Evidence map›Paper›PMID 40519386›Full record

ArticleCureus2025

Identification of Prognostic Factors Related to Morbidity, Mortality, and Increased Healthcare Expenditure Following Surgery for Femoral Fracture or Hip Arthroplasty.

Zachary A Blashinsky, Silas Helbig, Chrisnel Lamy, Noel C Barengo, Rupa Seetharamaiah, Juan Ruiz-Pelaez

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zachary A BlashinskyOrthopedic Surgery, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
Silas HelbigHealth Sciences, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
Chrisnel LamyEpidemiology and Biostatistics, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
Noel C BarengoMedicine, Riga Stradiņš University, Riga, LVA.
Rupa SeetharamaiahSurgery, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
Juan Ruiz-PelaezTranslational Medicine, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Postoperative outcomes following hip arthroplasty and femoral fracture surgeries significantly impact patient care and healthcare resources. This study aimed to identify modifiable and non-modifiable prognostic factors that independently predict major postoperative complications and increased hospital resource utilization in these patients. Methods We conducted a retrospective cohort study using the 2019 National Surgical Quality Improvement Program (NSQIP) database, including adult patients who underwent hip arthroplasty or femoral fracture treatment. Patients with incomplete data were excluded. The primary outcome was a composite of major adverse events, including mortality and 11 complications; the secondary outcome was healthcare resource utilization, assessed by length of stay and readmissions. We used stepwise backward multivariable logistic regression for analysis. Results Out of 176,801 cases, 12,146 (6.87%) experienced adverse outcomes. Significant predictors of adverse events included higher American Society of Anesthesiologists (ASA) classification, age ≥65 years, underweight body mass index (BMI), male sex, use of general anesthesia, and comorbidities such as COPD, insulin-dependent diabetes, ascites, congestive heart failure (CHF), hypertension, dialysis requirement, steroid use, bleeding disorders, and sepsis. Overweight and obese BMI were protective against adverse events. Increased resource utilization was associated with higher ASA classification, underweight BMI, use of general anesthesia, and comorbidities like insulin and non-insulin-dependent diabetes, COPD, CHF, hypertension, dialysis, steroid use, bleeding disorders, and SIRS. Again, overweight and obese BMIs were protective. The predictive model achieved a mean area under the curve (AUC) of 0.73 through 10-fold cross-validation. Conclusions Key predictors of adverse outcomes and increased hospital resource use include specific comorbidities and surgical factors, notably underweight BMI and higher ASA classification. Targeted interventions to optimize perioperative care for high-risk patients are necessary to minimize complications. These findings can guide clinical practice and surgical decision-making. Further research should explore these associations and refine preoperative risk stratification models.

Indexed as

femoral fracturelength of stayorthopedic surgerypostoperative complicationsstatistics and numerical datasurgical risk factorstotal hip arthroplastyvalue based care

Identifiers

PMID40519386
PMCPMC12162269

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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.