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Open Access

Peer-reviewed

Research Article

Prevalence and risk factors for AMS: A systematic review and meta-analysis

  • Xinzhu Liu ,

    Contributed equally to this work with: Xinzhu Liu, Lixia Tan, Zeng Ren

    Roles Data curation, Formal analysis, Investigation, Project administration, Writing – original draft

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Lixia Tan ,

    Contributed equally to this work with: Xinzhu Liu, Lixia Tan, Zeng Ren

    Roles Data curation, Formal analysis, Project administration, Writing – original draft

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Zeng Ren ,

    Contributed equally to this work with: Xinzhu Liu, Lixia Tan, Zeng Ren

    Roles Data curation, Project administration

    Affiliation Neuroscience Department, Xizang Autonomous Region People’s Hospital, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Xueyezi Bai,

    Roles Data curation

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Shangyi Yong,

    Roles Data curation, Formal analysis, Investigation, Writing – review & editing

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Han Gao,

    Roles Data curation, Project administration, Writing – review & editing

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯
  • Sang Ba,

    Roles Data curation, Investigation, Writing – review & editing

    Affiliation Pumajiangtang Branch of Langkazi County Central Hospital, Shannan, Xizang Autonomous Region, China

    ⨯
  • Lanzi Gongga

    Roles Data curation, Formal analysis, Writing – review & editing

    35173588@qq.com

    Affiliation Medical College, Xizang University, Lhasa, Xizang Autonomous Region, China

    ⨯

Abstract

Background

Acute Mountain Sickness (AMS) is a high-altitude-specific condition with variable prevalence and poorly defined risk factors. Despite growing global exposure to high-altitude environments, no systematic review has comprehensively synthesized AMS epidemiology.

Objectives

To assess the prevalence of AMS and critically evaluate evidence on risk factors associated with increased susceptibility.

Design

A systematic review and meta-analysis following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines.

Data sources

PubMed, Cochrane Library, Web of Science, CINAHL Plus, China Knowledge Resource Integrated Database (CNKI), Wanfang Database, Chinese Biomedical Database (CBM), and Weipu Database (VIP) were comprehensively searched for observational studies investigating the prevalence and risk factors of AMS from January 1, 2004 to December 31, 2024.

Review methods

Original journal articles were included which met the inclusion criteria. The quality of the included studies was evaluated independently by two investigators. Meta-analysis was conducted using R software (v4.2.2), with estimates of AMS from pooled using a random-effects model.

Results

Fifty-eight studies (n = 2,705) were included. The pooled AMS prevalence was 48.25% (95% CI: 42.58–53.96%), with substantial heterogeneity (I² = 82.3%). Significant risk factors included extreme altitude (>5500 m; RR = 1.89), rapid ascent (<6 h; RR = 1.60), marked heart rate increase (>20 bpm; RR = 2.35), and oxygen saturation decline (>10%; RR = 2.02). Prior AMS history (RR = 1.36) and male sex (RR = 1.15) were also associated with higher risk, while older age (>50 years) was protective (RR = 0.78).

Conclusion

AMS affects nearly half of high-altitude visitors. Altitude, ascent rate, cardiopulmonary response, and prior AMS history are key risk determinants. These findings support pre-exposure risk stratification, staged ascent protocols, and real-time physiological monitoring. PROSPERO CRD42024595365.

Citation: Liu X, Tan L, Ren Z, Bai X, Yong S, Gao H, et al. (2026) Prevalence and risk factors for AMS: A systematic review and meta-analysis. PLoS One 21(4): e0345796. https://doi.org/10.1371/journal.pone.0345796

Editor: UDAYAN BHATTACHARYA, Weill Cornell University, UNITED STATES OF AMERICA

Received: November 19, 2025; Accepted: March 10, 2026; Published: April 10, 2026

Copyright: © 2026 Liu et al. 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 data underlying the findings of this study are available from the Figshare repository: https://doi.org/10.6084/m9.figshare.31558336.

