of lithium carbonate are also expected to have the highest exposures to nicotine and carbon monoxide, alcohol, poor diet, a panoply of illegal narcotics, and socioeconomic stressors. Patorno et al. (2017) note the possibility of undetected confounding in their Table S2 (supplement) and in the main text as follows;³⁵

“First, although the availability of detailed maternal information through the MAX data set and our propensity-score adjustment allowed for control for a large number of confounders, we cannot rule out the possibility of residual confounding by characteristics that are not captured or are incompletely captured in our database. For example, suggested risk factors for cardiac malformations, such as obesity, smoking, or alcohol use disorders, appeared to be under recorded in our data and to be more prevalent among women exposed to lithium”.

The original concern that led to the establishment of the IRLB has now been widened by some more recent publications considering alternative causation for Ebstein- or other heart malformations independent of Li exposure. Boyle et al,⁴⁸ for example, investigated a European cohort (EURECAT) of 5.6 million births. In the introduction to their study, they write “An association between Ebstein’s anomaly and maternal lithium exposure was first reported in the 1970s and led to recommendations that are still in place today to switch to other antipsychotics during pregnancy where possible, but this association has been disputed in more recent literature. Associations have also been found with other exposures, including benzodiazepines, antihypertensives, valproic acid, marijuana, and organic solvents. A previous study of congenital anomalies associated with selective serotonin reuptake inhibitors use, using some of the same data, found an association with Ebstein’s anomaly.” The putative association of bipolar disorder with other (i.e., non-lithium) anti-psychotic drugs further questions whether the increased risk for CHD in bipolar disorder may be a consequence of the behavioral aspects associated with a bipolar disease condition – irrespective of the treatment regimen.

A small prospective study of an Israeli cohort (Diav-Citrin, 2014)⁵⁵ reports Odds Ratios for cardiovascular anomalies in association with the independent variable “Lithium exposed” and “Bipolar disorder” (the latter referring to diagnosis of disease irrespective of treatment). The Odds Ratios for CHD are 4.75 and 5.43, respectively. The Odds Ratio associated with “Lithium” (4.75) reaches statistical significance (p = .04) and is reported in the text of the paper. The higher Odds Ratio for “Bipolar Disorder” (5.43) does not reach statistical significance due to the wide 95% CI and a p-value of 0.06 and is consequently not reported in the text. The Odds Ratios are sufficiently close that they at least suggest an equal risk of CHD for a baby born to a lithium-treated versus a non-lithium-treated bipolar patient. In conclusion, the diagnosis of “Bipolar Disorder” itself being a risk factor for CHD is supported by these findings.

Exposure to therapeutic lithium carbonate is not comparable to industrial handling of lithium products

In industrial settings, process control engineers and industrial hygienists employ state-of-the-art technology to ensure that workers who handle lithium salts, and products containing lithium salts, are not exposed to dusts generated by handling lithium carbonate or lithium hydroxide. In addition to employing processes that minimize dust production and ventilate or filter dust away from the work area, appropriate personal protective equipment (PPE) is used whenever needed. PPE can include a hardhat, earplugs, safety glasses, gloves, steel-toed shoes, fire-retardant clothing, coveralls constructed of 3M™ Tyvek, Gentex (powered air-purifying respirator) PAPR with Acid Gas/high-efficiency particulate air (HEPA) cartridges or 3M™ filtering facepiece 8271 N-95 (personal communication with Kenneth Pirozzi, Corporate Industrial Hygienist). The therapeutic ingestion of 600–900 mgs of lithium carbonate per day is in no way comparable to an industrial environment in which the goal is no worker exposure to lithium salts. Therefore, the use of clinical pharmacology data to set hazard standards for industrial handling of lithium salts and products containing lithium salts is inappropriate.

Conclusions

Given the medical, financial, and logistical challenges associated with prescribing and monitoring lithium carbonate administered to a pregnant Medicaid patient, this population is almost certainly comprised of the most severe subset of bipolar patients who had not responded to other medications previously. The risk of substance abuse increases with disease severity as patients suffering from mood disorders struggle with poor impulse control, and manic episodes increase the perception of energy and decrease the perception of risk. Pregnant bipolar patients are a unique patient population experiencing numerous co-morbidities which have reported risk factors for CHDs of the same or larger magnitude than the reported risks attributed to lithium. Accurate self-reports of activities strongly contraindicated in pregnancy including degree of cigarette smoking, daily alcohol consumption, and illicit drug use cannot be obtained. Retrospective epidemiology studies cannot adequately disentangle any potential effect of lithium on CHDs from the large number of coincident risk factors for CHDs found in bipolar patient populations. The extremely large number of live births required to detect CHDs in lithium-exposed infants renders prospective epidemiology study designs attempting to better control for confounders logistically unfeasible.

