Timely identification and treatment of Diabetic Retinopathy (DR) is critical in avoiding vision loss. DR screening is challenging, especially in resource-limited areas where trained ophthalmologists are scarce. AI solutions show promise in addressing this challenge. In this study, the performance metrics of an AI solution (MadhuNetrAI) developed in India was evaluated for referring and grading DR.
Methods
MadhuNetrAI was developed de novo by the All India Institute of Medical Sciences (AIIMS) and Wadhwani AI (WIAI). It was tested on 1078 fundus images (from AIIMS Delhi and an unannotated subset of publicly available EyePACS images) against two ophthalmologists and an adjudicator serving as independent gold-standard annotators, wherein the disease status of the patients remained unknown.
Findings
MadhuNetrAI demonstrated high sensitivity (93·2 %; CI: 89·5 %–95·6 %) and specificity (95·3 %; CI: 93·7 %–96·6 %) in detecting referable DR (moderate, severe, proliferative DR). The area-under-the-curve for referring DR against the gold standard was 0·97 (CI: 0·95–0·99) indicating excellent diagnostic performance. The agreement in grading DR severity was high (kappa = 0·89, CI: 0·86–0·91). The model performed comparably in detecting DR too.
Interpretation
MadhuNetrAI's ability to grade DR severity and identify referrable cases could bring DR patients to care much earlier. Further research and clinical trials are needed to ensure its reliability and generalizability across diverse populations and image qualities.
Funding
MadhuNetrAI was developed by technical and programmatic teams at WIAI, with inputs and contributions by the clinical team at AIIMS, and funded by USAID. The authors have no financial or non-financial conflicts of interest to disclose.
{"title":"Artificial intelligence for advancing eye care in resource-poor settings: Assessing the predictive accuracy of an AI-model for diabetic retinopathy screening in India","authors":"Rohan Chawla , Prachi Karkhanis , Malay Shah , Aritra Das , Rishabh Sharma , Dhwani Almaula , Pradeep Venkatesh , Harsh Vardhan Singh , Mukul Kumar , Ramanuj Samanta , Vinod Kumarl , Amar Shah , Bhavin Vadera , Nakul Jain , Akanksha Sen , Shyamsundar Shreedhar , Vipin Garg , Soma Dhaval , Kowshik Ganesh , Srinivas Rana , Radhika Tandon","doi":"10.1016/j.gloepi.2025.100209","DOIUrl":"10.1016/j.gloepi.2025.100209","url":null,"abstract":"<div><h3>Background</h3><div>Timely identification and treatment of Diabetic Retinopathy (DR) is critical in avoiding vision loss. DR screening is challenging, especially in resource-limited areas where trained ophthalmologists are scarce. AI solutions show promise in addressing this challenge. In this study, the performance metrics of an AI solution (MadhuNetrAI) developed in India was evaluated for referring and grading DR.</div></div><div><h3>Methods</h3><div>MadhuNetrAI was developed de novo by the All India Institute of Medical Sciences (AIIMS) and Wadhwani AI (WIAI). It was tested on 1078 fundus images (from AIIMS Delhi and an unannotated subset of publicly available EyePACS images) against two ophthalmologists and an adjudicator serving as independent gold-standard annotators, wherein the disease status of the patients remained unknown.</div></div><div><h3>Findings</h3><div>MadhuNetrAI demonstrated high sensitivity (93·2 %; CI: 89·5 %–95·6 %) and specificity (95·3 %; CI: 93·7 %–96·6 %) in detecting referable DR (moderate, severe, proliferative DR). The area-under-the-curve for referring DR against the gold standard was 0·97 (CI: 0·95–0·99) indicating excellent diagnostic performance. The agreement in grading DR severity was high (kappa = 0·89, CI: 0·86–0·91). The model performed comparably in detecting DR too.</div></div><div><h3>Interpretation</h3><div>MadhuNetrAI's ability to grade DR severity and identify referrable cases could bring DR patients to care much earlier. Further research and clinical trials are needed to ensure its reliability and generalizability across diverse populations and image qualities.</div></div><div><h3>Funding</h3><div>MadhuNetrAI was developed by technical and programmatic teams at WIAI, with inputs and contributions by the clinical team at AIIMS, and funded by USAID. The authors have no financial or non-financial conflicts of interest to disclose.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100209"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144231531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2024-12-25DOI: 10.1016/j.gloepi.2024.100179
Louis Anthony Cox Jr. , R. Jeffrey Lewis , Saumitra V. Rege , Shubham Singh
AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions. These reveal the extent of heterogeneity in risks across individuals for different levels of exposure, holding other variables fixed. By applying these methods to an illustrative dataset on blood lead levels (BLL) and mortality risk among never-smoker men from the NHANES III survey, we show how AI can clarify inter-individual variations in exposure-associated risks. The results add insights not easily obtained from traditional parametric or semi-parametric models such as logistic regression and Cox proportional hazards models, illustrating the advantages of non-parametric approaches for quantifying heterogeneous causal effects on survival times. This paper also suggests some practical implications of using AI in regulatory health risk assessments and public policy decisions.
