A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement: A cohort study of data from the National Joint Registry in England and Wales
| Autor: | Adrian Sayers, Michael R Whitehouse, J. Mark Wilkinson, Chris M Penfold, Andrew Judge, Ashley W Blom |
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| Rok vydání: | 2021 |
| Předmět: |
Male
Viral Diseases Distribution Curves Epidemiology Arthroplasty Replacement Hip medicine.medical_treatment Total hip replacement Knee replacement Comorbidity Logistic regression Cohort Studies Medical Conditions Endocrinology Risk Factors Medicine and Health Sciences Risk of mortality Hospital Mortality Registries Arthroplasty Replacement Knee Musculoskeletal System Multidisciplinary Middle Aged Infectious Diseases England Elective Surgical Procedures Nephrology Hemorrhagic Fever with Renal Syndrome Renal Cancer Physical Sciences Medicine Female Anatomy Research Article Statistical Distributions Cohort study medicine.medical_specialty Endocrine Disorders Science Surgical and Invasive Medical Procedures Pelvis Age and gender Musculoskeletal System Procedures Internal medicine Diabetes Mellitus medicine Humans Skeleton Aged Wales Joint Replacement Surgery Hip Hip Fractures business.industry Comorbidity score Biology and Life Sciences Probability Theory medicine.disease ROC Curve Medical Risk Factors Metabolic Disorders business Mathematics |
| Zdroj: | PLoS ONE, Vol 16, Iss 8, p e0255602 (2021) Penfold, C, Whitehouse, M R, Blom, A W, Judge, A, Wilkinson, J M & Sayers, A E 2021, ' A comparison of comorbidity measures for predicting mortality after elective hip and knee replacement : A cohort study of data from the National Joint Registry in England and Wales ', PLoS ONE, vol. 16, no. 8, e0255602 . https://doi.org/10.1371/journal.pone.0255602 PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | Background The risk of mortality following elective total hip (THR) and knee replacements (KR) may be influenced by patients’ pre-existing comorbidities. There are a variety of scores derived from individual comorbidities that can be used in an attempt to quantify this. The aims of this study were to a) identify which comorbidity score best predicts risk of mortality within 90 days or b) determine which comorbidity score best predicts risk of mortality at other relevant timepoints (30, 45, 120 and 365 days). Patients and methods We linked data from the National Joint Registry (NJR) on primary elective hip and knee replacements performed between 2011–2015 with pre-existing conditions recorded in the Hospital Episodes Statistics. We derived comorbidity scores (Charlson Comorbidity Index—CCI, Elixhauser, Hospital Frailty Risk Score—HFRS). We used binary logistic regression models of all-cause mortality within 90-days and within 30, 45, 120 and 365-days of the primary operation using, adjusted for age and gender. We compared the performance of these models in predicting all-cause mortality using the area under the Receiver-operator characteristics curve (AUROC) and the Index of Prediction Accuracy (IPA). Results We included 276,594 elective primary THRs and 338,287 elective primary KRs for any indication. Mortality within 90-days was 0.34% (N = 939) after THR and 0.26% (N = 865) after KR. The AUROC for the CCI and Elixhauser scores in models of mortality ranged from 0.78–0.81 after THR and KR, which slightly outperformed models with ASA grade (AUROC = 0.77–0.78). HFRS performed similarly to ASA grade (AUROC = 0.76–0.78). The inclusion of comorbidities prior to the primary operation offers no improvement beyond models with comorbidities at the time of the primary. The discriminative ability of all prediction models was best for mortality within 30 days and worst for mortality within 365 days. Conclusions Comorbidity scores add little improvement beyond simpler models with age, gender and ASA grade for predicting mortality within one year after elective hip or knee replacement. The additional patient-specific information required to construct comorbidity scores must be balanced against their prediction gain when considering their utility. |
| Databáze: | OpenAIRE |
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