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Abstract

French

Introduction:

The goal of this study was to investigate the association between worsening renal function (WRF) and central venous pressure, right ventricular function, and lung fluid overload assessed by point-of-care ultrasound (POCUS) in hospitalized patients with acute heart failure (AHF).

Methods:

This was a prospective cohort study including AHF adult inpatients, conducted in Geneva University Hospitals from October 2019 to March 2020. The primary outcome was WRF, defined by an increase in creatinine of ≥1.5 times from baseline value or an increase of ≥0.3 mg/dL between admission and day 4 to 6. Expert ultrasonographers used POCUS to examine lungs, inferior vena cava during spontaneous expiration (IVCe), and tricuspid annular plane systolic excursion (TAPSE) at admission.

Results:

A total of 43 patients were included in the study. A total of 8 patients (19%) developed WRF during the study period (between October 8, 2019 and March 16, 2020), of whom 4 were in the higher quartile of lung fluid overload, 2 had TAPSE <14 mm, and 4 had IVCe ≥ 21 mm. In uni- and multi-variate logistic regression model, neither admission IVCe nor TAPSE was associated with WRF. However, lung congestion, as assessed by the number of B-lines, was significantly associated with WRF (odds ratio [OR] per quartile = 2.47, 95% confidence interval [CI] = 1.01 to 5.86, P = .04). This result remained statistically significant after adjustment for daily diuretic dose in mg/kg (OR = 2.98, 95% CI = 1.11 to 8.00, P = .03).

Conclusion:

This study showed that lung congestion as assessed by POCUS was associated with WRF in AHF patients, whereas IVCe and TAPSE were not. Due to the small number of participants, our results need to be prospectively validated in future adequately powered clinical trials.

Keywords

point-of-care ultrasonography POCUS acute heart failure acute kidney failure lung congestion

Introduction

Worsening renal function (WRF) during episodes of acute heart failure (AHF), also referred to as “cardiorenal syndrome type 1,”¹ is a common finding and an independent predictor of poor outcomes.^2-6 Heart and kidney dysfunctions are strongly interrelated; WRF has been classically attributed to low cardiac output; however, kidney venous congestion seems to have an important role to play in WRF pathogenesis.^7-9 Increased central venous pressure (CVP), either caused by fluid overload or right ventricular dysfunction, is transmitted backward to the renal veins, possibly leading to increased kidney interstitial pressure and impaired glomerular filtration.¹⁰ In fact, elevated CVP is associated with reduced renal function in a variety of cardiovascular diseases⁸ and right rather than left ventricular dysfunction was shown to be associated with chronic kidney disease progression.¹¹ Activation of the neuro-humoral system and fluid retention may lead to WRF by diminishing medullary perfusion pressure (the so-called renal tamponade hypothesis).¹² Clinical evaluation of CVP and fluid overload is challenging for clinicians.¹³ Indeed, gold standard for CVP assessment is direct measurement of pressure in the superior vena cava or right atrium with catheterization. This kind of invasive equipment is, however, unpractical for daily clinical assessment. In addition, it is recognized that considerable disagreement and inaccuracy exist in the clinical assessment of CVP through jugular vein visual examination.^14,15 This may lead to insufficient diuretic treatment and residual congestion at discharge, which is associated with worse clinical outcomes.^16,17 Point-of-care ultrasonography (POCUS) outperforms physical examination for both fluid overload, right ventricular dysfunction, and CVP assessment.^18-20 The aim of the present study was to investigate the association between WRF and POCUS-estimated CVP, right ventricular function, and lung fluid overload in hospitalized patients with AHF.

