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Analysis of antiseizure drug-related adverse reactions from the electronic health record using the common data model

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EPILEPSIA 2020年第4期61卷 610-616页

作者： Choi, Sun Ah Kim, Hunmin Kim, Seok Yoo, Sooyoung Yi, Soyoung Jeon, Yonghoon Hwang, Hee Kim, Ki Joong Seoul Natl Univ Coll Med Dept Pediat Bundang Hosp Seongnam South Korea Dankook Univ Dankook Univ Hosp Dept Pediat Coll Med Cheonan South Korea Seoul Natl Univ Bundang Hosp Off eHlth Res & Business Seongnam South Korea Seoul Natl Univ Coll Med Dept Pediat Childrens Hosp Seoul South Korea

Objective Antiseizure drugs (ASDs) are known to cause a wide range of adverse drug reactions (ADRs). Recently, electronic health care data using the common data model (CDM) have been introduced and commonly adopted in pharmacovigilance research. We aimed to analyze ASD-related ADRs using CDM and to assess the feasibility of CDM analysis in monitoring ADR in a single tertiary hospital. Methods We selected five ASDs: oxcarbazepine (OXC), lamotrigine (LTG), levetiracetam (LEV), valproic acid (VPA), and topiramate (TPM). Patients diagnosed with epilepsy and exposed to monotherapy with one of the ASDs before age 18 years were included. We measured four ADR outcomes: (1) hematologic abnormality, (2) hyponatremia, (3) elevation of liver enzymes, and (4) subclinical hypothyroidism. We performed a subgroup analysis to exclude the effects of concomitant medications. Results From the database, 1344 patients were included for the study. Of the 1344 patients, 436 were receiving OXC, 293 were receiving LTG, 275 were receiving LEV, 180 were receiving VPA, and 160 were receiving TPM. Thrombocytopenia developed in 14.1% of patients taking VPA. Hyponatremia occurred in 10.5% of patients taking OXC. Variable ranges of liver enzyme elevation were detected in 19.3% of patients taking VPA. Subclinical hypothyroidism occurred in approximately 21.5% to 28% of patients with ASD monotherapy, which did not significantly differ according to the type of ASD. In a subgroup analysis, we observed similar ADR tendencies, but with less thrombocytopenia in the TPM group. Significance The incidence and trends of ADRs that were evaluated by CDM were similar to the previous literature. CDM can be a useful tool for analyzing ASD-related ADRs in a multicenter study. The strengths and limitations of CDM should be carefully addressed.

关键词： adverse drug reaction antiseizure drugs common data model epilepsy pharmacovigilance

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Development and validation of common data model-based fracture prediction model using machine learning algorithm

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OSTEOPOROSIS INTERNATIONAL 2023年第8期34卷 1437-1451页

作者： Kong, Sung Hye Kim, Sihyeon Kim, Yisak Kim, Jung Hee Kim, Kwangsoo Shin, Chan Soo Seoul Natl Univ Dept Internal Med Bundang Hosp Seongnam South Korea Seoul Natl Univ Dept Internal Med Coll Med Seoul South Korea Seoul Natl Univ Hosp Dept Integrat Med Seoul 03080 South Korea Seoul Natl Univ Interdisciplinary Program Bioengn Grad Sch Seoul South Korea Seoul Natl Univ Hosp Dept Internal Med Seoul 03080 South Korea

The need for an accurate country-specific real-world-based fracture prediction model is increasing. Thus, we developed scoring systems for osteoporotic fractures from hospital-based cohorts and validated them in an independent cohort in Korea. The model includes history of fracture, age, lumbar spine and total hip T-score, and cardiovascular *** fractures are substantial health and economic burden. Therefore, the need for an accurate real-world-based fracture prediction model is increasing. We aimed to develop and validate an accurate and user-friendly model to predict major osteoporotic and hip fractures using a common data model *** study included 20,107 and 13,353 participants aged >= 50 years with data on bone mineral density using dual-energy X-ray absorptiometry from the CDM database between 2008 and 2011 from the discovery and validation cohort, respectively. The main outcomes were major osteoporotic and hip fracture events. DeepHit and Cox proportional hazard models were used to identify predictors of fractures and to build scoring systems, respectively. ResultsThe mean age was 64.5 years, and 84.3% were women. During a mean of 7.6 years of follow-up, 1990 major osteoporotic and 309 hip fracture events were observed. In the final scoring model, history of fracture, age, lumbar spine T-score, total hip T-score, and cardiovascular disease were selected as predictors for major osteoporotic fractures. For hip fractures, history of fracture, age, total hip T-score, cerebrovascular disease, and diabetes mellitus were selected. Harrell's C-index for osteoporotic and hip fractures were 0.789 and 0.860 in the discovery cohort and 0.762 and 0.773 in the validation cohort, respectively. The estimated 10-year risks of major osteoporotic and hip fractures were 2.0%, 0.2% at score 0 and 68.8%, 18.8% at their maximum scores, *** developed scoring systems for osteoporotic fractures from hospital-based cohorts and

