Wona Choi,1– 3,* Jae Won Yoo,4,* Bo Yeon Choi,1 Ki-Hoon Kim,1,5 Yoona Choi,6,7 Bo Kyung Kim,8,9 Jung-Hyun Won,10 Hyoung Jin Kang,8,9 Howard Lee,10– 13 In Young Choi,1 Nack-Gyun Chung41Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; 2School of Nursing, Hallym University, Chuncheon, Gangwon-do, 24252, Republic of Korea; 3Research Institute of Medical-Bio Convergence, Hallym University, Chuncheon, Gangwon-do, 24252, Republic of Korea; 4Division of Pediatric Hematology and Oncology, Department of Pediatrics, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; 5Department of Biomedicine and Health Sciences, The Catholic University of Korea, Seoul, Republic of Korea; 6Child Cancer and Rare Disease Project, Seoul National University Hospital, Seoul, Republic of Korea; 7Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea; 8Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea; 9Seoul National University Cancer Research Institute, Seoul, Republic of Korea; 10Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea; 11Center for Convergence Approaches in Drug Development, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea; 12Department of Clinical Pharmacology and Therapeutics, Seoul National University Hospital, Seoul, Republic of Korea; 13Advanced Institutes of Convergence Technology, Suwon, Republic of Korea*These authors contributed equally to this workCorrespondence: In Young Choi, Department of Medical Informatics, College of Medicine, The Catholic University of Korea, 222 Banpo-Daero, Seocho-Gu, Seoul, 06591, Republic of Korea, Tel +82-2-2255-4222, Email iychoi@catholic.ac.kr Nack-Gyun Chung, Division of Pediatric Hematology and Oncology, Department of Pediatrics, Catholic Hematology Hospital, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 222 Banpo-Daero, Seocho-Gu, Seoul, 06591, Republic of Korea, Tel +82-2-2255-6188, Email cngped@catholic.ac.krPurpose: To compare outcomes after total body irradiation (TBI)-based and chemotherapy-based conditioning in pediatric acute lymphoblastic leukemia (ALL).Patients and Methods: This retrospective two-center PeARL registry cohort comprised 325 patients diagnosed with ALL at age ≤ 18 years who underwent first allogeneic hematopoietic stem cell transplantation during 2009– 2023. Primary Cox and Fine–Gray models used full follow-up, adjusted for transplantation age, remission status and donor type, and were stratified by center. Propensity-score weighting was supplementary. Graft-versus-host disease (GVHD) analyses excluded recorded cases with unavailable or inconsistent onset dates and accounted for competing relapse and death; acute GVHD included any or unspecified grade.Results: Of 325 patients, 210 received TBI-based and 115 chemotherapy-based conditioning; median follow-up by reverse Kaplan–Meier was 5.85 and 1.88 years, respectively. Unweighted 5-year overall survival was 65.5% versus 67.1%, and leukemia-free survival was 57.5% versus 53.4%. Adjusted hazard ratios were 1.30 (95% confidence interval [CI], 0.54– 3.12) and 0.92 (0.43– 2.01), respectively. Adjusted subdistribution hazard ratios were 0.79 (0.31– 2.07) for relapse and 1.39 (0.43– 4.49) for non-relapse mortality (NRM); supplementary propensity-score-weighted NRM estimates ranged from 4.20 to 6.48. Among patients included in the respective GVHD time-to-event analyses, 100-day acute GVHD cumulative incidence was 62.7% versus 32.2% (n=315), and 5-year chronic GVHD cumulative incidence was 24.9% versus 5.2% (n=314).Conclusion: Primary analyses did not detect statistically significant survival differences, but clinically important differences could not be excluded. NRM estimates varied across analyses. Non-random treatment selection, unequal follow-up, incomplete outcome recording and residual confounding limit causal interpretation.Keywords: pediatric acute lymphoblastic leukemia, conditioning regimen, relapse, survival outcomes, late effects, real-world evidence
Maxime Pluquet,1 Thibaut Balcaen,2 Solène M Laville,1,3 Sophie Liabeuf1,31Pharmacoepidemiology Unit, Department of Clinical Pharmacology, Amiens-Picardie University Medical Center, Amiens, France; 2Department of Medical Information, Amiens-Picardie University Medical Center, Amiens, France; 3MP3CV Laboratory, Jules Verne University of Picardie, Amiens, FranceCorrespondence: Sophie Liabeuf, Pharmacoepidemiology Unit, Clinical Pharmacology Department, Amiens-Picardie University Medical Center, Rond-Point du Professeur Christian Cabrol, Amiens cedex, F-80054, France, Tel +33-322-087-995, Email liabeuf.sophie@chu-amiens.frPurpose: Drug-induced QT interval prolongation increases the risk of ventricular arrhythmias and cardiac arrest. Assessing these outcomes in electronic health databases and evaluating their association with drug exposure requires prior validation