It is not surprising that retrospective epidemiology studies attempting to estimate the strength of an association between first-trimester exposure to lithium carbonate would report very small increases in the risk of CHDs caused by comorbidities commonly experienced by bipolar patients. The biomedical literature is replete with examples of “indication bias” wherein administration of a therapy or therapeutic can appear to be associated with an outcome, but the outcome is in fact caused by the condition for which the patient is being treated.¹³⁸ Similarly, epidemiology studies can suffer from Berkson’s bias wherein cases missing disproportionately from either the active treatment group or the control group can adversely alter the statistical analysis and thus the conclusions of the study.¹³⁹

The weight-of-the-evidence strongly suggests that workers in an industrial environment, employing standard methods of industrial hygiene practice, are not at increased risk from lithium exposure in the workplace. Classification of lithium as a reproductive toxicant will not improve worker safety but will unnecessarily burden the recycling of products containing lithium, along with the transport, storage, and handling of these materials.

Footnotes

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Carr J. Smith, Ph.D., DABT is employed by Albemarle Corporation, a manufacturer of lithium.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Albemarle Corporation. Victoria M. Payne, M.D., M.S., was compensated for consulting services to Albemarle Corporation regarding the pharmacological treatment and management challenges inherent in care for pregnant bipolar patients.

Orcid iD

Carr J. Smith

References

NIMH . Bipolar disorder, https://www.nimh.nih.gov/health/topics/bipolar-disorder (2023).

Clinic

. Bipolar disorder, 2022, https://www.mayoclinic.org/diseases-conditions/bipolar-disorder/symptoms-causes/syc-20355955.

Shen

. Clinical psychopharmacology in the twenty-first century. Taipei, Taiwan: Hochi Publishing Company, 2004.

López-Muñoz

Shen

D'Ocon

, et al. A history of the pharmacological treatment of bipolar disorder. Int J Mol Sci 2018; 19: 20180723. DOI: 10.3390/ijms19072143.

Wen

Sawmiller

Wheeldon

, et al. A review for lithium: pharmacokinetics, drug design, and toxicity. CNS Neurol Disord: Drug Targets 2019; 18: 769–778. DOI: 10.2174/1871527318666191114095249.

Brown

. Manic-depressive illness, A brief history. Lithium A doctor, a drug, and a breakthrough. New York: Liveright Publishing Corporation, 2019, p. 25.

Drugs.com . Lithium dosage, https://www.drugs.com/dosage/lithium.html 2023.

Jefferson

. A clinician's guide to monitoring kidney function in lithium-treated patients. J Clin Psychiatry 2010; 71: 1153–1157. DOI: 10.4088/JCP.09m05917yel.

Mammen

Wilting

, et al. The International Society for Bipolar Disorders (ISBD) consensus guidelines for the safety monitoring of bipolar disorder treatments. Bipolar Disord 2009; 11: 559–595. DOI: 10.1111/j.1399-5618.2009.00737.x.

10.

Butler

MUS

Desai

, et al. Treatment for bipolar disorder in adults: a systematic review [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2018.

11.

Young

Hammond

. Lithium in mood disorders: increasing evidence base, declining use? Br J Psychiatry 2007; 191: 474–476. DOI: 10.1192/bjp.bp.107.043133.

12.

Hidalgo-Mazzei

Mantingh

Pérez de Mendiola

, et al. Clinicians’ preferences and attitudes towards the use of lithium in the maintenance treatment of bipolar disorders around the world: a survey from the ISBD Lithium task force. Int J Behav Dev 2023; 11: 20. DOI: 10.1186/s40345-023-00301-y.

13.

Armstrong

. ACOG guidelines on psychiatric medication use during pregnancy and lactation. Am Fam Physician 2008; 78: 772–778.

14.

USFDA . Highlights of presecribing information for lithium and lithium carbonate, 2018, https://www.accessdata.fda.gov/drugsatfda_docs/label/2018/017812s033,018421s032,018558s027lbl.pdf (accessed 27 January 2022).

15.

Aiken

Newsome

. Four myths about lamotrigine, 2021, https://www.psychiatrictimes.com/view/four-myths-lamotrigine.

16.

Cohen

. Options for treatment of bipolar disorder during pregnancy, 2018, https://womensmentalhealth.org/obgyn/options-for-treatment-of-bipolar-disorder-during-pregnancy/.

17.

Tran

Ford

. Lurasidone hydrochloride for bipolar disorder: a review of clinical effectiveness, cost-effectiveness, and guidelines. Ottawa (ON): Canadian Agency for Drugs and Technologies in Health, 2020.

18.

Holman

. In: eech

(ed) Europe proposal to classify lithium as toxic could hinder battery supply chain. NY, USA: S&P Global Commodity Insights, 2022.

19.

Van Deun

Hatch

Jacobi

, et al. Lithium carbonate: updated reproductive and developmental toxicity assessment using scientific literature and guideline compliant studies. Toxicology 2021; 461: 152907. DOI: 10.1016/j.tox.2021.152907.