关键词： Fracture Prediction model Osteoporosis common data model

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Identification of patients with drug-resistant epilepsy in electronic medical record data using the Observational Medical Outcomes Partnership common data model

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EPILEPSIA 2022年第11期63卷 2981-2993页

作者： Castano, Victor G. Spotnitz, Matthew Waldman, Genna J. Joiner, Evan F. Choi, Hyunmi Ostropolets, Anna Natarajan, Karthik McKhann, Guy M. Ottman, Ruth Neugut, Alfred, I Hripcsak, George Youngerman, Brett E. Columbia Univ Vagelos Coll Phys & Surg Dept Neurol Surg New York NY 10032 USA Columbia Univ Vagelos Coll Phys & Surg Dept Biomed Informat New York NY 10032 USA Columbia Univ Vagelos Coll Phys & Surg Dept Neurol New York NY 10032 USA Columbia Univ Irving Med Ctr Gertrude H Sergievsky Ctr New York NY 10032 USA Columbia Univ Mailman Sch Publ Hlth Dept Epidemiol New York NY 10032 USA New York State Psychiat Inst & Hosp Div Translat Epidemiol & Mental Hlth Equ New York NY 10032 USA Columbia Univ Vagelos Coll Phys & Surg Dept Med New York NY 10032 USA Columbia Univ Vagelos Coll Phys & Surg Herbert Irving Comprehens Canc Ctr New York NY 10032 USA

Objective More than one third of appropriately treated patients with epilepsy have continued seizures despite two or more medication trials, meeting criteria for drug-resistant epilepsy (DRE). Accurate and reliable identification of patients with DRE in observational data would enable large-scale, real-world comparative effectiveness research and improve access to specialized epilepsy care. In the present study, we aim to develop and compare the performance of computable phenotypes for DRE using the Observational Medical Outcomes Partnership (OMOP) common data model. Methods We randomly sampled 600 patients from our academic medical center's electronic health record (EHR)-derived OMOP database meeting previously validated criteria for epilepsy (January 2015-August 2021). Two reviewers manually classified patients as having DRE, drug-responsive epilepsy, undefined drug responsiveness, or no epilepsy as of the last EHR encounter in the study period based on consensus definitions. Demographic characteristics and codes for diagnoses, antiseizure medications (ASMs), and procedures were tested for association with DRE. Algorithms combining permutations of these factors were applied to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for DRE. The F1 score was used to compare overall performance. Results Among 412 patients with source record-confirmed epilepsy, 62 (15.0%) had DRE, 163 (39.6%) had drug-responsive epilepsy, 124 (30.0%) had undefined drug responsiveness, and 63 (15.3%) had insufficient records. The best performing phenotype for DRE in terms of the F1 score was the presence of >= 1 intractable epilepsy code and >= 2 unique non-gabapentinoid ASM exposures each with >= 90-day drug era (sensitivity = .661, specificity = .937, PPV = .594, NPV = .952, F1 score = .626). Several phenotypes achieved higher sensitivity at the expense of specificity and vice versa. Significance OMOP algorithms can identify DRE in EH

关键词： common data model computable phenotype drug-resistant epilepsy electronic health record Observational Health data Science and Informatics Observational Medical Outcomes Partnership

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Association between pre-diagnostic serum uric acid levels in patients with newly diagnosed epilepsy and conversion rate to drug-resistant epilepsy within 5 years: A common data model analysis

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SEIZURE-EUROPEAN JOURNAL OF EPILEPSY 2024年 118卷 103-109页

