Changes in the Rate of Emergency Presentation in Patients with Functional Neurological Disorder Attending a Long-term Community Care Program for FND
Bibliographic record
Abstract
Introduction Patients with Functional Neurological Disorder have a high return rate to Emergency Rooms. Objectives To assess possible changes in Emergency Room presentation rates in patients with Functional Neurological Disorder following their attendance of specialized long-term multidisciplinary treatment and rehabilitation program. Methods Seventy-two adult patients with Functional Neurological Disorder were included. These patients were consecutive referrals accepted for ongoing specialist FND treatment. The total number of Emergency Room presentations in the year prior to program admission was obtained from central health records. Patients were provided ongoing treatment for one year, during which the number of ER presentations was monitored. Patients received one or more of the following treatment modalities: psychoeducation, psychological therapy, psychologically informed physical and occupational rehabilitation and psychopharmacological treatments. We subsequently compared high and low emergency service users. Low ER users are those with pre-treatment Emergency Room presentations of less than 3 per year. High emergency service users are those who presented to the emergency room 3 or more times per year before the start of their treatment. Results The mean emergency room presentation per year in the year leading to patients referral was 2.6 per patient, SD 9.4; dropped to 1.2 emergency room presentations per year, with a standard deviation of 4.4 in the year following the start of treatment. The difference was statistically significant (p= 0.02). There was a strong positive correlation between the pre and post-treatment number of presentations with a Pearson Correlation Coefficient of 0.976 (95% Confidence Interval 0.962 to 0.985). The reduction in emergency room presentations in both high and low-emergency service user groups was significant, with a mean difference of 12 ER visits a year in high-frequency emergency service users (p= 0.04) and a mean difference of 0.5 visits a year in low-frequency emergency service users (p < 0.001). Conclusions Ongoing specialist treatment and rehabilitation of patients with Functional Neurological Disorder significantly reduce their need for emergency room presentation, regardless of the treatment modality. Disclosure of Interest None Declared
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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 | 0.006 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".