The burden of severe chest injuries in five East Asian countries: a secondary age-period-cohort analysis of GBD 2023

Introduction

Trauma represents a major global public health challenge. According to the Global Burden of Disease (GBD) 2019 study, injuries accounted for nearly 8% of global deaths and 10% of disability-adjusted life years (DALYs) in 2019 (1,2). Chest injury or thoracic injury represents a critical subset of this burden. Studies indicate that approximately one-quarter of all trauma deaths are attributable to thoracic injuries or their complications; among polytrauma patients, it ranks as the third leading cause of mortality, following head and abdominal injuries (3-6). The mortality associated with specific chest injuries can be exceptionally high, as illustrated by the finding that more than 75% of individuals who sustain stab wounds to the heart die before hospital admission (6). Chest injury involves injuries to the chest wall, ribs, tracheobronchial tree, lungs, diaphragm, esophagus, heart, and major vessels, contributing to a considerable disease burden (4).

Despite its global impact, the epidemiological landscape of chest injury exhibits considerable heterogeneity across different regions and countries (7). While some regions are exhibiting a declining trend in incidence, others are exhibiting a concerning increase (8). This variation highlights the critical need for region-specific epidemiological assessments to understand the underlying dynamics of disease burden. A detailed evaluation of recent temporal trends and reliable future projections are indispensable for guiding rational resource allocation within healthcare systems, prioritizing preventive strategies, and optimizing clinical management protocols (7). Such a data-driven approach is vital for mitigating the growing burden imposed by chest injury.

The five East Asian countries and regions—China, Japan, Mongolia, the Democratic People’s Republic of Korea (DPRK), and the Republic of Korea (ROK)—share certain cultural and socioeconomic contexts but are at diverse stages of development and demographic transition (9). This makes them an ideal cohort for a comparative study. However, a comprehensive, quantitative analysis dissecting the long-term trends, age patterns, and independent effects of period (temporal influences) and birth cohort (generational risks) on chest injury burden in this region is currently lacking.

This study systematically assessed the long-term trends in the incidence, prevalence, and disability burden of severe chest injury in the five East Asian countries from 1990 to 2023, utilizing data from the GBD Study 2023 of injuries and risk factors. On the basis of advanced statistical methods, such as the age-period-cohort (APC) model and decomposition analysis, this study elucidates the underlying age, period, and cohort effects, as well as the core drivers of these trends. These findings are expected to provide a scientific basis for formulating targeted trauma prevention and control strategies in East Asia. We present this article in accordance with the GATHER reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1000/rc).

Methods

Data source and definitions

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The data for this study were obtained from the Global Health Data Exchange GBD Results Tool (https://vizhub.healthdata.org/gbd-results/) for the years 1990 to 2023 (10). We focused on the disease entity of severe chest injury, which was defined as an abbreviated injury score of 3 or higher. Patients with severe chest injury usually face life-threatening or long-term dysfunction and require intensive care unit or emergency operations. This usually includes the following conditions classified by the International Classification of Diseases version 10 (ICD-10): tension pneumothorax or massive hemothorax (S27.0, S27.1, S27.2); flail chest (S22.5, S22.4); pulmonary contusion or laceration (S27.31, S27.32); myocardial contusion or cardiac laceration (S26.81, S26.0, S26.2); greater vessel injury of the thorax (S25.0, S25); tracheal or bronchial rupture (S27.5, S27.4); and diaphragmatic rupture with herniation (S27.80). Data for the following five East Asian countries/territories were extracted: China, the Democratic People’s Republic of Korea (DPRK), Japan, Mongolia, and the Republic of Korea (ROK).

Data analysis

Disease burden metrics

Three key metrics were analyzed in this study: incidence, prevalence, and years lived with disability (YLDs). Both the absolute number of cases and the age-standardized rates (ASRs) were calculated for each metric. The age-standardized incidence rate (ASIR), age-standardized prevalence rate (ASPR), and age-standardized YLDs rate (ASYR) were computed using the GBD 2023 world standard population to allow for cross-country and cross-time comparisons, independent of differences in population age structures. The estimated annual percentage change (EAPC) and its 95% confidence interval (CI) were calculated on the basis of the ASRs to quantify the long-term trend from 1990 to 2023. A regression line was fitted to the natural logarithm of the annual rates:

In(rate)=α+β×year+ε[1]

The EAPC was calculated as follows:

EAPC=(eβ−1)∗100%[2]

An EAPC with a 95% CI that did not overlap zero was considered statistically significant.