Methods

This study was a pre-specified supplementary analysis of a prospective cohort study including AHF adult inpatients, conducted in Geneva University Hospitals from October 2019 to March 2020. Patients were recruited from the general internal medicine and cardiology inpatient units. Patients were routinely screened each working day by a study nurse for a diagnosis of AHF. Participation in the study was proposed to eligible patients within 72 hours of admission in the ward, and informed consent was obtained. Patients sequentially underwent a structured clinical examination, POCUS, and blood analysis twice: within 72 hours from admission (T0) and 4 to 6 days later (T1). Ultrasonographers were masked to clinical data files, and clinicians were blinded to POCUS findings. Paper case report forms were subsequently entered in the database with data entry verified by an independent data service provider (Data Conversion Service SA, Geneva, Switzerland). Baseline patient characteristics obtained from patients or electronic medical records were collected and documented by the study nurse. More details about study methods and patient recruitment are available in our previous report.²¹ Acute heart failure was defined according to the European Society of Cardiology criteria by the presence of at least 1 sign or symptom and a value of N-terminal pro-B type natriuretic peptide (NT-proBNP) of ≥300 ng/L.²² Serum creatinine baseline level was defined as the lowest value available in the year preceding hospital admission in the absence of dialysis.

Point-of-Care Ultrasonography

Bedside ultrasonography was performed by expert sonographers using a high-end device (Philips SparQ, Philips AG Health Systems, Zurich, Switzerland) and a phased array probe (frequencies: 4-10 MHz) with preset 60% of gain and 15 cm of depth. Tissue harmonics were switched off for lung examination, allowing a better visualization of B-lines as previously described;²³ a cardiac preset was selected (starting gain 50%, depth 15 cm). Patients laid supine with 30 to 45° bed elevation for lung ultrasound (LUS) and 0 to 30° for inferior vena cava during spontaneous expiration (IVCe) and tricuspid annular plane systolic excursion (TAPSE) measure. The thorax was explored bilaterally following a previously described 28-point protocol.²⁴ The sum of the higher number of B-lines visualized in each point on a frozen image was calculated for the estimation of lung fluid overload. Right ventricular function was assessed in apical 4-chamber view measuring the TAPSE, the M-mode cursor positioned at the lateral portion of the tricuspid annulus with a cut-off for right ventricular systolic dysfunction (RVD) of <14 mm.^25,26 Due to the existence of different cut-off values in the literature, a sensitivity analysis was performed with a cut-off value of 17 mm. Finally, as surrogate of CVP, inferior vena cava (IVC) size was measured in the subcostal view during unforced expiration (IVCe), using M-mode with a cut-off for high CVP of ≥21 mm.²⁷ Only admission POCUS measures (T0) were used for the purpose of this study.

Study Variables

The primary outcome was the development of WRF during the hospital stay. Worsening of renal function (WRF) was defined by an increase in creatinine of ≥1.5 from baseline value to T0 or T1 (worst value obtained) and/or an increase of ≥0.3 mg/dL (26.5 µmol/L) between T0 and T1. Predictor variables were the number of B-lines (in quartiles), TAPSE (below or above 14 mm), and IVCe size (below or above 21 mm) at T0. The total dose of diuretics from T0 to T1 was calculated retrospectively in daily normalized furosemide equivalents (mg/kg/day) by reviewing hospital electronic medical records. Results were adjusted for the normalized daily dose of diuretics. Figure 1 shows a representative image of each organ examined by ultrasound before and after decongestion.

Figure 1.

Representative image of each organ examined by ultrasound before and after decongestion.

Statistical Analysis

Baseline characteristics of participants are presented as mean (standard deviation) or number (percentage), as appropriate.

To compare the incidence of the primary outcome across the B-line quartiles, TAPSE groups, or IVCe size groups, the chi-square or chi-square for trend was used, as appropriate. In addition, the association between WRF and POCUS-estimated lung fluid congestion (ie, B-lines quartiles), RVD (as estimated by TAPSE), or CVP (as estimated by IVCe) was assessed with univariate binary logistic regression. Results were adjusted in a multivariate model including the mean normalized daily dose of diuretics administered between T0 and T1 (mg/days/kg of intravenous [IV] furosemide equivalents). The small number of events prevented us from adjusting results for additional variables. P-values < .05 were considered statistically significant. SPSS software (version 27.0, SPSS Inc, Chicago, Illinois) was used for all statistical analyses.

