Aim of the study was the definition of a predictive model for the initial diagnosis of thrombotic microangiopathies (TMA). We retrospectively collected data on all adult patients admitted to the Gemelli Hospital from 2010 to 2014. ICD-9 codes from primary diagnoses were used for TMA diagnosis. Demographic and laboratory characteristics on admission of patients with TMA were then compared with a random sample of 500 patients with other diagnoses. The prediction model was externally validated in a cohort from another hospital. Overall, 23 of 187,183 patients admitted during the study period received a primary diagnosis of TMA. LDH (OR 1.26, 95% CI 1.05, 1.63) and platelets (OR 0.96, 95% CI 0.94, 0.98) were the only independent predictors of TMA. The AUROC of the final model including only LDH and platelets was 0.96 (95% CI 0.91, 1.00). The HosmerâLemeshow (HL) test (p = 0.54) suggested good calibration. Our model also confirmed good discriminatory power (AUROC 0.72 95% CI 0.60, 0.84) and calibration (HL test p = 0.52) in the validation sample. We present a simple prediction model for use in diagnosing TMA in hospitalized patients. The model performs well and can help clinicians to identify patients at high risk of TMA.
Ferraro, P. M., Lombardi, G., Naticchia, A., Sturniolo, A., Zuppi, C., De Stefano, V., Bonelli, P., Buonocore, R., Cervellin, G., Lippi, G., Gambaro, G., A STARD-compliant prediction model for diagnosing thrombotic microangiopathies, <<JN. JOURNAL OF NEPHROLOGY>>, 2018; 31 (3): 405-410. [doi:10.1007/s40620-018-0468-4] [http://hdl.handle.net/10807/112307]
A STARD-compliant prediction model for diagnosing thrombotic microangiopathies
Ferraro, Pietro Manuel
Primo
;Naticchia, Alessandro;Sturniolo, Antonio;Zuppi, Cecilia;de Stefano, Valerio;Gambaro, Giovanni
2018
Abstract
Aim of the study was the definition of a predictive model for the initial diagnosis of thrombotic microangiopathies (TMA). We retrospectively collected data on all adult patients admitted to the Gemelli Hospital from 2010 to 2014. ICD-9 codes from primary diagnoses were used for TMA diagnosis. Demographic and laboratory characteristics on admission of patients with TMA were then compared with a random sample of 500 patients with other diagnoses. The prediction model was externally validated in a cohort from another hospital. Overall, 23 of 187,183 patients admitted during the study period received a primary diagnosis of TMA. LDH (OR 1.26, 95% CI 1.05, 1.63) and platelets (OR 0.96, 95% CI 0.94, 0.98) were the only independent predictors of TMA. The AUROC of the final model including only LDH and platelets was 0.96 (95% CI 0.91, 1.00). The HosmerâLemeshow (HL) test (p = 0.54) suggested good calibration. Our model also confirmed good discriminatory power (AUROC 0.72 95% CI 0.60, 0.84) and calibration (HL test p = 0.52) in the validation sample. We present a simple prediction model for use in diagnosing TMA in hospitalized patients. The model performs well and can help clinicians to identify patients at high risk of TMA.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.