Epidemiology最新文献

{"title":"Illustrating an Adaptive Prespecification Framework for Observational Research: Target Trial Emulations Comparing Immunomodulator Treatments for COVID-19.","authors":"Andrew R Weckstein, Vera Frajzyngier, Sarah E Vititoe, Aidan Baglivo, Elisha Beebe, Priya Govil, Marie C Bradley, Silvia Perez-Vilar, Wei Liu, Donna R Rivera, Tamar Lasky, Aloka Chakravarty, Elizabeth M Garry, Nicolle M Gatto","doi":"10.1097/EDE.0000000000001901","DOIUrl":"10.1097/EDE.0000000000001901","url":null,"abstract":"<p><p>Rigid prespecification can be impractical for noninterventional studies using secondary datasets, where data-driven flexibility is often required. Using target trial emulations comparing immunomodulator treatments for COVID-19, we piloted an adaptive strategy that accommodates warranted mid-course refinements within a prespecified framework. Our preregistered protocol outlined an initial study plan along with predetermined diagnostic thresholds and contingencies. Implementation proceeded through sequential phases, allowing researcher decisions to be guided by prespecified criteria under varying degrees of blinding to results. The adaptive approach led to alterations in the underlying target trial and to the analysis plan used for emulation, strengthening the plausibility of causal assumptions and improving the relevance of findings. During the initial baseline phase, indicated contingencies included sample restrictions, redefining treatments from class-level to product-specific comparisons, a revised propensity score model, and weight truncation. In the subsequent postbaseline phase, diagnostic checks triggered a modified causal contrast, inverse probability of censor weighting to address noncompliance, cause-specific hazard estimation to contextualize competing events, and additional reporting of hazard ratios for progressively truncated follow-up periods. For a secondary study objective, the adaptive framework allowed for some iterative attempts to improve validity while providing a clear stopping point. Similar approaches could lend transparent structure to the process of learning what causal questions the data are equipped to support. Beyond guarding against researcher bias, prespecification of adaptive protocols may promote more robust designs by encouraging investigators to be explicit about their assumptions, strategies for interrogating those assumptions, and specific criteria for determining when and how deviations may be required.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 6","pages":"791-801"},"PeriodicalIF":4.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12459141/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136830","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":"Does Delayed Response Due to Busy Ambulances Impact Risk of Death and Hospital Service Use?: A Cohort Study of 240,000 Medical Emergencies.","authors":"Andreas Asheim, Lars Eide Næss, Andreas Krüger, Oddvar Uleberg, Jostein Dale, Helge Haugland, Ole Erik Ulvin, Sara Marie Nilsen, Gudrun Maria Waaler Bjørnelv, Jon-Ola Wattø, Johan Håkon Bjørngaard","doi":"10.1097/EDE.0000000000001894","DOIUrl":"10.1097/EDE.0000000000001894","url":null,"abstract":"<p><strong>Objectives: </strong>When ground ambulances are busy with any task, delays are likely for concurrent emergencies. Whereas time-critical conditions are affected by delays, general impacts remain unclear. We aimed to assess how delayed ambulance response due to busy ambulances affects risk of death and use of hospital services.</p><p><strong>Methods: </strong>We studied individuals with out-of-hospital emergencies that precipitated a call to the medical emergency number in Central Norway from 2013 to 2022. Emergency service and hospital data were linked to assess subsequent death and hospitalizations. We addressed potential bias by multivariable adjustment and a natural experiment: For emergencies that occurred in the same area at similar times, we compared outcomes for patients with differences in busy ambulances to analyze delays in response that were arguably unrelated to prioritization due to the patient severity.