The effect of multimorbidity on changes in health-related quality of life following hip and knee arthroplasty
Bibliographic record
Abstract
Aims: The aim of this study was to assess the effect of multimorbidity on improvements in health-related quality of life (HRQoL) following total hip arthroplasty (THA) and total knee arthroplasty (TKA). Patients and Methods: Using data from a regional joint registry for 14 573 patients, HRQoL was measured prior and one year following surgery using the Oxford Hip Score (OHS) and Oxford Knee Score (OKS), and the 12-Item Short-Form Health Survey Physical and Mental Component Summary scores (PCS and MCS, respectively). Multimorbidity was defined as the concurrence of two or more self-reported chronic conditions. A linear mixed-effects model was used to test the effects of multimorbidity and the number of chronic conditions on improvements in HRQoL. Results: Almost two-thirds of patients had multimorbidity, which adversely effected improvements in HRQoL. For THA, mean improvements in HRQoL scores were reduced by 2.21 points in OHS, 1.62 in PCS, and 4.14 in MCS; for TKA, the mean improvements were reduced by 1.71 points in OKS, 1.92 in PCS, and 3.55 in MCS (all p < 0.0001). An increase in the number of chronic conditions was associated with increasing reductions in HRQoL improvements. Conclusion: Multimorbidity adversely effects improvements in HRQoL following THA and TKA. Our findings are relevant to healthcare providers focused on the management of patients with chronic conditions and for administrators reporting and monitoring the outcomes of THA and TKA. Cite this article: Bone Joint J 2018;100-B:1168-74.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".