Development of Risk Score Model for Hospital-acquired Acute Kidney Injury in a Tertiary Care Hospital in Thailand
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Abstract
Hospital-acquired acute kidney injury (HA-AKI) is a common complication in hospitalized patients and is characterized as rapidly decrease in kidney function after hospitalization over 24 hours. The consequence effect of HA-AKI might be serious complications, health-care service utilizations, longer length of stay, morbidity or mortality. Therefore, if AKI could be detected earlier, the problem would be prevented or solved, and the severity would be reduced. The aim of the study was to develop a risk score model for assessing HA-AKI. Methods: This retrospective cohort study was done using data from computerized hospital database belonged to inpatients with HA-AKI (322 patients) and without AKI (12,056 patients) at UdonThani Hospital during 1 April 2016 - 30 September 2016. A risk score model for HA-AKI was developed from statistically significant risk factors composed of 11 chronic medical conditions (elderly, chronic kidney disease, chronic lung disease, chronic liver disease, congestive heart failure, diabetes mellitus, hypertension, ASCVD, morbid obesity, cancer and HIV infection) and 10 acute medical conditions (high risk operation, pH≤ 7.3, sepsis, mechanical ventilation, traumatic brain Injury, rhabdomyolysis, anemia, hyperglycemia, decreased albumin and nephrotoxin exposure) by multiple regression analysis and was further evaluated using all patients who met all criteria for risk score model. The optimum cut-off point and the model calibration were assessed by the area under the curve (AUC) of receiver operating characteristic (ROC) curve and confusion matrix method, respectively. Results: From the multiple regression analysis, 5 factors were included into multiple regression equation and presented as HA-AKI = -3.277 + [2.06(CHF)] + [1.811(ASCVD)] + [1.478(Blood pH≤7.3)] + [3.284(Sepsis)] + [1.79(Anemia)]. Risk score model was developed with totally 51 points. From ROC curve of the optimum cut-off point (17 scores), this model had best yield with AUC of ROC 0.92 (95% CI: 0.90-0.95), sensitivity 0.85 and specificity 0.93. Conclusion: This risk score model may be very useful for detecting HA-AKI in high risk patient who need closely monitoring.
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