20.

Greco

Engineer

Saiyin

, et al. Maternal nicotine exposure induces congenital heart defects in the offspring of mice. J Cell Mol Med 2022; 26: 3223–3234. DOI: 10.1111/jcmm.17328.

21.

Menegola

Broccia

Nau

, et al. Teratogenic effects of sodium valproate in mice and rats at midgestation and at term. Teratog Carcinog Mutagen 1996; 16: 97–108. DOI: 10.1002/(SICI)1520-6866.

22.

Hood

Naughton

Hayes

. Prenatal effects of Ochratoxin A in hamsters. Teratology 1976; 13: 11–14. DOI: 10.1002/tera.1420130103.

23.

Rasdi

Kamaludin

Ab Rahim

, et al. The impacts of intrauterine Bisphenol A exposure on pregnancy and expression of miRNAs related to heart development and diseases in animal model. Sci Rep 2020; 10: 5882. DOI: 10.1038/s41598-020-62420-1.

24.

Kuribayashi

Roberts

. Tetralogy of Fallot, truncus arteriosus, abnormal myocardial architecture and anomalies of the aortic arch system induced by bis-diamine in rat fetuses. J Am Coll Cardiol 1993; 21: 768–776. DOI: 10.1016/0735-1097(93)90111-d.

25.

Johnson

Dawson

Goldberg

. Cardiac teratogenicity of trichloroethylene metabolites. J Am Coll Cardiol 1998; 32: 540–545. DOI: 10.1016/s0735-1097(98)00232-0.

26.

Gonzalez

Diez-Pardo

, et al. Effects of vitamin A on malformations of neural-crest-controlled organs induced by nitrofen in rats. Pediatr Surg Int 2002; 18: 600–605. DOI: 10.1007/s00383-002-0865-5.

27.

Miyagawa

Ando

Takao

. Cardiovascular anomalies produced by nimustine hydrochloride in the rat fetus. Teratology 1988; 38: 553–558. DOI: 10.1002/tera.1420380602.

28.

Xiumei

, et al. Research into the intervention effect of folic acid on arsenic-induced heart abnormalities in fetal rats during the periconception period. BMC Cardiovasc Disord 2020; 20: 139–202. DOI: 10.1186/s12872-020-01418-z.

29.

Corno

Milano

Samaja

, et al. Chronic hypoxia: a model for cyanotic congenital heart defects. J Thorac Cardiovasc Surg 2002; 124: 105–112. DOI: 10.1067/mtc.2002.121302.

30.

Kurtz

Capobianco

Martinez

, et al. PPAR ligands improve impaired metabolic pathways in fetal hearts of diabetic rats. J Mol Endocrinol 2014; 53: 237–246. DOI: 10.1530/jme-14-0063.

31.

Meyer

Zhang

. Short- and long-term adverse effects of cocaine abuse during pregnancy on the heart development. Ther Adv Cardiovasc Dis 2009; 3: 7–16. DOI: 10.1177/1753944708099877.

32.

Beauchemin

Jr. Gartner

Provenza

. Alcohol induced cardiac malformations in the rat. Anat Anzeiger 1984; 155: 17–28.

33.

Schou

Goldfield

Weinstein

, et al. Lithium and pregnancy. I. Report from the register of lithium babies. Br Med J 1973; 2: 135–136. DOI: 10.1136/bmj.2.5859.135.

34.

Weinstein

Goldfield

. Cardiovascular malformations with lithium use during pregnancy. Am J Psychiatr 1975; 132: 529–531. DOI: 10.1176/ajp.132.5.529.

35.

Patorno

Huybrechts

Bateman

, et al. Lithium use in pregnancy and the risk of cardiac malformations. N Engl J Med 2017; 376: 2245–2254. DOI: 10.1056/NEJMoa1612222.

36.

Weinstein

. Lithium treatment of women during pregnancy and in the post-delivery period. In: Johnson

(ed). Handbook of Lithium Therapy. Dordrecht: Springer Netherlands, 1980, pp. 421–430.

37.

Boden

Lundgren

Brandt

, et al. Risks of adverse pregnancy and birth outcomes in women treated or not treated with mood stabilisers for bipolar disorder: population based cohort study. BMJ 2012; 345: e7085. DOI: 10.1136/bmj.e7085.

38.

Boyle

Garne

Loane

, et al. The changing epidemiology of Ebstein's anomaly and its relationship with maternal mental health conditions: a European registry-based study. Cardiol Young 2017; 27: 677–685. DOI: 10.1017/S1047951116001025.

39.

Caton

Bell

Druschel

, et al. Antihypertensive medication use during pregnancy and the risk of cardiovascular malformations. Hypertension 2009; 54: 63–70. DOI: 10.1161/HYPERTENSIONAHA.109.129098.

40.

