Clinical Epidemiology最新文献

{"title":"Modelling Asthma Treatment Dynamics: Insights from the g-Formula.","authors":"Irene Mommers, Job F M van Boven, Jens H J Bos, Sumaira Mubarik, Eelko Hak, Maarten J Bijlsma","doi":"10.2147/CLEP.S486869","DOIUrl":"10.2147/CLEP.S486869","url":null,"abstract":"<p><strong>Purpose: </strong>The g-formula offers a promising approach to analyze long-term dynamic asthma treatment trajectories. This study investigates whether the g-formula can simulate real-world asthma treatment trajectories and predicts subgroup differences in switching behavior.</p><p><strong>Patients and methods: </strong>This retrospective cohort study identified individuals aged 16- to 45 years who initiated inhaled asthma medication in the Netherlands between 1994 and 2021, from the IADB.nl pharmacy dispensing database. We used the g-formula combined with logistic regression to predict treatment trajectories and their associations with various patient characteristics, such as age, sex, chronic drug treatment for atopic diseases (ATD), cardiovascular diseases (CVD), thyroid diseases, arthritis, diabetes, gastroesophageal reflux disease (GERD), mental health problems (MHP), and immunosuppressants.</p><p><strong>Results: </strong>The simulations predicted 76% of individuals to switch treatment, on average 2.3 times, with the first switch occurring on average after 8.3 months, which agrees with the real-world observations (77%, 2.3 times and 7.9 months, respectively). Fewer 45-year-olds switched treatment compared to 16-year-olds (74% vs 78%, p < 0.001), but they switched earlier (8.1 vs 8.6 months, p < 0.001) and more frequently (2.4 vs 2.3 times, p < 0.001). Women were more likely to switch compared to men. Patients with ATD, CVD, MHP, or GERD switched significantly less often (p < 0.05).</p><p><strong>Conclusion: </strong>The g-formula effectively simulates asthma treatment trajectories and found higher age, male sex, ATD, CVD, MHP, and GERD to decrease overall switching behavior. These patients might benefit from earlier intervention or closer monitoring to reduce delays in treatment progression.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"265-276"},"PeriodicalIF":3.4,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11913031/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Postoperative Adverse Outcomes in Patients With Frailty Undergoing Urologic Surgery Among American Patients: A Propensity-Score Matched Retrospective Cohort Study.","authors":"Cheng-Wei Hsu, Chuen-Chau Chang, Fai Lam, Ming-Che Liu, Chun-Chieh Yeh, Ta-Liang Chen, Chao-Shun Lin, Chien-Chang Liao","doi":"10.2147/CLEP.S493366","DOIUrl":"https://doi.org/10.2147/CLEP.S493366","url":null,"abstract":"<p><strong>Objective: </strong>Although the 5-item modified frailty index (mFI-5) has been found to be associated postoperative outcomes, there are limited studies examining its utility in urologic surgery. Our purpose is to evaluate the association between the mFI-5 and postoperative mortality and complications among patients undergoing urologic surgery.</p><p><strong>Methods: </strong>This retrospective cohort study used the American College of Surgeons National Surgical Quality Improvement Program database from 2015 to 2020. All adult patients who underwent urologic procedures were included. The mFI-5 includes five items: hypertension, diabetes, congestive heart failure, chronic obstructive pulmonary disease, and physical function status. Each item is assigned one point, and an mFI-5 score of 2 or greater indicates frailty. The primary outcome was postoperative mortality, while secondary outcomes were postoperative complications. Propensity score analysis was employed to control for confounders.</p><p><strong>Results: </strong>After propensity score matching, each group contained 55,322 surgical patients. The patients in the frailty group were at risks of in-hospital mortality (absolute risk increase [ARI] 0.29%) and higher postoperative complications, including acute myocardial infarction (ARI 0.25%), pneumonia (ARI 0.42%), sepsis (ARI 0.41%), and septic shock (0.2%). Compared to the non-frailty group, the length of hospital stay was higher in the frailty group.</p><p><strong>Conclusion: </strong>Patients with an mFI-5 score of 2 or greater were associated with an increased risk of postoperative mortality and complications, including myocardial infarction, pneumonia, sepsis, and septic shock. The mFI-5 is a simple index that quickly identifies frail patients. This allows for the implementation of prehabilitation and nutritional strategies targeted at enhancing their physiological reserve and optimizing their surgical outcomes.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"241-250"},"PeriodicalIF":3.4,"publicationDate":"2025-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital-Treated Infections and 15-year Incidence of Musculoskeletal Disorders: A Large Population-Based Cohort Study.","authors":"Yaqing Gao, Dylan McGagh, Lei Ding, Shenda Hong, Zhengxiao Ouyang, Jie Wei, Chao Zeng, Guanghua Lei, Junqing Xie","doi":"10.2147/CLEP.S494047","DOIUrl":"https://doi.org/10.2147/CLEP.S494047","url":null,"abstract":"<p><strong>Background: </strong>Basic science evidence reveals interactions between the immune and bone systems. However, population studies linking infectious diseases and musculoskeletal (MSK) disorders are limited and inconsistent. We aimed to examine the risk of six main MSK disorders (osteoarthritis, rheumatoid arthritis, osteoporosis, gout, low back pain, and neck pain) following hospital-treated infections in a large cohort with long follow-up periods.