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Abstract

Polypharmacy is becoming more prevalent due to an ageing population. As more patients are undergoing surgical procedures, it is important to determine which group of patients are at higher risk of poorer outcomes. This review aimed to provide a summary of existing literature and to determine if polypharmacy is associated with poorer perioperative outcomes and to identify any gaps in the literature. This systematic review was conducted using electronic databases PubMed, Embase and Web of Science from their inception to December 2024. Statistical analysis was performed using generic inverse variance method. We identified 45 eligible studies from different countries and different surgical populations. Thirty-two studies (71.11%) defined polypharmacy as the use of five or more medications. Polypharmacy is significantly associated with postoperative delirium (odds ratio = 1.62, 95% confidence interval = 1.32–1.98, I² = 0%). Although polypharmacy is found to be significantly associated with postoperative delirium, the relationship between polypharmacy and postoperative delirium remains complex.

Keywords

Polypharmacy Perioperative outcomes Postoperative delirium Systematic review

Introduction

Polypharmacy is the use of multiple medications, more commonly in older patients with multiple comorbidities (Krustev et al 2022). Although different definitions exist in the literature, polypharmacy is usually defined as the use of five or more medications (Masnoon et al 2017). Polypharmacy is associated with poorer health outcomes such as drug interactions and adverse drug events, but is becoming more common due to the burden of chronic diseases in an ageing population (Kim et al 2024, Maher et al 2014). Moreover, more than 300 million major surgical procedures are performed yearly, and as the demand for surgical procedures continues to increase, many of these patients with polypharmacy will undergo surgical procedures (Etzioni et al 2003, Weiser et al 2015).

Preoperative screening tools can be useful to aid preoperative optimisation and risk counselling as they help to identify patients who are at high risk of postoperative complications (Aitken et al 2021). Polypharmacy is included in some preoperative screening tools such as the comprehensive geriatric assessment (CGA). CGA evaluates other domains such as function, nutrition, cognitive, mood, comorbidity and frailty (Aitken et al 2021). Perioperative outcomes that are measured include length of stay (LOS), intensive care unit (ICU) admission, patient-centred measures such as disability-free survival and pain score have been evaluated as well (Myles 2016). A meta-analysis of six studies on gastrointestinal cancer patients evaluated the effectiveness of CGA in predicting postoperative complication (Xue et al 2018). Polypharmacy was found to be one of the predictive factors for postoperative complications.

To our knowledge, there is no systematic review that has assessed the association of polypharmacy on perioperative outcomes. The rationale for this review is to provide a summary of existing literature that evaluates the association of polypharmacy and perioperative outcomes. The primary objective of this review is to determine whether polypharmacy is associated with poorer perioperative outcomes and the secondary objective to identify any gaps in the literature with regard to this topic.

Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Page et al 2021). The inclusion criteria were English peer-reviewed journals which studied adults 18 years old and above and sought to determine the effect of polypharmacy on perioperative outcomes. Exclusion criteria were studies that involve subjects below 18 years old and non-English studies. In addition, guidelines, systematic reviews, meta-analyses, case reports and case series were excluded. We did not register a protocol for this review.

The literature search was conducted using electronic databases PubMed, Embase and Web of Science. The databases were searched from their inception to December 2024. The keywords used were (‘polypharmacy’ OR ‘multiple drugs’ OR ‘multiple medications’ OR ‘drug interaction’ OR ‘many drugs’ OR ‘many medications’) AND (‘outcome’ OR ‘outcomes’) AND (‘perioperative’ OR ‘postoperative’ OR ‘preoperative’ OR ‘operative’ OR ‘surgical’ OR ‘surgery’).

Two independent reviewers were involved in the data extraction and article selection process based on inclusion and exclusion criteria. Data such as type of study, country of study, number of patients, type of surgical procedures, definition of polypharmacy and perioperative outcomes assessed were extracted and presented accordingly.

The perioperative outcomes explored include those identified by the International Standardised Endpoints in Perioperative Medicine (StEP) initiative such as LOS, death within 30 days of surgery, death within 1 year of surgery, postoperative morbidity, admission to ICU within 14 days of surgery, readmission to hospital within 30 days of surgery, postoperative delirium and discharge disposition (Evered et al 2018, Haller et al 2019, Jackson et al 2023, Moonesinghe et al 2019). Postoperative delirium was commonly assessed using Confusion Assessment Method (Ho et al 2021). Postoperative morbidity was commonly measured using Clavien–Dindo classification (Jackson et al 2023). Grade I is defined as any complications without the need of intervention, and Grade II is complications requiring pharmacological treatment or blood transfusion. Grade III is complications requiring surgical, endoscopic or radiological intervention. Grade IV is life-threatening complications requiring ICU management. Grade V is patient death.