Cohen

Friedman

Jefferson

, et al. A reevaluation of risk of in utero exposure to lithium. JAMA 1994; 271: 146–150.

41.

Cohen

Huybrechts

Patorno

, et al. Anticonvulsant mood stabilizer and lithium use and risk of adverse pregnancy outcomes. J Clin Psychiatry 2019; 80: 20190618. DOI: 10.4088/JCP.18m12572.

42.

Correa-Villasenor

Ferencz

Neill

, et al. Ebstein's malformation of the tricuspid valve: genetic and environmental factors. The Baltimore-Washington Infant Study Group. Teratology 1994; 50: 137–147. DOI: 10.1002/tera.1420500208.

43.

Cunniff

CMSD

Reed

Chambers

, et al. The teratology society twenty-ninth annual meeting june 3–8, 1989. Abstract. Teratology 1989; 39: 447–448, DOI: 10.1002/tera.1420390503.

44.

Czeizel

Racz

. Evaluation of drug intake during pregnancy in the Hungarian case-control surveillance of congenital anomalies. Teratology 1990; 42: 505–512. DOI: 10.1002/tera.1420420507.

45.

Diav-Citrin

Shechtman

Tahover

, et al. Pregnancy outcome following in utero exposure to lithium: a prospective, comparative, observational study. Am J Psychiatr 2014; 171: 785–794. DOI: 10.1176/appi.ajp.2014.12111402.

46.

Edmonds

LDOG

. Ebstein’s anomaly and maternal lithium exposure during pregnancy. Teratology 1990; 41: 551–552, DOI: 10.1002/tera.1420410503.

47.

Elnazer

Sampson

Baldwin

. Lithium and sexual dysfunction: an under-researched area. Hum Psychopharmacol 2015; 30: 66–69. DOI: 10.1002/hup.2457.

48.

Filkins

Linn

Kerr

, et al. Prospective ascertainment of lithium exposure during pregnancy. Teratology 1994; 49: 370, DOI: 10.1002/tera.1420490503.

49.

Fornaro

Maritan

Ferranti

, et al. Lithium exposure during pregnancy and the postpartum period: a systematic review and meta-analysis of safety and efficacy outcomes. Am J Psychiatr 2020; 177: 76–92. DOI: 10.1176/appi.ajp.2019.19030228.

50.

Frayne

Nguyen

Mok

, et al. Lithium exposure during pregnancy: outcomes for women who attended a specialist antenatal clinic. J Psychosom Obstet Gynaecol 2018; 39: 211–219. DOI: 10.1080/0167482X.2017.1337743.

51.

Harari

Langeen

Casimiro

, et al. Environmental exposure to lithium during pregnancy and fetal size: a longitudinal study in the Argentinean Andes. Environ Int 2015; 77: 48–54. DOI: 10.1016/j.envint.2015.01.011.

52.

Jacobson

Jones

Johnson

, et al. Prospective multicentre study of pregnancy outcome after lithium exposure during first trimester. Lancet 1992; 339: 530–533. DOI: 10.1016/0140-6736(92)90346-5.

53.

Källén

Tandberg

. Lithium and pregnancy. A cohort study on manic-depressive women. Acta Psychiatr Scand 1983; 68: 134–139. DOI: 10.1111/j.1600-0447.1983.tb06991.x.

54.

Kramer

Knoppert-Van der Klein

EAM

Van Kamp

, et al. 169 Bipolar and pregnant? No problem! A clinical evaluation of lithium use during pregnancy. Eur Neuropsychopharmacol 2003; 13: S246, DOI: 10.1016/S0924-977X(03)91879-7.

55.

Levin

Amsterdam

Winokur

, et al. Effects of psychotropic drugs on human sperm motility**Supported in part by the McCabe fund, by NIMH grant MH-32702 (dr. Amsterdam), by NIMH Research scientist development award MH-0044 (dr. Winokur), by research funds from the veterans administration, and by the michael R. Babitts fund for psychoneuroendocrinology. Fertil Steril 1981; 36: 503–506, DOI: 10.1016/S0015-0282(16)45801-2.

56.

Munk-Olsen

Liu

Viktorin

, et al. Maternal and infant outcomes associated with lithium use in pregnancy: an international collaborative meta-analysis of six cohort studies. Lancet Psychiatr 2018; 5: 644–652. DOI: 10.1016/s2215-0366(18)30180-9.

57.

Reis

Källén

. Maternal use of antipsychotics in early pregnancy and delivery outcome. J Clin Psychopharmacol 2008; 28: 279–288. DOI: 10.1097/JCP.0b013e318172b8d5.

58.

Troyer

Pereira

Lannon

, et al. Association of maternal lithium exposure and premature delivery. J Perinatol 1993; 13: 123–127.

59.

van der Lugt

van de Maat

van Kamp

, et al. Fetal, neonatal and developmental outcomes of lithium-exposed pregnancies. Early Hum Dev 2012; 88: 375–378. DOI: 10.1016/j.earlhumdev.2011.09.013.