Results

Between October 8, 2019 and March 16, 2020, 43 patients were included in the study (mean age of 75 years; 23% of women, mean left ventricular ejection fraction of 43%; 28% with chronic kidney disease, defined as an estimated glomerular filtration rate < 60 ml/min/1.73 m²). Mean baseline creatinine was 101 ± 52 µmol/L; mean creatinine was 126 ± 63 µmol/L at T0 and 127 ± 70 µmol/L at T1. On average, patients received 1.1 ± 1.0 mg/kg/day of intravenous furosemide equivalents. Point-of-care ultrasonography was performed by 3 expert ultrasonographers within 1 day (interquartile range [IQR] = 1-3 days) after admission to the ward. Participants had an average total sum of 21.9 ± 14.7 B-lines on admission LUS. Significant pulmonary congestion was detected in 91% of study individuals on admission, as defined by the presence of ≥6 B-lines;²⁸ one fifth (19.5%; 8/41) had abnormal value of TAPSE, and 58.5% (24/41) had enlarged IVCe. In 2 patients, an accurate value of TAPSE or IVCe could not be obtained for technical reasons. One patient who presented with WRF did not have an IVCe value on arrival. Key baseline characteristics are reported in Table 1; complete data are available in our previous report for this study.²¹ The NT-proBNP level was considerably higher in Quartile 4 than in the other groups (Table 1).

Table 1.

Key Baseline Characteristics of the Study Population According to Admission B-Lines Quartiles, TAPSE, and IVCe Size.

	All patients	LUS quartiles, no. of B-lines (N = 43)				TAPSE, mm (N = 41)		IVCe, mm (N = 41)
Characteristics	N = 43	Q1, 1-11(N = 11)	Q2, 12-19(N = 11)	Q3, 19-27(N = 11)	Q4, >27(N = 10)	<14(N = 8)	≥14(N = 33)	<21(N = 17)	≥21(N = 24)
Demographics
Men, no. (%)	33 (76)	10 (90.9)	7 (63.6)	8 (72.7)	8 (80)	8 (100)	24 (72.7)	8 (47.1)	23 (95.8)
Age, mean (SD)	75 (11)	71 (12)	74 (11)	77 (10)	76 (14)	71 (12)	75 (12)	76 (10)	72 (12)
Comorbidities
Diabetes, no. (%)	18 (42)	7 (63.6)	2 (18.2)	5 (45.5)	4 (40)	3 (37.5)	14 (42.4)	7 (41.2)	10 (41.7)
Hypertension, no. (%)	31 (72)	10 (90.9)	7 (63.6)	7 (63.6)	7 (70)	7 (87.5)	22 (66.7)	12 (70.6)	17 (70.8)
Prior heart failure, no. (%)	23 (54)	7 (63.6)	5 (45.5)	5 (45.5)	6 (60)	4 (50)	18 (54.5)	10 (58.8)	11 (45.8)
CKD, no. (%)	12 (28)	3 (27.3)	1 (9.1)	5 (45.5)	3 (30)	1 (12.5)	11 (33.3)	6 (35.3)	6 (25)
Medications
Renin-angiotensin inhibitor, no. (%)	25 (58)	9 (81.8)	5 (45.5)	6 (54.5)	5 (50)	4 (50)	20 (60.6)	9 (52.9)	14 (58.3)
Beta-blocker, no. (%)	20 (46.5)	8 (72.7)	6 (54.5)	4 (36.4)	2 (20)	3 (37.5)	15 (45.5)	7 (41.2)	12 (50)
Diuretic dose in furosemide equivalent, mg/kg/d, (SD)	1.1 (1)	1.1 (0.9)	1.3 (1.6)	1 (0.9)	1 (0.7)	1.6 (2)	1 (0.7)	0.9 (0.6)	1.2 (1.3)
Laboratory tests
Serum creatinine (µmol/L), mean (SD)	101 (52)	97 (31)	89 (25)	95 (38)	125 (90)	86 (16)	105 (58)	106 (76)	96 (28)
NT-proBNP (ng/L), mean (SD)	6742 (7076)	5075 (4507)	3616 (3151)	4294 (4605)	14707 (9127)	5345 (2791)	7410 (7823)	9238 (9932)	4772 (2918)

