| Autor: |
Jasmin Das, Ashu mathai, Rahul sood |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH. :1-4 |
| DOI: |
10.36106/ijsr/4710082 |
| Popis: |
Acute kidney injury in hospitalized patients is associated with high mortality rates and increased length of hospital stay. Prognostication of patients with AKI is of immense value in making decisions regarding the optimal type and intensity of treatment, patient selection, and clinical discussions on prognosis and in assessment of the quality of an ICU. Prognostic scores are comprised of relevant clinical and laboratory variables of patients associated to the clinical endpoint. There are limited studies that have evaluated which prognostic score may be used in patients with AKI. Studies have shown that APACHE II underestimates hospital mortality whereas AKI specific Liano score has better statistical correlation with mortality. Materials and methods: All patients admitted to the ICU fulfilling the inclusion criteria during the study period were recruited and evaluated for AKI by both RIFLE and AKI criteria. Prognostic scores, APACHE II and Liano were used in predicting hospital mortality. Assessment of score performance was made through analysis of the discrimination and calibration using area under a receiver operating characteristic curve (AUROC) and Hosmer and Lemeshow goodness of fit test. Results: Mean APACHE II score was higher in AKI subjects compared to non AKI and was statistically significant and it increased with the severity of AKI. The AUROC for APACHE II score was 0.739 and 0.706 for AKIN and RIFLE respectively and signifies APACHE II score increases with AKI. An AUROC curve of prognostic scores for predicting mortality was 0.677 and 0.639 for Liano and APACHE II respectively and on comparison showed insignificant p value (0.6331). Assessment of calibration showed that the calibration was good for specific score. Conclusion:Assessment of performance of both the prognostic scores APACHE II and Liano had poor discrimination but calibration was good for Liano model |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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