Funding: This work was supported by the Key R&D Program of Xizang Autonomous Region Science and Technology Plan (Grant No. XZ202301ZY0011G) awarded to L.Z., the Joint Key Program of the National Natural Science Foundation of China (Grant No. U22A20340) awarded to L.Z., the National Natural Science Foundation of China (Grant No. 82060588), and the Young Doctor Academic Development Support Program of Xizang University (Grant No. ZDBS202216) awarded to L.Z. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Acute Mountain Sickness (AMS), a high-altitude-specific disease, arises when the body fails to acclimate promptly to hypoxia following a rapid ascent to high altitudes. Its symptoms are predominantly headaches, nausea, vomiting, dizziness, fatigue, and insomnia, and in severe cases, it can progress to High-Altitude Pulmonary Edema (HAPE) or High-Altitude Cerebral Edema (HACE) [1]. Early descriptions of high-altitude illness date back several centuries, with initial reports by Joseph Acosta [2] and later physiological studies by investigators such as Daniel Vergara Lope and Carlos Monge Medrano [3]. These early observations laid the foundation for the modern understanding of human responses to hypoxic high-altitude environments. In recent decades, the number of people traveling to high-altitude regions for tourism, research, or work has increased significantly. This trend has led to a rise in AMS cases, particularly among those without prior acclimatization. Beyond individual health impacts, AMS also places a burden on local healthcare systems and disrupts high-altitude industries such as trekking, mining, and scientific expeditions.

The reported prevalence of AMS varies widely, ranging from 5.5% [4] to 83% [5]. The observed discrepancies in the reported prevalence of acute mountain sickness (AMS) across studies can be attributed to several factors. First, a variety of diagnostic scales are employed in AMS assessment—including the Lake Louise AMS scoring system (LLS), the Hackett clinical score, the Acute Mountain Sickness–Cerebral score (AMS-C), the Clinical Functional Score (CFS), the visual analog scale (VAS), and the Chinese AMS Score (CAS) [6]. These instruments vary in their sensitivity and specificity, influencing case identification. Second, inconsistencies in study quality, sample size, and sampling methodologies contribute to variability in prevalence estimates and reduce the precision of the findings. Third, the diagnosis of AMS relies predominantly on subjective symptomatology in the absence of established biomarkers, rendering it susceptible to influences such as social support, physical exertion, and patient mood. As a result, under differing ascent conditions, individuals may exhibit varied symptomatic responses, further contributing to disparities in prevalence rates [7]. Moreover, the effects of major AMS risk factors—such as sex, age, physical fitness, smoking history, rate of ascent, and prior AMS experience—remain inconclusive and warrant further clarification through evidence-based systematic reviews [8]. To our knowledge, no comprehensive systematic review has synthesized the evidence on AMS prevalence and associated risk factors. This study aims to fill this knowledge gap by determining the overall AMS prevalence, exploring potential risk factors, and providing evidence-based recommendations to enhance AMS awareness, control, and treatment, and to guide high-altitude healthcare and tourism safety.

Materials and methods

This review was conducted following the Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. A detailed study protocol is available on the PROSPERO website under the registration number CRD42024595365, register name Prevalence and risk factors for Acute mountain sickness: a systematic review and meta-analysis.

Search strategy

A comprehensive search of the literature was performed using eight electronic databases: PubMed, the Cochrane Library, Web of Science, CINAHL Plus, China National Knowledge Infrastructure (CNKI), Wanfang Database, Chinese Biomedical Literature Database (CBM), and Weipu Database (VIP). Searches spanned from January 1, 2004 to December 31, 2024. The starting year of 2004 was selected to focus on studies conducted after the widespread adoption of the revised Lake Louise Scoring System (LLS) for diagnosing acute mountain sickness, which improved the consistency and comparability of AMS assessment across studies. Restricting the time frame also helped reduce methodological heterogeneity related to earlier diagnostic approaches.

