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Record W4212790581 · doi:10.1093/jcag/gwab049.150

A151 RISK FACTORS FOR VENOUS THROMBOEMBOLISM AFTER HOSPITAL DISCHARGE IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE: A SYSTEMATIC REVIEW AND META-ANALYSIS

2022· review· en· W4212790581 on OpenAlexaff
M Gozdzik, Dana Unninayar, D. R. Sarker, Kevin Chin Koon Siw, Jeffrey D. McCurdy

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typereview
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineMeta-analysisObservational studyOdds ratioConfidence intervalInternal medicinePopulationInflammatory bowel diseaseAbsolute risk reductionHazard ratioSystematic reviewMEDLINERisk factorDiseasePediatricsEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background Inflammatory bowel disease (IBD) is a chronic inflammatory condition which is independently associated with venous thromboembolism (VTE). Although the absolute risk of VTE is greatest during hospitalization, the risk remains elevated in the early post-discharge period. The risk factors for VTE during this vulnerable period remain unknown. Aims We performed a systematic review and meta-analysis to determine risk factors for VTE in the post discharge period among adult patients with IBD. Methods We performed a systematic search of Embase, MEDLINE, and the Cochrane Central Register of Controlled Trials from inception through April 29, 2021 for publications that reported risk factors for VTE during the post-discharge period among patients with IBD. Study eligibility was assessed independently in duplicate without age or language restriction. We defined the post-discharge period as within 6 months of discharge. Pooled summary estimates of adjusted hazard/odds ratios, when available, were calculated for individual risk factors using random effects model with 95% confidence intervals. The analysis was performed when a minimum of three studies were available for a given risk factor. Heterogeneity was assessed using I2 statistic. Study quality was assessed using an adapted version of the National Institute of Health criteria. Results We identified 10 studies from a total of 4339 abstracts that met our inclusion criteria: 8 population-based studies, 1 multicenter observational study and 1 single center observational study. Risk factors for post-discharge VTE were assessed at 6 weeks in 1 study, 1 month in 5 studies, 3 months in 2 studies, and 6 months in 2 studies. The variables assessed in our meta-analysis are reported in Table 1. Exposure to corticosteroid (odds ratio [OR], 1.77; 95% CI, 1.53–2.06) but not biologics (OR, 1.21; 95% CI 0.80–1.82) was associated with an increased risk of VTE. Furthermore, greater length of stay (OR 1.49; 95% CI, 1.01–2.20), ulcerative colitis (OR 1.41; 95% CI, 1.19–1.66), history of malignancy (OR 1.35; 95% CI, 1.12–1.62), and surgery during admission (OR 1.26; 95% CI, 1.12–1.42) but not female sex (OR 0.98; 95% CI, 0.88–1.10) or surgery type (OR 1.09; 95% CI, 0.75–1.57) were associated with increased risk of VTE after discharge. Overall, the study quality was rated as fair. Conclusions In our meta-analysis, which consisted of moderate quality of evidence, we identified multiple risk factors associated with VTE in the post-discharge period. This work will help inform which factors should be considered for developing point of care clinical predictive models to help guide when extended VTE prophylaxis is required. Funding Agencies None

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)0.010
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: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.029
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0190.040
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0040.002
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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