Joinpoint regression analysis

To identify significant turning points in temporal trends, joinpoint regression analysis was performed on the ASRs from 1990 to 2023. The analysis was conducted using the Joinpoint Regression Program (Version 5.0.2) from the National Cancer Institute. The model started with the minimum number of joinpoints (0) and tested whether adding more joinpoints (up to a maximum of 5) significantly improved the model fit using a Monte Carlo permutation test. The optimal model was selected on the basis of the Bayesian information criterion (BIC). For each identified segment, the annual percentage change and its 95% CI were calculated. The data were stratified by country and sex.

APC modeling

An intrinsic estimator (IE) APC model was applied to the ASR data to disentangle the independent effects of age, period, and birth cohort. The age variable was grouped into consecutive 5-year intervals from 0–4 to 95+ years. The period variable spans from 1990–1994 to 2019–2023 in 5-year intervals. Corresponding birth cohorts were derived by subtracting the midpoint age of each age group from the midpoint year of each period. The reference groups were set as the 50-54 age group, the 2004–2008 period, and the 1954–1963 birth cohort. The model output provided the relative risks (RRs) and 95% CIs for age, period, and cohort effects. The analysis was conducted using the “apc” package in R software (version 4.3.2).

Decomposition analysis

A standard demographic decomposition technique was employed to partition the change in total YLDs between 1990 and 2023 into contributions from two components: (I) changes in population size and age structure (defined as the demographic effect) and (II) changes in the ASYR (defined as the rate effect). The rate effect primarily reflects changes in case fatality and disease severity (11).

Time-series forecasting [autoregressive integrated moving average (ARIMA) modeling]

To model and forecast future trends, ARIMA models were fitted to the time series of the ASRs for each country, stratified by sex. The optimal ARIMA (p, d, q) parameters were determined through a systematic process: assessment of the stationarity using the Augmented Dickey-Fuller test, identification of potential autoregressive (p) and moving average (q) orders by examining the autocorrelation function (ACF) and partial autocorrelation function (PACF) plots of the differenced series, and selection of the final model that minimized the Akaike information criterion (AIC). Model diagnostic checks, including analyses of residuals for white noise, were performed. The selected best-fitting models were used to generate short-term forecasts. All time-series analyses were conducted using the forecast package in R software (version 4.3.2).

Results

Temporal trends in chest trauma incidence, prevalence, and DALYs in five East Asian countries

Analysis of the GBD 2023 data from 1990 to 2023 revealed divergent temporal trends in the burden of severe chest injury across the five East Asian countries. At the regional level, the total number of incident cases decreased from 2,420,522 in 1990 to 2,319,660 in 2023. The total number of prevalent cases increased from 491,824 to 605,457, while the total YLDs remained relatively stable (113,163 to 111,156) (Table S1, Figures S1-S3). In 2023, China accounted for the greatest number of cases, with 2,004,337 [95% uncertainty interval (UI): 1,494,630 to 2,700,060] incident cases, 477,224 (95% UI: 392,555 to 572,311) prevalent cases, and 97,369 (95% UI: 62,026 to 156,273) YLDs (Figure S1).

