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Record W4200470016 · doi:10.1080/07853890.2021.2017474

Use of serotonin reuptake inhibitor antidepressants and the risk of bleeding complications in patients on anticoagulant or antiplatelet agents: a systematic review and meta-analysis

2021· review· en· W4200470016 on OpenAlexaff
Surapon Nochaiwong, Chidchanok Ruengorn, Ratanaporn Awiphan, Chatree Chai‐Adisaksopha, Apichat Tantraworasin, Chabaphai Phosuya, Penkarn Kanjanarat, Wilaiwan Chongruksut, Manish M. Sood, Kednapa Thavorn

Bibliographic record

VenueAnnals of Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineMeta-analysisOdds ratioAntithromboticInternal medicineCochrane LibraryRandomized controlled trialGastrointestinal bleedingCohort study

Abstract

fetched live from OpenAlex

Background Serotonin reuptake inhibitor (SRI) antidepressants are implicated in increasing the risk of bleeding among users; however, the comparative increase in bleeding risk with concurrent antithrombotic therapy (anticoagulant or antiplatelet) remains unclear. As such, we performed a systematic review and meta-analysis of all available evidence to evaluate the effects of SRI and the risk of bleeding complications among patients receiving antithrombotic therapy.Methods We searched Medline, Embase, PubMed, PsycINFO, Cochrane Library, Web of Science, Scopus, CINAHL, and grey literature (Google Scholar and preprint reports) up to 26 November, 2020, with no language restrictions (updated on 31 July 2021). The primary outcome of interest was major bleeding. Secondary outcomes included intracranial haemorrhage, gastrointestinal bleeding, and any bleeding events. We used a random-effects model meta-analysis to estimate the odds ratios (ORs) and 95% confidence intervals (CIs).Results We did not identify any randomised studies but found 32 non-randomized studies (cohort or case–control) with 1,848,285 patients that fulfilled the study selection criteria and were included in the meta-analysis. Among individuals receiving anticoagulants (13 studies), SRI users experienced a statistically higher risk of major bleeding compared to non-SRI users: pooled OR was 1.39 (95% CI, 1.23–1.58; p < .001; moderate heterogeneity). Among individuals receiving antiplatelet therapy (2 studies), SRI users were associated with an increased risk of major bleeding: pooled OR was 1.45 (95% CI, 1.17–1.80; p = .001; low heterogeneity). For secondary outcomes, the use of SRI among individuals treated with antithrombotic therapy revealed a higher risk of gastrointestinal bleeding or any bleeding events, whereas only anticoagulant use was illustrated an increased risk of intracranial haemorrhage.Conclusions The use of SRI antidepressants among patients treated with antithrombotic therapy (either anticoagulant or antiplatelet) is associated with a higher risk of bleeding complications, suggesting that caution is warranted in co-prescription.PROSPERO Registration CRD42018083917KEY MESSAGESIn this meta-analysis of 32 non-randomized studies, SRI users were associated with the risk of bleeding complications compared to non-SRI users, with concurrent antithrombotic use (either anticoagulant or antiplatelet).The risk was consistently elevated across types of bleeding events (major bleeding, gastrointestinal bleeding, or any bleeding events), whereas only anticoagulant use was associated with intracranial haemorrhage.To promote the rational use of medicines, our findings suggest that the risk-benefit ratio must account for the clear efficacy of SRI against safety concerns in terms of bleeding risks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0200.037
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.338
GPT teacher head0.440
Teacher spread0.102 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations81
Published2021
Admission routes1
Has abstractyes

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