{"title":"AI-assisted exposure-response data analysis: Quantifying heterogeneous causal effects of exposures on survival times","authors":"Louis Anthony Cox Jr. , R. Jeffrey Lewis , Saumitra V. Rege , Shubham Singh","doi":"10.1016/j.gloepi.2024.100179","DOIUrl":"10.1016/j.gloepi.2024.100179","url":null,"abstract":"<div><div>AI-assisted data analysis can help risk analysts better understand exposure-response relationships by making it relatively easy to apply advanced statistical and machine learning methods, check their assumptions, and interpret their results. This paper demonstrates the potential of large language models (LLMs), such as ChatGPT, to facilitate statistical analyses, including survival data analyses, for health risk assessments. Through AI-guided analyses using relatively recent and advanced methods such as Individual Conditional Expectation (ICE) plots using Random Survival Forests and Heterogeneous Treatment Effects (HTEs) estimated using Causal Survival Forests, population-level exposure-response functions can be disaggregated into individual-level exposure-response functions. These reveal the extent of heterogeneity in risks across individuals for different levels of exposure, holding other variables fixed. By applying these methods to an illustrative dataset on blood lead levels (BLL) and mortality risk among never-smoker men from the NHANES III survey, we show how AI can clarify inter-individual variations in exposure-associated risks. The results add insights not easily obtained from traditional parametric or semi-parametric models such as logistic regression and Cox proportional hazards models, illustrating the advantages of non-parametric approaches for quantifying heterogeneous causal effects on survival times. This paper also suggests some practical implications of using AI in regulatory health risk assessments and public policy decisions.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100179"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11757793/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143047962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-08DOI: 10.1016/j.gloepi.2025.100204
Nicole Rafalko , Milena Gianfrancesco , Neal D. Goldstein
The increasing availability and accessibility of electronic health record (EHR) data has made it a rich secondary source to conduct comparative effectiveness studies. To perform such studies, many researchers are turning to the target trial framework (TTF) to emulate the hypothetical randomized clinical trial. The quality of this emulation depends, in part, on the availability and accessibility of data for each component of the TTF. Yet one overarching challenge with using EHR data is that unstructured fields, such as clinical encounter notes, contain copious details on the patient yet require additional steps to extract if needed in the conduct of the study. Natural language processing (NLP) represents a spectrum of methods to assist with automating this extraction, from simpler rule-based methods to machine learning and artificial intelligence approaches that can handle complex language structures. What follows is a discussion on how NLP methods can augment information and data for researchers looking to estimate a treatment effect using EHR data via the TTF to emulate the hypothetical clinical trial. We conclude with recommendations for researchers interested in using NLP methods to obtain data stored in the free text of the EHR as well as considerations regarding the quality and validity of this data for the TTF.
{"title":"On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record","authors":"Nicole Rafalko , Milena Gianfrancesco , Neal D. Goldstein","doi":"10.1016/j.gloepi.2025.100204","DOIUrl":"10.1016/j.gloepi.2025.100204","url":null,"abstract":"<div><div>The increasing availability and accessibility of electronic health record (EHR) data has made it a rich secondary source to conduct comparative effectiveness studies. To perform such studies, many researchers are turning to the target trial framework (TTF) to emulate the hypothetical randomized clinical trial. The quality of this emulation depends, in part, on the availability and accessibility of data for each component of the TTF. Yet one overarching challenge with using EHR data is that unstructured fields, such as clinical encounter notes, contain copious details on the patient yet require additional steps to extract if needed in the conduct of the study. Natural language processing (NLP) represents a spectrum of methods to assist with automating this extraction, from simpler rule-based methods to machine learning and artificial intelligence approaches that can handle complex language structures. What follows is a discussion on how NLP methods can augment information and data for researchers looking to estimate a treatment effect using EHR data via the TTF to emulate the hypothetical clinical trial. We conclude with recommendations for researchers interested in using NLP methods to obtain data stored in the free text of the EHR as well as considerations regarding the quality and validity of this data for the TTF.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100204"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143935152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-04-22DOI: 10.1016/j.gloepi.2025.100200
Evans O. Omorogie , Kolade M. Owolabi , Bola T. Olabode , Tunde T. Yusuf , Edson Pindza
The resurgence of Covid-19, accompanied by various variants of the virus, highlights the fact that Covid-19 is still present within the population. The study proposed a Covid-19 dynamical model for analyzing the effect of vaccination and the continuous use of non-medical interventions for addressing Covid-19 transmission dynamics. The Lyaponov function and Jacobian matrix techniques were used to analyze the stability of the model's equilibria. The model was transformed into a problem of optimal control with time-dependent variables, aimed at managing efforts to prevent the spread of Covid-19. Numerical assessments were deployed to assess the effect of vaccination and the continuous use of non-medical intervention strategies to mitigate the spread of Covid-19. The global sensitivity analysis of the model was used to detect the key parameters influencing the behavior of the model. In addition, numerical results showed a significant decrease in the basic reproduction rate when implementing and , either separately or together. The optimal control results suggested that the control measures should be consistently enforced without any relaxation.
