Predicting Day-Case Arthroplasty Outcomes

Which patient factors best predict success/failure of day-case arthroplasty?

Increased age, female sex (OR 1.63-4.22), high ASA classification, and multiple comorbidities (OR up to 3.9) are the primary predictors of day-case arthroplasty failure.

Abstract

Day‐case arthroplasty outcomes are influenced by clear patient factors. Studies report that increased age—which in over 20 analyses shows odds ratios from 1.01 to 4.16—and female sex—with odds ratios from 1.63 to 4.22 in more than 15 investigations—predict lower same‐day discharge success. A higher body mass index (supported in 10+ studies) and non‐white race (noted in 5+ studies) similarly relate to reduced success. Clinical indicators such as an ASA classification of III or IV and a comorbidity burden of three or more conditions consistently predict failure, with odds ratios up to 3.9 and highly significant p‐values. Other conditions, including hypertension, diabetes, cardiovascular disease, and chronic obstructive pulmonary disease, are also cited as contributing to poor day‐case outcomes. Although a couple of studies flag younger age (<40) as a potential risk factor, this finding remains inconsistent.

Methods

We analyzed 40 sources from an initial pool of 500, using 8 screening criteria. Each paper was reviewed for 6 key aspects that mattered most to the research question.

Paper search

Using your research question “Which patient factors best predict success/failure of day-case arthroplasty?”, we searched across over 126 million academic papers from the Semantic Scholar corpus. We retrieved the 500 papers most relevant to the query.

Screening

We screened in sources based on their abstracts that met these criteria:

• Study Setting: Outpatient/day-case/ambulatory arthroplasty procedures?
• Patient Population - Age: Adult patients (≥18 years)?
• Procedure Type: Primary (non-revision) hip, knee, shoulder, or ankle arthroplasty?
• Clinical Context: Planned elective procedures (not emergency or trauma-related cases)?
• Predictive Factors: Patient-related predictive factors (age, BMI, comorbidities, or social support)?
• Outcome Measures: Specific outcomes related to success/failure of day-case surgery (same-day discharge, unplanned overnight stays, or 30-day readmissions)?
• Study Design: Prospective/retrospective cohort study, case-control study, RCT, or systematic review with 10 or more patients?
• Study Focus: Patient-related factors (not exclusively focusing on surgical technique, anesthetic protocol, or hospital/surgeon factors)?

Data extraction

• Study Design: 30 retrospective studies, 4 prospective studies, 5 systematic reviews (including meta-analyses), 1 review.
• Patient Selection Criteria: List all explicit inclusion criteria (age range, type of arthroplasty, patient health status). Insufficient information noted if criteria are not fully detailed.
• Patient Demographic and Clinical Factors: Key patient characteristics that could predict day-case arthroplasty success, such as age, gender, BMI, and comorbidities.
• Reasons for Same-Day Discharge Failure: List all documented reasons for unsuccessful same-day discharge, ranked if provided.
• Predictive Factors for Same-Day Discharge Success: List statistically significant factors, record odds ratios, confidence intervals, and p-values.
• Surgical Procedure Details: Types of arthroplasty performed, surgical timing, anesthesia type, surgical duration.

Results

Characteristics of Included Studies

Success Rates and Risk Patterns

Overall Success Rates

Common Failure Patterns

References

• James Murrell, N. Khadabadi, Thomas Moores, Fahad Hossain (2023)
• M. Keulen et al. (2020)
• David P Foley et al. (2023)