Note. Percentages are reported within each quartile or group. LUS = lung ultrasonography; TAPSE = tricuspid annular plane systolic excursion; IVCe = inferior vena cava during unforced expiration; CKD = chronic kidney disease; NT-proBNP = N-terminal pro-B type natriuretic peptide.

We assessed body weight and NT-proBNP values at T0 and T1. Weight dropped by a median of −1.2 kg (IQR = −3.3 to −0.7) and NT-proBNP by a median of −1220 ng/L (IQR = −4146 to −56).

A total of 8 patients (19%) developed WRF during the study period, of whom 4 were in the higher quartile of lung fluid overload, 2 had TAPSE <14 mm, and 4 IVCe ≥ 2.1. The incidence of the primary outcome was higher in patients in the highest quartile for the number of B-lines (p-value for trend 0.03, Figure 2). In a univariate logistic regression model, neither IVCe nor TAPSE were associated with WRF (Figure 2 and Table 2). Results were similar when a TAPSE cut-off of <17 mm was used. More significant lung fluid overload, as estimated by the number of B-lines, however, significantly correlated with WRF as shown in Figure 2 and Table 2 (odds ratio (OR) = 2.47, 95% confidence interval (CI) = 1.01 to 5.86, P = .04). This result remained statistically significant after adjustment for normalized daily diuretic dose (OR = 2.98, 95% CI = 1.11 to 8.00, P = .03).

Figure 2.

Association between B-line quartiles, TAPSE, or IVCe size and development of worsening of renal failure during hospital stay.

Table 2.

Univariate and Multivariate Association Between B-Line Quartiles, TAPSE, or IVCe Size and Development of Worsening of Renal Function.

	Patients, no (%)	Unadjusted OR (95% CI)	P	Adjusted OR (95% CI)^a	P
B-lines
Q1	11/43 (25.6) ref
Q2	11/43 (25.6)	2.47 (1.01-5.86)^b	0.04	2.98 (1.11-8.00)^b	.03
Q3	11/43 (25.6)
Q4	10/43 (23.3)
TAPSE
<14 mm	8/41 (19.5)	1.50 (0.24-9.34)	0.66	0.97 (0.12-7.99)	.98
≥14 mm	33/41 (80.5) ref
IVCe
<21 mm	17/41 (41.5) ref
≥21 mm	24/41 (58.5)	0.93 (0.18-4.84)	0.94	0.71 (0.12-4.10)	.70

ORs are adjusted for daily normalized diuretic dose.

For each incremental quartile.

We also examined change in B-lines in patients who developed WRF or not between T0 and T1. Patients without WRF had an average change in B-lines of −7.4 ± 2.2, while patients with WRF had an average change in B-lines of −13.5 ± 6.6 (difference between the 2 groups of 6.1, 95% CI = −5.1 to 17.3, P = .28). Similarly, there was no statistically significant difference in change in body weight or NT-proBNP between T0 and T1 in patients with and without WRF (P of 0.96 and 0.14, respectively).

Discussion

In this prospective cohort study including 43 patients hospitalized for AHF, pulmonary fluid overload on admission evaluated by LUS significantly correlated with WRF, whereas echographic markers of RVD (TAPSE < 14 mm) and elevated CVP (IVC diameter ≥ 21 mm) did not.

Our main objective was to determine whether significant congestion, as assessed by LUS, could predict WRF during hospitalization. This association had been shown in the past in patients in the intensive care unit (ICU)⁷ using CVP measures, but it had never been shown with LUS. It has to be highlighted that patients with more severe congestion at presentation probably represent a sicker patient group, and this is explaining the identified association between the number of B-lines and incidence of WRF during the hospital stay.