The visual and quantitative comparisons of the ASRs in 1990 and 2023 are provided in Figures 1,2 and Table 1. Overall, the ASIR, ASPR, and ASYR tended to decrease across the region. The ASIR demonstrated significant increasing trends in China (EAPC =0.35, 95% CI: 0.01 to 0.69) and the DPRK (EAPC =0.61, 95% CI: 0.54 to 0.68), whereas significant decreasing trends were observed in Japan (EAPC =−0.87, 95% CI: −0.95 to −0.79), Mongolia (EAPC =−0.65, 95% CI: −0.75 to −0.55), and the ROK (EAPC =−1.43, 95% CI: −1.52 to −1.34). The trends for ASPR and ASYR closely mirrored those of the ASIR within each country. However, significant national heterogeneity was observed. In particular, the ROK exhibited the highest age-standardized burden among all the countries in both 1990 and 2023, yet a significant decline was observed: the ASIR decreased from 274.21 (95% UI: 212.27 to 347.45) in 1990 to 190.34 (95% UI: 142.75 to 265.83) in 2023, the ASPR decreased from 89.20 (95% UI: 77.42 to 102.17) to 56.35 (95% UI: 47.95 to 67.01), and the ASYR decreased from 14.67 (95% UI: 9.84 to 21.39) to 9.91 (95% UI: 6.41 to 15.30) per 100,000 population. This corresponded to a substantial declining trend from 1990 to 2023, with an average annual percentage change (AAPC) of −1.11% (95% CI: −1.14 to −1.08) for the ASIR, −1.39% (95% CI: −1.41 to −1.37) for the ASPR, and −1.19% (95% CI: −1.22 to −1.16) for the ASYR in the total population (Figure 3A-3C). The ASRs of severe chest injury burden in the DPRK significantly increased from 1990 to 2023, as measured by the AAPC (0.54, 95% CI: 0.51 to 0.56).

Figure 1 ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; ASYR, age-standardized YLDs rate; YLDs, years lived with disability.

Figure 2 AAPC, average annual percentage change; ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; ASYR, age-standardized YLDs rate; EAPC, estimated annual percentage change; YLDs, years lived with disability.

Figure 3 AAPC, average annual percentage change; CI, confidence interval; YLDs, years lived with disability.

Further analysis of age-specific patterns revealed a significant epidemiological shift. The incidence patterns between 1990 and 2023 are compared in Figure S2. In 1990, the peak incidence occurred in the 20–44-year-old population across all countries. By 2023, the patterns had diverged: the peak incidence remained concentrated in young and middle-aged adults in China, Mongolia, and the DPRK, whereas Japan and the ROK exhibited a shift to a pattern characterized by the highest incidence among the population aged 80 years and older. A marked sex disparity was evident across all age groups, with rates approximately two to three times greater for males than for females. This disparity was most pronounced in young and middle adulthood (ages 15–44 years).

Joinpoint regression analysis revealed complex temporal dynamics (Table S2). In China, a sharp increase was observed from 2005 to 2009 (APC =5.15, 95% CI: 4.31 to 6.30), which moderated but remained significant from 2009 to 2015 (APC =1.73, 95% CI: 1.19 to 2.17). This was followed by a notable sharp decline during 2015–2020 (APC =−6.58, 95% CI: −7.04 to −6.11). However, this downward trend reversed, with a significant rebound occurring after 2020 (2020–2023: APC =3.21, 95% CI: 2.19 to 4.17). Japan also exhibited a critical trend reversal, with a long-term decline reversing to a significant increase after 2020 (APC =2.03, 95% CI: 0.71 to 4.09). The DPRK showed a persistent slow increase, and that in Mongolia demonstrated a consistent downward trend (APC =−0.65, 95% CI: −0.75 to −0.55), whereas the decline in the ROK has fluctuated but has stabilized in recent years (Figures S3,S4).

APC analysis

The age, period, and cohort effects for the ASIR, ASPR and ASYR of severe chest trauma derived from the APC model analysis across the five East Asian countries are shown in Figure 4. Age-specific analysis revealed a characteristic J-shaped curve across the lifespan. The ASIR was highest in early childhood, decreased through adolescence and early adulthood, and increased steadily from middle age onward, with the oldest age groups (80+ years) showing the highest rates. This pattern for ASIR, ASPR, and ASYR was consistent across all five countries (Tables S3-S5). Period effects showed divergent patterns. Using 2004–2008 as a reference (RR =1), the ASIR for China and the DPRK showed increased RRs in later periods (China 2014–2018: RR =1.22; 95% UI: 1.15 to 1.29; DPRK 2019–2023: RR =1.14; 95% UI: 1.06 to 1.22), whereas these values decreased favorably in Japan, Mongolia, and the ROK, with RRs significantly below 1 in recent periods (Japan 2019–2023: RR =0.89; 95% UI: 0.87 to 0.92; Mongolia 2014–2018: RR =0.83; 95% UI: 0.7 to 0.98; and the ROK 2019–2023: RR =0.89; 95% UI: 0.87 to 0.91). Similar patterns of period effects were consistently observed for the ASPR and the ASYR (Tables S6-S8). The cohort effects revealed significant heterogeneity in intergenerational risk. Using the 1954–1963 birth cohort as the reference (RR =1), a clear divergence emerged. In China and the DPRK, more recent birth cohorts faced progressively higher risks. Conversely, in Japan, the ROK, and Mongolia, younger cohorts exhibited progressively lower RRs.