of administrative diagnostic codes. This study aimed to evaluate the positive predictive value (PPV) of International Classification of Diseases, 10th revision (ICD-10) codes for ventricular arrhythmias and cardiac arrest in the French hospital discharge summary database (Programme de Médicalisation des Systèmes d’Information (PMSI)).Methods: In a retrospective validation study, we examined PMSI data recorded at Amiens University Medical Center (Amiens, France). Hospital stays between September 2022 and August 2025 with ICD-10 codes for cardiac arrest (I46.0, I46.9), ventricular tachycardia (I47.2), or ventricular fibrillation/flutter (I49.0) were identified. Events were confirmed by electronic medical record review. PPVs with 95% confidence intervals (CI) were calculated. The study design prevented the estimation of sensitivity, specificity, and negative predictive values. Sensitivity analyses were stratified by year, and by type of care unit. Exposure to QT-prolonging medications prior to events was also assessed.Results: In a population of 182 patients (median age: 66 years; 75% males; in-hospital mortality rate: 45%), PPVs [95% CI] for all diagnosis codes were high: 0.98 [0.95; 1.00] for cardiac arrest with successful resuscitation, 0.96 [0.79; 1.00] for unspecified cardiac arrest, 0.99 [0.94; 1.00] for ventricular tachycardia, and 0.93 [0.87; 0.97] for ventricular fibrillation/flutter. Sensitivity analyses yielded consistent results. Overall, 49.7% of patients had been exposed to ≥ 1 QT-prolonging medications prior to a validated event, and 26.5% to ≥ 2 of these medications concomitantly.Conclusion: The high PPVs in PMSI data supports the use of the evaluated ICD-10 codes for outcome identification in pharmacoepidemiological studies of electronic health databases in general, and those investigating QT-prolonging medication use and the risk of serious cardiac events in particular.Keywords: administrative codes, cardiac arrest, electronic medical records, ICD-10, PMSI, validation, ventricular arrhythmia
Anjum Khurshid,1 Jennifer L Winkler,2 Mohammad Jafari,3 Henrik Toft Sorensen21Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA; 2Department of Clinical Epidemiology, Center for Population Medicine, Aarhus University and Aarhus University Hospital, Aarhus, Denmark; 3Independent Interoperability Consultant, Phoenix, AZ, USACorrespondence: Anjum Khurshid, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA, Email anjum_khurshid@hphci.harvard.eduAbstract: International travel by people with multimorbidity and polypharmacy is increasing, and clinicians who treat these patients abroad seldom have access to accurate and current information about them. Mechanisms for cross-border exchange do exist: the International Patient Summary (IPS), European cross-border health services, and national patient portals all move summary clinical data between jurisdictions. What none of them yet provides is automated abstraction of decades of longitudinal records into a short summary, and reliable determination of which diagnoses are active and which medications are current. They also do not provide consistent deployment across jurisdictions that record and code data differently. Sørensen (2022) established the clinical case for a Global Medical Record System (GMRS) and outlined its core data elements. We argue that four recent developments provide a window of policy opportunity: COVID-19 vaccination credentials, which showed that portable health data can be deployed at population scale; formalization of the HL7 IPS as an ISO standard with an implementation guide (FHIR IG); regulatory mandates for health data interoperability in the United States and the European Union; and an ongoing transatlantic collaboration aimed at mapping a GMRS algorithm onto those standards. Herein we make a policy case for coordinated international action, describe the standards pathway of mapping the GMRS to the FHIR IPS and United States Core Data for Interoperability (USCDI), and propose a structured maturation pathway for research and validation via a Denmark–United States collaboration. The GMRS would add to the IPS an abstraction layer that decides which of a patient’s accumulated entries belong in the summary. We present this as a proposed roadmap and policy argument as the GMRS algorithm has not yet undergone formal validation which would be required before actual deployment.Keywords: global medical records, international patient summary, portable clinical summary, HL7 FHIR, USCDI, travel medicine, chronic disease, polypharmacy, health data interoperability, algorithm validation, maturation pathway, clinical epidemiology
