Evidence map›Paper›PMID 37930697›Full record

ArticleJAMA network open2023

Automated Electronic Frailty Index-Identified Frailty Status and Associated Postsurgical Adverse Events.

Ashish K Khanna, Vida Motamedi, Bethany Bouldin, Timothy Harwood, Nicholas M Pajewski, Amit K Saha, Scott Segal

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Review
  5. Article
  6. Neural embedding of frailty in cognitively unimpaired aging and dementia across Latin America.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. External validation of an AI-based preoperative frailty index using real-world data.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors.

Ashish K KhannaDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Vida MotamediDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Bethany BouldinDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Timothy HarwoodDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Nicholas M PajewskiDepartment of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Amit K SahaDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.
Scott SegalDepartment of Anesthesiology, Wake Forest University School of Medicine, Winston-Salem, North Carolina.

Funding

Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
NCATS NIH HHS UL1 TR001420
6 · The paper itself

Abstract

Importance: Electronic frailty index (eFI) is an automated electronic health record (EHR)-based tool that uses a combination of clinical encounters, diagnosis codes, laboratory workups, medications, and Medicare annual wellness visit data as markers of frailty status. The association of eFI with postanesthesia adverse outcomes has not been evaluated. Objective: To examine the association of frailty, calculated as eFI at the time of the surgical procedure and categorized as fit, prefrail, or frail, with adverse events after elective noncardiac surgery. Design, Setting, and Participants: This cohort study was conducted at a tertiary care academic medical center in Winston-Salem, North Carolina. The cohort included patients 55 years or older who underwent noncardiac surgery of at least 1 hour in duration between October 1, 2017, and June 30, 2021. Exposure: Frailty calculated by the eFI tool. Preoperative eFI scores were calculated based on available data 1 day prior to the procedure and categorized as fit (eFI score: ≤0.10), prefrail (eFI score: >0.10 to ≤0.21), or frail (eFI score: >0.21). Main Outcomes and Measures: The primary outcome was a composite of the following 8 adverse component events: 90-item Patient Safety Indicators (PSI 90) score, hospital-acquired conditions, in-hospital mortality, 30-day mortality, 30-day readmission, 30-day emergency department visit after surgery, transfer to a skilled nursing facility after surgery, or unexpected intensive care unit admission after surgery. Secondary outcomes were each of the component events of the composite. Results: Of the 33 449 patients (median [IQR] age, 67 [61-74] years; 17 618 females [52.7%]) included, 11 563 (34.6%) were classified as fit, 15 928 (47.6%) as prefrail, and 5958 (17.8%) as frail. Using logistic regression models that were adjusted for age, sex, race and ethnicity, and comorbidity burden, patients with prefrail (odds ratio [OR], 1.24; 95% CI, 1.18-1.30; P < .001) and frail (OR, 1.71; 95% CI, 1.58-1.82; P < .001) statuses were more likely to experience postoperative adverse events compared with patients with a fit status. Subsequent adjustment for all other potential confounders or covariates did not alter this association. For every increase in eFI of 0.03 units, the odds of a composite of postoperative adverse events increased by 1.06 (95% CI, 1.03-1.13; P < .001). Conclusions and Relevance: This cohort study found that frailty, as measured by an automatically calculated index integrated within the EHR, was associated with increased risk of adverse events after noncardiac surgery. Deployment of eFI tools may support screening and possible risk modification, especially in patients who undergo high-risk surgery.

Indexed as

FrailtyAcademic Medical CentersAgedCohort StudiesElectronicsFemaleHumansMedicareUnited States

Identifiers

PMID37930697
PMCPMC10628731

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.