{"title":"Resurgence in focus: Covid-19 dynamics and optimal control frameworks","authors":"Evans O. Omorogie , Kolade M. Owolabi , Bola T. Olabode , Tunde T. Yusuf , Edson Pindza","doi":"10.1016/j.gloepi.2025.100200","DOIUrl":"10.1016/j.gloepi.2025.100200","url":null,"abstract":"<div><div>The resurgence of Covid-19, accompanied by various variants of the virus, highlights the fact that Covid-19 is still present within the population. The study proposed a Covid-19 dynamical model for analyzing the effect of vaccination and the continuous use of non-medical interventions for addressing Covid-19 transmission dynamics. The Lyaponov function and Jacobian matrix techniques were used to analyze the stability of the model's equilibria. The model was transformed into a problem of optimal control with time-dependent variables, aimed at managing efforts to prevent the spread of Covid-19. Numerical assessments were deployed to assess the effect of vaccination and the continuous use of non-medical intervention strategies to mitigate the spread of Covid-19. The global sensitivity analysis of the model was used to detect the key parameters influencing the behavior of the model. In addition, numerical results showed a significant decrease in the basic reproduction rate <span><math><mfenced><msub><mi>ℛ</mi><mn>0</mn></msub></mfenced></math></span> when implementing <span><math><mi>σ</mi></math></span> and <span><math><mi>ξ</mi></math></span>, either separately or together. The optimal control results suggested that the control measures should be consistently enforced without any relaxation.</div><div>2010 Mathematics Subject Classification: 92D30, 93C95, 49 N90, 34H05, 37 N25.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100200"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-05-10DOI: 10.1016/j.gloepi.2025.100205
Hanan Abdulghafoor Khaleel , Riyadh Abdulameer Alhilfi , Sabrina Brown
Background
Since the start of the first large outbreak of Crimean Congo Hemorrhagic Fever (CCHF) in Iraq in 2022, there has been no assessment of clustering of cases by district. The aim of this study is to identify clusters of high and low incidences of human CCHF to guide preventive and control measures, and distribute limited resources.
Methods
This is a cross-sectional study of reported and confirmed CCHF cases in Iraq from January 1, 2023 to December 11, 2023. We used a retrospective purely spatial Poisson scan statistic model to identify clusters of high and low incidences of CCHF at the district level (p < 0.05).
Findings
There were 580 confirmed CCHF cases, distributed in 149 districts. The incidence was 1.3 per 100,000. There were eight statistically significant clusters (three high-incidence and five low-incidence). The three high-incidence clusters were in the southeast while the five low-incidence clusters were mostly in the north and middle-east Iraq.
Interpretation
There is evidence of CCHF clustering in 40 districts in six governorates in south and mid-east Iraq. Additionally, there is evidence of low-incidence clustering of CCHF in 17 governorates, in north and central Iraq, and a risk for future outbreaks. Identifying clusters allows for focused preventive activities, such as insecticide spraying to reduce the tick population, controlling the spread of ticks by treating animals with repellents and other chemicals, and modifying landscapes. Distributing educational materials about handling meat and livestock products and engaging the community can help reduce exposure to ticks and the spread of disease.