</p><p><strong>Results: </strong>Among 239,320 acute emergencies, 4.1% of patients died within 7 days. An interquartile range of variation in the probability a busy ambulance was associated with a 2.9-minute delay (95% confidence interval [CI] = 2.8, 3.0). Overall, a 5-minute delay was associated with a risk difference of 0.10 percentage points in the risk of death (95% CI = -0.17, 0.36) and 1.24 for hospitalization (95% CI = 0.59, 1.94). The cost of hospital treatment within 1 year increased by 616 euros (95% CI = 183, 1069).</p><p><strong>Conclusion: </strong>While we found no substantial increase in the overall risk of death associated with delayed ambulance response, the observed rise in hospital costs suggests a potential increase in morbidity.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":"36 6","pages":"830-840"},"PeriodicalIF":4.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12459146/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145136812","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":"Opioid Agonist Therapy Adherence Trajectories Among Commercially and Publicly Insured People Living With Hepatitis C in the United States.","authors":"Catherine Psaras, Onyebuchi A Arah, Kara W Chew, Sung-Jae Lee, Marjan Javanbakht, Roch A Nianogo, Marissa J Seamans","doi":"10.1097/EDE.0000000000001895","DOIUrl":"10.1097/EDE.0000000000001895","url":null,"abstract":"<p><strong>Background: </strong>Hepatitis C virus (HCV) infection is a public health concern, with people living with opioid use disorder having a higher risk of infection. Despite the cooccurrence of HCV and opioid use disorder, little is known about the treatment patterns for the disorder in this population. This study characterized opioid agonist therapy adherence trajectories over 15 months following opioid agonist therapy initiation among people living with HCV and opioid use disorder and described the baseline characteristics of the patients within distinct opioid agonist therapy adherence trajectories.</p><p><strong>Methods: </strong>We used Merative MarketScan healthcare claims data from 2015 to 2019 to identify distinct medication treatment adherence trajectories via growth mixture modeling among 5,495 people who initiated opioid agonist therapy for opioid use disorder and were living with HCV.</p><p><strong>Results: </strong>Our models identified three distinct opioid agonist therapy adherence trajectories over the 15 months of follow-up. We named these trajectories rapidly declining opioid agonist therapy adherence (class 1; N = 1,904; 35%), steadily declining opioid agonist therapy adherence (class 2; N = 2,150; 39%), and consistently high opioid agonist therapy adherence (N = 1,441; 26%). People in the consistently high adherence group were older, more likely to be women (vs. men), White (vs. Black), had HCV direct-acting antiviral treatment during the baseline period, and had the lowest prevalence of nonopioid substance use diagnoses.</p><p><strong>Conclusions: </strong>These results may inform support for populations with elevated baseline risk of low opioid agonist therapy adherence during follow-up.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"820-829"},"PeriodicalIF":4.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disaggregating Health Differences and Disparities With Machine Learning and Observed-to-expected Ratios: Application to Major Lower Limb Amputation.","authors":"Paula D Strassle, Samantha D Minc, Corey A Kalbaugh, Macarius M Donneyong, Jamie S Ko, Katharine L McGinigle","doi":"10.1097/EDE.0000000000001892","DOIUrl":"10.1097/EDE.0000000000001892","url":null,"abstract":"<p><strong>Background: </strong>Major lower limb amputation is a devastating but preventable complication of peripheral artery disease. It is unclear whether racial and ethnic and rural differences in amputation rates are due to clinical, hospital, or structural factors.</p><p><strong>Methods: </strong>We included all peripheral artery disease hospitalizations of patients ≥40 years old between 2017 and 2019 in Florida, Georgia, Maryland, Mississippi, or New York (HCUP State Inpatient Databases). We estimated the expected number of amputations using three models: (1) unadjusted, (2) adjusted for clinical factors, and (3) adjusted for clinical factors, hospital factors, and social determinants of health using least absolute shrinkage and selection operator (LASSO). We calculated and compared observed-to-expected ratios and quantified the role of these factors in amputation rates.