</p><p><strong>Methods: </strong>We analysed data from 502,409 UK Biobank participants. Participants free of specific MSK disorders at baseline were included in each analysis. Hospital-treated infections before baseline were identified using national inpatient data, while incident MSK outcomes were ascertained from inpatient records, primary care, and death registers. Participants with prior infections were propensity score matched (1:5) with those without. Hazard ratios (HRs) and absolute rate differences (ARDs) with 95% confidence intervals (CIs) were calculated using Cox proportional hazards models. To assess potential reverse causality due to delayed diagnosis of preexisting illness, analyses were repeated excluding MSK disorder cases that occurred within the first 5 and 10 years post-baseline.</p><p><strong>Results: </strong>A hospital-treated infection was associated with increased risks of all six MSK disorders, with particularly strong associations for osteoporosis (HR, 1.55 [1.48-1.63]; ARD, 1.48 [95% CI 1.29-1.68] per 1000 person-years) and rheumatoid arthritis (HR, 1.53 [1.41-1.65]; ARD, 0.58 [0.46-0.71] per 1000 person-years), while other disorders showed HRs of 1.28-1.32. Bacterial and viral infections showed similar associations, with MSK infections (generally stronger risk) and other locations both linked to increased risks. Associations remained significant even for incident cases that occurred more than 10 years post-baseline.</p><p><strong>Conclusion: </strong>Hospital-treated infections are associated with long-term MSK disorder risks, regardless of pathogen type or disorder nature (inflammatory or degenerative). Long-term monitoring and care for MSK health in patients with prior hospital-treated infections are recommended.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"251-264"},"PeriodicalIF":3.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910040/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable Prediction of Long-Term Glycated Hemoglobin Response Change in Finnish Patients with Type 2 Diabetes Following Drug Initiation Using Evidence-Based Machine Learning Approaches.","authors":"Gunjan Chandra, Piia Lavikainen, Pekka Siirtola, Satu Tamminen, Anusha Ihalapathirana, Tiina Laatikainen, Janne Martikainen, Juha Röning","doi":"10.2147/CLEP.S505966","DOIUrl":"10.2147/CLEP.S505966","url":null,"abstract":"<p><strong>Purpose: </strong>This study applied machine learning (ML) and explainable artificial intelligence (XAI) to predict changes in HbA1c levels, a critical biomarker for monitoring glycemic control, within 12 months of initiating a new antidiabetic drug in patients diagnosed with type 2 diabetes. It also aimed to identify the predictors associated with these changes.</p><p><strong>Patients and methods: </strong>Electronic health records (EHR) from 10,139 type 2 diabetes patients in North Karelia, Finland, were used to train models integrating randomized controlled trial (RCT)-derived HbA1c change values as predictors, creating offset models that integrate RCT insights with real-world data. Various ML models-including linear regression (LR), multi-layer perceptron (MLP), ridge regression (RR), random forest (RF), and XGBoost (XGB)-were evaluated using <i>R²</i> and RMSE metrics. Baseline models used data at or before drug initiation, while follow-up models included the first post-drug HbA1c measurement, improving performance by incorporating dynamic patient data. Model performance was also compared to expected HbA1c changes from clinical trials.</p><p><strong>Results: </strong>Results showed that ML models outperform RCT model, while LR, MLP, and RR models had comparable performance, RF and XGB models exhibited overfitting. The follow-up MLP model outperformed the baseline MLP model, with higher <i>R²</i> scores (0.74, 0.65) and lower RMSE values (6.94, 7.62), compared to the baseline model (R²: 0.52, 0.54; RMSE: 9.27, 9.50). Key predictors of HbA1c change included baseline and post-drug initiation HbA1c values, fasting plasma glucose, and HDL cholesterol.</p><p><strong>Conclusion: </strong>Using EHR and ML models allows for the development of more realistic and individualized predictions of HbA1c changes, accounting for more diverse patient populations and their heterogeneous nature, offering more tailored and effective treatment strategies for managing T2D. The use of XAI provided insights into the influence of specific predictors, enhancing model interpretability and clinical relevance. Future research will explore treatment selection models.