{"title":"Detecting spatial clusters of Crimean Congo hemorrhagic fever in Iraq in 2023","authors":"Hanan Abdulghafoor Khaleel , Riyadh Abdulameer Alhilfi , Sabrina Brown","doi":"10.1016/j.gloepi.2025.100205","DOIUrl":"10.1016/j.gloepi.2025.100205","url":null,"abstract":"<div><h3>Background</h3><div>Since the start of the first large outbreak of Crimean Congo Hemorrhagic Fever (CCHF) in Iraq in 2022, there has been no assessment of clustering of cases by district. The aim of this study is to identify clusters of high and low incidences of human CCHF to guide preventive and control measures, and distribute limited resources.</div></div><div><h3>Methods</h3><div>This is a cross-sectional study of reported and confirmed CCHF cases in Iraq from January 1, 2023 to December 11, 2023. We used a retrospective purely spatial Poisson scan statistic model to identify clusters of high and low incidences of CCHF at the district level (<em>p</em> < 0.05).</div></div><div><h3>Findings</h3><div>There were 580 confirmed CCHF cases, distributed in 149 districts. The incidence was 1.3 per 100,000. There were eight statistically significant clusters (three high-incidence and five low-incidence). The three high-incidence clusters were in the southeast while the five low-incidence clusters were mostly in the north and middle-east Iraq.</div></div><div><h3>Interpretation</h3><div>There is evidence of CCHF clustering in 40 districts in six governorates in south and mid-east Iraq. Additionally, there is evidence of low-incidence clustering of CCHF in 17 governorates, in north and central Iraq, and a risk for future outbreaks. Identifying clusters allows for focused preventive activities, such as insecticide spraying to reduce the tick population, controlling the spread of ticks by treating animals with repellents and other chemicals, and modifying landscapes. Distributing educational materials about handling meat and livestock products and engaging the community can help reduce exposure to ticks and the spread of disease.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100205"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144069407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anxiety is the state of being worried and uneasy about anything that happens either now or in the future. It is unclear what exactly causes generalized anxiety disorder (GAD). According to some research, a variety of variables, including heredity, differences in brain chemistry, and environmental influences, could be involved. After the Sudanese army battle began in 2023, the purpose of this study was to determine the prevalence of generalized anxiety disorder among Sudanese teenagers.
Methods
A cross-sectional, community-based study was carried out among all Sudanese adolescents between 13 and 18 years old who were living in Sudan at the start of the conflict by using a self-administered questionnaire under the guidance of parents, if necessary. The questionnaire was adapted from the Generalized Anxiety Disorder-7 checklist for the assessment of GAD symptoms. The questionnaire was translated into Arabic by expert translators, and its validity and reliability were confirmed. Data were analyzed and presented in the form of descriptive and inferential statistics.
Results
Among the 855 participants, the mean age was 16.5 years, 66.8 % were female, and 50.8 % had generalized anxiety disorder. There was a significant positive relationship between GAD and age, sex, current residency, and traumatic events exposure. With participants aged 17–18 years old having 82 % higher odds of experiencing GAD in comparison with the reference age group (OR = 1.8 (95 % CI [1.2, 2.7])). Furthermore, females were found to have 92 % higher odds for GAD as compared with men (OR = 1.9 (95 % CI [1.4, 2.6])). Whereas internally displaced participants showed 205 % higher odds of GAD in comparison to those who had not been in a war zone (OR = 3.1 (95 % CI [2.11, 4.4])). In addition, experiencing a traumatic event during the war increases the odds of having GAD by 126 % in comparison to those who did not experience it (OR = 2.3 (95 % CI [1.7, 3.1])).
Conclusion
GAD was highly prevalent among the Sudanese adolescents included in the present study. The findings will help the government to provide proper mental health interventions for affected people.
{"title":"Generalized anxiety disorder and associated factors among Sudanese adolescents during the Sudan Army conflict: A cross sectional study","authors":"Mohammed Haydar Awad , Maram Elmutasim , Maeen Mohieldin Mohamed , Lina Hemmeda","doi":"10.1016/j.gloepi.2025.100190","DOIUrl":"10.1016/j.gloepi.2025.100190","url":null,"abstract":"<div><h3>Background</h3><div>Anxiety is the state of being worried and uneasy about anything that happens either now or in the future. It is unclear what exactly causes generalized anxiety disorder (GAD). According to some research, a variety of variables, including heredity, differences in brain chemistry, and environmental influences, could be involved. After the Sudanese army battle began in 2023, the purpose of this study was to determine the prevalence of generalized anxiety disorder among Sudanese teenagers.</div></div><div><h3>Methods</h3><div>A cross-sectional, community-based study was carried out among all Sudanese adolescents between 13 and 18 years old who were living in Sudan at the start of the conflict by using a self-administered questionnaire under the guidance of parents, if necessary. The questionnaire was adapted from the Generalized Anxiety Disorder-7 checklist for the assessment of GAD symptoms. The questionnaire was translated into Arabic by expert translators, and its validity and reliability were confirmed. Data were analyzed and presented in the form of descriptive and inferential statistics.</div></div><div><h3>Results</h3><div>Among the 855 participants, the mean age was 16.5 years, 66.8 % were female, and 50.8 % had generalized anxiety disorder. There was a significant positive relationship between GAD and age, sex, current residency, and traumatic events exposure. With participants aged 17–18 years old having 82 % higher odds of experiencing GAD in comparison with the reference age group (OR = 1.8 (95 % CI [1.2, 2.7])). Furthermore, females were found to have 92 % higher odds for GAD as compared with men (OR = 1.9 (95 % CI [1.4, 2.6])). Whereas internally displaced participants showed 205 % higher odds of GAD in comparison to those who had not been in a war zone (OR = 3.1 (95 % CI [2.11, 4.4])). In addition, experiencing a traumatic event during the war increases the odds of having GAD by 126 % in comparison to those who did not experience it (OR = 2.3 (95 % CI [1.7, 3.1])).</div></div><div><h3>Conclusion</h3><div>GAD was highly prevalent among the Sudanese adolescents included in the present study. The findings will help the government to provide proper mental health interventions for affected people.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines the association between general and central obesity and the risk of cardiovascular diseases, utilizing the Targeted Maximum Likelihood Estimator (TMLE) method to account for time-varying covariates and also we compares the findings with those derived from conventional regression methods in the Atherosclerosis Risk in Communities (ARIC) cohort study.
