2.1

Data related to patients undergoing TAA from the National Readmissions Database (NRD), a component of the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases, for 2017, 2018, and 2019, was extracted. The NRD includes patient-level information regarding hospital stays across multiple states, representing 60 % of the U.S. population and 58.2 % of all U.S. hospitalizations. This database captures hospital admissions from various settings and includes comprehensive details such as patient demographics (age, gender, income quartile), diagnoses (ICD-10-CM codes), procedures (ICD-10-PCS codes), total hospital charges, and length of stay. Additionally, hospital-specific information such as teaching status, ownership type, bed size, and urban-rural designation is included.

2.2

Patients who underwent primary TAA for primary osteoarthritis (OA) between January and November of 2017, 2018, and 2019 were identified using ICD-10-PCS and ICD-10-CM codes ( Fig. 1 and Fig. 2 , respectively). Adult patients (greater than or equal to 18 years) with complete demographic and procedural data were included. Patients who died during their initial hospital stay were excluded from the analysis. The Hospital Frailty Risk Score (HFRS) was calculated for each patient using ICD-10-CM codes ( Fig. 3 ). An HFRS greater than or equal to five was used to classify patients as frail, based on previous literature linking higher HFRS scores to increased postoperative risks .

Specific ICD-10-PCS Codes for Primary Total Ankle Replacement.

Specific ICD-10-CM Codes for Diagnoses.

ICD-10-CM codes used to identify HFRS frailty risk score.

2.3

The primary healthcare utilization outcomes assessed in this study included 30-day readmission rates, length of hospital stay (LOS), and hospitalization costs following TAA. Readmissions were defined as any non-elective admission occurring within 30 days of the primary TAA. Hospital costs were estimated by multiplying the total hospital charges by the cost-to-charge ratio provided by HCUP, which reflects hospital expenditures such as wages, supplies, and utilities. All costs were adjusted to 2019 U.S. dollars using the Consumer Price Index.

Secondary clinical outcomes included complication rates and reoperation rates. Complications were grouped into operative (e.g., periprosthetic fracture, wound healing complications, periprosthetic joint infection), medical (e.g., acute coronary syndrome, pneumonia, acute renal failure), and other complications (e.g., pulmonary embolism, cerebrovascular accident, postoperative delirium) using ICD-10-CM codes ( Fig. 4 ). Reoperations were identified as subsequent procedures involving the ankle joint within 30 days, based on ICD-10-PCS codes ( Supplemental Figure 1 ).

ICD-10-CM Codes used to identify complications.

2.4

Categorical variables were compared between frail and non-frail groups using Pearson’s chi-squared test, and continuous variables were compared using independent t -tests. Multivariate logistic regression models were constructed to evaluate the association of frailty with 30-day readmission rates, while controlling for patient demographics (age, sex, income quartile), hospital characteristics (teaching status, urban-rural designation, bed size), and comorbidities. Negative binomial regression models were used to assess the relationship between frailty and LOS, as well as hospitalization costs, with incidence rate ratios (IRRs) and 95 % confidence intervals (CIs) calculated. Odds ratios (OR) with 95 % CIs were also calculated. A p value < 0.05 was considered statistically significant. All analyses were conducted using R version 4.03 (R Foundation for Statistical Computing, Vienna, Austria).

3.1

Patient demographics and hospitalization characteristics for OA patients undergoing TAA are listed in Table 1 . Overall, frail patients (N = 862) were statistically significantly older compared to non-frail patients (N = 5285), with 23.8 % of the frail cohort over age 74 compared to 17.9 % of non-frail patients ( p < 0.01). Frail patients were more likely to be covered by Medicare (69.1 % vs. 60.4 %, p < 0.01) and less likely to have private insurance (24.9 % vs. 32.2 %, p < 0.01). Frail individuals had a higher proportion discharged to a higher level of care (44.0 % vs. 26.0 %, p < 0.01) and longer median hospital stays (2.4 vs. 1.6 days, p < 0.01). Median costs were significantly greater for frail patients ($27,181 vs. $24,777, p < 0.01), while 30-day readmission rates were comparable between the 2 cohorts (1.9 % vs. 1.5 %, p = 0.37).

3.2

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