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"225-240"},"PeriodicalIF":3.4,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11899941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143613766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Occupational Physical Activity Among Pregnant Employees in the Danish Workforce: The PRECISE Occupational Cohort Profile.","authors":"Hannah Nørtoft Frankel, Katia Keglberg Hærvig, Esben Meulengracht Flachs, Mette Korshøj, Charlotte Bertelsen, Mette Backhausen, Camilla Sandal Sejbaek, Luise Mølenberg Begtrup","doi":"10.2147/CLEP.S496585","DOIUrl":"10.2147/CLEP.S496585","url":null,"abstract":"<p><strong>Purpose: </strong>Occupational physical activity (OPA) has been linked to adverse pregnancy outcomes, although findings are not consistent. This paper describes the PRECISE Occupational Cohort, designed with the purpose to obtain comprehensive information on OPA with objective measurements and prospective information on pregnancy-related discomforts and sick leave among pregnant employees in Denmark.</p><p><strong>Methods: </strong>A total of 1556 pregnant participants were included between January 2023 and June 2024 from six obstetric departments in relation to the first trimester ultrasound scan. Information on OPA, pregnancy-related discomforts and sick leave was collected by repeated weekly questionnaires. Additionally, a subgroup of 327 pregnant participants and 90 non-pregnant co-workers were invited for repeated objective measurements, and/or workplace observations. A total of 603 accelerometer measurements from 412 unique participants, and 138 workplace observations were obtained from 102 unique participants. Time spent standing, walking and forward bending was acquired by accelerometers, and information on lifting and person-handlings was quantified by observations. All participants covered 197 occupational codes.</p><p><strong>Results: </strong>A total of 1008 pregnant participants on average responded to the weekly questionnaires from pregnancy weeks 12-40. High frequencies of pregnancy discomforts were reported throughout pregnancy, and on average only 11% reported no discomforts. Pregnancy-related sick leave increased throughout pregnancy, peaking in pregnancy week 29, where 26% reported at least one day of pregnancy-related sick leave in the past week.</p><p><strong>Conclusion: </strong>This cohort provides unique repeated measurements with comprehensive information about pregnant employees across many jobs, disclosing high levels of pregnancy discomforts and sick leave throughout pregnancy. The information will enable investigation of the associations of OPA, pregnancy-related discomforts and sick leave on a more detailed level than now. The objective measurements with novel information on OPA will contribute to the development of quantitative Job Exposure Matrices enabling investigation of the association between OPA and adverse pregnancy outcomes in larger populations, with the potential to strengthen preventive guidelines.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"211-224"},"PeriodicalIF":3.4,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11883179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143571706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cohort Update: ESPRESSO (Epidemiology Strengthened by Histopathology Reports in Sweden).","authors":"Jonas F Ludvigsson, Mariam Lashkariani","doi":"10.2147/CLEP.S499859","DOIUrl":"https://doi.org/10.2147/CLEP.S499859","url":null,"abstract":"","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"193-196"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mental Health Disorders in Patients with Inflammatory Bowel Disease Onset in Childhood or Youth - A Nationwide Cohort Study from Denmark.","authors":"Julie Rasmussen, Anna Sofie Kjærgaard Hansen, Bente Mertz Nørgård, Rasmus Gaardskær Nielsen, Niels Qvist, Henrik Bøggild, Kirsten Fonager","doi":"10.2147/CLEP.S491881","DOIUrl":"https://doi.org/10.2147/CLEP.S491881","url":null,"abstract":"<p><strong>Purpose: </strong>The study aims to explore the association between patients diagnosed with inflammatory bowel disease (IBD) in childhood or youth and mental health disorders.</p><p><strong>Methods: </strong>The study is a register-based cohort study of patients with IBD-onset before 25 years of age and matched references. They were followed until 30 years of age. The incidence rate and incidence rate ratio (IRR) for a wide spectrum of mental health disorders were assessed based on diagnostic codes from the Danish National Patient Registry, reimbursed prescriptions for psychotropic medications, and composite measures combining diagnosis and medication. Furthermore, the relative excess risk due to interaction (RERI) for parental educational level and parental mental health disorders were estimated.</p><p><strong>Results: </strong>A total of 4904 patients with Crohn's disease (CD), 5794 with ulcerative colitis (UC), and 94,802 matched references were identified. Patients with CD-onset before age 18 had a higher risk of anxiety disorders (IRR 1.58 (CI95%: 1.33-1.86)), while patients with CD-onset between age 18 to 24 had a higher risk of both anxiety and mood disorders. Patients with UC-onset before age 18 had a higher risk of anxiety disorders (IRR: 1.39 (CI95%: 1.19-1.64)). In general, patients with IBD had a higher risk of receiving psychotropic medication. Parental education had a subadditive interaction with the risk of emotional disorders for both patients with CD and UC, while maternal mental health disorders had a subadditive interaction for patients with UC.