60.

Zalzstein

Koren

Einarson

, et al. A case-control study on the association between first trimester exposure to lithium and Ebstein's anomaly. Am J Cardiol 1990; 65: 817–818. DOI: 10.1016/0002-9149(90)91398-.

61.

Clinic

. Tricuspid valve, https://my.clevelandclinic.org/health/body/21851-tricuspid-valve.

62.

Russ

Paschalides

, et al. Mechanical considerations for polymeric heart valve development: biomechanics, materials, design and manufacturing. Biomaterials 2019; 225: 119493. DOI: 10.1016/j.biomaterials.2019.119493.

63.

Cherry

DeBord

Moustapha-Nadler

. Ebstein's anomaly: a complex congenital heart defect. AORN J 2009; 89: 1098–1110. DOI: 10.1016/j.aorn.2009.03.003.

64.

Attenhofer Jost

Connolly

Dearani

, et al. Ebstein's anomaly. Circulation 2007; 115: 277–285. DOI: 10.1161/CIRCULATIONAHA.106.619338.

65.

Medicaid.gov . Medicaid eligibility, https://www.medicaid.gov/medicaid/eligibility/index.html 2023.

66.

TheraThink . Insurance reimbursement rates for psychiatrists. https://therathink.com/insurance-reimbursement-rates-for-psychiatrists/ 2023.

67.

Zhu

Renfro

Watson

, et al. Medicaid reimbursement for psychiatric services: comparisons across states and with Medicare. Health Aff 2023; 42: 556–565. DOI: 10.1377/hlthaff.2022.00805.

68.

Association

. Medicaid patients and “No-show” fees, https://www.texmed.org/Template.aspx?id=7796 (accessed 22 August 2023 2023).

69.

Majeroni

Cowan

Osborne

, et al. Missed appointments and Medicaid managed care. Arch Fam Med 1996; 5: 507–511. DOI: 10.1001/archfami.5.9.507.

70.

Brown

Schwartz

Shi

, et al. Understanding why urban, low-income patients miss primary care appointments: insights from qualitative interviews of west philadelphians. J Ambul Care Manag 2020; 43: 30–40. DOI: 10.1097/JAC.0000000000000316.

71.

Jackson

. How to manage Medicaid patient No-shows. 2023.

72.

Wen

Wilk

Druss

, et al. Medicaid acceptance by psychiatrists before and after Medicaid expansion. JAMA Psychiatr 2019; 76: 981. DOI: 10.1001/jamapsychiatry.2019.0958.

73.

Chapel

Ritchey

Zhang

, et al. Prevalence and medical costs of chronic diseases among adult Medicaid beneficiaries. Am J Prev Med 2017; 53: S143–S154. DOI: 10.1016/j.amepre.2017.07.019.

74.

Christopher

McCormick

Woolhandler

, et al. Access to care and chronic disease outcomes among medicaid-insured persons versus the uninsured. Am J Publ Health 2016; 106: 63–69. DOI: 10.2105/ajph.2015.302925.

75.

Decker

Kostova

Kenney

, et al. Health status, risk factors, and medical conditions among persons enrolled in Medicaid vs uninsured low-income adults potentially eligible for Medicaid under the Affordable Care Act. JAMA 2013; 309: 2579–2586. DOI: 10.1001/jama.2013.7106.

76.

Hill

Abdus

Hudson

, et al. Adults in the income range for the affordable care act’s Medicaid expansion are healthier than pre-ACA enrollees. Health Aff 2014; 33: 691–699. DOI: 10.1377/hlthaff.2013.0743.

77.

SRD

. Of old age population (65 years and older) in the total U.S. population from 1950 to 2050. Hamburg Germany: Statista, 2023.

78.

Ward

Schiller

. Prevalence of multiple chronic conditions among US adults: estimates from the National Health Interview Survey. Prev Chronic Dis 2013; 10: E65. 20130425. DOI: 10.5888/pcd10.120203.

79.

Ward

Schiller

Goodman

. Multiple chronic conditions among US adults: a 2012 update. Prev Chronic Dis 2014; 11: E62. DOI: 10.5888/pcd11.130389.

80.

Holahan

Kenney

GJP

. The health status of new Medicaid enrollees under health reform: timely analysis of immediate health policy issues, 2010, https://www.urban.org/sites/default/files/publication/29121/412206-Health-Status-of-New-Medicaid-Enrollees-Under-Health-Reform.PDF

81.

Khoury

Hall

Andresen

, et al. The association between chronic disease and physical disability among female Medicaid beneficiaries 18-64 years of age. Disabil Health J 2013; 6: 141–148. DOI: 10.1016/j.dhjo.2012.11.006.

82.

Buescher

Whitmire

Pullen-Smith

. Medical care costs for diabetes associated with health disparities among adult Medicaid enrollees in North Carolina. N C Med J 2010; 71: 319–324.

