https://orcid.org/0009-0000-7216-6104
Figures
Abstract
Background
There is still a significant gap in understanding the impact of concomitant or previous cancer diagnoses on clinical outcomes of acute myocardial infarction (AMI)
Objective
To provide updated evidence on the effect of concomitant or previous cancer diagnoses on mortality and risk of complications, specifically major bleeding, myocardial reinfarction, and stroke, of patients with AMI.
Methods
A literature search was conducted across PubMed, EMBASE, and Scopus databases. English-language cohort studies published in peer-reviewed journals were included. Pooled effect estimates were calculated using random-effects models and reported as odds ratio (OR) or hazards ratio (HR) with 95% confidence intervals (CI). The certainty of the evidence was assessed using the standard GRADE approach.
Results
A total of 22 studies were included. AMI patients with previous or concurrent cancer had increased risk of in-hospital mortality (OR 1.44, 95% CI: 1.20, 1.73), in-hospital mortality related to cardiovascular complications (OR 2.06, 95% CI: 1.17, 3.65), mortality at 30-days follow up (OR 1.47, 95% CI: 1.24, 1.74) and mortality at 1 year follow up (HR 2.67, 95% CI: 1.73, 4.11), compared to patients without cancer. The risk of major bleeding (OR 1.74, 95% CI: 1.40, 2.16), reinfarction (OR 1.20, 95% CI: 1.05, 1.37), and stroke (OR 1.16, 95% CI: 0.99, 1.37) was also higher in patients with previous or concurrent cancer. The certainty of evidence was rated as "low" for all outcomes, except for the risk of major bleeding, which was rated as "very low."
Conclusion
Based on the low to very low certainty of evidence, we conclude that the presence of previous cancer diagnosis or concurrent cancer may increase the risk of adverse outcomes in patients with AMI. Early interventions, such as close monitoring of cardiac function, lifestyle modifications, and targeted pharmacological therapies, might help mitigate the risk of AMI and improve overall clinical outcomes. However, further methodologically rigorous studies are needed to validate the findings of this review.
Citation: Wang J, Yu J (2025) A meta-analysis on the impact of concurrent or pre-existing cancer diagnosis on acute myocardial infarction outcomes. PLoS ONE 20(1): e0318437. https://doi.org/10.1371/journal.pone.0318437
Editor: Jie Yang, Sichuan University, CHINA
Received: July 11, 2024; Accepted: January 15, 2025; Published: January 31, 2025
Copyright: © 2025 Wang, Yu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Cardiovascular diseases, such as acute myocardial infarction (AMI), and cancer are among the most substantial contributors to global morbidity and mortality [1–3]. Advances in early detection and improvements in cancer treatments have led to an ever-increasing population of cancer survivors. However, such patients often face long-term health implications and are at a higher risk for cardiovascular incidents [4,5]. The increased risk of cardiovascular morbidities persists even after cancer treatments have been completed [6,7]. Furthermore, both cancer and AMI share risk factors such as old age, smoking, hypertension, diabetes, and obesity [8,9]. Malignancy exerts detrimental effects on the cardiovascular system. Chronic inflammation, a hallmark of cancer, can induce and exacerbate atherosclerosis, leading to an increased risk of cardiovascular diseases [10,11]. Additionally, cancer-associated factors can promote endothelial damage, impair vascular function, and disturb the delicate balance of thrombotic and fibrinolytic processes, further contributing to cardiovascular complications [12,13].
Due to the acute, life-threatening nature of AMI, understanding the impact of a cancer diagnosis on AMI outcomes is crucial for optimizing patient management and improving overall care. While there is a substantial body of literature examining the impact of pre-existing or concurrent cancer on AMI outcomes, this association is still unclear due to the lack of consistency across studies. Existing studies vary in their designs, populations, and reported outcomes, making it difficult to draw definitive conclusions about the overall risks that cancer patients face when experiencing AMI.
Previous meta-analyses attempted to address this issue but with certain limitations [14,15]. Dongchen et al. conducted a meta-analysis that incorporated data from 10 studies. However, their analysis missed some of the published studies on the topic [14]. The key findings of the meta-analysis were that cancer patients experiencing AMI had increased risks of all-cause mortality, recurrent myocardial infarction, and major bleeding. However, no notable disparities were observed in the risk of mortality attributable to cardiovascular causes or the risk of stroke. Similarly, another meta-analysis conducted by Balakrishna et al. only included 7 studies with percutaneous coronary intervention (PCI), which significantly limited the scope of the analysis [15], and found that cancer patients undergoing PCI had higher rates of mortality and need for blood transfusion. However, no significant variances in the risk of myocardial reinfarction or stroke were identified.