作者： Koh, Seungyon Lee, Dong Yun Cha, Jae Myung Kim, Yerim Kim, Hyung Hoi Yang, Hyeon-Jong Park, Rae Woong Choi, Jun Young Ajou Univ Sch Med Dept Brain Sci 164 World Cup Ro Suwon 16499 Gyeonggi Do South Korea Ajou Univ Grad Sch Dept Biomed Sci Suwon South Korea Ajou Univ Sch Med Dept Neurol Suwon South Korea Ajou Univ Sch Med Dept Biomed Informat Suwon South Korea Ajou Univ Grad Sch Dept Med Sci Suwon South Korea Ajou Univ Sch Med Dept Psychiat Suwon South Korea Kyung Hee Univ Gang Dong Kyung Hee Univ Hosp Dept Gastroenterol Seoul South Korea Hallym Univ Kangdong Sacred Heart Hosp Coll Med Dept Neurol Seoul South Korea Pusan Natl Univ Hosp Dept Lab Med Busan South Korea Soonchunhyang Univ Coll Med Dept Pediat Seoul South Korea

Purpose: Drug -resistant epilepsy (DRE) poses a significant challenge in epilepsy management, and reliable biomarkers for identifying patients at risk of DRE are lacking. This study aimed to investigate the association between serum uric acid (UA) levels and the conversion rate to DRE. Methods: A retrospective cohort study was conducted using a common data model database. The study included patients newly diagnosed with epilepsy, with prediagnostic serum UA levels within a six-month window. Patients were categorized into hyperUA (>= 7.0 mg/dL), normoUA ( <7.0 and >2.0 mg/dL), and hypoUA (<= 2.0 mg/dL) groups based on their prediagnostic UA levels. The outcome was the conversion rate to DRE within five years of epilepsy diagnosis. Results: The study included 5,672 patients with epilepsy and overall conversion rate to DRE was 19.4%. The hyperUA group had a lower DRE conversion rate compared to the normoUA group (HR: 0.81 [95% CI: 0.69 -0.96]), while the hypoUA group had a higher conversion rate (HR: 1.88 [95% CI: 1.38 -2.55]). Conclusions: Serum UA levels have the potential to serve as a biomarker for identifying patients at risk of DRE, indicating a potential avenue for novel therapeutic strategies aimed at preventing DRE conversion.

关键词： Uric acid Drug-resistant epilepsy Neuroprotection common data model

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Performance of a semi-automated approach for risk estimation using a common data model for longitudinal healthcare databases

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STATISTICAL METHODS IN MEDICAL RESEARCH 2013年第1期22卷 97-112页

作者： Hoa Van Le Beach, Kathleen J. Powell, Gregory Pattishall, Ed Ryan, Patrick Mera, Robertino M. Univ N Carolina Dept Epidemiol Gillings Sch Global Publ Hlth Chapel Hill NC 27599 USA GlaxoSmithKline Res Triangle Pk NC USA

Different structures and coding schemes may limit rapid evaluation of a large pool of potential drug safety signals using multiple longitudinal healthcare databases. To overcome this restriction, a semi-automated approach utilising common data model (CDM) and robust pharmacoepidemiologic methods was developed;however, its performance needed to be evaluated. Twenty-three established drug-safety associations from publications were reproduced in a healthcare claims database and four of these were also repeated in electronic health records. Concordance and discrepancy of pairwise estimates were assessed between the results derived from the publication and results from this approach. For all 27 pairs, an observed agreement between the published results and the results from the semi-automated approach was greater than 85% and Kappa coefficient was 0.61, 95% CI: 0.19-1.00. Ln(IRR) differed by less than 50% for 13/27 pairs, and the IRR varied less than 2-fold for 19/27 pairs. Reproducibility based on the intra-class correlation coefficient was 0.54. Most covariates (>90%) in the publications were available for inclusion in the models. Once the study populations and inclusion/exclusion criteria were obtained from the literature, the analysis was able to be completed in 2-8 h. The semi-automated methodology using a CDM produced consistent risk estimates compared to the published findings for most selected drug-outcome associations, regardless of original study designs, databases, medications and outcomes. Further assessment of this approach is useful to understand its roles, strengths and limitations in rapidly evaluating safety signals.