Figure 4 .

This pattern was consistent across different burden metrics. For the ASIR in the 2004–2013 cohort, the RR increased in China (RR =1.32, 95% UI: 1.22–1.43) and the DPRK (RR =1.46, 95% UI: 1.38–1.54) but decreased in Japan (RR =0.65, 95% UI: 0.61–0.70), the ROK (RR =0.42, 95% UI: 0.39–0.44), and Mongolia (RR =0.72, 95% UI: 0.64–0.81). A nearly identical protective pattern was observed for the ASYR in the same cohort, with RRs of 0.64 (95% UI: 0.59–0.70) in Japan, 0.41 (95% UI: 0.36–0.46) in the ROK, and 0.70 (95% UI: 0.41–1.20) in Mongolia, which contrast with elevated risks in China (RR =1.29, 95% UI: 1.20–1.39) and the DPRK (RR =1.43, 95% UI: 1.19–1.72). These findings indicate that cohort effects profoundly influence not only the incidence but also the long-term disabling consequences of severe chest trauma (Tables S9-S11).

Decomposition analysis of changes in YLDs

Decomposition analysis quantified the contributions of population aging and changes in case fatality/disease severity to YLDs changes from 1990 to 2023 (Table S12, Figure 5). In China, the overall increase in YLDs (3,119.31 thousand) was driven by a large positive contribution from case fatality/disease severity changes (+162.59%), which offset a substantial negative contribution from population aging (−378.33%). A similar pattern was observed in the DPRK, where an overall increase was primarily attributable to case fatality/disease severity changes (+8.06%). Conversely, in Japan and the ROK, overall decreases in YLDs were driven by favorable case fatality/disease severity changes, which counteracted the upward pressure from population aging. Mongolia exhibited a slight increase, which was driven mainly by changes in case fatality/disease severity (+12.69%).

Figure 5 .

Sex-stratified analysis revealed that these patterns were generally consistent f or both sexes within each country, although the magnitude of the contributions varied. The analysis highlights that temporal changes in YLDs were predominantly driven by changes in case fatality and disease severity across the region.

ARIMA prediction

Short-term forecasts (2024–2048) based on optimal ARIMA models indicate a clear divergence in the future burden trends of severe chest injury among the five East Asian countries (Table S13, Figure 6). The models for YLDs demonstrated superior goodness-of-fit, with AIC and BIC values that were negative across all countries, indicating higher robustness for YLD projections than for incidence and prevalence models. The projections show that the ASIR, ASPR, and ASYR in China, Mongolia, and the DPRK are expected to remain stable or exhibit a slight increasing trend over the forecast period. In contrast, the corresponding indicators for Japan and the ROK are projected to remain stable or continue to decline. Notably, although the projected disease burden levels in Japan and the ROK remain numerically higher than those in the other three countries—which is consistent with historical patterns—their declining trends suggest that regional disparities in disease burden are likely to persist rather than converge in the near term.

Figure 6 ASIR, age-standardized incidence rate; ASPR, age-standardized prevalence rate; ASYR, age-standardized YLDs rate; YLDs, years lived with disability.

Discussion

This study, for the first time, systematically assessed the trends in the disease burden of severe chest injury across five East Asian countries from 1990 to 2023 on the basis of GBD 2023 data. APC modeling, decomposition analysis, and time series modeling were employed for in-depth examination. Research findings indicate that while the overall ASR across the region shows a slight downward trend, significant heterogeneity exists among countries: China and the DPRK exhibit increasing trends in ASRs, whereas Japan, Mongolia, and the ROK demonstrate consistent declining trends in these indicators. APC modeling further revealed that period and cohort effects are the primary drivers of these cross-national disparities. Decomposition analysis revealed that changes in case severity constitute the key factor influencing the evolution of severe chest injury burden, with its impact surpassing the contribution of demographic shifts. Moreover, the study revealed consistent and significant J-shaped age-risk curves and persistent male disease burden advantages across all countries, providing crucial demographic evidence for the development of targeted public health interventions.