Patient-reported outcomes assessed include health-related quality of life (HRQOL), pain, disability and functional decline. HRQOL was measured using questionnaires such as Medical Outcomes Study Short Form 36 (SF-36) and Patient-Reported Outcomes Measurement Information System (PROMIS) (Cella et al 2010, Lins & Carvalho 2016). Disability was measured using World Health Organization Disability Assessment Schedule (WHODAS2.0) and Oswestry disability index (Ustün et al 2010). Functional decline was deemed to be present if there is decrease in WHODAS2.0. Pain was assessed using visual analogue scale (VAS) and was also included as a component of SF-36.

The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). The score ranges from 0 to 9 points, with a higher score indicating better quality. Studies with NOS scores of at least 7 are considered as high quality. For cohort studies, NOS addresses three areas, namely selection, comparability and outcome (Wells et al 2014).

Statistical analysis was performed using Review Manager Web (RevMan Web) Version 8.4.0. Studies that define polypharmacy as five or more medications were included in the meta-analysis. Outcomes from studies were pooled using unadjusted odds ratio with 95% confidence intervals (CIs), calculated using the generic inverse variance method. If odds ratio was not available, absolute numbers were used to calculate the unadjusted odds ratio. Due to heterogeneity across selected studies, random effect models were used. A p value of <0.05 was considered to be statistically significant. The I² value measured consistency between included trials in the meta-analysis. According to the Cochrane guidelines, I² value <50% was considered to be low, 50%–74% considered to be moderate and ⩾75% is considered to be high (Higgins et al 2003). Sensitivity analysis was performed using the leave-one-out method, and each study was omitted sequentially from the analysis to test the stability of the result.

Results

A total of 3459 articles were retrieved from the three databases, consisting of 800 from PubMed, 2141 from Embase and 518 from Web of Science. Figure 1 shows the PRISMA 2020 flow diagram (Page et al 2021). Out of the 3459 articles, only 45 articles were included in this review as shown in Table 1, 44 were cohort studies and one study was a case–control study (Marušič et al 2017).