The current meta-analysis aimed to provide updated evidence on the impact of concomitant or previous cancer diagnoses on the clinical outcomes of patients with AMI. The outcomes of interest for this study are mortality and risk of complications (major bleeding, myocardial reinfarction and stroke).
Methodology
Compliance with relevant guidelines
PRISMA guidelines were followed [16] (S1 File). The study protocol was registered in PROSPERO (CRD42024526099).
Identification of studies
Medline via PubMed, Embase, and Scopus databases were searched. The search terms included a combination of keywords: (active malignancy or concurrent cancer or cancer survivor or prior cancer) AND (cardiac disease or acute myocardial infarction OR myocardial infarction or AMI or myocardial ischemia) AND (mortality or survival or complications or clinical outcome or prognosis). The detailed search strategy for each of the three databases has been presented in S1–S3 Tables. The search was limited to studies published until 10th March 2024. Furthermore, to ensure thoroughness, we conducted manual searches of reference lists and relevant review articles, thus supplementing the electronic search process to include any additional studies that might have been overlooked.
The outcomes of interest were mortality and complications (major bleeding, reinfarction, and stroke). The operational definitions for major bleeding, reinfarction, and stroke were adopted as specified in the individual studies. For the mortality outcome, the primary interest was to examine risk of mortality within one year of follow-up, including in-hospital mortality and mortality within 30 days. Additionally, we also examined the risk of mortality at more than one year of follow-up.
Included studies focused on evaluating outcomes of interest in patients with both AMI and cancer (either previous or concurrent). A comparison group included patients with AMI but without a cancer diagnosis. We focused on studies reporting outcomes in the general population of patients with acute myocardial infarction (AMI). Studies that exclusively examined specific subgroups of AMI, such as patients with cardiogenic shock or cardiac arrest, were excluded. We preferred to include studies with a cohort design, either prospective or retrospective, and those that either presented confounder adjusted estimates or had done propensity score matching to account for baseline differences in participant characteristics. Only studies published in peer-reviewed journals, conducted on human subjects, and available in English were considered. Only studies that obtained a quality assessment score of 6 or more, from the maximum score of 9, based on the Newcastle-Ottawa Scale (NOS) assessment, were eligible for inclusion [17]. Studies not directly addressing the impact of cancer on AMI outcomes, case reports, letters, reviews, and conference abstracts, studies lacking a control group, studies with insufficient data, presenting unadjusted effect sizes or substantial bias were excluded.
After implementing the search strategy in the designated databases, studies were deduplicated. Subsequently, two authors reviewed the titles and abstracts of the remaining studies to assess their potential relevance to the research question. Selected studies showing potential relevance underwent further evaluation. In the subsequent stage, a thorough examination of the full text was conducted to ascertain the eligibility for inclusion. Any discrepancies or disagreements regarding study inclusion were resolved through discussions.
Data extraction and quality assessment
The data extraction process from the final set of studies was independently conducted by two authors using a standardized data extraction form. In cases of any disparities between the two authors, discussions were initiated to reconcile and reach a consensus. The Newcastle-Ottawa Scale (NOS) was used to evaluate the risk of bias within the included studies [17]. Two study authors independently carried out the quality assessment.
Statistical analysis
The pooled effect sizes were reported as odds ratios (OR) or hazard ratios (HR) with 95% confidence intervals (CI). A random-effects model was used for all the analyses to account for the differences in the baseline characteristics of the studies [18]. Egger’s test and funnel plots were used to assess publication bias [19]. A p-value less than 0.05 denoted statistical significance. Subgroup analyses were conducted based on whether the study included subjects with prior or concurrent cancer and whether percutaneous intervention (PCI) was the primary treatment modality. We evaluated the certainty of the evidence using the standard GRADE approach (gradepro.org) and GRADE Pro Software [20].
Results
The initial search across the databases yielded 1284 studies. After eliminating 339 duplicates, the titles and abstracts of the remaining 945 studies underwent screening, and an additional 916 studies were excluded. A thorough full-text review of the remaining 29 studies was conducted, excluding 7 additional studies that did not meet our criteria (S2 File). The screening process and the reasons for exclusion are described in Fig 1. No studies were excluded solely based on obtaining an NOS score of less than 6. Our final analysis comprised 22 studies [21–42]. Detailed study information is provided in Table 1.