Our sample size is inadequate to demonstrate whether changes in volume status during hospitalization, ie, better decongestion, are associated with changes in renal function or not. Although we did not find any significant difference in the change in the number of B-lines, weight, and NT-proBNP levels between T0 and T1 in patients with and without WRF, the small number of patients in our cohort precludes any definite conclusions with respect to the effect of decongestion on renal endpoints.

The LUS provides a semiquantitative assessment of pulmonary congestion, identifying extravascular lung water as B-lines.^29-33 B-lines are significantly correlated with established parameters of AHF.³⁴ Moreover, pulmonary congestion assessed by LUS is associated with a worse prognosis.³⁵ Interestingly, in a recent randomized trial, a decongestive strategy mainly driven by IVC measurement did not impact short-term hospital readmission,³⁶ whereas an LUS-guided decongestive therapy allowed a significant reduction in hospitalization in chronic HF patients with reduced ejection fraction.³⁷ Moreover, during follow-up, lower rates of WRF were observed in patients allocated to the LUS-group, in comparison to those for whom decongestion rely on physical examination suggesting a role of subclinical fluid overload in cardiorenal syndrome pathogenesis. Remarkably, in a recent cohort of 39 inpatients with acute renal injury, a third of clinically euvolemic and a half of hypovolemic patients had moderate to severe lung fluid overload (ie, >15 B-lines).³⁸ Thus, LUS in patients suffering from HF seems to outperform clinical examination in fluid overload assessment and decongestion guidance and might be useful to predict and prevent WRF secondary to acute cardiorenal syndrome.

A retrospective study by Mavrakanas et al¹¹ demonstrated a significant, independent association between right ventricular diameter or function and chronic kidney disease (CKD) progression. The present study failed to find this association in patients with WRF in the context of AHF. This could be explained by inadequate power due to the small sample of our study or different pathophysiological mechanisms underlying acute and chronic kidney disease related to HF. Furthermore, there is a controversy about the normal value of TAPSE. A value below 14 mm is associated with a poor prognosis in patients with chronic heart failure, but even a value below 17 mm indicates RVD.^27,39 In a post-hoc analysis using a TAPSE cut-off of <17 mm, however, there was still no significant association (results not shown).

Many physicians rely on IVC measurement to assess the volume status of patient. However, IVC measurement is associated with subjective variability⁴⁰ and cannot be considered as a reliable standalone tool to assess CVP.⁴¹ Recently, Bhardwaj et al⁴² evaluated a modified VEXUS protocol (combination of IVC diameter, hepatic venous flow, and portal vein pulsatility index) in predicting acute kidney injury (AKI) in patients with cardiorenal syndrome. They found a strong correlation between grades of VEXUS and the stages of AKI. Renal venous ultrasound could also be an interesting tool.⁴³ A recent study also described POCUS assessment of the jugular venous pressure and concluded that it is feasible, reproducible, and accurately predictive of elevated CVP in patients undergoing right heart catheterization.⁴⁴

Another important point that needs to be highlighted is the clinical significance of WRF. It has been shown in the DOSE trial that patients with WRF actually had better clinical outcomes, compared with patients with improved renal function during hospitalization, which seems counterintuitive but could be possibly due to better decongestion in patients with WRF. Therefore, identification of patients at risk for AKI with B-line assessment should not preclude volume status optimization with adequate doses of diuretics, as small changes in creatinine levels during hospitalization may not represent AKI and are not related to hard clinical endpoints.^45,46

This study has some limitations. First, the number of participants was modest due to recruitment interruption during the COVID-19 pandemic. The small number of events only allowed us to adjust results for daily normalized diuretic dose, precluding us to consider other potential confounders. Second, the 28-point LUS protocol used for this study has been largely validated, but it does not take into account the presence of pleural effusions, which is a very common marker of fluid overload. Other possible causes of WRF, such as postrenal injury, were not systematically investigated, and this may have influenced results; however, it is expected to lower the association more than strengthen it. Finally, non-cardiogenic pulmonary edema cannot be formally ruled out with LUS, and the higher number of B-lines in patients with WRF could potentially represent other causes not directly related to congestion.