Figure 1

PRISMA flow diagram

Table 1

Characteristics of included studies

Study	Country	Number of patients	Type of surgery	Polypharmacy definition	Outcomes assessed
Holden et al (2022)	USA	132	Abdominal surgery	5 or more medications	Length of stay, in-hospital complications, discharge disposition, 30-day emergency room visit, 30-day all-cause readmission, 30-day readmission for surgery-related complication, 30-day wound outcome
Pujara et al (2015)	USA	279	Cancer surgery	5 or more medications	90-day major morbidity (Clavien–Dindo grade III-IV), 90-day mortality, discharge disposition, 30-day readmission
Badgwell et al (2013)	USA	111	Cancer surgery	5 or more medications	Length of stay, 90-day morbidity or death (Clavien–Dindo grade I-V), 90-day major morbidity (Clavien–Dindo grade III-V), 90-day readmission, discharge disposition
Jeong et al (2016)	Korea	475	Cancer surgery	5 or more medications	Post operative delirium
Kenig et al (2015)	Poland	75	Cancer surgery	5 or more medications	30-day major complication (Clavien–Dindo grade III-V), 30-day all complication (Clavien–Dindo grade I-V)
Kenig et al (2022)	Poland	334	Cancer surgery	8 or more medications	30-day morbidity (Clavien–Dindo grade III-IV), 30-day mortality, 12-month mortality
van Winden et al (2022)	The Netherlands	539	Cancer surgery	5 or more medications	Treatment burden 2–4 months after surgery
Lemij et al (2022)	The Netherlands	3274	Cancer surgery	5 or more medications	30-day any postoperative complication
Souwer et al (2021)	The Netherlands	1088	Cancer surgery	5 or more medications	30-day severe complication (require Intensive care unit admission, prolonged length of stay, mortality)
Samuelsson et al (2019)	Sweden	49	Cancer surgery	5 or more medications	Postoperative complication, length of stay
Argillander et al (2022)	The Netherlands	575	Cancer surgery	5 or more mediations	30-day overall complication, 30-day severe complication (Clavien–Dindo III or more), 30-day mortality, discharge disposition, length of stay, postoperative delirium
McAlpine (2008)	Canada	103	Cancer surgery	6 or more medications	Postoperative delirium
Kristjansson et al (2010)	Norway	182	Cancer surgery	5 or more medications	30-day severe complication (Clavien–Dindo grade 2 or higher), 30-day all complication, long-term survival
Fagard et al (2017)	Belgium	190	Cancer surgery	5 or more medications	30-day complication (Clavien–Dindo grade 2 or higher)
Fagard et al (2020)	Belgium	96	Cancer surgery	5 or more medications	30-day complication (Clavien–Dindo grade 2 or higher), length of stay
Watanabe et al (2024)	Japan	236	Cancer surgery	Not defined	Any postoperative complication
Verwijmeren et al (2023)	The Netherlands	555	Cardiac surgery	5 or more medications	12-month mental health–related quality of life, 12-month physical health–related quality of life, 12-month disability, severe inpatient complication (mortality, life-threatening event including reoperative, respiratory insufficiency, reintubation, stroke, renal replacement therapy, life-threatening bleeding or readmittance into intensive care unit)
Verwijmeren et al (2020)	The Netherlands	537	Cardiac surgery	5 or more medications	3-month disability
Arends et al (2022a)	The Netherlands	518	Cardiac surgery	5 or more medications and less than 10 medications	Functional decline 1 year after surgery
Arends et al (2022b)	The Netherlands	518	Cardiac surgery	5 or more medications and less than 10 medications	Chronic pain 1 year after surgery
Dautzenberg et al (2022)	The Netherlands	210	Cardiac surgery	5 or more medications and less than 10 medications	1-year mortality, 1-year complication
Imamura et al (2023)	Japan	345	Cardiac surgery	10 or more medication	2-year mortality, 2-year heart failure readmission and 2-year all-cause readmission
Tanos et al (2023)	Belgium and England	419	Emergency general surgery	5 or more medications	90-day mortality, length of stay, 30-day readmission, 30-day mortality
Goeteyn et al (2017)	The Netherlands	98	Emergency general surgery	5 or more medications	30-day mortality, 90-day mortality, 30-day readmission
Saljuqi et al (2020)	USA	163	Emergency general surgery	3 or more medications	Postoperative delirium
Jónsdóttir et al (2023)	Iceland	55997	Emergency general surgery	5 or more medications and less than 10 medications	30-day mortality, length of stay, 30-day readmission, 1-year mortality
Yohannan et al (2024)	India	130	Orthopaedic surgery	5 or more medications	Length of stay, intensive care unit admission
Liang et al (2014)	Taiwan	232	Orthopaedic surgery	5 or more medications	Postoperative delirium
Chilakapati et al (2022)	India	161	Orthopaedic surgery	5 or more medications	6-month and 1-year health-related quality of life, 90-day readmission
Lee et al (2023)	Taiwan	1353	Orthopaedic surgery	5 or more medications	Postoperative delirium
Al-Khatib et al (2023)	England	224	Orthopaedic surgery	5 or more medications	30-day mortality, 1-year mortality
de Haan et al (2023)	The Netherlands	2051	Orthopaedic surgery	5 or more medications	Postoperative delirium
Mayordomo-Cava et al (2020)	Spain	1137	Orthopaedic surgery	5 or more medications	30-day mortality
Kawabata et al (2024)	Japan	148	Orthopaedic surgery	5 or more medications and less than 10 medications	1-year and 2-year health-related quality of life
Shen et al (2024)	China	268	Orthopaedic surgery	Not defined	Length of stay
Härstedt et al (2016)	Sweden	272	Various	Not defined	6-month readmission, 6-month mortality
Venianaki et al (2021)	Greece	501	Various	5 or more medications	Any in-hospital complication, serious in-hospital complication (Clavien–Dindo grade III or higher), in-hospital mortality
Pelavski et al (2017)	Spain	127	Various	7 or more medications	30-day mortality, in-hospital morbidity, length of stay, escalation of care
Cadwell et al (2020)	USA	1025	Various	5 or more medications	6-month mortality
Eschweiler et al (2021)	Germany	880	Various	5 or more medications	Postoperative delirium
McIsaac et al (2018)	Canada	266,499	Various	4 to 6 medications	90-day mortality, length of stay, discharge disposition, 30-day readmission, in-hospital complication
Mueller et al (2020)	Germany	651	Various	6 or more medications	Postoperative delirium
Tefera et al (2020)	Ethiopia	269	Various	Not defined	In-hospital mortality, length of stay
Ambler et al (2020)	England	410	Vascular surgery	9 or more medications	5-year mortality and 5-year readmission
Marušič et al (2017)	Slovenia	257	Not specified	8 or more medications	Deep vein thrombosis or pulmonary embolism development within 5 years of surgery

As shown in Table 1, studies were conducted in different countries. Of 45 studies, 28 studies (62.22%) were conducted in Europe, nine studies (20%) were conducted in Asia, five studies (11.11%) were conducted in the United States, two studies (4.44%) were conducted in Canada and one study (2.22%) was conducted in Africa. Studies were conducted on different surgical populations, including abdominal, cancer, cardiac, emergency, orthopaedic and vascular surgical procedures.

