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Cause of Death

Clinical Research · NLM MeSH · updated 2026-10-29 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 10 min read

Factors which produce cessation of all vital bodily functions.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (2,019 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

Factors which produce cessation of all vital bodily functions. They can be analyzed from an epidemiologic viewpoint.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Causes of Death; Death Cause; Death Causes.

Where it fits in the MeSH classification

Broader topics
Mortality

Research landscape

PubMed indexes 59,297 records tagged with the MeSH heading “Cause of Death” (counts retrieved 2026-10-29). 10,389 of them (17.5%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 20,815 records.

Reviews account for 5,247 records (8.8%) and meta-analyses for 1,539. Randomized controlled trials number 1,521 (2.6%) as a share of all records on the topic.

PubMed records by publication periodthrough 1999: 13,713 records; 2000-2009: 14,380 records; 2010-2019: 20,815 records; 2020 onward: 10,389 records13,713through 199914,3802000-200920,8152010-201910,3892020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 199913,713
2000-200914,380
2010-201920,815
2020 onward10,389
Share of records by publication typeReviews: 8.8 percent; Meta-analyses: 2.6 percent; Randomized controlled trials: 2.6 percentReviews8.8% (5,247)Meta-analyses2.6% (1,539)Randomized controlled trials2.6% (1,521)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 59,297 PubMed records
TypeRecordsShare
Reviews5,2478.8%
Meta-analyses1,5392.6%
Randomized controlled trials1,5212.6%

Method: PubMed query "Cause of Death"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.

Reading the evidence in clinical research

Research methods determine how much a result can be trusted. Randomized trials guard against confounding, systematic reviews and meta-analyses combine many studies, and observational designs are valuable but can show only association. Reporting standards, trial registration and pre-specified outcomes reduce bias. When reading about a method, ask what problem it is designed to solve and which problems it does not solve.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021
GBD 2021 Causes of Death Collaborators
2024Research article
Design not recorded in structured metadata
2,549cc by
PMID 38582094 · DOI · PMC11126520
Global, regional, and national causes of under-5 mortality in 2000-19: an updated systematic analysis with implications for the Sustainable Development Goals
Perin J, Mulick A, Yeung D, Villavicencio F, Lopez G, Strong KL, et al.
2022Research article
Design not recorded in structured metadata
1,056cc by
PMID 34800370 · DOI · PMC8786667
Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study
Burkart KG, Brauer M, Aravkin AY, Godwin WW, Hay SI, He J, et al.
2021Research article
Design not recorded in structured metadata
279cc by
PMID 34419204 · DOI · PMC8387975
Ischemic and non-ischemic myocardial injuries at autopsy- an overview for forensic pathologists
Michaud K, Basso C, de Boer HH, Fracasso T, de Gaspari M, Giordano C, et al.
2025Review article
Design not recorded in structured metadata
3cc by
PMID 40172635 · DOI · PMC12170769

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021 [1]

Research article GBD 2021 Causes of Death Collaborators · · 2024 · cited 2,549 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making.
Closing excerpt
FundingBill & Melinda Gates Foundation.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (948 words)

BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere.FundingBill & Melinda Gates Foundation.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38582094 · DOI · PMC11126520

Global, regional, and national causes of under-5 mortality in 2000-19: an updated systematic analysis with implications for the Sustainable Development Goals [2]

Research article Perin J, Mulick A, Yeung D, Villavicencio F, Lopez G, Strong KL, et al. · · 2022 · cited 1,056 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundCauses of mortality are a crucial input for health systems for identifying appropriate interventions for child survival.
Closing excerpt
FundingBill & Melinda Gates Foundation; WHO.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (284 words)

BackgroundCauses of mortality are a crucial input for health systems for identifying appropriate interventions for child survival. We present an updated series of cause-specific mortality for neonates and children younger than 5 years from 2000 to 2019.MethodsWe updated cause-specific mortality estimates for neonates and children aged 1-59 months, stratified by level (low, moderate, or high) of mortality. We made a substantial change in the statistical methods used for previous estimates, transitioning to a Bayesian framework that includes a structure to account for unreported causes in verbal autopsy studies. We also used systematic covariate selection in the multinomial framework, gave more weight to nationally representative verbal autopsy studies using a random effects model, and included mortality due to tuberculosis.FindingsIn 2019, there were 5·30 million deaths (95% uncertainty range 4·92-5·68) among children younger than 5 years, primarily due to preterm birth complications (17·7%, 16·1-19·5), lower respiratory infections (13·9%, 12·0-15·1), intrapartum-related events (11·6%, 10·6-12·5), and diarrhoea (9·1%, 7·9-9·9), with 49·2% (47·3-51·9) due to infectious causes. Vaccine-preventable deaths, such as for lower respiratory infections, meningitis, and measles, constituted 21·7% (20·4-25·6) of under-5 deaths, and many other causes, such as diarrhoea, were preventable with low-cost interventions. Under-5 mortality has declined substantially since 2000, primarily because of a decrease in mortality due to lower respiratory infections, diarrhoea, preterm birth complications, intrapartum-related events, malaria, and measles. There is considerable variation in the extent and trends in cause-specific mortality across regions and for different strata of all-cause under-5 mortality.InterpretationProgress is needed to improve child health and end preventable deaths among children younger than 5 years. Countries should strategize how to reduce mortality among this age group using interventions that are relevant to their specific causes of death.FundingBill & Melinda Gates Foundation; WHO.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 34800370 · DOI · PMC8786667

Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study [3]

Research article Burkart KG, Brauer M, Aravkin AY, Godwin WW, Hay SI, He J, et al. · · 2021 · cited 279 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundAssociations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done.
Closing excerpt
FundingBill & Melinda Gates Foundation.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (578 words)

BackgroundAssociations between high and low temperatures and increases in mortality and morbidity have been previously reported, yet no comprehensive assessment of disease burden has been done. Therefore, we aimed to estimate the global and regional burden due to non-optimal temperature exposure.MethodsIn part 1 of this study, we linked deaths to daily temperature estimates from the ERA5 reanalysis dataset. We modelled the cause-specific relative risks for 176 individual causes of death along daily temperature and 23 mean temperature zones using a two-dimensional spline within a Bayesian meta-regression framework. We then calculated the cause-specific and total temperature-attributable burden for the countries for which daily mortality data were available. In part 2, we applied cause-specific relative risks from part 1 to all locations globally. We combined exposure-response curves with daily gridded temperature and calculated the cause-specific burden based on the underlying burden of disease from the Global Burden of Diseases, Injuries, and Risk Factors Study, for the years 1990-2019. Uncertainty from all components of the modelling chain, including risks, temperature exposure, and theoretical minimum risk exposure levels, defined as the temperature of minimum mortality across all included causes, was propagated using posterior simulation of 1000 draws.FindingsWe included 64·9 million individual International Classification of Diseases-coded deaths from nine different countries, occurring between Jan 1, 1980, and Dec 31, 2016. 17 causes of death met the inclusion criteria. Ischaemic heart disease, stroke, cardiomyopathy and myocarditis, hypertensive heart disease, diabetes, chronic kidney disease, lower respiratory infection, and chronic obstructive pulmonary disease showed J-shaped relationships with daily temperature, whereas the risk of external causes (eg, homicide, suicide, drowning, and related to disasters, mechanical, transport, and other unintentional injuries) increased monotonically with temperature. The theoretical minimum risk exposure levels varied by location and year as a function of the underlying cause of death composition. Estimates for non-optimal temperature ranged from 7·98 deaths (95% uncertainty interval 7·10-8·85) per 100 000 and a population attributable fraction (PAF) of 1·2% (1·1-1·4) in Brazil to 35·1 deaths (29·9-40·3) per 100 000 and a PAF of 4·7% (4·3-5·1) in China. In 2019, the average cold-attributable mortality exceeded heat-attributable mortality in all countries for which data were available. Cold effects were most pronounced in China with PAFs of 4·3% (3·9-4·7) and attributable rates of 32·0 deaths (27·2-36·8) per 100 000 and in New Zealand with 3·4% (2·9-3·9) and 26·4 deaths (22·1-30·2). Heat effects were most pronounced in China with PAFs of 0·4% (0·3-0·6) and attributable rates of 3·25 deaths (2·39-4·24) per 100 000 and in Brazil with 0·4% (0·3-0·5) and 2·71 deaths (2·15-3·37). When applying our framework to all countries globally, we estimated that 1·69 million (1·52-1·83) deaths were attributable to non-optimal temperature globally in 2019. The highest heat-attributable burdens were observed in south and southeast Asia, sub-Saharan Africa, and North Africa and the Middle East, and the highest cold-attributable burdens in eastern and central Europe, and central Asia.InterpretationAcute heat and cold exposure can increase or decrease the risk of mortality for a diverse set of causes of death. Although in most regions cold effects dominate, locations with high prevailing temperatures can exhibit substantial heat effects far exceeding cold-attributable burden. Particularly, a high burden of external causes of death contributed to strong heat impacts, but cardiorespiratory diseases and metabolic diseases could also be substantial contributors. Changes in both exposures and the composition of causes of death drove changes in risk over time. Steady increases in exposure to the risk of high temperature are of increasing concern for health.FundingBill & Melinda Gates Foundation.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 34419204 · DOI · PMC8387975

Ischemic and non-ischemic myocardial injuries at autopsy- an overview for forensic pathologists [4]