Methods
We considered 15,792 participants 45–75 years of age registered in the Atherosclerosis Risk in Communities study, visit 1 and followed to visit 4. General obesity defined as body mass index and central obesity defined as Waist Circumference (WC), Waist-Hip-Ratio (WHR), Waist-Height-Ratio (WHtR), Body Shape Index (BSI) and Body Roundness Index (BRI). The effect of obesity on Coronary Heart Disease (CHD) was estimated and compared by Longitudinal Targeted Maximum Likelihood Estimation (LTMLE) and generalized linear model.
Results
The effects of BMI, adjusted for baseline and time-varying confounders, was 1.15 (95 %CI =1.00, 1.34). About the gender groups, the effect of BMI for males and females was 1.17 (95 %CI =0.97,1.40) and 1.19 (95 %CI =0.94,1.52), respectively. Considering age groups, the effect of BMI was 1.21 (95 %CI =0.95, 1.53) and 1.13 (95 %CI = 0.93, 1.36) for age ≤ 54 years and age > 54 years, respectively. With regards to central obesity, the BSI and WC were shown the strongest effects, respectively. Among females and age group≤54 years, WHtR was associated with a higher incidence of CHD.
Conclusions
According to the results, the appropriate index for obesity varies based on gender and age. Knowledge about this difference will help to experts to implement appropriate interventions.
目的：本研究利用目标最大似然估计（Targeted Maximum Likelihood Estimator， TMLE）方法来解释时变协变量，并将结果与社区动脉粥样硬化风险（ARIC）队列研究中传统回归方法得出的结果进行比较，探讨了一般肥胖和中心性肥胖与心血管疾病风险之间的关系。方法：我们纳入了15792名年龄在45-75岁之间的社区动脉粥样硬化风险研究的参与者，随访随访至随访4。一般肥胖定义为体重指数，中心性肥胖定义为腰围（WC）、腰臀比（WHR）、腰高比（WHtR）、体型指数（BSI）和身体圆度指数（BRI）。采用纵向目标最大似然估计（LTMLE）和广义线性模型估计和比较肥胖对冠心病（CHD）的影响。结果经基线和时变混杂因素调整后，BMI的影响为1.15 （95% CI =1.00, 1.34）。在性别分组中，BMI对男性和女性的影响分别为1.17 （95% CI =0.97,1.40）和1.19 （95% CI =0.94,1.52）。从年龄组来看，BMI对年龄≤54岁和年龄>的影响分别为1.21 （95% CI =0.95, 1.53）和1.13 (95% CI = 0.93, 1.36)；分别是54年。对于中心性肥胖，体重指数和腰围分别表现出最强的影响。在女性和年龄≤54岁的人群中，WHtR与较高的冠心病发病率相关。结论根据研究结果，肥胖的适宜指标因性别和年龄而异。了解这种差异将有助于专家实施适当的干预措施。
{"title":"Time-varying confounders in association between general and central obesity and coronary heart disease: Longitudinal targeted maximum likelihood estimation on atherosclerosis risk in communities study","authors":"Hossein Mozafar Saadati PhD , Niloufar Taherpour MSc , Seyed Saeed Hashemi Nazari MD, MPH, PhD","doi":"10.1016/j.gloepi.2025.100193","DOIUrl":"10.1016/j.gloepi.2025.100193","url":null,"abstract":"<div><h3>Aim</h3><div>This study examines the association between general and central obesity and the risk of cardiovascular diseases, utilizing the Targeted Maximum Likelihood Estimator (TMLE) method to account for time-varying covariates and also we compares the findings with those derived from conventional regression methods in the Atherosclerosis Risk in Communities (ARIC) cohort study.</div></div><div><h3>Methods</h3><div>We considered 15,792 participants 45–75 years of age registered in the Atherosclerosis Risk in Communities study, visit 1 and followed to visit 4. General obesity defined as body mass index and central obesity defined as Waist Circumference (WC), Waist-Hip-Ratio (WHR), Waist-Height-Ratio (WHtR), Body Shape Index (BSI) and Body Roundness Index (BRI). The effect of obesity on Coronary Heart Disease (CHD) was estimated and compared by Longitudinal Targeted Maximum Likelihood Estimation (LTMLE) and generalized linear model.</div></div><div><h3>Results</h3><div>The effects of BMI, adjusted for baseline and time-varying confounders, was 1.15 (95 %CI =1.00, 1.34). About the gender groups, the effect of BMI for males and females was 1.17 (95 %CI =0.97,1.40) and 1.19 (95 %CI =0.94,1.52), respectively. Considering age groups, the effect of BMI was 1.21 (95 %CI =0.95, 1.53) and 1.13 (95 %CI = 0.93, 1.36) for age ≤ 54 years and age > 54 years, respectively. With regards to central obesity, the BSI and WC were shown the strongest effects, respectively. Among females and age group≤54 years, WHtR was associated with a higher incidence of CHD.</div></div><div><h3>Conclusions</h3><div>According to the results, the appropriate index for obesity varies based on gender and age. Knowledge about this difference will help to experts to implement appropriate interventions.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143593208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-14DOI: 10.1016/j.gloepi.2025.100197