83.

Cheung

Wiler

Lowe

, et al. National study of barriers to timely primary care and emergency department utilization among Medicaid beneficiaries. Ann Emerg Med 2012; 60: 4–10. DOI: 10.1016/j.annemergmed.2012.01.035.

84.

Chang

Davis

. Potential adult Medicaid beneficiaries under the patient protection and affordable care act compared with current adult Medicaid beneficiaries. Ann Fam Med 2013; 11: 406–411. DOI: 10.1370/afm.1553.

85.

Widmer

Basu

Hochhalter

. The association between office-based provider visits and emergency department utilization among Medicaid beneficiaries. J Community Health 2015; 40: 549–554. DOI: 10.1007/s10900-014-9970-3.

86.

Downie

Schmid

Plescia

, et al. Racial disparities in blood pressure control and treatment differences in a Medicaid population, North Carolina, 2005-2006. Prev Chronic Dis 2011; 8: A55.

87.

Esposito

Bagchi

Verdier

, et al. Medicaid beneficiaries with congestive heart failure: association of medication adherence with healthcare use and costs. Am J Manag Care 2009; 15: 437–445.

88.

Yang

Howard

Will

, et al. Association of antihypertensive medication adherence with healthcare use and Medicaid expenditures for acute cardiovascular events. Med Care 2016; 54: 504–511. DOI: 10.1097/mlr.0000000000000515.

89.

Bagchi

Esposito

Kim

, et al. Utilization of, and adherence to, drug therapy among Medicaid beneficiaries with congestive heart failure. Clin Therapeut 2007; 29: 1771–1783. DOI: 10.1016/j.clinthera.2007.08.015.

90.

DiGiulio

Jump

, et al. State Medicaid coverage for tobacco cessation treatments and barriers to accessing treatments - United States, 2015-2017. MMWR Morb Mortal Wkly Rep 2018; 67: 390–395. DOI: 10.15585/mmwr.mm6713a3.

91.

Howard

Singh

Englesbe

. Prevalence and trends in smoking among surgical patients in Michigan, 2012-2019. JAMA Netw Open 2021; 4: e210553–20210301. DOI: 10.1001/jamanetworkopen.2021.0553.

92.

Mylona

Benitez

Shehadeh

, et al. The association of obesity with health insurance coverage and demographic characteristics: a statewide cross-sectional study. Medicine (Baltim) 2020; 99: e21016. DOI: 10.1097/MD.0000000000021016.

93.

Rumalla

Reddy

Mittal

. Recreational marijuana use and acute ischemic stroke: a population-based analysis of hospitalized patients in the United States. J Neurol Sci 2016; 364: 191–196. DOI: 10.1016/j.jns.2016.01.066.

94.

Sullivan

Bauer

Fulton-Kehoe

, et al. Trends in opioid dosing among Washington state Medicaid patients before and after opioid dosing guideline implementation. J Pain 2016; 17: 561–568. DOI: 10.1016/j.jpain.2015.12.018.

95.

Singh

. Epidemiology of hospitalizations with cocaine use disorder: a 17-year U.S. national study. J Psychiatr Res 2021; 144: 32–36. DOI: 10.1016/j.jpsychires.2021.09.052.

96.

Suen

Makam

Snyder

, et al. National prevalence of alcohol and other substance use disorders among emergency department visits and hospitalizations: nhamcs 2014-2018. J Gen Intern Med 2022; 37: 2420–2428. DOI: 10.1007/s11606-021-07069-w.

97.

Verma

. Services DHH. Baltimore, ML: Centers for Medicare & Medicaid Services 2018.

98.

Freeman

Fleming

, et al. Smoking prevalence and cigarette consumption in 187 countries, 1980-2012. JAMA 2014; 311: 183–192. DOI: 10.1001/jama.2013.284692.

99.

Heffner

Strawn

DelBello

, et al. The co-occurrence of cigarette smoking and bipolar disorder: phenomenology and treatment considerations. Bipolar Disord 2011; 13: 439–453. DOI: 10.1111/j.1399-5618.2011.00943.x.

100.

Lasser

Boyd

Woolhandler

, et al. Smoking and mental illness: a population-based prevalence study. JAMA 2000; 284: 2606–2610. DOI: 10.1001/jama.284.20.2606.

101.

Kessler

Crum

Warner

, et al. Lifetime co-occurrence of DSM-III-R alcohol abuse and dependence with other psychiatric disorders in the National Comorbidity Survey. Arch Gen Psychiatr 1997; 54: 313–321. DOI: 10.1001/archpsyc.1997.01830160031005.

102.

Cardoso

Kauer Sant'Anna

Dias

, et al. The impact of co-morbid alcohol use disorder in bipolar patients. Alcohol 2008; 42: 451–457. DOI: 10.1016/j.alcohol.2008.05.003.