</p><p><strong>Results: </strong>Overall, 1,577,061 hospitalizations (990,152 unique patients) and 21,233 major lower limb amputations (1.4%) were included. After accounting for clinical differences, we observed amputation disparities among rural Black, Hispanic, Native American, and White patients and nonrural Black and Native American patients. After accounting for hospital factors and social determinants of health, disparities were no longer present among rural White adults (0.93, 95% confidence interval [CI]: 0.77, 1.09); however, disparities persisted among rural Black (1.26, 95% CI: 1.01, 1.51), Hispanic (1.50, 95% CI: 0.89, 2.12), and Native American patients (1.13, 95% CI: 0.68, 1.58) and nonrural Black (1.12, 95% CI: 1.09, 1.15) and Native American (1.15, 95% CI: 0.86, 1.44) patients.</p><p><strong>Conclusion: </strong>Clinical factors did not fully explain differences in amputation rates, and hospital factors and social determinants of health did not fully explain disparities. These findings provide additional evidence that implicit bias is associated with amputation disparities.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":"841-848"},"PeriodicalIF":4.4,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12400468/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144590757","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":"Unbiased estimates using temporally aggregated outcome data in time series analysis: generalization to different outcomes, exposures and types of aggregation.","authors":"Xavier Basagaña, Joan Ballester","doi":"10.1097/EDE.0000000000001923","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001923","url":null,"abstract":"<p><strong>Background: </strong>A new method for time series analysis was recently formulated and implemented that uses temporally aggregated outcome data to generate unbiased estimates of the underlying association between temporally disaggregated outcome and covariate data. However, the performance of the method was only tested in the context of the delayed nonlinear relation between temperature and mortality, and only in the case of the aggregation of sets of consecutive days.</p><p><strong>Methods: </strong>We conduct a simulation analysis to test the performance of the method using (i) mortality and hospital admissions as health outcomes, (ii) temperature and nitrogen dioxide as exposures, and (iii) the three aggregation schemes most widely used in open access health data, including aggregations of sets of non-consecutive days.</p><p><strong>Results: </strong>With sufficient data for analysis, the method can recover the underlying association for all combinations of outcomes, exposures, and aggregation schemes. The bias and variability of the estimates increase with the degree of aggregation of the outcome data, and they decrease with increasing sample size (length of dataset, number of cases). Remarkably, estimates are also unbiased even in extreme cases with weekly outcome data in an association confounded by the day of the week, such as those of air pollution models.</p><p><strong>Conclusions: </strong>With sufficient data, the method is able to flexibly generate unbiased estimates, generalizing previous results to other outcomes, exposures and types and degrees of aggregation. Such results can boost the use of available temporally aggregated health data for research, translation, and policymaking, especially in low-resource and rural areas.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145205930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Causal mediation analysis with mediator-outcome confounders affected by exposure - on definition and identification of generalized natural indirect effect.","authors":"Yan-Lin Chen, Tsung Yu, Sheng-Hsuan Lin","doi":"10.1097/EDE.0000000000001922","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001922","url":null,"abstract":"<p><p>Causal mediation analysis aims to disentangle the pathways through which an exposure influences an outcome. In the presence of mediator-outcome confounders affected by exposure (intermediate confounders), the natural indirect effect (NIE) is not identifiable under nonparametric structural equation models (SEM) with independent errors. To address this challenge, we focus on the indirect pathway and introduce a novel class of indirect effect measures, referred to as generalized natural indirect effects, of which the NIE is a special case. In particular, we introduce a case of generalized