NOS quality assessment scores of the included studies ranged from 7 to 9, with a mean score of 7.7, indicating high quality. The quality assessment of the individual studies is presented in S4 and S5 Tables. All included studies were retrospective; most used registry-based data or data from medical records. Most of the studies were conducted in Japan (n = 7), followed by five studies in the United States and two in Israel. One study each was conducted in France, the United Kingdom, Singapore, the Netherlands, China, Canada, and Switzerland. One multicentric study was conducted in different institutions across Europe. In 11 studies, the included patients had prior cancer and were cancer survivors. In the remaining 11 studies, the patients had concurrent cancer. In the majority of the studies (n = 16), the primary modality of management was PCI. There was one study by Ye et al (2023) that presented separate findings from the analysis of two different large databases (eICU Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care IV (MIMIC-IV) database) [26]. Therefore, for the present analysis, this study was considered as two individual studies and labeled as Ye_A (2023) and Ye_B (2023) (Table 1). Most studies reported baseline differences among the study participants between the two groups (patients with or without previous/concurrent cancer) regarding age, sex distribution, and the proportion of patients with comorbidities. Patients with previous/concurrent cancer were usually older, of the male gender, and had a higher prevalence of diabetes, hypertension, peripheral vascular disease, previous stroke, and previous myocardial infarction (MI). The included studies had variability in the definitions adopted for non-mortality outcomes (major bleeding, reinfarction, and stroke). Most included studies reported confounder-adjusted findings or findings from multivariable regression analysis. Some studies employed propensity score matching to adjust baseline participant characteristics. In these cases, most characteristics were balanced between the groups, eliminating the need for further adjustment in the analytic model. The generation of pooled estimates in this meta-analysis was based on adjusted findings from each of the included studies.
Mortality outcomes
Patients with previous or concurrent cancer and AMI had an increased risk of in-hospital mortality (OR 1.44, 95% CI: 1.20, 1.73; n = 13, I2 = 90.2%), mortality at 30-days follow up (OR 1.47, 95% CI: 1.24, 1.74; n = 7, I2 = 92.2%) and mortality at 12 months of follow up (HR 2.67, 95% CI: 1.73, 4.11; n = 3, I2 = 92.0%) (Figs 2 and 3). AMI patients with previous or concurrent cancer exhibited a higher risk of in-hospital mortality related to cardiovascular complications (OR 2.06, 95% CI: 1.17, 3.65; n = 4, I2 = 55.4%) (Fig 2).
Despite the limitations of pooling findings from follow-up periods of more than one year, with varying durations, the analysis showed an increased risk of all-cause mortality in patients with previous or concurrent cancer (HR 1.87, 95% CI: 1.65, 2.11; n = 15, I2 = 94.0%), while no statistically significant increase in cardiovascular-related mortality was observed (HR 1.20, 95% CI: 0.96, 1.50; n = 10, I2 = 74.4%) for the same population (S1 Fig).
The examination of the funnel plots and Egger’s test (p>0.05) did not indicate the presence of publication bias for mortality outcomes at any of the above-mentioned time points (S2–S4 Figs). According to the GRADE assessment criteria, the overall certainty of evidence for mortality-related outcomes was “low” (S6 Table).
The subgroup analysis revealed that individuals with both prior and concurrent cancer had an elevated risk of mortality across all time points, including in-hospital, at 30-days follow-up, and at 1 year of follow-up (Table 2; S5–S13 Figs). When the analysis was restricted to studies with PCI as the primary intervention modality, the risk of mortality continued to be higher at all time points in patients with previous or concurrent cancer compared with patients who did not have a cancer diagnosis (Table 2; S5–S13 Figs).
Risk of complications
In patients with previous or concurrent cancer, the risk of major bleeding (OR 1.74, 95% CI: 1.40, 2.16; n = 12, I2 = 95.8%) and reinfarction (OR 1.20, 95% CI: 1.05, 1.37; n = 12, I2 = 88.9%) was significantly higher compared to patients without cancer (Fig 4).
Patients with AMI and previous or concurrent cancer were at a higher risk of stroke (OR 1.16, 95% CI: 0.99, 1.37; n = 11, I2 = 89.3%. However, the difference was not statistically significant (Fig 4). The presence of publication bias for the outcome of "major bleeding" was detected, as indicated by both the funnel plot and Egger’s test (p = 0.04) (S14 Fig). However, no indication of publication bias was found for the outcomes of reinfarction and stroke based on the same assessments (S15 and S16 Figs). The certainty of evidence for the risk of major bleeding was assessed as "very low," while the certainty for the risk of reinfarction and stroke was rated as "low," based on the GRADE assessment criteria (S6 Table).