To our knowledge, no study has yet shown a correlation between signs of congestion on LUS and WRF in the context of AHF, which is a strength of this study. However, our results remain hypothesis generating and will have to be prospectively validated in a future adequately powered clinical trial.

Footnotes

Author Contributions

G.S., MD, and A.L., MD: conceptualization, data curation, formal analysis, investigation, methodology, validation, writing—original draft, and writing—review and editing. A.L., MD: investigation and writing—review and editing. C.M., MD: writing—review and editing. S.C., MD: writing—review and editing. J.S., MD, PhD: writing—review and editing. O.G., MD: investigation and writing—review and editing. Professor J.-L.R., MD, PhD: writing—review and editing. T.A.M., MD: conceptualization, data curation, formal analysis, methodology, validation, supervision, and writing—review and editing.

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: Professor T.A.M. has received speaker honoraria from Bayer, BMS Canada, Janssen, AstraZeneca, and Pfizer and has served on advisory boards for Boehringer Ingelheim, Bayer, GSK, Novo Nordisk, and Servier outside the submitted work. He has also received a research grant from AstraZeneca and fellowship grants from Pfizer, Janssen, and Bayer. He has also received operating grants from the Canadian Institutes of Health Research, the Kidney Foundation of Canada, and the Heart and Stroke Foundation of Canada. He is supported by a Fonds de Recherche Santé Québec (FRSQ) J1 Clinician Scholar award and a Kidney Research Scientist Core Education and National Training (KRESCENT) Program New Investigator Award.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Statement of Ethics

The investigation conforms with the principles outlined in the Declaration of Helsinki and was reviewed and approved by the local ethics committee (Commission Cantonale d’Ethique de la Recherche sur l’être humain [CCER], approval no. CCER 2019–01596). Written informed consent was obtained from all patients prior to inclusion.

ORCID iD

Guillaume Soret

Data Availability

All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.

References

Ronco

Haapio

House

Anavekar

Bellomo

. Cardiorenal syndrome. J Am Coll Cardiol. 2008;52(19):1527-1539.

Berra

Garin

Stirnemann

, et al. Outcome in acute heart failure: prognostic value of acute kidney injury and worsening renal function. J Card Fail. 2015;21(5):382-390.

Forman

Butler

Wang

, et al. Incidence, predictors at admission, and impact of worsening renal function among patients hospitalized with heart failure. J Am Coll Cardiol. 2004;43(1):61-67.

Metra

Nodari

Parrinello

, et al. Worsening renal function in patients hospitalised for acute heart failure: clinical implications and prognostic significance. Eur J Heart Fail. 2008;10(2):188-195.

Hata

Yokoyama

Shinada

, et al. Acute kidney injury and outcomes in acute decompensated heart failure: evaluation of the RIFLE criteria in an acutely ill heart failure population. Eur J Heart Fail. 2010;12(1):32-37.

Domanski

Norman

Pitt

Haigney

Hanlon

Peyster

. Diuretic use, progressive heart failure, and death in patients in the studies of left ventricular dysfunction (SOLVD). J Am Coll Cardiol. 2003;42(4):705-708.

Mullens

Abrahams

Francis

, et al. Importance of venous congestion for worsening of renal function in advanced decompensated heart failure. J Am Coll Cardiol. 2009;53(7):589-596.

Damman

van Deursen

Navis

Voors

van Veldhuisen

Hillege

. Increased central venous pressure is associated with impaired renal function and mortality in a broad spectrum of patients with cardiovascular disease. J Am Coll Cardiol. 2009;53(7):582-588.