103.

Hasin

Stinson

Ogburn

, et al. Prevalence, correlates, disability, and comorbidity of DSM-IV alcohol abuse and dependence in the United States: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatr 2007; 64: 830–842. DOI: 10.1001/archpsyc.64.7.830.

104.

Grant

Saha

Ruan

, et al. Epidemiology of DSM-5 drug use disorder: results from the national epidemiologic survey on alcohol and related conditions-III. JAMA Psychiatr 2016; 73: 39–47. DOI: 10.1001/jamapsychiatry.2015.2132.

105.

McDonald

Rossell

Phillipou

. The comorbidity of eating disorders in bipolar disorder and associated clinical correlates characterised by emotion dysregulation and impulsivity: a systematic review. J Affect Disord 2019; 259: 228–243, DOI: 10.1016/j.jad.2019.08.070.

106.

Azorin

J-M

Lefrere

Belzeaux

. The impact of bipolar disorder on couple functioning: implications for care and treatment. A systematic review. Medicina 2021; 57: 771. DOI: 10.3390/medicina57080771.

107.

Hirschfeld

Lewis

Vornik

. Perceptions and impact of bipolar disorder: how far have we really come? Results of the national depressive and manic-depressive association 2000 survey of individuals with bipolar disorder. J Clin Psychiatry 2003; 64: 161–174.

108.

Kupfer

Frank

Grochocinski

, et al. Demographic and clinical characteristics of individuals in a bipolar disorder case registry. J Clin Psychiatry 2002; 63: 120–125. DOI: 10.4088/jcp.v63n0206.

109.

Zwerling

Whitten

Sprince

, et al. Workforce participation by persons with disabilities: the national health interview survey disability supplement, 1994 to 1995. J Occup Environ Med 2002; 44: 358–364. DOI: 10.1097/00043764-200204000-00017.

110.

McElroy

Keck

Jr . Obesity in bipolar disorder: an overview. Curr Psychiatr Rep 2012; 14: 650–658. DOI: 10.1007/s11920-012-0313-8.

111.

Deputy

Dub

Sharma

. Prevalence and trends in prepregnancy normal weight - 48 states, New York city, and District of Columbia, 2011-2015. MMWR Morb Mortal Wkly Rep 2018; 66: 1402–1407. DOI: 10.15585/mmwr.mm665152a3.

112.

Watkins

Rasmussen

Honein

, et al. Maternal obesity and risk for birth defects. Pediatrics 2003; 111: 1152–1158.

113.

Moore

Singer

Bradlee

, et al. A prospective study of the risk of congenital defects associated with maternal obesity and diabetes mellitus. Epidemiology 2000; 11: 689–694. DOI: 10.1097/00001648-200011000-00013.

114.

Mills

Troendle

Conley

, et al. Maternal obesity and congenital heart defects: a population-based study. Am J Clin Nutr 2010; 91: 1543–1549. DOI: 10.3945/ajcn.2009.28865.

115.

Madsen

Schwartz

Lewin

, et al. Prepregnancy body mass index and congenital heart defects among offspring: a population-based study. Congenit Heart Dis 2013; 8: 131–141. DOI: 10.1111/j.1747-0803.2012.00714.x.

116.

Cedergren

Kallen

. Maternal obesity and infant heart defects. Obes Res 2003; 11: 1065–1071. DOI: 10.1038/oby.2003.146.

117.

Waller

Shaw

Rasmussen

, et al. Prepregnancy obesity as a risk factor for structural birth defects. Arch Pediatr Adolesc Med 2007; 161: 745–750. DOI: 10.1001/archpedi.161.8.745.

118.

Helle

Priest

. Maternal obesity and diabetes mellitus as risk factors for congenital heart disease in the offspring. J Am Heart Assoc 2020; 9: e011541. DOI: doi:10.1161/JAHA.119.011541.

119.

Harvey

Baer

Bandoli

, et al. Association of alcohol use diagnostic codes in pregnancy and offspring conotruncal and endocardial cushion heart defects. J Am Heart Assoc 2022; 11: e022175. DOI: 10.1161/JAHA.121.022175.

120.

Malik

Cleves

Honein

, et al. Maternal smoking and congenital heart defects. Pediatrics 2008; 121: e810–816. DOI: 10.1542/peds.2007-1519.

121.

Lee

Lupo

. Maternal smoking during pregnancy and the risk of congenital heart defects in offspring: a systematic review and metaanalysis. Pediatr Cardiol 2013; 34: 398–407. DOI: 10.1007/s00246-012-0470-x.

122.

Ramphul

Mejias

Joynauth

. In-utero exposure to opioid increases the risk of congenital heart defects. EXCLI J 2020; 19: 239–240. DOI: 10.17179/excli2020-1051.

123.