NIE defined through a randomized intervention, which, under the nonparametric SEM with independent errors, coincides with the interventional indirect effect (IIE)-even though identifying the IIE generally does not rely on the cross-world assumptions implied by nonparametric SEM with independent errors. Furthermore, when an additional no-heterogeneity assumption is imposed, the NIE becomes equal to this generalized NIE and hence identifiable. Unlike prior approaches, we propose new indirect effect measures criteria that ensure valid mediation interpretation even in the presence of intermediate confounders. Under traditional identification assumptions alone, the IIE fails to satisfy these criteria. In contrast, all proposed generalized NIEs meet them, providing a wide range of options beyond the existing measures. Our findings highlight the generalized NIEs as a more pragmatic and reasonable alternative in settings where intermediate confounders are inevitable.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145191331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OpenSAFELY: Effectiveness of COVID-19 vaccination in children and adolescents.","authors":"Colm D Andrews, Edward P K Parker, Elsie Horne, Venexia Walker, Tom Palmer, Andrea L Schaffer, Amelia Ca Green, Helen J Curtis, Alex J Walker, Lucy Bridges, Christopher Wood, Victoria Speed, Christopher Bates, Jonathan Cockburn, John Parry, Amir Mehrkar, Brian MacKenna, Sebastian Cj Bacon, Ben Goldacre, Miguel A Hernan, Jonathan Ac Sterne, William J Hulme","doi":"10.1097/EDE.0000000000001908","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001908","url":null,"abstract":"<p><strong>Background: </strong>We assessed the safety and effectiveness of first and second dose BNT162b2 COVID-19 vaccination, offered as part of the national COVID-19 vaccine roll-out from September 2021, in children and adolescents in England.</p><p><strong>Methods: </strong>Our observational study using OpenSAFELY-TPP, included adolescents aged 12-15 years, and children aged 5-11 years. It compared individuals receiving i) first vaccination to unvaccinated controls and ii) second vaccination to single-vaccinated controls. We matched vaccinated individuals with controls on age, sex, and other important characteristics. Outcomes were positive SARS-CoV-2 test (adolescents only); COVID-19 accident and emergency (A&E) attendance; COVID-19 hospitalization; COVID-19 critical care admission; COVID-19 death, with safety outcomes A&E attendance, unplanned hospitalization, pericarditis, and myocarditis.</p><p><strong>Results: </strong>Amongst 820,926 previously unvaccinated adolescents, 20-week incidence rate ratios (IRR) comparing vaccination with no vaccination were 0.74 for positive SARS-CoV-2 test, 0.60 for COVID-19 A&E attendance and 0.58 for COVID-19 hospitalization. Amongst 441,858 adolescents who had received first vaccination IRRs comparing second dose with single-vaccination were 0.67 for positive SARS-CoV-2 test, 1.00 for COVID-19 A&E attendance and 0.60 for COVID-19 hospitalisation. In both children groups COVID-19-related outcomes were too rare to allow IRRs to be estimated precisely. Across all analyses there were no COVID-19-related deaths, and fewer than seven COVID-19-related critical care admissions. Myocarditis and pericarditis were documented only in the vaccinated groups, with rates of 27 and 10 cases/million after first and second doses respectively.</p><p><strong>Conclusions: </strong>BNT162b2 vaccination in adolescents reduced COVID-19 A&E attendance and hospitalisation, although these outcomes were rare. Protection against positive SARS-CoV-2 tests was transient.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145124543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pregnancy Length Measurement Error: A comparison of Last Menstrual Period and Ultrasonography with Ovulation-Based Estimation.","authors":"Ginna L Doss, Julie L Daniels, Sunni L Mumford, Charles Poole, Anne Z Steiner, Enrique F Schisterman, Robert M Silver, Michelle R Klawans, Anne Marie Z Jukic","doi":"10.1097/EDE.0000000000001918","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001918","url":null,"abstract":"<p><strong>Background: </strong>Last menstrual period (LMP) and ultrasound are commonly used to estimate pregnancy length. Ovulation, which precedes fertilization by ≤24 hours, should give a more accurate estimate.