关键词： common data model drug safety observational database pharmacovigilance propensity score safety signal risk estimation

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Transformation of Pathology Reports Into the common data model With Oncology Module: Use Case for Colon Cancer

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JOURNAL OF MEDICAL INTERNET RESEARCH 2020年第12期22卷 e18526页

作者： Ryu, Borim Yoon, Eunsil Kim, Seok Lee, Sejoon Baek, Hyunyoung Yi, Soyoung Na, Hee Young Kim, Ji-Won Baek, Rong-Min Hwang, Hee Yoo, Sooyoung Seoul Natl Univ Bundang Hosp Off eHlth Res & Business 82 173rd St Seongnam 13620 South Korea Seoul Natl Univ Dept Pathol & Translat Med Bundang Hosp Seongnam South Korea Seoul Natl Univ Div Hematol & Med Oncol Bundang Hosp Seongnam South Korea Seoul Natl Univ Dept Plast Surg Bundang Hosp Seongnam South Korea

Background: common data models (CDMs) help standardize electronic health record data and facilitate outcome analysis for observational and longitudinal research. An analysis of pathology reports is required to establish fundamental information infrastructure for data-driven colon cancer research. The Observational Medical Outcomes Partnership (OMOP) CDM is used in distributed research networks for clinical data;however, it requires conversion of free text-based pathology reports into the CDM's format. There are few use cases of representing cancer data in CDM. Objective: In this study, we aimed to construct a CDM database of colon cancer-related pathology with natural language processing (NLP) for a research platform that can utilize both clinical and omics data. The essential text entities from the pathology reports are extracted, standardized, and converted to the OMOP CDM format in order to utilize the pathology data in cancer research. Methods: We extracted clinical text entities, mapped them to the standard concepts in the Observational Health data Sciences and Informatics vocabularies, and built databases and defined relations for the CDM tables. Major clinical entities were extracted through NLP on pathology reports of surgical specimens, immunohistochemical studies, and molecular studies of colon cancer patients at a tertiary general hospital in South Korea. Items were extracted from each report using regular expressions in Python. Unstructured data, such as text that does not have a pattern, were handled with expert advice by adding regular expression rules. Our own dictionary was used for normalization and standardization to deal with biomarker and gene names and other ungrammatical expressions. The extracted clinical and genetic information was mapped to the Logical Observation Identifiers Names and Codes databases and the Systematized Nomenclature of Medicine (SNOMED) standard terminologies recommended by the OMOP CDM. The database-table relationships we

关键词： common data model natural language processing oncology module colon cancer electronic health record oncology pathology clinical data

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A Study to Evaluate the Effectiveness and Safety of Prephase Steroid Treatment before Remission Induction Chemotherapy in Patients with Pediatric Acute Lymphoblastic Leukemia Using common data model-Based Real-World data: A Retrospective Observational Study

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CLINICAL EPIDEMIOLOGY 2024年 16卷 293-304页

作者： Choi, Yoona Kim, Bo Kyung Won, Jung-Hyun Yoo, Jae Won Choi, Wona Jung, Surin Kim, Jae Yoon Choi, In Young Chung, Nack-Gyun Lee, Jae Wook Choi, Jung Yoon Kang, Hyoung Jin Lee, Howard Seoul Natl Univ Grad Sch Convergence Sci & Technol Dept Appl Bioengn Seoul South Korea Seoul Natl Univ Ctr Convergence Approaches Drug Dev Grad Sch Convergence Sci & Technol Seoul South Korea Seoul Natl Univ Hosp Dept Pediat Seoul South Korea Seoul Natl Univ Canc Res Inst Seoul South Korea Seoul Natl Univ Grad Sch Convergence Sci & Technol Dept Mol Med & Biopharmaceut Sci Seoul South Korea Catholic Univ Korea Seoul St Marys Hosp Coll Med Dept Pediat Seoul South Korea Catholic Univ Korea Coll Med Dept Med Informat Seoul South Korea Catholic Univ Korea Dept Biomed & Hlth Sci Seoul South Korea Seoul Natl Univ Dept Pediat Coll Med 101 Daehak Ro Seoul 03080 South Korea Adv Inst Convergence Technol Suwon South Korea Seoul Natl Univ Hosp Dept Clin Pharmacol & Therapeut 101 Daehak Ro Seoul 03080 South Korea