The search strategies utilized a combination of MeSH terms and free-text keywords. The specific search string used in PubMed was:

((((((((((((Acute mountain sickness) OR (Acute mountain diseases)) OR (Acute mountain illnesses)) OR (Acute altitude sickness)) OR (Acute altitude diseases)) OR (Acute altitude illnesses)) OR (High altitude sickness)) OR (High altitude diseases)) OR (High altitude illnesses)) OR (High altitude cerebral edema)) OR (High altitude pulmonary edema)) OR (Acute high altitude disease)) AND (((((((((risk factors) OR (risk elements)) OR (risk markers)) OR (risk indicators)) OR (risk predictors)) OR (hazard factors)) OR (vulnerability factors)) OR (((((((prevalence) OR (Prevalency)) OR (Prevalence Rate)) OR (epidemiology)) OR (incidence)) OR (morbidity)))))

In addition to the electronic database searches, we manually reviewed the reference lists of the retrieved articles to identify further relevant publications and also searched grey literature. In cases of uncertainty or need for additional details, corresponding authors were contacted via email. As this study is based entirely on previously published research, it did not require Ethics Committee approval.

Study selection

After the removal of duplicate studies, two investigators independently assessed the eligible publications by screening titles and abstracts, using the inclusion and exclusion criteria. Full-text articles were retrieved when at least one reviewer decided that an abstract was eligible for inclusion. Each publication was assessed independently by both investigators for final study inclusion. Disagreements were resolved by discussion.

No language restrictions were applied during the literature search. In addition to international databases (PubMed, Web of Science, Cochrane Library, and CINAHL Plus), several Chinese databases (CNKI, Wanfang, CBM, and VIP) were also searched to minimize retrieval bias. However, the studies ultimately included in the meta-analysis were all published in English and met the predefined eligibility criteria.

The criteria for inclusion of a study in the systematic review were as follows: (1) Observational studies (e.g., cohort, cross-sectional) or baseline data of clinical trials/randomized controlled trials reporting on AMS prevalence and risk factors; (2) Studies must involve human participants, with some exposed to high-altitude environments (usually ≥ 2500 m); (3) Studies must report AMS prevalence or its related risk factors; (4) No language restrictions were applied; (5) Only include literature with full-text accessibility, either publicly available or legally obtainable through libraries, research institutions, co-authors, etc; (6) Included studies should be published between January 1, 2004, and December 31, 2024. The exclusion criteria were as follows: (1) Non-peer-reviewed articles, conference abstracts, reviews, case reports, and animal studies are excluded; (2) Studies that don’t explicitly state participants’ altitude or have a participant altitude below 1500 m are excluded; (3) Studies not reporting AMS prevalence or risk factor data are excluded; (4) Studies with incomplete data or unextractable relevant data are excluded; (5) Studies with low methodological quality in quality assessment, such as those with obvious selection bias, information bias, or insufficient control of confounding factors, are excluded; (6) Studies published before January 1, 2004, are excluded.

Study process

The literature screening followed the standard systematic review procedures. Two investigators independently screened the titles and abstracts of all retrieved records, followed by a full-text review of potentially eligible articles. Studies that did not meet the predefined eligibility criteria were excluded, and any disagreements between the reviewers were resolved through consultation with a third researcher.

The initial search identified 195 articles, of which 43 duplicates were removed. Screening of titles and abstracts based on the inclusion criteria led to the selection of 90 articles for full-text assessment. Among these, 25 were excluded for the following reasons: inadequate sample size (n = 8), use of non-conforming diagnostic criteria (n = 3), and lack of prevalence data (n = 14). After evaluating the remaining 65 articles, six were excluded due to irrelevant interventions and one due to ineligible outcome measures. Ultimately, 58 studies involving 2,705 participants and published between 2004 and 2024 were included in the meta-analysis (Fig 1).

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Fig 1. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram for the study selection process.

https://doi.org/10.1371/journal.pone.0345796.g001

Data extraction

Data were extracted from the included studies by two independent investigators. The following information was recorded: first author name, publication year, study location, sample size, diagnostic criteria, the prevalence of AMS, and stated risk factors. All extracted data were stored in the Microsoft Excel file format.

Quality appraisal

The quality of the included studies was evaluated independently by two investigators, using the tool for disease prevalence quality developed by Loney et al [9]. Any disagreement regarding the quality of studies was resolved by a third investigator. The total score of the evaluation items is 8 points. Each item that was completely compliant was scored 1, and noncompliant or partly compliant items were scored 0. A higher cumulative score indicates a smaller risk of bias in the study. As is shown in Fig 2, the greener each criterion met, the lesser the risk of bias in the studies.

