Quality of Life and Associated Socio-Clinical Factors after Encephalitis in Children and Adults in England: A Population-Based, Prospective Cohort Study
Bibliographic record
Abstract
OBJECTIVE: We sought to measure HRQoL in all-cause encephalitis survivors and assess the impact of various socio-clinical factors on outcome. METHODS: We used a prospective cohort study design, using the short-form 36 (SF-36) to measure the HRQoL in patients 15 years and older, and the short-form 10 (SF-10) for patients less than 15 years old. We posted questionnaires to individuals six months after discharge from hospital. All scores were normalised to the age- and sex-matched general population. We used multivariate statistical analysis to assess the relative association of clinical and socio-demographic variables on HRQoL in adults. RESULTS: Of 109 individuals followed-up, we received 61 SF-36 and twenty SF-10 questionnaires (response rate 74%). Patients scored consistently worse than the general population in all domains of the SF-36 and SF-10, although there was variation in individual scores. Infectious encephalitis was associated with the worst HRQoL in those aged 15 years and over, scoring on average 5.64 points less than immune-mediated encephalitis (95% CI -8.77- -2.89). In those aged less than 15 years the worst quality of life followed encephalitis of unknown cause. Immuno compromise, unemployment, and the 35-44 age group all had an independent negative association with HRQoL. A poor Glasgow Outcome Score was most strongly associated with a poor HRQoL. Less than half of those who had made a 'good' recovery on the score reported a HRQoL equivalent to the general population. CONCLUSIONS: Encephalitis has adverse effects on the majority of survivors' wellbeing and quality of life. Many of these adverse consequences could be minimised by prompt identification and treatment, and with better rehabilitation and support for survivors.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".