Interrante

Ailes

Lind

, et al. Risk comparison for prenatal use of analgesics and selected birth defects, National Birth Defects Prevention Study 1997-2011. Ann Epidemiol 2017; 27: 645-653. DOI: 10.1016/j.annepidem.2017.09.003.

124.

Sahramian

Noori

Moradi

, et al. The rate of addiction in parents of toddlers with congenital heart disease. Int J High Risk Behav Addiction 2013; 1: 154–158. DOI: 10.5812/ijhrba.7312.

125.

Broussard

Rasmussen

Reefhuis

, et al. Maternal treatment with opioid analgesics and risk for birth defects. Am J Obstet Gynecol 2011; 204: 314. DOI: 10.1016/j.ajog.2010.12.039.

126.

Forrester

Merz

. Risk of selected birth defects with prenatal illicit drug use, Hawaii, 1986-2002. J Toxicol Environ Health 2007; 70: 7-18. DOI: 10.1080/15287390600748799.

127.

Lipshultz

Frassica

Orav

. Cardiovascular abnormalities in infants prenatally exposed to cocaine. J Pediatr 1991; 118: 44–51. DOI: 10.1016/s0022-3476(05)81842-6.

128.

Williams

Correa

Rasmussen

. Maternal lifestyle factors and risk for ventricular septal defects. Birth Defects Res A Clin Mol Teratol 2004; 70: 59–64. DOI: 10.1002/bdra.10145.

129.

McElhatton

Bateman

Evans

, et al. Congenital anomalies after prenatal ecstasy exposure. Lancet 1999; 354: 1441–1442. DOI: 10.1016/s0140-6736(99)02423-x.

130.

Peyvandi

Baer

Chambers

, et al. Environmental and socioeconomic factors influence the live-born incidence of congenital heart disease: a population-based study in California. J Am Heart Assoc 2020; 9: e015255. DOI: 10.1161/jaha.119.015255.

131.

Miao

Dunn

Wen

, et al. Neighbourhood maternal socioeconomic status indicators and risk of congenital heart disease. BMC Pregnancy Childbirth 2021; 21: 72. DOI: 10.1186/s12884-020-03512-8.

132.

Agha

Glazier

Moineddin

, et al.

Socioeconomic status and prevalence of congenital heart defects: does universal access to health care system eliminate the gap?

Birth Defects Res A Clin Mol Teratol 2011; 91: 1011–1018. DOI: 10.1002/bdra.22857.

133.

Zhang

Sun

Zhao

, et al. How parental predictors jointly affect the risk of offspring congenital heart disease: a nationwide multicenter study based on the China birth cohort. Front Cardiovasc Med 2022; 9: 860600–20220603. DOI: 10.3389/fcvm.2022.860600.

134.

Luo

Wang

Huang

, et al. Association and interaction effect of BHMT gene polymorphisms and maternal dietary habits with ventricular septal defect in offspring. Nutrients 2022; 14: 20220728. DOI: 10.3390/nu14153094.

135.

Yang

Chang

Dang

, et al. Dietary quality during pregnancy and congenital heart defects. Nutrients 2022; 14: 20220904. DOI: 10.3390/nu14173654.

136.

Botto

Krikov

Carmichael

, et al. Lower rate of selected congenital heart defects with better maternal diet quality: a population-based study. Arch Dis Child Fetal Neonatal 2016; 101: F43–49. DOI: 10.1136/archdischild-2014-308013.

137.

Cao

Zhang

, et al. High maternal blood lipid levels during early pregnancy are associated with increased risk of congenital heart disease in offspring. Acta Obstet Gynecol Scand 2021; 100: 1806–1813. DOI: 10.1111/aogs.14225.

138.

Jk Aronson

Mahtani

Nunan

. Confounding by indication https://catalogofbias.org/biases/confounding-by-indication/ 2018.

139.

Westreich

. Berkson's bias, selection bias, and missing data. Epidemiology 2012; 23: 159–164. DOI: 10.1097/EDE.0b013e31823b6296.

140.

Sullivan

Dervan

Reiger

, et al. Risk of congenital heart defects in the offspring of smoking mothers: a population-based study. J Pediatr 2015; 166: 978–984. DOI: 10.1016/j.jpeds.2014.11.042.

Epidemiology studies on effects of lithium salts in pregnancy are confounded by the inability to control for other potentially teratogenic factors

Abstract

Introduction

Methods

Results

Conclusions

Keywords

Introduction

Putative developmental toxicity of lithium

Lithium is not teratogenic in rats

Epidemiology studies reporting developmental effects

Lithium and Ebstein’s anomaly

Risk factors in medicaid beneficiaries and patients

Risk factors in bipolar patients

Risk factors for congenital heart defects

Differences among the low, medium, and high-dose groups in Patorno et al. (2017)

Exposure to therapeutic lithium carbonate is not comparable to industrial handling of lithium products

Conclusions

Footnotes

Declaration of conflicting interests

Funding

Orcid iD

References