Subgroup analyses showed that the risk of major bleeding was increased in patients with previous cancer (OR 1.45, 95% CI: 1.25, 1.69; n = 5, I2 = 43.3%), concurrent cancer (OR 1.85, 95% CI: 1.43, 2.38; n = 7, I2 = 92.0%) and patients managed using PCI (OR 1.68, 95% CI: 1.41, 2.00; N = n = 9, I2 = 75.5%) (Table 2; S5–S13 Figs). The risk of reinfarction was significantly higher in patients undergoing PCI (OR 1.28, 95% CI:1.10, 1.49; n = 10; I2 = 90.4%) (S20 Fig). While not statistically significant, patients with concurrent cancer (but not prior cancer) had a higher risk of reinfarction compared to those without cancer (Table 2; S21 and S22 Figs). No statistically significant difference in the risk of stroke was detected by subgroup analyses based on the PCI as a management modality, prior cancer, or concurrent cancer (Table 2; S23–S25 Figs).
Discussion
The present meta-analysis aimed to assess the impact of previous or concurrent cancer diagnoses on the risk of mortality and other complications in patients with AMI. The findings of our meta-analysis revealed a significant association between previous or concurrent cancer diagnoses and increased mortality, risk of major bleeding, reinfarction, and possibly stroke in this group of patients. The certainty of the evidence for the pooled findings was “low” to “very low”. Therefore, further robust and methodologically rigorous studies are needed to confirm these conclusions.
Our findings are consistent with the outcomes of two previous meta-analyses on this subject [14,15]. More specifically, our findings further confirm the results reported by Dongchen et al wherein patients with AMI were found to have a higher risk of mortality (all-cause), recurrent myocardial infarction, and major bleeding [14]. This review noted no significant difference in the risk of mortality due to cardiovascular causes or the risk of stroke. Another meta-analysis conducted by Balakrishna et al also documented that cancer patients undergoing PCI had higher rates of mortality and a need for blood transfusion (indicating major bleeding) [15]. However, the review did not find significant differences in the risk of myocardial reinfarction and stroke.
The underlying mechanisms for increased risk of mortality could be multifactorial. Cancer is associated with chronic inflammation, which can promote atherosclerosis, impair vascular function, and increase the risk of thrombotic events [10,43,44]. Furthermore, cancer-related treatments such as chemotherapy, radiation, and targeted therapies may have cardiotoxic and vascular toxic effects, leading to cardiac and vascular dysfunction and subsequent adverse outcomes in AMI patients [45–48]. Such patients often have a higher prevalence of other chronic conditions, such as diabetes, hypertension, and renal dysfunction, which can adversely affect the management and outcomes of AMI [49]. Additionally, cancer-related factors such as tumor burden, metastasis, and treatment-related immunosuppression may make AMI patients more susceptible to adverse events and complications [50,51]. Furthermore, patients with cancer might have delayed or suboptimal access to cardiac care, as the focus of their healthcare may primarily revolve around cancer treatment. This delay in seeking medical attention or receiving appropriate cardiovascular interventions could also contribute to worse outcomes.
Our analysis demonstrated a higher risk of major bleeding in patients with AMI with previous or concurrent cancer. Cancer can lead to coagulation system abnormalities, such as thrombocytopenia, impaired platelet function, or alterations in clotting factors [44–46]. Additionally, cancer treatments, particularly anticoagulant therapies and antiplatelet agents, may further contribute to the increased bleeding risk [52]. The presence of cancer-related comorbidities, such as liver dysfunction or gastrointestinal involvement, can also enhance the propensity for bleeding in this population [53,54]. We also found an increased risk of reinfarction, which may be the result of cancer-related systemic inflammation, accelerated atherosclerosis, and impaired vascular healing, contributing to the destabilization of coronary plaques and subsequent reinfarction [43–46]. Moreover, the cardiotoxic effects of cancer treatments may further exacerbate the risk of recurrent ischemic events [47,48]. The meta-analysis identified an increased risk of stroke in this patient population. The mechanisms underlying this association could be related to hypercoagulability, endothelial dysfunction, and increased inflammatory markers, promoting a prothrombotic state and predisposing individuals to ischemic stroke [11,12,45,46].