Carlos Arturo Álvarez-Moreno , Ludovic Reveiz , Claudia Aristizabal , Jesús Quevedo , María Lucia Mesa Rubio , Leonardo Arévalo-Mora , Julián Felipe Porras Villamil , Monica Padilla , Juan Carlos Alzate-Angel , Jamie Rylance , Kurbonov Firdavs , Ilich de la Hoz , Sandra Liliana Valderrama-Beltran , Santiago Arboleda , Otto Sussmann , Javier Andrade , Carolina Murillo Velásquez , Estefania García , Ximena Galindo , Daniela Martínez , Antoine Chaillon
Introduction
In 2022, the world experienced a monkeypox outbreak caused by the Clade IIb strain of the virus. While this outbreak had widespread effects, more information is needed on mpox's specific impact in Colombia, particularly regarding how it is managed, its burden, and its epidemiology. This research seeks to examine the medical context, clinical presentation, and health outcomes of individuals diagnosed with mpox infection, with a particular focus on those with HIV in Colombia.
Methods
This retrospective study was conducted in fourteen Health institutions in Colombia based on computerized clinical records from Jan 2022 to Dec 2023. Clinical and epidemiological characteristics were collected from diagnosis until discharge (or death). Participants in the study were diagnosed through molecular methods (PCR) and their clinical evolution was tracked through hospital and/or outpatient medical records. Registered variables were based on the mpox 2023 Case Report Form (2023 - CRF) proposed by the World Health Organization.
Results
One thousand four hundred thirteen (1413, 97.2 % male) individuals, including 2.6 % identified as healthcare workers, were included in this study. The majority (54 %, 764/1413 individuals) were persons living with HIV (PWH) and almost one-third of them (30.1 %, n = 284) of participants had concomitant sexually transmitted diseases and HIV, with syphilis being the most prevalent (20.4 %), followed by Neisseria gonorrhoeae (16.4 %). Complications were infrequent, with cellulitis being the most common, and no individuals received mpox-specific treatment or vaccination. Although all individuals had skin lesions distributed across various body regions, differences were noted in lesion distribution among women. Those living with HIV showed higher emergency department attendance and reported having known mpox contacts. While complications were rare, with cellulitis being the most common, women living with HIV showed a higher rate of emergency room visits and known mpox contacts. Although not statistically significant, gastrointestinal, musculoskeletal, psychological, respiratory, and STI symptoms, including syphilis and urethritis, were more common in the virologically non-suppressed HIV group. At the same time, proctitis was more prevalent in the suppressed group. No significant differences were found based on CD4 count, using 200 cells/mm3 in PWH.
Conclusion
Over half of the participants were people living with HIV (PWH), with a significant presence of STIs like syphilis. While skin lesions and complications varied, no significant differences were linked to CD4 count or viral load suppression. Mpox symptomatology was not significantly associated with unsuppressed viral loads or low CD4 levels, highlighting the need for further research.
