Evidence map›Paper›PMID 42583107›Full record

ArticleJournal of thoracic disease2026

Safety signals for drug-related respiratory depression: a disproportionality analysis of the FDA Adverse Event Reporting System (FAERS).

Yang Rui, Zhe Chen, Jun Zhou

Abstract read
In one paragraph

Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yang Rui *Laboratory of Cough, Affiliated Kunshan Hospital of Jiangsu University, Kunshan Key Laboratory of Chronic Cough, Suzhou, China.
Zhe Chen *Laboratory of Cough, Affiliated Kunshan Hospital of Jiangsu University, Kunshan Key Laboratory of Chronic Cough, Suzhou, China.ORCID https://orcid.org/0000-0003-2611-9635
Jun ZhouDepartment of Pharmacy, Affiliated Kunshan Hospital of Jiangsu University, Suzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Drug-induced respiratory depression is a severe and potentially life-threatening adverse event (AE); however, its systematic risk profile based on real-world data remains incomplete. Using real-world data from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS), this study systematically identified drugs associated with respiratory depression and generated reporting safety signals to provide exploratory evidence for optimizing clinical medication safety. Methods: The reporting odds ratio (ROR) was used to evaluate reports of drug-induced respiratory depression from the first quarter of 2015 to the third quarter of 2025. Single-factor, least absolute shrinkage and selection operator (LASSO), and multi-factor regression models were employed to analyze the association between various medications and respiratory depression events. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the associated risks. Results: A total of 869 drugs associated with respiratory depression were identified, with nervous system drugs being the predominant category. Multivariate analysis identified 16 of 17 LASSO-screened drugs and male patients under 41 years of age as significant safety signals for respiratory depression, exhibiting strong disproportionate reporting signals. The median duration of drug-related respiratory depression was 1 day [interquartile range (IQR), 23 days], with approximately 75% of AEs occurring within this 23-day period. Conclusions: These findings assist clinicians in the early identification of the risk of drug-related respiratory depression, underscoring the necessity for proactive assessment and management of this risk in both analgesia and disease treatment.

Indexed as

acute respiratory distress syndrome (ARDS)adverse event (AE)FDA Adverse Event Reporting System (FAERS)Respiratory depression

Identifiers

PMID42583107
PMCPMC13459844

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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.