Of 45 studies, 32 studies (71.11%) defined polypharmacy as the use of five or more medications as shown in Table 1. Other reported cut-offs for polypharmacy ranged from three or more medications to ten or more medications. For patients on ten or more medications, two studies defined that as excessive polypharmacy and two studies defined that as hyper polypharmacy. For perioperative outcomes, nine studies (20%) evaluated postoperative delirium and 12 studies (26.67%) have evaluated on prolonged LOS. Eight studies (17.78%) evaluated 30-day complication. Eight studies (17.78%) evaluated 30-day mortality.

The studies included are of good quality, with at least seven stars in the NOS rating scale as shown in Table 2. Twenty-three studies (52.27%) had 9 stars, eight studies (18.18%) had 8 stars and 13 studies (29.55%) had 7 stars.

Table 2

Newcastle-Ottawa Scale for cohort studies (N = 44)

Author	Selection representativeness of the exposed cohort	Selection of non-exposed cohort	Ascertainment of exposure	Demonstration that outcome of interest was not present at start of study	Comparability of cohorts on the basis of design or analysis	Outcome assessment of outcome	Was follow-up long enough for outcomes to occur	Adequacy of follow-up of cohort	Total score
Timothy R Holden	*	*	*	*	**	*	*	*	9
Deep Pujara	*	*	*	*	**	*	*	*	9
Brian Badgwell	*	*	*	*	*	*	*	*	9
Young Mi Jeong	*	*	*	*	0	*	*	*	7
Jakub Kenig	*	*	*	*	**	*	*	0	8
Jakub Kenig	*	*	*	*	**	*	*	*	9
Marieke E C van Winden	*	*	*	*	**	*	*	0	8
A A Lemij	*	*	*	*	**	*	*	0	8
Esteban T D Souwer	*	*	*	*	**	*	*	*	9
Katja Schubert Samuelsson	*	*	*	*	0	*	*	*	7
T E Argillander	*	*	*	*	0	*	*	*	7
J N McAlpine	*	*	*	*	**	*	*	*	9
Siri R. Kristjansson	*	*	*	*	*	*	*	*	8
Katleen Fagard	*	*	*	*	*	*	*	*	8
Katleen Fagard	*	*	*	*	**	*	*	*	9
Takashi Watanabe	*	*	*	*	**	*	*	*	9
Lisa Verwijmeren	*	*	*	*	**	*	*	0	8
Lisa Verwijmeren	*	*	*	*	0	*	*	*	7
Britta C. Arends	*	*	*	*	**	*	*	*	9
Britta C. Arends	*	*	*	*	**	*	*	*	9
Lauren Dautzenberg	*	*	*	*	**	*	*	*	9
Teruhiko Imamura	*	*	*	*	**	*	*	*	9
Panayiotis Tanos	*	*	*	*	**	*	*	*	9
Jens Goeteyn	*	*	*	*	*	*	*	*	8
Abdul Tawab Saljuqi	*	*	*	*	**	*	*	*	9
Freyja Jónsdóttir	*	*	*	*	**	*	*	*	9
Sara Yohannan	*	*	*	*	0	*	*	*	7
Chih-Kuang Liang	*	*	*	*	0	*	*	*	7
Sai Chilakapati	*	*	*	*	**	*	*	*	9
Deng Horng Lee	*	*	*	*	0	*	*	*	7
Yousef Al-Khatib	*	*	*	*	*	*	*	*	8
Eveline de Haan	*	*	*	*	0	*	*	*	7
Jennifer Mayordomo-Cava	*	*	*	*	**	*	*	*	9
Soya Kawabata	*	*	*	*	**	*	*	*	9
Jianghua Shen	*	*	*	*	**	*	*	*	9
Maria Harstedt	*	*	*	*	**	*	*	*	9
Maria Venianaki	*	*	*	*	0	*	*	*	7
Andres D. Pelavski	*	*	*	*	0	*	*	*	7
Joshua B. Cadwell	*	*	*	*	0	*	*	*	7
Gerhard W. Eschweiler	*	*	*	*	0	*	*	*	7
Daniel I. McIsaac	*	*	*	*	**	*	*	*	9
Anika Mueller	*	*	*	*	0	*	*	*	7
Gosaye Mekonen Tefera	*	*	*	*	**	*	*	*	9
Graeme K. Ambler	*	*	*	*	**	*	*	*	9