Background: Rapid reduction of leukemic cells in the bone marrow during remission induction chemotherapy (RIC) can lead to significant complications such as tumor lysis syndrome (TLS). We investigated whether prephase steroid treatment before RIC could decrease TLS incidence and improve overall survival in pediatric patients with acute lymphoblastic leukemia (ALL). Methods: data were extracted from the common data model databases in two tertiary -care hospitals in Seoul, South Korea. Patients were classified into the treated or untreated group if they had received RIC with prephase steroid treatment >= 7 days before RIC in 2012-2021 or not, respectively. Stabilized Inverse Probability of Treatment Weighting (sIPTW) was applied to ensure compatibility between the treated and untreated groups. The incidence of TLS within 14 days of starting RIC, overall survival (OS), and the incidence of adverse events of special interest were the primary endpoints. Multiple sensitivity analyses were performed. Results: Baseline characteristics were effectively balanced between the treated (n=308.4) and untreated (n=246.6) groups after sIPTW. Prephase steroid treatment was associated with a significant 88% reduction in the risk of TLS (OR 0.12, 95% CI: 0.03-0.41). OS was numerically greater in the treated group than in the untreated group although the difference was not statistically significant (HR 0.64, 95% CI 0.25-1.64). The treated group experienced significantly elevated risks for hyperbilirubinemia and hyperglycemia. The reduction in TLS risk by prephase steroid treatment was maintained in all of the sensitivity analyses. Conclusion: Prephase steroid treatment for >= 7 days before RIC in pediatric patients with ALL reduces the risk of TLS, while careful monitoring for toxicities is necessary. If adequately analyzed, real -world data can provide crucial effectiveness and safety information for proper management of pediatric patients with ALL, for whom prospective randomized stud

关键词： pediatric acute lymphoblastic leukemia tumor lysis syndrome remission induction chemotherapy prephase steroid treatment common data model

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Risks of long-term use of proton pump inhibitor on ischemic vascular events: A distributed network analysis of 5 real-world observational Korean databases using a common data model

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INTERNATIONAL JOURNAL OF STROKE 2023年第5期18卷 590-598页

作者： Kim, Yerim Seo, Seung In Lee, Kyung Joo Kim, Jinseob Yoo, Jong Jin Seo, Won-Woo Shin, Woon Geon Hallym Univ Kangdong Sacred Heart Hosp Dept Neurol Coll Med Seoul South Korea Hallym Univ Kangdong Sacred Heart Hosp Dept Internal Med Coll Med Seoul South Korea Hallym Univ Univ Ind Fdn Chunchon South Korea Seoul Natl Univ Sch Publ Hlth Dept Epidemiol Seoul South Korea

Background: Proton pump inhibitors (PPIs) are frequently prescribed drugs. However, it has been suggested that they are associated with an increased risk of ischemic vascular events (IVE) including stroke, although the data are inconsistent. Aims: We investigated the association between PPIs use and IVE in five observational Korean databases using a common data model (CDM). Methods: This study included patient-based retrospective, observational cohort data of subjects aged over 18 years between January 1, 2004, and December 31, 2020, from five medical centers as part of the Observational Medical Outcomes Partnership (OMOP) CDM. Subjects who were included in both cohorts or had a previous history of ischemic stroke were excluded. After propensity matching, 8007 propensity-matched pairs between the PPIs and H-2 receptor antagonist (H(2)RA) users were included in this study. Results: In the 1:1 propensity score matching with 8007 in each group, long-term PPIs use (> 365 days) was not associated with ischemic stroke (odds ratio (OR) = 1.05, 95% confidence interval (CI) 0.71-1.56;I-2 = 57%), ischemic stroke and transient ischemic attack (OR = 1.02, 95% CI 0.71-1.48;I-2 = 53%), and net adverse clinical events (OR = 1.08, 95% CI 0.83-1.40;I-2 = 47%) compared with H2RAs users. Conclusions: Our analysis in a large dataset found no evidence that long-term use of PPIs was associated with an increased risk of ischemic stroke.