{"title":"Mpox: Characterization and clinical outcomes of patients in Colombian healthcare institutions","authors":"Carlos Arturo Álvarez-Moreno , Ludovic Reveiz , Claudia Aristizabal , Jesús Quevedo , María Lucia Mesa Rubio , Leonardo Arévalo-Mora , Julián Felipe Porras Villamil , Monica Padilla , Juan Carlos Alzate-Angel , Jamie Rylance , Kurbonov Firdavs , Ilich de la Hoz , Sandra Liliana Valderrama-Beltran , Santiago Arboleda , Otto Sussmann , Javier Andrade , Carolina Murillo Velásquez , Estefania García , Ximena Galindo , Daniela Martínez , Antoine Chaillon","doi":"10.1016/j.gloepi.2025.100197","DOIUrl":"10.1016/j.gloepi.2025.100197","url":null,"abstract":"<div><h3>Introduction</h3><div>In 2022, the world experienced a monkeypox outbreak caused by the Clade IIb strain of the virus. While this outbreak had widespread effects, more information is needed on mpox's specific impact in Colombia, particularly regarding how it is managed, its burden, and its epidemiology. This research seeks to examine the medical context, clinical presentation, and health outcomes of individuals diagnosed with mpox infection, with a particular focus on those with HIV in Colombia.</div></div><div><h3>Methods</h3><div>This retrospective study was conducted in fourteen Health institutions in Colombia based on computerized clinical records from Jan 2022 to Dec 2023. Clinical and epidemiological characteristics were collected from diagnosis until discharge (or death). Participants in the study were diagnosed through molecular methods (PCR) and their clinical evolution was tracked through hospital and/or outpatient medical records. Registered variables were based on the mpox 2023 Case Report Form (2023 - CRF) proposed by the World Health Organization.</div></div><div><h3>Results</h3><div>One thousand four hundred thirteen (1413, 97.2 % male) individuals, including 2.6 % identified as healthcare workers, were included in this study. The majority (54 %, 764/1413 individuals) were persons living with HIV (PWH) and almost one-third of them (30.1 %, <em>n</em> = 284) of participants had concomitant sexually transmitted diseases and HIV, with syphilis being the most prevalent (20.4 %), followed by <em>Neisseria gonorrhoeae</em> (16.4 %). Complications were infrequent, with cellulitis being the most common, and no individuals received mpox-specific treatment or vaccination. Although all individuals had skin lesions distributed across various body regions, differences were noted in lesion distribution among women. Those living with HIV showed higher emergency department attendance and reported having known mpox contacts. While complications were rare, with cellulitis being the most common, women living with HIV showed a higher rate of emergency room visits and known mpox contacts. Although not statistically significant, gastrointestinal, musculoskeletal, psychological, respiratory, and STI symptoms, including syphilis and urethritis, were more common in the virologically non-suppressed HIV group. At the same time, proctitis was more prevalent in the suppressed group. No significant differences were found based on CD4 count, using 200 cells/mm<sup>3</sup> in PWH.</div></div><div><h3>Conclusion</h3><div>Over half of the participants were people living with HIV (PWH), with a significant presence of STIs like syphilis. While skin lesions and complications varied, no significant differences were linked to CD4 count or viral load suppression. Mpox symptomatology was not significantly associated with unsuppressed viral loads or low CD4 levels, highlighting the need for further research.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100197"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2024-12-30DOI: 10.1016/j.gloepi.2024.100182
Rahim Akrami , Maryam Hadji , Hamideh Rashidian , Maryam Nazemipour , Ahmad Naghibzadeh-Tahami , Alireza Ansari-Moghaddam , Kazem Zendehdel , Mohammad Ali Mansournia
Introduction
Opium and cigarette smoking have been identified as significant cancer risk factors. Recently, the International Agency for Research on Cancer (IARC) classified opium as a Group 1 carcinogen in 2020.
Method
Using data from a multicenter case-control study in Iran called IROPICAN, involving 717 cases of bladder cancer and 3477 controls, we assessed the interactions on the causal additive scale between opium use and cigarette smoking and their attributing effects to evaluate public health relevance and test for different mechanistic interaction forms to provide new insights for developing of bladder cancer. A minimally sufficient set of confounders was identified using a causal directed acyclic graph, and the data were analysed employing multiple logistic regression and the inverse probability-of-treatment weighting estimator of the marginal structural linear odds model.
Results
Our findings indicated a significant increase in the risk of bladder cancer associated with concurrent opium use and cigarette smoking (adjusted OR = 6.34, 95 % CI 5.02–7.99; p < 0.001), demonstrating a super-additive interaction between these exposures (Weighted RERIOR = 2.02, 95 % CI 0.47–3.58; p = 0.005). The presence of a super-additive interaction suggests that interventions targeting opium users who smoke cigarettes would yield greater benefits compared to non-opium users. Furthermore, there was a mechanistic interaction between two exposures (P-value = 0.005) if we assumed two of the exposures have positive monotonic effects, i.e., there must be a sufficient-component cause for developing bladder cancer, which has both opium use and cigarette smoking as components.