Sun

Guo

Wang

, et al. Central venous pressure and acute kidney injury in critically ill patients with multiple comorbidities: a large retrospective cohort study. BMC Nephrol. 2022;23(1):83.

10.

Tang

WHW

Mullens

. Cardiorenal syndrome in decompensated heart failure. Heart. 2010;96(4):255-260.

11.

Mavrakanas

Khattak

Singh

Charytan

. Echocardiographic parameters and renal outcomes in patients with preserved renal function, and mild- moderate CKD. BMC Nephrol. 2018;19(1):176.

12.

Boorsma

Ter Maaten

Voors

van Veldhuisen

. Renal compression in heart failure. JACC Heart Fail. 2022;10(3):175-183.

13.

Pellicori

Kaur

Clark

. Fluid management in patients with chronic heart failure. Card Fail Rev. 2015;1(2):90-95.

14.

McGee

. Physical examination of venous pressure: a critical review. Am Heart J. 1998;136(1):10-18.

15.

Cook

. Clinical assessment of central venous pressure in the critically ill. Am J Med Sci. 1990;299(3):175-178.

16.

Setoguchi

Stevenson

Schneeweiss

. Repeated hospitalizations predict mortality in the community population with heart failure. Am Heart J. 2007;154(2):260-266.

17.

Rubio-Gracia

Demissei

ter Maaten

, et al. Prevalence, predictors and clinical outcome of residual congestion in acute decompensated heart failure. Int J Cardiol. 2018;258:185-191.

18.

Elhassan

Chao

Curiel

. The conundrum of volume status assessment: revisiting current and future tools available for physicians at the bedside. Cureus. 2021;13:e15253.

19.

Argaiz

Koratala

Reisinger

. Comprehensive assessment of fluid status by point-of-care ultrasonography. Kidney360. 2021;2(8):1326-1338.

20.

Koratala

Kazory

. Point of care ultrasonography for objective assessment of heart failure: integration of cardiac, vascular, and extravascular determinants of volume status. Cardiorenal Med. 2021;11(1):5-17.

21.

Leidi

Soret

Mann

, et al. Eight versus 28-point lung ultrasonography in moderate acute heart failure: a prospective comparative study. Intern Emerg Med. 2022;17:1375-1383. https://link.springer.com/10.1007/s11739-022-02943-9. Accessed April 28, 2022.

22.

Ponikowski

Voors

Anker

, et al. 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European society of cardiology (ESC) developed with the special contribution of the heart failure association (HFA) of the ESC. Eur Heart J. 2016;37(27):2129-2200.

23.

Lichtenstein

. Lung ultrasound in the critically ill. Ann Intensive Care. 2014;4(1):1.

24.

Gargani

Pang

Frassi

, et al. Persistent pulmonary congestion before discharge predicts rehospitalization in heart failure: a lung ultrasound study. Cardiovasc Ultrasound. 2015;13(1):40.

25.

Dini

Demmer

Simioniuc

, et al. Right ventricular dysfunction is associated with chronic kidney disease and predicts survival in patients with chronic systolic heart failure. Eur J Heart Fail. 2012;14(3):287-294.

26.

Ghio

Recusani

Klersy

, et al. Prognostic usefulness of the tricuspid annular plane systolic excursion in patients with congestive heart failure secondary to idiopathic or ischemic dilated cardiomyopathy. Am J Cardiol. 2000;85(7):837-842.

27.

Lang

Badano

Mor-Avi

, et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. Eur Heart J Cardiovasc Imaging. 2015;16(3):233-271.

28.

Picano

Pellikka

. Ultrasound of extravascular lung water: a new standard for pulmonary congestion. Eur Heart J. 2016;37(27):2097-2104.

29.

Lichtenstein

Mezière

Biderman

Gepner

. The comet-tail artifact: an ultrasound sign ruling out pneumothorax. Intensive Care Med. 1999;25(4):383-388.

30.

Lichtenstein

Mezière

. Relevance of lung ultrasound in the diagnosis of acute respiratory failure*: the BLUE protocol. Chest. 2008;134(1):117-125.

