Postoperative Quality of Life in Patients with Pyogenic Spondylodiscitis
Bibliographic record
Abstract
Abstract Background Pyogenic spondylodiskitis affects a fragile patient population frequently fraught with severe comorbidities. Data on long-term outcomes, especially for patients undergoing surgery, are scarce. The aim of this study was to assess the long-term quality of life after surgical instrumentation. Methods Data of 218 patients who were treated for spondylodiskitis at our institution between January 2008 and July 2017 were reviewed. In-hospital death and mortality rates at 1 year and follow-up were assessed. A survey was conducted using the following questionnaires: Oswestry Disability Index (ODI), Short Form Work Ability Index (SF-WAI), 36-Item Short Form Health Survey (SF-36), and Short Form McGill Pain Questionnaire (SF-MPQ). We investigated the correlation between the assessed variables and clinical data including patient age, comorbidity score at admission, number of operated levels, corpectomy, and length of hospital stay. Results In-hospital mortality rate was 1.8% and 1-year mortality rate was 5.5%. At the final follow-up (mean 7 ± 6 years), the mortality rate was 45.4%. Seventy-four patients were lost to follow-up or refused to participate in the study. Forty-four patients responded to the survey and had a mean age of 73 years and mean follow-up of 7 ± 2 years. In the ODI questionnaire, disability grades were classified as minimal (23%), moderate (21%), severe (19%), complete (33%), and bed bound (4%). We found a significant correlation between inability to return to work and severe disability on ODI (p < 0.001), as well as a low score on any component of the SF-36 (p < 0.05). Conclusion Despite low in-hospital and 1-year mortality rates, patients with surgically treated pyogenic spondylodiskitis are prone to long-term limitation in all domains of quality of life, especially in physical health and work ability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".