ArticlePatient safety in surgery2022
Predictive Power of the "Trigger Tool" for the detection of adverse events in general surgery: a multicenter observational validation study.
Article in Patient safety in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 2 of them syntheses that pooled it.
What it found
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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.
The trial behind it
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Who cites it
2 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Predictive values of trigger tools for identifying adverse events in hospitalized patients using a medical record review: a systematic review.International journal for quality in health care : journal of the International Society for Quality in Health Care · 2025Pooled it
- Variation in detected adverse events using trigger tools: A systematic review and meta-analysis.PloS one · 2022Pooled it
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundIn spite of the global implementation of standardized surgical safety checklists and evidence-based practices, general surgery remains associated with a high residual risk of preventable perioperative complications and adverse events. This study was designed to validate the hypothesis that a new "Trigger Tool" represents a sensitive predictor of adverse events in general surgery.
methodsAn observational multicenter validation study was performed among 31 hospitals in Spain. The previously described "Trigger Tool" based on 40 specific triggers was applied to validate the predictive power of predicting adverse events in the perioperative care of surgical patients. A prediction model was used by means of a binary logistic regression analysis.
resultsThe prevalence of adverse events among a total of 1,132 surgical cases included in this study was 31.53%. The "Trigger Tool" had a sensitivity and specificity of 86.27% and 79.55% respectively for predicting these adverse events. A total of 12 selected triggers of overall 40 triggers were identified for optimizing the predictive power of the "Trigger Tool".
conclusionsThe "Trigger Tool" has a high predictive capacity for predicting adverse events in surgical procedures. We recommend a revision of the original 40 triggers to 12 selected triggers to optimize the predictive power of this tool, which will have to be validated in future studies.
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