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Fig 2. Critical appraisal of studies.

https://doi.org/10.1371/journal.pone.0345796.g002

Data analysis

All statistical analyses were done with R software (v4.2.2). For AMS prevalence, we used the metaprop function in the meta package. We applied log transformation (PLOGIT) and maximum likelihood (ML) to estimate the heterogeneity parameter τ² and used a random-effects model to get the overall prevalence and 95% CI. Heterogeneity was assessed by I², with I² > 50% indicating moderate to high heterogeneity. Subgroup analyses were done to explore heterogeneity sources. For risk factor analysis, we performed meta-analysis using pooled ORs or SMDs, selecting metabin or metacont functions based on variable types. A detailed step-by-step protocol for the literature search, study selection, data extraction, quality appraisal, and statistical analysis is available at protocols.io: https://dx.doi.org/10.17504/protocols.io.dm6gpkdzjlzp/v1

Results

Characteristics of the included studies

The characteristics of the 58 studies are summarized in Table 1.

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Table 1. Characteristics of included studies.

https://doi.org/10.1371/journal.pone.0345796.t001

Prevalence of AMS

This meta-analysis included 58 studies to estimate the overall AMS prevalence. AMS prevalence across studies ranged from 5.5% [4] to 83% [5]. Using a random-effects model to pool data from all studies, the overall AMS prevalence was 48.25% (95% CI: 42.58%–53.96%). There was significant heterogeneity between studies (I² = 82.3%, P < 0.0001) (Fig 3).

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Fig 3. Forest plot of prevalence of AMS.

https://doi.org/10.1371/journal.pone.0345796.g003

Subgroup analysis for AMS risk factors

This subgroup analysis examined factors strongly associated with the prevalence of AMS, including target altitude, rate of ascent, stress level, heart rate change, oxygen saturation, sex, age, and history of AMS. Using an altitude below 4500 m as the reference, comparisons were made with very high altitude (4500–5500 m) and extreme altitude (>5500 m). The high-altitude group showed a significantly higher risk of AMS than the reference (RR = 1.47, 95% CI: 1.25–1.73), and the extreme-altitude group exhibited a further increased risk (RR = 1.89, 95% CI: 1.42–2.51), indicating a significant rise in AMS prevalence with ascending altitude (P < 0.05). Regarding the rate of ascent, compared with a gradual ascent, a moderate ascent (6–24 h) was associated with an increased risk of AMS (RR = 1.25, 95% CI: 1.12–1.40), and a rapid ascent was further associated with a higher risk (RR = 1.60, 95% CI: 1.44–1.78), indicating a positive correlation between ascent speed and AMS risk. An increase in heart rate was also correlated with higher AMS prevalence, with robust confidence intervals. Oxygen saturation was negatively correlated with AMS prevalence. Males had a slightly higher risk of AMS than females (RR = 1.15, 95% CI: 1.02–1.30). Participants with a history of AMS had a higher risk than those without (RR = 1.36, 95% CI: 1.25–1.48), indicating possible individual susceptibility. In terms of age, older individuals (>50 years) had a lower risk of AMS compared with younger adults (RR = 0.78, 95% CI: 0.67–0.90), suggesting that older age may be a protective factor. Additionally, the use of non-LLS diagnostic criteria was associated with a 7% lower risk of AMS compared with LLS criteria (RR = 0.93) (Fig 4).

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Fig 4. Forest plot of subgroup analysis for risk factors associated with AMS.

https://doi.org/10.1371/journal.pone.0345796.g004

Quality of evidence and recommendations

Using the GRADE framework, we comprehensively assessed the evidence quality for 15 key risk factors associated with AMS. We detailed the combined effect size, sample size, quality of evidence, and strength of recommendation for each factor (Table 2). Among these, the evidence regarding a substantial increase in heart rate (>20 bpm) was rated as high certainty (aRR = 2.35), followed by a major reduction in blood oxygen saturation (>10%; moderate certainty, aRR = 2.02) and a rapid ascent profile (<6 h; moderate certainty, aRR = 1.60). Furthermore, we used the GRADE evidence quality forest plot (Fig 5) to visually present the relative risk (RR) of each factor and its 95% confidence interval, and mark the GRADE evidence symbols: ⨁⨁⨁⨁ (high), ⨁⨁⨁○ (moderate), ⨁⨁○○ (low). It is worth noting that extreme altitude (> 5500 m) showed the highest risk (RR = 1.89), but was downgraded to low certainty evidence due to small sample size (n = 120).

