Chapter 6 94 high-volume center for transvenous lead extractions (approximately 50 cases annually). 2.6. PADIT-score The PADIT score was developed to predict the risk of hospitalization for device infection within 1 year (14). A correction was published to the original risk score and this modified score was used (15). This model includes 5 independent predictors of CIED infection including number of Prior procedures, Age, Depressed renal function (estimated glomerular filtration rate [GFR] < 30 mL/min), being Immunocompromised, and procedure Type. Immunocompromised was defined in the PADIT trial as receiving therapy that suppresses resistance to infection (e.g., immunosuppression, chemotherapy, radiation, long-term, or recent high-dose steroids) or having a disease that is sufficiently advanced to suppress resistance to infection (e.g., leukemia, lymphoma, HIV infection). The minimum risk score is 0 and the maximum is 13 (Supplemental Table 1). The PADIT score was calculated using the online calculator (https://padit-calculator.ca) which used the corrected version of the PADIT score. Based on the PADIT score, 3 risk categories could be identified according to the original publication: low risk (≤ 4), intermediate risk (5,6), and high risk (≥ 7) (14). 2.7. Study endpoint The primary endpoint was a CIED infection requiring hospitalization within 1 year of the procedure. This definition was also used in the original PADIT trial (2). The diagnosis of CIED or pocket infection followed the 2019 International CIED Infection criteria (16). 2.8. Statistical analysis Continuous parameters were tested for normality before analysis and are expressed as mean ± standard deviation (SD) or median (interquartile range [IQR]), as appropriate. Categorical data are presented as frequencies and percentages. Comparisons between groups were performed with an independent Student t-test, chi-square test, Fisher exact test, or a Mann–Whitney U test, as appropriate. We used the receiver operating characteristic (ROC) curve to evaluate the performance of the PADIT score to predict the 1-year risk of device infection. Discrimination was assessed by using the Harrell’s C-statistic. Model discrimination was deemed poor if
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