Review article Michaud K, Basso C, de Boer HH, Fracasso T, de Gaspari M, Giordano C, et al. · · 2025 · cited 3 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Cardiovascular diseases are major causes of morbidity and death worldwide, and most cardiac deaths are related to ischemic injury of the myocardium (myocardial infarction).
Closing excerpt
From this perspective we propose a diagnostic approach to myocardial injuries in a forensic pathology context.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (209 words)

Cardiovascular diseases are major causes of morbidity and death worldwide, and most cardiac deaths are related to ischemic injury of the myocardium (myocardial infarction). As underlined in the current clinical definition and classification of myocardial infarctions, not all myocardial injuries are due to ischemia: irreversible injury, ending in necrosis, can be induced also by various other factors, such as infections, immune disorders, physical and chemical agents, and trauma. This is supported by clinical studies showing that elevated serum levels of cardiac troponins, as a measure of myocardial damage, are also a common finding in the non-ischemic types of myocardial injury. Forensic pathologists confronted with autopsy findings suggestive of myocardial injury should therefore realize that both ischemic and non-ischemic forms of myocardial death can be observed, and not only in natural but also non-natural deaths (intoxications, asphyxia, traumatic and iatrogenic deaths, and others). Distinguishing these different types of injuries and underlying diseases or circumstances of death is critical, not only to determine the cause and mechanism of death, but also to help investigate often challenging medico-legal scenarios. This article reviews the broad spectrum of ischemic and non-ischemic myocardial injuries in natural and violent deaths. From this perspective we propose a diagnostic approach to myocardial injuries in a forensic pathology context.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40172635 · DOI · PMC12170769

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis [5]
    Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al. · J Am Coll Cardiol · 2010 · cited 2,011 times (Europe PMC)
  • Research article Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents [6]
    Global BMI Mortality Collaboration, Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, et al. · Lancet · 2016 · cited 1,983 times (Europe PMC)
  • Research article Sex and gender: modifiers of health, disease, and medicine [7]
    Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero JJ, DeMeo DL, et al. · Lancet · 2020 · cited 1,549 times (Europe PMC)
  • Research article Amyotrophic lateral sclerosis [8]
    van Es MA, Hardiman O, Chio A, Al-Chalabi A, Pasterkamp RJ, Veldink JH, et al. · Lancet · 2017 · cited 981 times (Europe PMC)
  • Research article Global Cancer in Women: Burden and Trends [9]
    Torre LA, Islami F, Siegel RL, Ward EM, Jemal A · Cancer Epidemiol Biomarkers Prev · 2017 · cited 823 times (Europe PMC)
  • Research article Global incidence and mortality of idiopathic pulmonary fibrosis: a systematic review [10]
    Hutchinson J, Fogarty A, Hubbard R, McKeever T · Eur Respir J · 2015 · cited 684 times (Europe PMC)

References

  1. GBD 2021 Causes of Death Collaborators. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021. . 2024. PMID 38582094 · DOI · PMC11126520
  2. Perin J, Mulick A, Yeung D, Villavicencio F, Lopez G, Strong KL, et al.. Global, regional, and national causes of under-5 mortality in 2000-19: an updated systematic analysis with implications for the Sustainable Development Goals. . 2022. PMID 34800370 · DOI · PMC8786667
  3. Burkart KG, Brauer M, Aravkin AY, Godwin WW, Hay SI, He J, et al.. Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study. . 2021. PMID 34419204 · DOI · PMC8387975
  4. Michaud K, Basso C, de Boer HH, Fracasso T, de Gaspari M, Giordano C, et al.. Ischemic and non-ischemic myocardial injuries at autopsy- an overview for forensic pathologists. . 2025. PMID 40172635 · DOI · PMC12170769
  5. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, et al.. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol. 2010. PMID 20863953 · DOI
  6. Global BMI Mortality Collaboration, Di Angelantonio E, Bhupathiraju ShN, Wormser D, Gao P, Kaptoge S, et al.. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016. PMID 27423262 · DOI · PMC4995441
  7. Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero JJ, DeMeo DL, et al.. Sex and gender: modifiers of health, disease, and medicine. Lancet. 2020. PMID 32828189 · DOI · PMC7440877
  8. van Es MA, Hardiman O, Chio A, Al-Chalabi A, Pasterkamp RJ, Veldink JH, et al.. Amyotrophic lateral sclerosis. Lancet. 2017. PMID 28552366 · DOI
  9. Torre LA, Islami F, Siegel RL, Ward EM, Jemal A. Global Cancer in Women: Burden and Trends. Cancer Epidemiol Biomarkers Prev. 2017. PMID 28223433 · DOI
  10. Hutchinson J, Fogarty A, Hubbard R, McKeever T. Global incidence and mortality of idiopathic pulmonary fibrosis: a systematic review. Eur Respir J. 2015. PMID 25976683 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-29.

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At a glance

59,297
PubMed records on this heading
18%
published since 2020
5,247
review articles
1,521
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-29; they show how much has been written, not how strong the evidence is.

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