</p><p><strong>Methods: </strong>The Effects of Aspirin in Gestation and Reproduction (EAGeR) trial preconceptionally enrolled participants from four US medical centers from 2006-2012. Participants in our analyses delivered a singleton live birth, had prospectively recorded LMP, ovulation detected by fertility monitor, and early first-trimester crown-rump length measurements. We estimated pregnancy length, preterm birth (<37 weeks) prevalence, and sex-specific size for gestational age by LMP, ultrasound, and ovulation. We report sensitivity and specificity of LMP and ultrasound for detecting preterm birth compared to our gold standard, ovulation.</p><p><strong>Results: </strong>In our analytic sample (n=392), pregnancies were longest, preterm birth least common (prevalence = 0.07, 95% CI: 0.04, 0.10), and small for gestational age most common when measured by LMP. Pregnancies were shortest, preterm birth most common (prevalence = 0.10 (95% CI: 0.07,0.13), and small for gestational age least common when measured by ultrasound. The prevalence of preterm birth was 0.08 (95% CI: 0.06, 0.12) by ovulation. Using ovulation as the gold standard measure, LMP was less sensitive in detecting preterm birth (0.76, 95% CI: 0.61, 0.90) than ultrasound (0.94, 95% CI: 0.86, 1.00). The specificity of LMP was 1.00 (95% CI: 0.99, 1.00), and the specificity of ultrasound was 0.97 (95%CI: 0.96, 0.99).</p><p><strong>Conclusion: </strong>While this study's pregnancy length information is best-case scenario, we observed misclassification of outcomes that may inform future bias analyses.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum: Definition and Interpretation of Separable Path-specific Effects With Multiple Ordered Mediators.","authors":"Yan-Lin Chen, Sheng-Hsuan Lin","doi":"10.1097/EDE.0000000000001911","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001911","url":null,"abstract":"","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145079889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative risks of opioid overdose in patients on oxycodone initiating selective serotonin reuptake inhibitors.","authors":"Katsiaryna Bykov, C Andrew Basham, Nazleen F Khan, Robert J Glynn, Shruti Belitkar, Seanna M Vine, Sungho Bea, Brian T Bateman, Krista F Huybrechts","doi":"10.1097/EDE.0000000000001914","DOIUrl":"https://doi.org/10.1097/EDE.0000000000001914","url":null,"abstract":"<p><strong>Background: </strong>Selective-serotonin reuptake inhibitors (SSRIs) are often co-prescribed with oxycodone, yet may potentiate respiratory depression. We aimed to assess the comparative effects of SSRIs on opioid overdose when added to oxycodone.</p><p><strong>Methods: </strong>Using US commercial and public health insurance claims data (2004-2020), we conducted a cohort study in adults who initiated SSRI while on oxycodone. We assigned patients to one of five exposures (sertraline, citalopram, escitalopram, fluoxetine, paroxetine) and followed them for opioid overdose (hospitalization or emergency room visit) for 365 days and while they stayed on both oxycodone and index SSRI. We used propensity score matching weights to adjust for potential confounders and weighted Cox proportional hazard models to estimate hazard ratios (HRs) with 95% confidence intervals (CI).</p><p><strong>Results: </strong>Among 753,263 eligible individuals (mean age 46 years [SD 16]; 527,340 females [70%]), 221,792 initiated sertraline, 173,352 citalopram, 153,968 escitalopram, 126,954 fluoxetine, and 77,197 paroxetine. Overall, 1250 opioid overdose events occurred, with incidence rates ranging from 10.8 to 15.2 per 1,000 person-years across individual SSRIs. Weighted HRs, relative to sertraline, were 1.24 (95% CI, 1.04 - 1.50) for citalopram, 1.22 (95% CI, 1.01 - 1.47) for escitalopram, 1.26 (95% CI, 1.04 - 1.53) for fluoxetine, and 1.26 (95% CI, 1.01 - 1.57) for paroxetine. No differences were observed across SSRIs other than sertraline.</p><p><strong>Conclusions: </strong>In this study of individuals who added an SSRI to oxycodone, incidence of opioid overdose was low. Patients who initiated sertraline experienced overdose at a slightly lower rate than patients who initiated other SSRIs.</p>","PeriodicalId":11779,"journal":{"name":"Epidemiology","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145063715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}