Evidence map›Paper›PMID 40538423›Full record

ArticleGeriatric orthopaedic surgery & rehabilitation2025

Risk Factors for Readmission Following Elderly Low Energy Pelvis Fractures.

Sean Thomas, Avinaash Korrapati, Brendan O'Leary, Cooper Haaland, Alexandra K Schwartz, William T Kent

Abstract read
In one paragraph

Article in Geriatric orthopaedic surgery & rehabilitation, 2025. 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

6 authors.

Sean ThomasUniversity of California San Diego School of Medicine, La Jolla, CA, USA.
Avinaash KorrapatiDepartment of Orthopaedic Surgery, University of California San Diego, CA, USA.
Brendan O'LearyDepartment of Orthopaedic Surgery, University of California San Diego, CA, USA.
Cooper HaalandUniversity of California San Diego School of Medicine, La Jolla, CA, USA.
Alexandra K SchwartzDepartment of Orthopaedic Surgery, University of California San Diego, CA, USA.
William T KentDepartment of Orthopaedic Surgery, University of California San Diego, CA, USA.ORCID https://orcid.org/0000-0002-7065-9551

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Fragility fractures of the pelvis (FFP) are associated with loss of mobility and significant mortality in elderly patients. The purpose of this study was to assess the 60-day readmission rates following FFP and to identify what factors may predict readmission. Methods: Six hundred thirty-one patients over 65 years of age presenting for FFP to a level 1 trauma center between 2010 and 2022 were reviewed. The chi-square test of independence and logistic regression were performed to identify factors associated with readmission. Results: One hundred and thirty-six patients met inclusion criteria. Of these, 31 (23%) returned to the Emergency Department (ED) within 60 days of discharge and 16 (12%) were readmitted. Chronic obstructive pulmonary disease (COPD) (OR = 3.30, Conclusion: Return to the ED and readmission following FFP is common, with an incidence of 23% and 12% in our cohort. Patients who were not admitted as an inpatient after their initial presentation, and patients who were discharged home instead of to a SNF, both had a higher risk of repeat presentation within 60 days of discharge. Additionally, ambulation by patients in the ED may provide false reassurance, as these patients were less likely to be admitted as an inpatient, but more likely to subsequently return within 60 days.

Indexed as

discharge dispositionfragility fracturesosteoporosispelvic fracturereadmission

Identifiers

PMID40538423
PMCPMC12177243

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Registered trials

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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.