Evidence map›Paper›PMID 39711671›Full record

ArticleAnnals of surgery open : perspectives of surgical history, education, and clinical approaches2024

The Perioperative NonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) Risk Stratification Tool.

Laurence Weinberg, Dong Kyu Lee, Luke Fletcher, Bobby Ou Yang, Jadon Karp, Anoop N Koshy, Ranjan Guha, Hugh Slifirski, Michael R D'Silva, Rinaldo Bellomo and 1 more

Abstract read
In one paragraph

Article in Annals of surgery open : perspectives of surgical history, education, and clinical approaches, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Laurence WeinbergFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Dong Kyu LeeDepartment of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Republic of Korea.
Luke FletcherFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Bobby Ou YangFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Jadon KarpFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Anoop N KoshyDepartment of Cardiology, Austin Health, Heidelberg, Australia.
Ranjan GuhaFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Hugh SlifirskiFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Michael R D'SilvaFrom the Department of Anesthesia, Austin Health, Heidelberg, Australia.
Rinaldo BellomoDepartment of Critical Care, The University of Melbourne, Austin Health, Heidelberg, Australia.
Leonid ChurilovDepartment of Medicine, Royal Melbourne Hospital, Melbourne Brain Centre at Royal Melbourne Hospital, Melbourne Medical School, Faculty of Medicine, The University of Melbourne; Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop age-appropriate nonaGEnaRIan And cenTenarian suRgICal (GERIATRIC) risk tool for classifying patients who may or may not develop postoperative complications or die within their index hospital admission. Background: There are no validated perioperative risk stratification tools for use in nonagenarian and centenarian patients-people aged 90 to 99 years and >100 years. Methods: In this retrospective observational study, nonagenarians and centenarians undergoing any surgical procedure were profiled. Surgery severity was stratified, and the incidence and grade of postoperative complications were recorded. Multivariable logistic regression analysis was performed on a training cohort, followed by calibration on a validation cohort, followed by performance evaluation on a testing cohort. The discriminative accuracy was compared to that of the age-adjusted Charlson Comorbidity Index for each outcome. The primary outcome was the ability of the risk stratification tool to effectively classify patients into those who may or may not experience a postoperative complications or mortality within their index hospital stay. Results: A total of 3085 patients were enrolled. The GERIATRIC risk tool had good discriminative accuracy for any postoperative complication [area under the receiver operating characteristic curves (AUROC), 0.857; 95% CI = 0.824-0.890] and any severe postoperative complication (AUROC, 0.833; 95% CI = 0.793-0.874), and fair discriminative accuracy for in-hospital mortality (AUROC, 0.780; 95% CI = 0.668-0.893). Conclusions: Compared to the age-adjusted Charlson Comorbidity Index, The GERIATRIC risk tool was accurate in classifying patients into those who may or may not experience severe complications or die during their index admission. The tool can be used to assist perioperative clinicians with shared decision-making and short-term prognostication.

Indexed as

anesthesiacentenariannonagenarianrisksurgery

Identifiers

PMID39711671
PMCPMC11661723

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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.