The marked difference in the burden of severe chest trauma among the five East Asian countries reflects profound underlying disparities in socioeconomic development stages, the efficacy of trauma prevention and treatment systems, and the implementation of public policies (12-14). For nations with worsening trends (China and the DPRK), the increase in period and cohort risks should be interpreted within the framework of a “trauma epidemiological transition” (14). Taking China as an example, a key paradox arises: while the age-standardized mortality rate from road traffic injuries involving motor vehicles has shown an overall decline (9,14), the burden of severe chest injury continues to increase. This phenomenon is attributed primarily to two major shifts. First, a transformation in trauma patterns, whereby advances in emergency response and clinical care have increased the survival of critically injured patients, although often with significant long-term disability (15-17). Second, a structural change in the system of high-risk exposures. The rapid proliferation of electric bicycles and electric mopeds, coupled with trends toward higher speeds and heavier vehicles, has positioned riders as an extremely high-risk group for severe cranial and thoracic trauma (18,19). Injuries associated with these emerging modes of transport have become a major public health challenge (20). Concurrently, occupational injury risks persist in high-hazard sectors such as construction (7). Furthermore, the efficiency of macro-level policy warrants scrutiny. Research has indicated a positive correlation between the scale of transportation investment and traffic fatalities, particularly in underdeveloped regions such as northwest China (12). This suggests that investments prioritizing network expansion over improvements in road quality, safety infrastructure, and refined traffic management may inadvertently increase the incidence of high-risk accidents. The persistent upward trajectory in the DPRK is likely closely associated with its relatively constrained public health resources, lagging modernization of the healthcare system, and ongoing economic challenges (21).

For nations with improving trends (Japan, the ROK, and Mongolia), the favorable period and cohort effects corroborate the efficacy of population-wide prevention and systematic improvements. The declining trends in Japan and the ROK are attributable to decades of stringent traffic safety regulations, occupational safety, and the establishment of efficient regionalized trauma care networks (22). Global research provides corroborating evidence indicating that the ROK experienced one of the most substantial declines globally in the ASRs for occupational injury-related transport and unintentional injuries between 1990 and 2021, reflecting its exceptional success in occupational injury prevention (23). The declining trend in Mongolia may be associated with its lower population density and progressively improving primary healthcare coverage (24). However, a signal warranting heightened vigilance is the trend reversal observed in Japan after 2020. This may stem from a confluence of factors, including a surge in fall risk driven by a profoundly aging society, compounded by disruptions in the management of chronic conditions and alterations in social activity patterns associated with the COVID-19 pandemic (25). This finding suggests that even high-performing trauma prevention and care systems must confront novel challenges arising from dramatic demographic shifts and major public health crises.

The application of the APC model provided mechanistic insights that extend beyond simple descriptive trends in the burden of chest trauma (25). The consistent observation of a J-shaped age effect corroborates the established biological and social behavioral underpinnings of trauma risk. Children and adolescents exhibit heightened vulnerability because of the ongoing development of motor coordination and risk perception, whereas older adults face increased susceptibility attributable to factors such as osteoporosis, diminished postural stability, and a higher prevalence of comorbidities (26,27). This pattern underscores the enduring importance of targeted prevention strategies at both ends of the life course—namely, child safety and fall prevention among elderly people. Concurrently, the substantial absolute burden related to the young and middle-aged adult population, located at the nadir of the J curve, warrants considerable attention. Although this group demonstrates lower RR, their role as the primary workforce and key participants in road traffic—particularly as riders of vehicles such as electric bicycles—subject them to the greatest cumulative duration and intensity of exposure to high-risk environments. Consequently, the absolute trauma burden and its associated socioeconomic impact on this demographic remain considerable (13).

The APC model elucidates the mechanisms behind national trends through period and cohort effects. The adverse period effects (RR >1) in China and the DPRK indicate that, over recent decades, the intensification of risk factors—primarily from rapid urbanization and motorization—has outstripped the development and enforcement of corresponding preventive measures (12,28). In contrast, the favorable period effects (RR <1) in Japan, the ROK, and Mongolia reflect the success of sustained, society-wide investments in areas such as stringent traffic legislation, vehicle safety standards, occupational oversight, and mature trauma systems, which have collectively created a safer historical environment for all citizens (20,22,29,30).