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Table 2. GRADE Evidence Summary of Risk Factors for AMS.

https://doi.org/10.1371/journal.pone.0345796.t002

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Fig 5. Forest Plot of Relative Risks and GRADE Certainty of Evidence for Key AMS Risk Factors.

https://doi.org/10.1371/journal.pone.0345796.g005

Publication bias

Funnel plot asymmetry (Fig 6) suggested the presence of publication bias or small-study effects. Results of Egger’s weighted regression test further supported the funnel plot asymmetry (P < 0.10).

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Fig 6. Funnel plot for assessing publication biases.

https://doi.org/10.1371/journal.pone.0345796.g006

Discussion

This meta-analysis synthesizes evidence from 58 studies (n = 2705 participants) to elucidate the epidemiology and risk determinants of AMS. The meta-analysis yielded a pooled AMS prevalence of 48.25% (95% CI: 42.58–53.96%). Significant heterogeneity was observed across studies (I² = 82.3%), which may reflect differences in target altitude, ascent profiles, participant characteristics, diagnostic criteria, and study settings. In addition, funnel plot asymmetry and the Egger’s test result suggest the possibility of publication bias or small-study effects, which should be considered when interpreting the pooled prevalence estimate.

The estimated prevalence exhibited a broad range (5.5%–83%), highlighting the considerable influence of factors such as altitude gradient, ascent profile, and the specific diagnostic criteria applied. For example, studies conducted at extreme altitudes (>4000 m) or those involving rapid ascent protocols consistently reported higher prevalence rates, consistent with the expected increased pathophysiological stress from severe hypoxia. Furthermore, the use of different diagnostic tools (e.g., LLS versus AMS-C), which possess varying sensitivities to cerebral and systemic symptoms, constituted another major source of heterogeneity and may contribute to the over- or underestimation of the true prevalence.

At high altitude, hypoxic exposure stimulates peripheral chemoreceptors, triggering parasympathetic nervous system activation as part of the metabolic adaptation to oxygen-deficient environments [66]. This acclimatization process, however, often coincides with the development of acute mountain sickness (AMS), which, while generally self-limiting, poses a substantial health risk to high-altitude travelers. Existing epidemiological studies on AMS have typically been regional in scope. For instance, a study by Jennifer et al. involving 150 trekkers in the southern Everest region reported an AMS prevalence that increased with altitude: 0% at 2500–3000 m, 10% at 3000–4000 m, and 51% at 4000–4500 m [67]. Interestingly, prevalence declined at elevations exceeding 5000 m, a pattern potentially explained by gradual acclimatization during prolonged ascent. This observation aligns with evidence that a slower ascent rate significantly reduces AMS incidence and supports the hypothesis that mild AMS may represent part of the spectrum of physiological acclimatization—though this interpretation requires further validation. The comparatively low prevalence reported in their study relative to the pooled estimate from our meta-analysis may be attributed to the cohort’s composition of experienced trekkers and their controlled, moderate ascent profile.

Subgroup analyses revealed that exposure to extreme altitude (>5000 m) was associated with an 89% increase in AMS risk relative to baseline, establishing it as the most significant risk factor. At 5000 meters, the partial pressure of atmospheric oxygen drops to approximately half of the sea-level value [68], inducing severe hypoxemia. In response, the organism enhances adrenaline release and catecholamine secretion to maintain cardiac output, leading to markedly elevated heart rates through stimulated myocardial contraction. This meta-analysis corroborates that under acute hypoxia, variations in oxygen saturation—resulting from hypoxemia—and adrenaline-mediated increases in heart rate exhibit an inverse relationship. Both parameters demonstrate a bidirectional association with AMS incidence, functioning not only as predisposing factors for its onset but also as exacerbating elements after AMS manifestation.

