Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study
(1) Background: “Kidney Disease: Improving Global Outcomes” (KDIGO) provides guidelines for identifying the stages of acute kidney injury (AKI) and chronic kidney disease (CKD). A data-driven rule-based engine was developed to determine KDIGO staging compared to KD-related keywords in discharge lett...
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MDPI AG
2024-11-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/14/22/2476 |
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| author | Olga Endrich Christos T. Nakas Karen Triep Georg M. Fiedler Jaime J. Caro Alistair McGuire |
| author_facet | Olga Endrich Christos T. Nakas Karen Triep Georg M. Fiedler Jaime J. Caro Alistair McGuire |
| author_sort | Olga Endrich |
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| description | (1) Background: “Kidney Disease: Improving Global Outcomes” (KDIGO) provides guidelines for identifying the stages of acute kidney injury (AKI) and chronic kidney disease (CKD). A data-driven rule-based engine was developed to determine KDIGO staging compared to KD-related keywords in discharge letters. (2) Methods: To assess potential differences in outcomes, we compare the patient subgroups with exact KDIGO staging to imprecise or missing staging for all-cause mortality, in-hospital mortality, selection bias and costs by applying Kaplan–Meier analysis and the Cox proportional hazards regression model. We analysed 63,105 in-patient cases from 2016 to 2023 at a tertiary hospital with AKI, CKD and acute-on-chronic KD. (3) Results: Imprecise and missing CKD staging were associated with an 85% higher risk of all-cause and in-hospital mortality (CI: 1.7 to 2.0 and 1.66 to 2.03, respectively) compared to exact staging for any given disease status; imprecise or missing AKI staging increased in-hospital mortality risk by 56% and 57% (CI: 1.43 to 1.70 and 1.37 to 1.81, respectively) in patients with AKI. (4) Conclusions: Exact staging is associated with better outcomes in KD management. Our study provides valuable insight into potential quality and outcome improvements and lower costs, considering elderly patients, women and patients with acute-on-chronic KD as the most vulnerable. |
| format | Article |
| id | doaj-art-baf3352248c7450e8d2288373bf7e3a3 |
| institution | Kabale University |
| issn | 2075-4418 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj-art-baf3352248c7450e8d2288373bf7e3a32024-11-26T17:59:29ZengMDPI AGDiagnostics2075-44182024-11-011422247610.3390/diagnostics14222476Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational StudyOlga Endrich0Christos T. Nakas1Karen Triep2Georg M. Fiedler3Jaime J. Caro4Alistair McGuire5Medical Directorate, Inselspital, Bern University Hospital, 3010 Bern, SwitzerlandUniversity Institute of Clinical Chemistry, University of Bern, Inselspital, Bern University Hospital, 3010 Bern, SwitzerlandMedical Directorate, Inselspital, Bern University Hospital, 3010 Bern, SwitzerlandUniversity Institute of Clinical Chemistry, University of Bern, Inselspital, Bern University Hospital, 3010 Bern, SwitzerlandDepartment of Health Policy, London School of Economics, London WC2A 2AE, UKDepartment of Health Policy, London School of Economics, London WC2A 2AE, UK(1) Background: “Kidney Disease: Improving Global Outcomes” (KDIGO) provides guidelines for identifying the stages of acute kidney injury (AKI) and chronic kidney disease (CKD). A data-driven rule-based engine was developed to determine KDIGO staging compared to KD-related keywords in discharge letters. (2) Methods: To assess potential differences in outcomes, we compare the patient subgroups with exact KDIGO staging to imprecise or missing staging for all-cause mortality, in-hospital mortality, selection bias and costs by applying Kaplan–Meier analysis and the Cox proportional hazards regression model. We analysed 63,105 in-patient cases from 2016 to 2023 at a tertiary hospital with AKI, CKD and acute-on-chronic KD. (3) Results: Imprecise and missing CKD staging were associated with an 85% higher risk of all-cause and in-hospital mortality (CI: 1.7 to 2.0 and 1.66 to 2.03, respectively) compared to exact staging for any given disease status; imprecise or missing AKI staging increased in-hospital mortality risk by 56% and 57% (CI: 1.43 to 1.70 and 1.37 to 1.81, respectively) in patients with AKI. (4) Conclusions: Exact staging is associated with better outcomes in KD management. Our study provides valuable insight into potential quality and outcome improvements and lower costs, considering elderly patients, women and patients with acute-on-chronic KD as the most vulnerable.https://www.mdpi.com/2075-4418/14/22/2476data-driven diagnosiselectronic health recordsdigital markersrule engineprecision medicinereal-world data |
| spellingShingle | Olga Endrich Christos T. Nakas Karen Triep Georg M. Fiedler Jaime J. Caro Alistair McGuire Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study Diagnostics data-driven diagnosis electronic health records digital markers rule engine precision medicine real-world data |
| title | Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study |
| title_full | Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study |
| title_fullStr | Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study |
| title_full_unstemmed | Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study |
| title_short | Impact of Precision in Staging Acute Kidney Injury and Chronic Kidney Disease on Treatment Outcomes: An Observational Study |
| title_sort | impact of precision in staging acute kidney injury and chronic kidney disease on treatment outcomes an observational study |
| topic | data-driven diagnosis electronic health records digital markers rule engine precision medicine real-world data |
| url | https://www.mdpi.com/2075-4418/14/22/2476 |
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