Chun-Tse Hung,1 Chen-Yen An,2 Chi-Won Suk31Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA; 2Department of Pharmacy, Taipei Medical University Hospital, Taipei, Taiwan; 3Division of Pulmonary Medicine, Department of Internal Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, TaiwanCorrespondence: Chun-Tse Hung, Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, 1007 E. Huron St, Ann Arbor, MI, 48104, USA, Email chuntseh@umich.eduBackground: Accurate identification of asthma exacerbations in electronic health records (EHRs) is essential for research and clinical decision-making. While composite definitions incorporating healthcare encounters and systemic corticosteroid use are commonly used, ICD-10 code-only definitions are often applied when detailed data are unavailable. However, their agreement remains unclear. This study aimed to (1) compare an ICD-10 code–only definition of asthma exacerbation with a composite definition, and (2) identify factors associated with concordance between both definitions in EHR data.Methods: We conducted a multicenter retrospective cohort study using the Taipei Medical University Clinical Research Database (2017– 2023). Asthma exacerbations were identified using (1) an ICD-10 code–only definition and (2) a composite definition incorporating asthma-related emergency department visits, hospitalization, or systemic corticosteroid use. Episodes were defined using a seven-day gap rule. Agreement was assessed using overall percent agreement (OPA), positive predictive value (PPV), negative predictive value (NPV), positive percent agreement (PPA), and negative percent agreement (NPA), with generalized estimating equations accounting for within-patient clustering.Results: Among 1,486,449 episodes, 40,180 (2.7%) met the code-only definition and 35,875 (2.4%) met the composite definition. After covariate adjustment, OPA was 0.930 (95% CI, 0.926– 0.933). PPV and PPA were 0.313 (95% CI, 0.293– 0.334) and 0.309 (95% CI: 0.291– 0.328), respectively, while NPV and NPA were high (0.968 and 0.962). Comorbidity burden, hospital, asthma severity, and index year were associated with concordance.Conclusion: ICD-10 code–only definition demonstrated high overall agreement with the composite definition, driven primarily by agreement on non-events, but limited agreement for identified exacerbations. These findings suggest that the two definitions may capture different levels of exacerbations. Several factors were associated with concordance between both definitions, highlighting the importance of accounting for these factors when analyzing EHR data. Code-only definitions may be used cautiously in EHR-based studies, given potential heterogeneity and misclassification.Keywords: asthma, asthma exacerbation, agreement, ICD-10, electronic health records
Purpose:Maternal smoking during pregnancy (SDP) is associated with adverse neonatal outcomes, but the specific conditions contributing to morbidity among term infants are poorly characterized. We examined whether maternal SDP increases the risk of neonatal intensive care unit (NICU) admission and antibiotic treatment during the first week of life, and identified NICU diagnoses more common among exposed infants. Methods:This register-based cohort study included all full-term (≥ 37+0 weeks' gestation) singleton births in Finland from 2006 to 2018, using data from the Finnish Medical Birth Register and Hospital Discharge Register (n = 795,836; 95.2% of singleton births). Maternal smoking was categorized as no smoking, quit smoking during the first trimester (early smoking), or continued smoking after the first trimester. Primary outcomes were NICU admission and antibiotic treatment during the first week of life. Secondary outcomes included neonatal diagnoses and perinatal mortality. Stillbirths and early neonatal deaths were excluded from the analyses of treatments and diagnoses. Adjusted odds ratios (aORs) were estimated using logistic regression, adjusting for maternal age, parity, prepregnancy BMI, mode of delivery, and year of delivery. Results:Continued smoking was associated with increased odds of NICU admission (aOR 1.43) and antibiotic treatment (aOR 1.22), while early smoking was associated with more modest increases (aORs 1.17 and 1.19, respectively), compared with no exposure. Both smoking exposures were associated with an increased risk of bacterial sepsis or congenital pneumonia. Neonatal hypoglycemia was increased only with continued smoking. Continued smoking was also associated with an increased the risk stillbirth (aOR, 1.49) whereas early smoking was not associated with perinatal mortality. Conclusion:Maternal smoking during pregnancy was associated with an increased risk of infections and metabolic disturbances requiring intensive care among term infants. Continued smoking also increased the risk of stillbirth. These findings further support the importance of smoking cessation during pregnancy.
