ArticleResuscitation2024
Accuracy of frailty instruments in predicting outcomes following perioperative cardiac arrest.
Article in Resuscitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Prediction of Cardiopulmonary Resuscitation Outcomes for Arrest in Surgical Settings.JAMA network open · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundFrailty is associated with increased 30-day mortality and non-home discharge following perioperative cardiac arrest. We estimated the predictive accuracy of frailty when added to baseline risk prediction models.
methodsIn this retrospective cohort study using 2015-2020 NSQIP data for 3048 patients aged 50+ undergoing non-cardiac surgery and resuscitation on post-operative day 0 (i.e., intraoperatively or postoperatively on the day of surgery), baseline models including age, sex, ASA physical status, preoperative sepsis or septic shock, and emergent surgery were compared to models that added frailty indices, either RAI or mFI-5, to predict 30-day mortality and non-home discharge. Predictive accuracy was characterized by area under the receiver operating characteristic curve (AUC-ROC), integrated calibration index (ICI), and continuous net reclassification index (NRI).
results1786 patients (58.6%) died in the study cohort within 30 days, and 38.6% of eligible patients experienced non-home discharge. The baseline model showed good discrimination (AUC-ROC 0.77 for 30-day mortality and 0.74 for non-home discharge). AUC-ROC and ICI did not significantly change after adding frailty for 30-day mortality or non-home discharge. Adding RAI significantly improved NRI for 30-day mortality and non-home discharge; however, the magnitude was small and difficult to interpret, given other results including false positive and negative rates showing no difference in predictive accuracy.
conclusionsIncorporating frailty did not significantly improve predictive accuracy of models for 30-day mortality and non-home discharge following perioperative resuscitation. Thus, demonstrated associations between frailty and outcomes of perioperative resuscitation may not translate into improved predictive accuracy. When engaging patients in shared decision-making regarding do-not-resuscitate orders perioperatively, providers should acknowledge uncertainty in anticipating resuscitation outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.