Two studies were included in the forest plot of ICU admission in patients with polypharmacy compared to non-polypharmacy as shown in Figure 2. Polypharmacy is not significantly associated with ICU admission (odds ratio (OR) = 1.73, 95% CI = 0.96–3.10, I² = 0%). Two studies were included in the forest plot of discharge to another care facility in patients with polypharmacy compared to non-polypharmacy as shown in Figure 3. Polypharmacy is significantly associated with discharge to another care facility (OR = 1.68, 95% CI = 1.08–2.61, I² = 0%). Three studies were included in the forest plot of 30-day mortality in patients with polypharmacy compared to non-polypharmacy as shown in Figure 4. Polypharmacy is significantly associated with 30-day mortality (OR = 5.28, 95% CI = 2.50–11.17, I² = 14%). Five studies were included in the forest plot of postoperative delirium in patients with polypharmacy compared to non-polypharmacy as shown in Figure 5. Polypharmacy is significantly associated with postoperative delirium (OR = 1.62, 95% CI = 1.32–1.98, I² = 0%).

Figure 2

Forest plot of ICU admission in patients with polypharmacy compared to non-polypharmacy

Figure 3

Forest plot of discharge to another care facility in patients with polypharmacy compared to non-polypharmacy

Figure 4

Forest plot of 30-day mortality in patients with polypharmacy compared to non-polypharmacy

Figure 5

Forest plot of postoperative delirium in patients with polypharmacy compared to non-polypharmacy

Leave-one-out sensitivity analysis for 30-day mortality in Table 3 showed that with the removal of study by Tanos et al, heterogeneity I² increased from 14% to 56%. In Table 4, the leave-one-out sensitivity analysis for postoperative delirium showed no significant change in pooled effect size and heterogeneity was caused by excluding any one study.

Table 3

Leave-one-out sensitivity analysis for 30-day mortality

Study excluded	Pooled effect size (OR [95% confidence interval])	I² (%)
Al-Khatib	3.82 [1.63–8.96]	0
Argillander	7.89 [3.24–19.23]	0
Tanos	5.12 [1.51–17.36]	56

Table 4

Leave-one-out sensitivity analysis for postoperative delirium

Study excluded	Pooled effect size (OR [95% confidence interval])	I² (%)
Argillander	1.54 [1.25–1.91]	0
de Haan	1.75 [1.22–2.52]	4
Jeong	1.60 [1.29–1.97]	1
Lee	1.69 [1.36–2.11]	0
Liang	1.60 [1.29–2.00]	4

Discussion

In this systematic review, we have identified 45 studies that explored the association of polypharmacy with various perioperative outcomes. Polypharmacy is most commonly defined as the use of five or more medications. Apart from comparing perioperative outcomes between polypharmacy and non-polypharmacy groups, there were some studies that investigated the association between the number of medications and perioperative outcomes. For perioperative outcomes, there were variations in the definitions of postoperative complications and different time points were selected for evaluation of complications. Different definitions were also used to define prolonged LOS. These differences made comparison challenging.

Our meta-analysis of five studies found that polypharmacy is significantly associated with postoperative delirium (Argillander et al 2022, de Haan et al 2023, Jeong et al 2016, Lee et al 2023, Liang et al 2014). The sensitivity analysis showed stability of results as no significant change in pooled effect size and heterogeneity was caused by excluding any one study. This finding presents a different perspective compared to the existing literature. A prior systematic review by Kassie et al, evaluating preoperative medication use and postsurgical delirium, found that there were limited number of high-quality studies that quantify the direct association between preoperative medication use and postsurgical delirium (Kassie et al 2017). Polypharmacy is known to be associated with delirium, but explanation of the link between polypharmacy and delirium remains complex (Hein et al 2014). Classes of medications that may induce delirium include anticholinergics, benzodiazepines and narcotics. These are commonly prescribed in the healthcare systems and some may be used as anaesthetic agents (Alagiakrishnan & Wiens 2004, Ghossein et al 2024, Smith et al 2024). However, it is also important to take note that delirium assessment tools only reveal the patient’s state at the time of assessment, and the frequency of postoperative delirium may increase with increased charting by healthcare professionals (Young et al 2022).