Furthermore, the divergence in cohort effects reveals a critical intergenerational legacy. The elevated risk among younger birth cohorts in China and the DPRK suggests that newer generations are maturing in an environment where emerging risks (e.g., from specific vehicle types or novel occupational hazards) are not yet adequately controlled (19,20). Conversely, the progressively lower risk in younger cohorts in Japan, the ROK, and Mongolia demonstrates the long-term, cross-generational return on early and sustained investment in public health infrastructure, safety culture, and preventive education, resulting in the cultivation of generations with inherently lower risk profiles (30).

According to decomposition analysis, temporal changes in YLDs are quantitatively attributed to two primary components, population aging and changes in case outcomes (mortality/severity); this analysis provided crucial evidence for interpreting observed trends (1,31). A recent global burden analysis focusing on sternal and/or rib fracture similarly reported increasing absolute case numbers and YLDs despite declining ASRs, underscoring the driving role of population growth and aging on the absolute burden (7).

The pervasive and substantial sex disparity observed in this study—with the male burden being approximately 2–3 times greater than the female burden—is highly consistent with the global epidemiology of trauma (1). This disparity is largely attributable to males’ greater exposure to hazardous occupations (e.g., construction, mining, and transport), higher-risk behavioral patterns (e.g., dangerous driving and alcohol use), and more frequent involvement in violent events (32). This disparity is most pronounced among young and middle-aged adults, highlighting the urgency of targeted behavioral interventions and safety education for men, particularly in occupational and high-risk recreational settings.

Projections based on the selected ARIMA models provide a basis for future planning. The variation in optimal models reflects the distinct temporal dynamics of chest trauma incidence in each country. These models establish a robust foundation for short-term burden forecasting, suggesting that if current trends persist, the disparity in disease burden between nations may widen, necessitating proactive and differentiated resource allocation strategies.

The core strength of this study lies in its pioneering multidimensional comparative analysis of the severe chest trauma burden across five East Asian countries over more than three decades. By integrating advanced statistical methodologies—including APC modeling, decomposition analysis, and time-series forecasting—it systematically elucidates the demographic forces, historical period effects, birth cohort risks, and core drivers influencing burden trends, offering profound insights into the complexity of trauma epidemiology in the region.

However, this study has several limitations. First, the GBD data are inherently modeled estimates, and for countries such as the DPRK with potentially less complete vital registration systems, the associated uncertainty is relatively high. Second, as an ecological study, it demonstrates statistical associations at the macro level but cannot infer causality at the individual level. Third, the APC model suffers from an inherent “identification problem” because of the perfect collinearity between age, period, and cohort effects; therefore, the interpretation of these effects requires cautious contextualization within specific historical and social backgrounds. Finally, this study did not incorporate national-level covariates—such as per capita GDP, physicians per 10,000 population, or the stringency of specific traffic safety legislation—into multivariate models for quantitative association analysis. Future research incorporating such socioeconomic and policy variables could further reveal the structural determinants underlying cross-national disparities in disease burden.

Conclusions

In conclusion, the trajectory of severe chest injury burden in East Asia is not demographically predetermined but is critically shaped by modifiable period and cohort risks, with trauma care system performance as a decisive factor. To address these patterns, we propose targeted strategies: for nations with rising burden (China, DPRK), strengthen primary prevention (e.g., e-bike regulation) and optimize trauma care; for aging societies (Japan, ROK), integrate fall prevention into core health strategies; and for all countries, implement sex-sensitive prevention and establish trauma registries for data-driven policymaking.

Acknowledgments

The authors thank the Global Burden of Disease (GBD) 2023 study team and the Institute for Health Metrics and Evaluation (IHME) for providing the data used in this analysis. The R code used for the age-period-cohort analysis, joinpoint regression, decomposition analysis, and ARIMA forecasting is available from the corresponding author upon reasonable request.

Footnote

Reporting Checklist: The authors have completed the GATHER reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1000/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1000/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1000/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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