31.

Lichtenstein

Mezière

. A lung ultrasound sign allowing bedside distinction between pulmonary edema and COPD: the comet-tail artifact. Intensive Care Med. 1998;24(12):1331-1334.

32.

Frassi

Gargani

Gligorova

Ciampi

Mottola

Picano

. Clinical and echocardiographic determinants of ultrasound lung comets☆. Eur J Echocardiogr. 2007;8(6):474-479.

33.

Agricola

Bove

Oppizzi

, et al. “Ultrasound comet-tail images”: a marker of pulmonary edema. Chest. 2005;127(5):1690-1695.

34.

Miglioranza

Gargani

Sant’Anna

, et al. Lung ultrasound for the evaluation of pulmonary congestion in outpatients. JACC Cardiovasc Imaging. 2013;6(11):1141-1151.

35.

Platz

Lewis

Uno

, et al. Detection and prognostic value of pulmonary congestion by lung ultrasound in ambulatory heart failure patients. Eur Heart J. 2016;37(15):1244-1251.

36.

Ricci

Aguilhon

Occean

, et al. Impact of daily bedside echocardiographic assessment on readmissions in acute heart failure: a randomized clinical trial. J Clin Med. 2022;11(7):2047.

37.

Marini

Fragasso

Italia

, et al. Lung ultrasound-guided therapy reduces acute decompensation events in chronic heart failure. Heart. 2020;106(24):1934-1939.

38.

Panuccio

Tripepi

Parlongo

, et al. Lung ultrasound to detect and monitor pulmonary congestion in patients with acute kidney injury in nephrology wards: a pilot study. J Nephrol. 2020;33(2):335-341.

39.

Aloia

Cameli

D’Ascenzi

Sciaccaluga

Mondillo

. TAPSE: an old but useful tool in different diseases. Int J Cardiol. 2016;225:177-183.

40.

Wallace

Allison

Stone

. Inferior vena cava percentage collapse during respiration is affected by the sampling location: an ultrasound study in healthy volunteers. Acad Emerg Med. 2010;17(1):96-99.

41.

Millington

. Ultrasound assessment of the inferior vena cava for fluid responsiveness: easy, fun, but unlikely to be helpful. Can J Anaesth. 2019;66(6):633-638.

42.

Bhardwaj

Vikneswaran

Rola

, et al. Combination of inferior vena cava diameter, hepatic venous flow, and portal vein pulsatility index: venous excess ultrasound score (VEXUS score) in predicting acute kidney injury in patients with cardiorenal syndrome: a prospective cohort study. Indian J Crit Care Med. 2020;24(9):783-789.

43.

Pellicori

Platz

Dauw

, et al. Ultrasound imaging of congestion in heart failure: examinations beyond the heart. Eur J Heart Fail. 2021;23(5):703-712.

44.

Wang

Harrison

Dranow

Aliyev

Khor

. Accuracy of ultrasound jugular venous pressure height in predicting central venous congestion. Ann Intern Med. 2022;175(3):344-351.

45.

Brisco

Zile

Hanberg

, et al. Relevance of changes in serum creatinine during a heart failure trial of decongestive strategies: insights from the DOSE trial. J Card Fail. 2016;22(10):753-760.

46.

Ahmad

Jackson

Rao

, et al. Worsening renal function in patients with acute heart failure undergoing aggressive diuresis is not associated with tubular injury. Circulation. 2018;137(19):2016-2028.

Point-of-Care Ultrasonography and Worsening of Renal Function in Acute Heart Failure: A Cohort Study

Abstract

Introduction:

Methods:

Results:

Conclusion:

Keywords

Introduction

Methods

Point-of-Care Ultrasonography

Study Variables

Statistical Analysis

Results

Discussion

Footnotes

Author Contributions

Declaration of Conflicting Interests

Funding

Statement of Ethics

ORCID iD

Data Availability

References