Our meta-analysis also found that polypharmacy is significantly associated with 30-day mortality and discharge to another care facility. However, a small number of studies were included in these meta-analyses. Furthermore, the sensitivity analysis for 30-day mortality showed that the removal of the study by Tanos et al led to increase in heterogeneity from 14% to 56%. This suggests that more studies are needed to investigate the association between polypharmacy and 30-day mortality as well as polypharmacy with discharge to another care facility. There is complex interplay between polypharmacy, frailty and chronic comorbidity, which may be associated with higher mortality. Poorer recovery after an operation may result in higher care needs, requiring transfer to care facilities such as a nursing home, instead of discharging patients back home (van Dam et al 2022).

Preoperative deprescribing is a possible consideration for patients with polypharmacy. A systematic review and meta-analysis identified 16 articles that studied deprescribing intervention (Lee et al 2022). It was found that deprescribing interventions were associated with positive or neutral outcomes. However, some studies included patients without polypharmacy. Furthermore, the authors highlighted that the evidence is weak due to heterogeneity of interventions and outcomes. In addition, polypharmacy is closely associated with comorbidities and frailty (van Dam et al 2022). This needs to be taken into consideration when deprescribing. Potential harms of deprescribing include adverse drug withdrawal reactions, pharmacokinetic and pharmacodynamic changes and return of medical condition (Reeve et al 2014).

Apart from clinical outcomes, this systematic review identified only six articles that evaluated patient-reported outcomes. Four of the six studies were derived from the Anaesthesia Geriatric Evaluation study cohort that included patients 70 years and above who underwent elective open-heart surgical procedure, and patient-reported outcomes were physical and mental HRQOL, disability and functional decline by using SF-36 and WHODAS2.0 questionnaires (Arends et al 2022a, 2022b, Verwijmeren et al 2020, Verwijmeren et al 2023). Another study was conducted on a cohort of spinal deformity patients aged 65 years and above, and patient-reported outcomes were disability, pain, and physical, mental and social wellbeing, measured by Oswestry Disability Index, VAS and PROMIS, respectively (Chilakapati et al 2022). The last study was conducted on patients with lumbar spine stenosis, and the HRQOL was assessed using questionnaires commonly used in patients with lumbar spinal stenosis, namely, Zurich Claudication Questionnaire (ZCQ), the Roland Morris Disability Questionnaire (RDQ) and the Japanese Orthopaedic Association Back Pain Evaluation Questionnaire (JOABPEQ) (Kawabata et al 2024). Different questionnaires were utilised in different studies with different time points and study populations. Thus, it may be difficult to compare outcomes between these studies.

This systematic review provides a comprehensive review of the articles that evaluate association of polypharmacy with various perioperative outcomes in different surgical populations across different countries. Our study identified key perioperative outcomes associated with polypharmacy. Given the increasing prevalence of polypharmacy, especially among the elderly population, it is important for perioperative practitioners to identify patients at higher risk of developing perioperative complications and, where possible, implement additional precautionary measures to mitigate these risks. Furthermore, our study highlighted areas for future research in perioperative practice, particularly in exploring more patient-reported outcomes during the perioperative period. Some limitations of our systematic review include significant heterogeneity as populations are drawn from different countries and surgical specialities. Furthermore, our analysis is limited by risk of bias from missing data and reporting from individual studies.

In conclusion, polypharmacy is found to be significantly associated with postoperative delirium. However, the relationship between polypharmacy and postoperative delirium is complex. Reduction of polypharmacy through deprescribing may potentially be explored for future research. More studies are needed to determine whether polypharmacy is associated with other perioperative outcomes. Patient-reported outcomes are not commonly evaluated as perioperative outcomes, and this may be an area for future research.

Footnotes

Acknowledgements

This work was carried out solely by the listed authors.

Author contributions

Y.L. and Y.L. prepared the manuscript draft. All authors revised the draft critically for important intellectual content and agreed to the final submission.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

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

ORCID iD

Yixuan Lee

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Association of polypharmacy and perioperative outcomes: Systematic review and meta-analysis

Abstract

Keywords

Introduction

Methods

Results

Discussion

Footnotes

Acknowledgements

Author contributions

Declaration of conflicting interests

Funding

ORCID iD

References