</p><p><strong>Conclusion: </strong>Patients with CD and UC have a higher risk of mental health disorders, primarily due to an elevated risk of emotional disorders and a higher use of psychotropic medication. Surprisingly, the study demonstrated subadditive effect of parental education and for patients with UC maternal mental health disorders on the risk of emotional disorders.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"177-192"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871872/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidence and Risk Factors of Lower Limb Deep Vein Thrombosis in Psychiatric Inpatients by Applying Machine Learning to Electronic Health Records: A Retrospective Cohort Study.","authors":"Liang Xu, Miao Da","doi":"10.2147/CLEP.S501062","DOIUrl":"https://doi.org/10.2147/CLEP.S501062","url":null,"abstract":"<p><strong>Background: </strong>Psychiatric inpatients face an increased risk of deep vein thrombosis (DVT) due to their psychiatric conditions and pharmacological treatments. However, research focusing on this population remains limited.</p><p><strong>Methods: </strong>This study analyzed 17,434 psychiatric inpatients at Huzhou Third Municipal Hospital, incorporating data on demographics, psychiatric diagnoses, physical illnesses, laboratory results, and medication use. Predictive models for DVT were developed using logistic regression, random forest, support vector machine (SVM), and XGBoost (Extreme Gradient Boosting). Feature importance was assessed using the random forest model.</p><p><strong>Results: </strong>The DVT incidence among psychiatric inpatients was 1.6%. Predictive model performance, measured by the area under the curve (AUC), showed logistic regression (0.900), random forest (0.885), SVM (0.890), and XGBoost (0.889) performed well. Logistic regression and random forest models exhibited optimal overall performance, while XGBoost excelled in recall. Significant predictors of DVT included elevated D-dimer levels, age, Alzheimer's disease, and Madopar use.</p><p><strong>Conclusion: </strong>Psychiatric inpatients require vigilance for DVT risk, with factors like D-dimer levels and age serving as critical indicators. Machine learning models effectively predict DVT risk, enabling early detection and personalized prevention strategies in clinical practice.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"197-209"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871911/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response to \"A Validation Study of the Danish ICD-10 Diagnosis Code K75.0 for Pyogenic Liver Abscess\" [Response to Letter].","authors":"Margarita Dudina, Hans Linde Nielsen","doi":"10.2147/CLEP.S522981","DOIUrl":"https://doi.org/10.2147/CLEP.S522981","url":null,"abstract":"","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"165-166"},"PeriodicalIF":3.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11871921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interaction Between Multimorbidity and Hip Fracture Surgery Leads to Excess Risk of Infection: A Danish Registry-Based Cohort Study of 92,599 Patients With Hip Fracture.","authors":"Cecilia Majlund Hansen, Nadia R Gadgaard, Christina Vandenbroucke-Grauls, Nils P Hailer, Alma Becic Pedersen","doi":"10.2147/CLEP.S507252","DOIUrl":"https://doi.org/10.2147/CLEP.S507252","url":null,"abstract":"<p><strong>Purpose: </strong>Infection in general is a frequent and serious complication after hip fracture (HF) surgery. Multimorbidity in HF patients is associated with elevated infection risk. It remains unclear whether multimorbidity interacts with HF surgery to increase infection risk beyond their individual effects.</p><p><strong>Methods: </strong>Using Danish registries, we identified 92,599 patients ≥65 years surgically treated for HF 2004 to 2018 and an age- and sex-matched comparison cohort from the background population without HF (n=462,993). Multimorbidity was defined using the Charlson Comorbidity Index in categories no, moderate, or severe. We computed incidence rates (IR) of any kind of hospital-treated infection within 1 month and 1 year with 95% confidence intervals and estimated the attributable proportion (in %) based on differences in IRs.</p><p><strong>Results: </strong>The IR of infection within 1 month was 181 (176-186) per 100 person years in HF patients with no multimorbidity and 9 (95% CI 8-9) in the comparison cohort with no multimorbidity. The IRs were 240 (234-246) and 302 (291-313) in HF patients with moderate and severe multimorbidity compared with 17 (16-18) and 31 (30-33) in the comparison cohort with same multimorbidity level. The attributable proportion indicates that 21% and 33% of the IR among HF patients with moderate and severe multimorbidity, respectively, was explained by interaction. Similar interactions were observed within 1 year.</p><p><strong>Conclusion: </strong>Multimorbidity and HF surgery interact synergistically, which substantially increases the infection risk. The interaction effect increased with multimorbidity level. Our findings highlight the potential benefits of implementing more targeted and personalized preventive initiatives for multimorbid patients.</p>","PeriodicalId":10362,"journal":{"name":"Clinical Epidemiology","volume":"17 ","pages":"167-176"},"PeriodicalIF":3.4,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11869750/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}