Notably, age appeared to confer a protective effect against AMS. Compared with the younger reference group, middle-aged and older participants showed 9% and 22% reductions in AMS risk, respectively. This pattern may be linked to the functional responsiveness of carotid body-adrenomedullary arterial chemoreceptors, which serve as central sensors for blood oxygen levels and initiate cardiopulmonary reflexes—such as hyperventilation and sympathetic activation—upon detecting hypoxia to promote acclimatization [69]. An alternative mechanistic explanation is that age-dependent cerebral atrophy enlarges the intracranial buffering compartment, thereby accommodating mild vasogenic oedema without a clinically relevant rise in intracranial pressure and, consequently, attenuating either the incidence or the severity of AMS [70]. Further investigation into the mechanistic basis of this age-dependent protection may yield novel strategies for AMS prevention.

Additionally, male gender was associated with a moderately elevated AMS risk compared with female participants (RR = 1.15). Collectively, these findings underscore the importance of managing modifiable environmental exposures—particularly altitude and ascent rate—as controllable risk factors, while reinforcing the value of real-time monitoring of heart rate and oxygen saturation as essential components of AMS risk mitigation.

Several methodological limitations should be considered when interpreting our findings. First, the reliance on symptom-based diagnostic criteria introduces an element of subjectivity, as symptom reporting may be influenced by psychological state (e.g., anxiety) or cultural perceptions of illness. Second, although no language restrictions were applied during the literature search and both international and Chinese databases were examined, the studies ultimately included in the meta-analysis were all published in English. Therefore, the possibility of language bias cannot be completely excluded. In addition, publication bias may also exist, as suggested by funnel plot asymmetry and Egger’s test (P < 0.10). Most importantly, the current approach to AMS diagnosis lacks objective biomarker support. The absence of physiological or biochemical markers hinders the identification of subclinical AMS cases and complicates the differential diagnosis from other high-altitude conditions with overlapping symptomatology [71]. Future studies incorporating validated biomarkers are needed to improve diagnostic accuracy and pathological understanding.

From a clinical perspective, these findings support the implementation of pre-ascent risk stratification, with particular attention to individuals with a history of AMS or suboptimal physiological indicators. Public health efforts could benefit from the widespread adoption of standardized ascent guidelines—such as staged ascent with a daily gain not exceeding 300 m above 2,500 m—along with the promotion of real-time blood oxygen saturation monitoring to reduce AMS incidence [72]. In the research domain, future prospective studies that integrate genomic, metabolic, and environmental data are warranted to identify predictive biomarkers and improve risk prediction models [73]. Furthermore, context-specific interventions—including altitude pre-acclimatization protocols or pharmacological prophylaxis (e.g., acetazolamide)—should be evaluated across diverse populations to enhance generalizability and clinical applicability [62].

This meta-analysis synthesizes previously fragmented evidence into a consolidated risk profile for AMS. The results offer a basis for refining pre-travel health assessments, optimizing ascent strategies, and assisting clinicians in the early identification of high-risk individuals prior to symptom onset.

Conclusion

This systematic review and meta-analysis, synthesizing evidence from 58 studies involving 2,705 participants, confirms that AMS remains highly prevalent among high-altitude travelers, with a pooled prevalence of 48.25%. The findings establish extreme altitude exposure (>5500 m), rapid ascent profiles (<6 hours), pronounced cardiopulmonary responses (heart rate increase >20 bpm; oxygen saturation decline >10%), and previous AMS episodes as consistent risk determinants. Considerable heterogeneity observed across studies highlights methodological variations in diagnostic approaches and ascent conditions. These results support the implementation of staged ascent protocols, pre-travel risk assessment targeting susceptible individuals, and real-time physiological monitoring as effective strategies for reducing the global burden of AMS.

Supporting information

S1 File. PRISMA_2020_checklist for this systematic review and meta-analysis.

https://doi.org/10.1371/journal.pone.0345796.s001

(DOCX)

Acknowledgments

The authors utilized ChatGPT/GPT-4 (OpenAI) for proofreading and improving the readability of the manuscript. The authors are solely responsible for the scientific content, data, analysis, and interpretations presented in this work. We also thank the editors and reviewers for their insightful comments.

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