Impact of frailty on perioperative outcomes following percutaneous nephrolithotomy in older persons: evidence from the US Nationwide Inpatient Sample

Patient selection

The patient selection process is depicted in Fig. 1. A total of 31,598 patients ≥ 60 years old and received PCNL were identified in the 2010 to 2020 NIS database. Patients with missing information on sex, study outcomes, and sample weight (n = 769) were excluded. Finally, 30,829 patients were included in the study (representing 151,763 hospitalized patients in the US after weighting) (Fig. 1).

Fig. 1figure 1

Flow diagram of patient selection

Patient characteristics

Patient information including demographic information, comorbidities, outcomes, and hospital characteristics are shown in Table 1. The mean age of the patients was 72.5 years, 54.9% were males, and 78.3% were white. Compared with patients with low and intermediate risk of frailty, those at high risk were older, and had the highest proportion of males, major comorbidities, and higher CCI. Additionally, patients at high risk of frailty had the greatest proportion of insurance coverage by Medicare or Medicaid, were admitted emergently, admitted in urban-teaching hospitals, and in the Western US.

Table 1 Characteristics of the study population

Compared to the low and intermediate frailty risk groups, the high frailty risk group had a significantly higher percentage of in-hospital mortality (4.8% vs. 0.3–2.1%, p < 0.001), unfavorable discharge (35.5% vs. 5.4–16.6%, p < 0.001), prolonged LOS (34.9% vs. 3.4–15.7%, p < 0.001), transfusion (24.8% vs. 2.3–12.5%, p < 0.001), and overall complications (85.9% vs. 22.6–60.8%, p < 0.001). In addition, the high frailty risk group had significantly higher total hospital costs (100,500 USD vs. 52,900 to 70,200 USD, p < 0.001) than the other groups (Table 1).

Associations between in-hospital outcomes and HFRS-defined frailty

The associations between outcomes and HFRS-defined frailty are summarized in Tables 2 and 3, and Fig. 2. After adjustment in the multivariable analysis, we found that the intermediate and high frailty risk groups had a significantly increased risk for in-hospital mortality (adjusted odds ratio [aOR] = 5.52, 95% confidence interval [CI]: 3.14–9.70, p < 0.001; aOR = 10.70, 95% CI: 6.38–18.62, p < 0.001, respectively), unfavorable discharge (aOR = 2.45, 95% CI: 2.13–2.82, p < 0.001; aOR = 5.09, 95% CI: 4.43–5.86, p < 0.001, respectively), prolonged LOS (aOR = 3.33, 95% CI: 2.77–3.99, p < 0.001; aOR = 7.67, 95% CI: 6.38–9.22, p < 0.001, respectively), and transfusion (aOR = 4.04, 95% CI: 3.29–4.95, p < 0.001; aOR = 8.05, 95% CI: 6.55–9.90, p < 0.001, respectively) compared to the low risk group (Table 2).

Table 2 Associations between in-hospital mortality, unfavorable discharge, prolonged LOS, and transfusion and HFRSTable 3 Associations between total hospital costs and HFRSFig. 2figure 2

Associations between complications and HFRS. Abbreviations CCI, Charlson comorbidity index; HFRS, hospital frailty risk score; aOR, adjusted odds ratio; CI, confidence interval. p-values < 0.05 are shown in bold. a Adjusted for variables that were significant (p < 0.05) in the univariate analysis (except for CCI), including age (continuous), sex, race, insurance status / primary payer, admission type, coronary artery disease, congestive heart failure, diabetes, cerebrovascular disease, chronic pulmonary disease, chronic kidney disease, severe liver disease, any malignancy, location/teaching status, and hospital region. b Adjusted for variables that were significant (p < 0.05) in the univariate analysis (except for CCI), including age (continuous), sex, race, insurance status / primary payer, admission type, coronary artery disease, congestive heart failure, diabetes, cerebrovascular disease, chronic pulmonary disease, chronic kidney disease, severe liver disease, rheumatic disease, any malignancy, location/teaching status, and hospital region. c Adjusted for variables that were significant (p < 0.05) in the univariate analysis (except for CCI), including age (continuous), sex, race, insurance status / primary payer, admission type, coronary artery disease, congestive heart failure, cerebrovascular disease, chronic pulmonary disease, chronic kidney disease, rheumatic disease, severe liver disease, any malignancy, location/teaching status, and hospital region

In addition, compared with the low risk group, the intermediate and high frailty risk groups had significantly greater total hospital costs (aBeta = 12.34, 95%CI: 11.18–13.50, p < 0.001; aBeta = 37.61, 95%CI: 36.39–38.83, p < 0.001, respectively) (Table 3).

Furthermore, the intermediate and high frailty risk groups had a significantly higher risk of any complication (aOR = 3.27, 95% CI: 2.98–3.60, p < 0.001; aOR = 8.52, 95% CI: 7.69–9.45, p < 0.001, respectively). For specific complications, the intermediate and high frailty risk groups had a significantly greater risk for sepsis (aOR = 14.48, 95% CI: 11.34–18.49, p < 0.001; aOR = 57.89, 95% CI: 45.32–73.94, p < 0.001, respectively), infection (aOR = 7.14, 95% CI: 6.11–8.33, p < 0.001; aOR = 23.36, 95% CI: 19.98–27.31, p < 0.001, respectively), and AKI (aOR = 5.12, 95% CI: 4.50–5.82, p < 0.001; aOR = 11.53, 95% CI: 10.16–13.10, p < 0.001, respectively) than the low risk group (Fig. 2).

ROC curves of HFRS for the prediction of in-hospital mortality

Figure 3 depicts the performance of the HFRS for predicting in-hospital mortality. Model 1: age (continuous); Model 2: a combination of significant variables (p < 0.05) in the univariate analysis (except for CCI); and Model 3: a combination of significant variables in the univariate analysis (except for CCI) plus HFRS. The results showed that Model 3, that included the HFRS, had superior performance (AUC = 0.756, 95% CI: 0.743–0.769) over that of Model 1 (AUC = 0.593, 95% CI: 0.574–0.612) and Model 2 (AUC = 0.730, 95% CI: 0.716–0.744) (Fig. 3).

Fig. 3figure 3

ROC curves of HFRS in the prediction of in-hospital mortality a, b, cAbbreviations CCI, Charlson comorbidity index; HFRS, hospital frailty risk score; ROC, receiver operating characteristic. a Model 1: Age (continuous). b Model 2: Significant variables (p < 0.05) in the univariate analysis (except for CCI), including age (continuous), race, insurance status / primary payer, admission type, coronary artery disease, congestive heart failure, diabetes, cerebrovascular disease, chronic pulmonary disease, chronic kidney disease, severe liver disease, any malignancy, location/teaching status, and hospital region. c Model 3: Significant variables in the univariate analysis plus HFRS

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