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

doi:10.7759/cureus.84056

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

Cureus. 2025 May 13;17(5):e84056. doi: 10.7759/cureus.84056. eCollection 2025 May.

Authors

Zachary A Blashinsky¹, Silas Helbig², Chrisnel Lamy³, Noel C Barengo^{4

5

6}, Rupa Seetharamaiah^{7

8}, Juan Ruiz-Pelaez^{6

9}

Affiliations

¹ Orthopedic Surgery, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
² Health Sciences, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
³ Epidemiology and Biostatistics, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
⁴ Medicine, Riga Stradiņš University, Riga, LVA.
⁵ Global Health, Florida International University, Robert Stempel College of Public Health, Miami, USA.
⁶ Translational Medicine, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
⁷ Surgery, Florida International University, Herbert Wertheim College of Medicine, Miami, USA.
⁸ Surgery, Baptist Hospital, Miami, USA.
⁹ Medical Education, Kangaroo Foundation, Bogota, COL.

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.

Keywords: femoral fracture; orthopedic surgery; postoperative complications; statistics and numerical data; surgical risk factors; total hip arthroplasty; value based care; length of stay.