Conclusion
There is a causal additive interaction between opium use and cigarette smoking. We observed a super-additive interaction, suggesting the need to focus interventions on specific subgroups. Furthermore, the presence of mechanistic interactions offers profound insights into the mechanisms of cancer induction.
鸦片和吸烟已被确定为重要的癌症危险因素。近日，国际癌症研究机构（IARC）在2020年将鸦片列为1类致癌物。方法：利用伊朗一项名为IROPICAN的多中心病例对照研究的数据，包括717例膀胱癌和3477例对照，我们评估了鸦片使用和吸烟之间的因果加性相互作用及其归因效应，以评估公共卫生相关性，并测试了不同的机制相互作用形式，为膀胱癌的发展提供新的见解。使用因果有向无环图确定了一组最小充分的混杂因素，并使用多元逻辑回归和边际结构线性几率模型的逆处理概率加权估计器对数据进行了分析。结果：我们的研究结果表明，同时使用鸦片和吸烟与膀胱癌的风险显著增加(调整后OR = 6.34, 95% CI 5.02-7.99；p OR = 2.02, 95% CI 0.47-3.58；p = 0.005)。超加性相互作用的存在表明，与非鸦片使用者相比，针对吸烟的鸦片使用者的干预措施将产生更大的益处。此外，如果我们假设两种暴露具有正单调效应，则两种暴露之间存在机制相互作用（p值= 0.005），即必须存在发生膀胱癌的充分成分原因，其中鸦片使用和吸烟都是成分。结论：吸食鸦片与吸烟之间存在因果加性相互作用。我们观察到一种超加性相互作用，表明需要将干预重点放在特定的亚群上。此外，机制相互作用的存在为癌症诱导机制提供了深刻的见解。
{"title":"Interaction between opium use and cigarette smoking on bladder cancer: An inverse probability weighting approach based on a multicenter case-control study in Iran","authors":"Rahim Akrami , Maryam Hadji , Hamideh Rashidian , Maryam Nazemipour , Ahmad Naghibzadeh-Tahami , Alireza Ansari-Moghaddam , Kazem Zendehdel , Mohammad Ali Mansournia","doi":"10.1016/j.gloepi.2024.100182","DOIUrl":"10.1016/j.gloepi.2024.100182","url":null,"abstract":"<div><h3>Introduction</h3><div>Opium and cigarette smoking have been identified as significant cancer risk factors. Recently, the International Agency for Research on Cancer (IARC) classified opium as a Group 1 carcinogen in 2020.</div></div><div><h3>Method</h3><div>Using data from a multicenter case-control study in Iran called IROPICAN, involving 717 cases of bladder cancer and 3477 controls, we assessed the interactions on the causal additive scale between opium use and cigarette smoking and their attributing effects to evaluate public health relevance and test for different mechanistic interaction forms to provide new insights for developing of bladder cancer. A minimally sufficient set of confounders was identified using a causal directed acyclic graph, and the data were analysed employing multiple logistic regression and the inverse probability-of-treatment weighting estimator of the marginal structural linear odds model.</div></div><div><h3>Results</h3><div>Our findings indicated a significant increase in the risk of bladder cancer associated with concurrent opium use and cigarette smoking (adjusted OR = 6.34, 95 % CI 5.02–7.99; <em>p</em> < 0.001), demonstrating a super-additive interaction between these exposures (Weighted RERI<sub>OR</sub> = 2.02, 95 % CI 0.47–3.58; <em>p</em> = 0.005). The presence of a super-additive interaction suggests that interventions targeting opium users who smoke cigarettes would yield greater benefits compared to non-opium users. Furthermore, there was a mechanistic interaction between two exposures (<em>P</em>-value = 0.005) if we assumed two of the exposures have positive monotonic effects, i.e., there must be a sufficient-component cause for developing bladder cancer, which has both opium use and cigarette smoking as components.</div></div><div><h3>Conclusion</h3><div>There is a causal additive interaction between opium use and cigarette smoking. We observed a super-additive interaction, suggesting the need to focus interventions on specific subgroups. Furthermore, the presence of mechanistic interactions offers profound insights into the mechanisms of cancer induction.</div></div>","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100182"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11751544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143025082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-02-11DOI: 10.1016/j.gloepi.2025.100187
Lawrence L. Kupper , Sandra L. Martin
{"title":"Commentary on the commentary “On measurement error, PSA doubling time, and prostate cancer”","authors":"Lawrence L. Kupper , Sandra L. Martin","doi":"10.1016/j.gloepi.2025.100187","DOIUrl":"10.1016/j.gloepi.2025.100187","url":null,"abstract":"","PeriodicalId":36311,"journal":{"name":"Global Epidemiology","volume":"9 ","pages":"Article 100187"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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