Evidence map›Paper›PMID 41531184›Full record

Observational studyBritish journal of clinical pharmacology2026

Antidepressants and the risk of hyponatremia: A multi-institutional cohort study using observational medical outcomes partnership-Common Data Model.

Kyungyeon Jung, Ju Hwan Kim, Da Eun Hyeon, Jeongmoon Ji, Min Young Lee, Hayun Choi, Dong Yun Lee, Min Woo Kim, Yoonmin Jang, Seonghoon Hwang and 12 more

Abstract readObservational StudyMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in British journal of clinical pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Kyungyeon JungDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0002-0990-9360
Ju Hwan KimDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0000-0001-7253-6515
Da Eun HyeonDepartment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea.ORCID https://orcid.org/0009-0000-0714-5673
Jeongmoon JiDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0002-5391-2057
Min Young LeeSchool of Pharmacy, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0002-1347-0493
Hayun ChoiDepartment of Psychiatry, Veteran Health Service Medical Center, Seoul, South Korea.ORCID https://orcid.org/0000-0002-8404-8006
Dong Yun LeeBongdam Forest Mental Health Clinic, Hwaseong, South Korea.ORCID https://orcid.org/0000-0002-3678-9862
Min Woo KimDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0009-8335-400X
Yoonmin JangDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0000-9284-3547
Seonghoon HwangDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0009-0007-7113-9527
Jaehyeong ChoDepartment of Research, Keimyung University Dongsan Medical Center, Daegu, South Korea.ORCID https://orcid.org/0000-0001-7213-5033
Seok Young SongDepartment of Anesthesiology and Pain Medicine, College of Medicine, Daegu Catholic University, Daegu, South Korea.ORCID https://orcid.org/0000-0002-5653-7005
Sang Youl RheeCenter for Digital Health, Kyung Hee University, Seoul, South Korea.ORCID https://orcid.org/0000-0003-0119-5818
Jae Myung ChaDepartment of Internal Medicine, Kyung Hee University Hospital at Gangdong, Kyung Hee University, Seoul, South Korea.ORCID https://orcid.org/0000-0001-9403-230X
Won-Woo SeoDepartment of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea.ORCID https://orcid.org/0000-0002-4406-5485
Chang-Won JeongSmart Business Team in Information Management Office, Wonkwang University Hospital, Iksan, South Korea.ORCID https://orcid.org/0000-0002-9305-4686
Seung-Jin KwagDepartment of Surgery, Gyeongsang National University School of Medicine and Gyeongsang National University Hospital, Jinju, South Korea.ORCID https://orcid.org/0000-0002-9267-9158
Woo Jin KimDepartment of Biomedical Informatics, Kangwon National University Medical College, Chuncheon, South Korea.ORCID https://orcid.org/0000-0003-2927-370X
Jaeuk HwangDepartment of Psychiatry, Soonchunhyang University Seoul Hospital, College of Medicine, Seoul, South Korea.ORCID https://orcid.org/0000-0003-0528-3305
Min-Ho KimEwha Medical Data Organization, Seoul, South Korea.ORCID https://orcid.org/0000-0003-4909-2308
Rae Woong ParkDepartment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea.ORCID https://orcid.org/0000-0003-4989-3287
Ju-Young ShinDepartment of Biohealth Regulatory Science, Sungkyunkwan University, Suwon, South Korea.ORCID https://orcid.org/0000-0003-1010-7525

Funding

Ministry of Health & Welfare, Republic of Korea RS-2024-00335936Ministry of Health & Welfare, Republic of Korea RS-2025-02215225
6 · The paper itself

Abstract

aimHyponatremia is a common yet potentially serious adverse event associated with antidepressants. Identifying the antidepressant class with the least risk of hyponatremia would improve patient safety.

methodsUsing electronic medical records from 15 hospitals standardized into Observational Medical Outcomes Partnership Common Data Model (2003-2023), we identified patients diagnosed with depression who initiated antidepressants, including selective serotonin reuptake inhibitor (SSRI), serotonin-norepinephrine reuptake inhibitor (SNRI), tricyclic antidepressants (TCA) or others (agomelatine, bupropion, mirtazapine, moclobemide and trazodone) for at least 30 days. The index date was defined as the first antidepressant prescription, and four mutually exclusive cohorts were constructed based on the antidepressant class prescribed on index date. Each cohort was compared with all other antidepressants. The primary outcome was incident hyponatremia (serum sodium <135 mmol/L) within the first 180 days. After propensity score stratification, hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using Cox proportional hazards regression. Fixed-effect meta-analysis was used to pool the results from each site.

resultsWe identified 17 895 (42.6%) patients in SSRI, 7395 (17.6%) in SNRI, 5424 (12.9%) in TCA and 11 322 (26.9%) in other group. The risk of hyponatremia increased within 180 days after SSRI initiation (HR 1.18, 95% CI 1.01-1.38) compared with all other depressants, with a higher risk in patients aged ≥60 years (1.29, 1.06-1.57). No significant association was found for SNRIs (1.05, 0.87-1.27), TCAs (1.03, 0.84-1.26) or other (0.90, 0.77-1.06).

conclusionClose monitoring of serum sodium levels is essential for SSRI users, especially those aged ≥60 years.

Indexed as

Antidepressive AgentsDepressionHyponatremiaAdultAgedCohort StudiesElectronic Health RecordsFemaleHumansMaleMiddle AgedRisk FactorsAntidepressive Agentsantidepressantcommon data modelhyponatremiaSNRISSRITCA

Identifiers

PMID41531184
PMCPMC13206258

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.