It is important to acknowledge some limitations of this meta-analysis. First, the included studies were primarily observational (retrospective cohort design). While a retrospective study design can be a practical and suitable approach for addressing the research question dealt with in this meta-analysis, it has certain limitations. Retrospective studies help investigate long-term outcomes, large populations, and rare events like AMI in cancer patients, as they enable broad data collection from medical records or registries. However, they also pose challenges, such as potential biases (e.g., selection bias, recall bias), incomplete data, and difficulty controlling for confounders. In this analysis, the included studies employed appropriate confounder adjustments (e.g., multivariable analysis, propensity score matching). However, there is still a risk of some unmeasured and unadjusted confounding factors and consequent bias. Second, heterogeneity was observed for many of the outcomes. This variability may be due to variations in patient characteristics, study settings, differential definitions of the outcomes among studies, and treatments offered. Although we employed a random-effects model to account for this heterogeneity, caution should be exercised when interpreting the pooled results. Most of the included studies did not provide specific information about the type and stage of cancer or the mode of cancer management, which may have limited our overall analysis and contributed to heterogeneity in our results. Therefore, further high-quality studies are needed to validate the findings of our meta-analysis. Additionally, pooling studies with differing follow-up periods beyond the first year can be a limitation. Time-to-event data should be consistent across studies to ensure accurate estimates. However, the included studies had variable follow-up durations, which technically prevented pooling. Despite this, we opted to pool these findings to provide a fair indication of the risk. Another limitation is related to the fact that we were unable to perform subgroup analysis based on the type of AMI (i.e., ST-segment elevated MI (STEMI) and non-STEMI) because most studies predominantly reported data on patients with STEMI (N = 10) and some studies did not report the type of acute myocardial infarction at all (N = 7). Also, potential limitation of our study is the exclusion of studies focusing on specific subgroups of AMI, such as those with cardiogenic shock or cardiac arrest. While our objective was to synthesize data on the broader AMI population, we recognize that outcomes in these high-risk subgroups may differ significantly. This exclusion may limit the generalizability of our findings.
Conclusion
Our study suggests that the presence of previous or concurrent cancer diagnoses in patients with AMI is associated with increased mortality and complications such as major bleeding, reinfarction, and stroke. Our findings highlight the importance of a multidisciplinary approach between oncologists, cardiologists, and other healthcare professionals to ensure comprehensive care that addresses both cancer-related concerns and cardiovascular health. Early cardioprotective interventions that are tailored to the specific needs of cancer patients can help mitigate the risk of MI and improve overall cardiovascular outcomes. Such interventions may include closely monitoring cardiac function, lifestyle modifications, and targeted pharmacological interventions. Further research is needed to investigate the specific mechanisms underlying these associations, as well as the impact of different cancer types, stages, and treatments on patient outcomes.
Supporting information
S1 Fig. Pooled risk of mortality at more than 1 year follow-up.
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S2 Fig. Funnel plot for in-hospital mortality.
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S4 Fig. Funnel plot for mortality at 1 year of follow up.
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S5 Fig. Pooled risk of in-hospital mortality among subgroup of patients undergoing PCI.
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S6 Fig. Pooled risk of in-hospital mortality among subgroup of patients with prior cancer.
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S7 Fig. Pooled risk of in-hospital mortality among subgroup of patients with concomitant cancer.
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S8 Fig. Pooled risk of 30-day mortality among subgroup of patients undergoing PCI.
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S9 Fig. Pooled risk of 30-day mortality among subgroup of patients with prior cancer.
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S10 Fig. Pooled risk of 30-day mortality among subgroup of patients with concomitant cancer.
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S11 Fig. Pooled risk of mortality at 1 year of follow-up among subgroup of patients undergoing PCI.
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S12 Fig. Pooled risk of mortality at 1 year of follow-up among subgroup of patients with prior cancer.
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S13 Fig. Pooled risk of mortality at 1 year of follow-up among subgroup of patients with concomitant cancer.
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S14 Fig. Funnel plot for risk of major bleeding.
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S15 Fig. Funnel plot for risk of reinfarction.
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S17 Fig. Pooled risk of major bleeding among subgroup of patients undergoing PCI.
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S18 Fig. Pooled risk of major bleeding among subgroup of patients with prior cancer.
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S19 Fig. Pooled risk of major bleeding among subgroup of patients with concomitant cancer.
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S20 Fig. Pooled risk of reinfarction among subgroup of patients undergoing PCI.
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S21 Fig. Pooled risk of reinfarction among subgroup of patients with prior cancer.
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S22 Fig. Pooled risk of reinfarction among subgroup of patients with concomitant cancer.
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S23 Fig. Pooled risk of stroke among subgroup of patients undergoing PCI.
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S24 Fig. Pooled risk of stroke among subgroup of patients with prior cancer.
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S25 Fig. Pooled risk of stroke among subgroup of patients with concomitant cancer.
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S4 Table. Author’s judgements about study quality using the Newcastle Ottawa Risk of Bias Assessment tool.
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S5 Table. Author’s judgements about study quality using the Newcastle Ottawa Risk of Bias Assessment tool.
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S6 Table. Quality of the pooled evidence using the GRADE assessment.
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S2 File. Excluded studies after full text review.
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