关键词： common data model H2 receptor antagonist ischemic stroke proton pump inhibitors stroke

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Real-World Use of Colonoscopy in an Older Population: A Nationwide Standard Cohort Study Using a common data model

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DIGESTIVE DISEASES AND SCIENCES 2021年第7期66卷 2227-2234页

作者： Kim, Ha Il Yoon, Jin Young Kwak, Min Seob Cha, Jae Myung Kyung Hee Univ Hosp Gangdong Div Gastroenterol Dept Internal Med Seoul South Korea Kyung Hee Univ Sch Med Div Gastroenterol Dept Internal Med Seoul South Korea

Backgrounds and Aims Rapid population aging is considered to be a major factor in increased colonoscopy use in Korea. However, real-world use of colonoscopy in older populations is rarely evaluated using Korean databases. Methods We conducted a retrospective, observational cohort study of individuals aged over 20 years between 2012 and 2017. We used the Health Insurance Review and Assessment-National Patient Samples database, previously converted to the standardized Observational Medical Outcomes Partnership-common data model. The use of diagnostic colonoscopy and colonoscopic polypectomy was evaluated, stratified by age group and sex. Results During the study period, we captured data from the database on 240,406 patients who underwent diagnostic colonoscopy and 88,984 who underwent colonoscopic polypectomy. During the study period, use of diagnostic colonoscopy and colonoscopic polypectomy steadily increased, but both procedures were most significantly increased in the 65- to 85-year group compared to other age groups (p < 0.05). Average ages for both procedures significantly increased in the most recent 3 years (p < 0.05). Polypectomy rates for men plateaued in the 50- to 64-year age group, but rates for women steadily increased up to the 65- to 85-year group. Polypectomy rates were higher for men than for women in all index years. Conclusions The use of diagnostic colonoscopy and colonoscopic polypectomy significantly increased in the 65- to 85-year age group. Our findings suggest that more available colonoscopy resources should be allocated to older populations, considering the aging society in Asian countries.

关键词： common data model Observational Medical Outcomes Partnership Colonoscopy Polypectomy Population

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Long-term proton pump inhibitor use and risk of osteoporosis and hip fractures: A nationwide population-based and multicenter cohort study using a common data model

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JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY 2022年第8期37卷 1534-1543页

作者： Park, Da Hee Seo, Seung In Lee, Kyung Joo Kim, Jinseob Kim, Yerim Seo, Won-Woo Lee, Hyung Seok Shin, Woon Geon Yoo, Jong Jin Hallym Univ Coll Med Kangdong Sacred Heart Hosp Div GastroenterolDept Internal Med Seoul South Korea Hallym Univ Coll Med Kangdong Sacred Heart Hosp Dept Neurol Seoul South Korea Hallym Univ Coll Med Kangdong Sacred Heart Hosp Div CardiolDept Internal Med Seoul South Korea Hallym Univ Coll Med Kangdong Sacred Heart Hosp Div RheumatolDept Internal Med Seoul South Korea Seoul Natl Univ Sch Publ Hlth Dept Epidemiol Seoul South Korea Hallym Univ Inst Liver & Digest Dis Chunchon South Korea Hallym Univ Univ Ind Fdn Chunchon South Korea Hallym Univ Coll Med Div Nephrol Dept Internal MedSacred Heart Hosp Anyang South Korea

Background and Aim Association between protonpump inhibitors (PPIs) and osteoporosis, hip fractures has not been fully elucidated. We aimed to evaluate the relationship between PPIs use and the risk of osteoporosis and hip fractures in the databases converted to a common data model (CDM) and to compare the results across the databases. Methods This was a population-based, propensity-matched, retrospective cohort study that included patients aged >= 50 years who were prescribed with PPIs for over 180 days. We compared the incidence of osteoporosis and hip fractures between new PPI user and new user of other drugs using the Cox proportional hazards model and performed meta-analysis in the electronic health record (EHR) databases. Results In the Korean National Health Insurance Service (NHIS)-CDM database, long-term PPI users had greater risk of osteoporosis [PPIs vs non-PPIs groups, 28.42/1000 person-years vs 19.29/1000 person-years;hazard ratio (HR), 1.62;95% confidence interval (CI), 1.22-2.15;P = 0.001]. The meta-analytic results of six EHR databases also showed similar result (pooled HR, 1.57;95% CI, 1.28-1.92). In the analysis of hip fracture, PPI use was not significantly associated with a hip fracture in the NHIS-CDM database (PPI vs non-PPI groups, 3.09/1000 person-years vs 2.26/1000 person-years;HR, 1.45;95% CI, 0.74-2.80;P = 0.27). However, in the meta-analysis of four EHR databases, the risk of hip fractures was higher in PPI users (pooled HR, 1.82;95% CI, 1.04-3.19). Conclusions Long-term PPI was significantly associated with osteoporosis;however, the results of hip fractures were inconsistent. Further study based on better data quality may be needed.

关键词： common data model hip fracture osteoporosis proton pump inhibitor

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