Diagnoses Received by Narcolepsy Patients in the Year Prior to Diagnosis by a Sleep Specialist
Bibliographic record
Abstract
STUDY OBJECTIVES: Narcolepsy is a neurological disorder whose clinical features include excessive daytime sleepiness, hypnagogic hallucinations, cataplexy, sleep paralysis, and disrupted nocturnal sleep. It has been shown that there may be quite a long interval between the onset of symptoms, and the correct diagnosis. We tested the hypothesis that given their severe symptomatology, these patients would have been diagnosed more often with a variety of psychiatric and neurologic conditions than controls in the year prior to confirmation of their narcolepsy diagnosis. DESIGN: Using the Province of Manitoba Health database, we compared the diagnoses made in the year prior to initial sleep disorder center evaluation of 77 patients with narcolepsy (33 males, 44 females) and 1,155 matched control subjects from the general population. SETTING: Sleep disorders center in University-based teaching hospital PARTICIPANTS: N/A. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Patients were much more likely than controls to be diagnosed with mental disorders (Odds ratio (OR) = 4.0645; 95% confidence limit (CL) = 2.4671-6.6962; p<0.0001) and nervous system disorders (OR= 5.0495; CL = 3.0606 -8.3309; p<0.0001) and there was a trend towards more injuries in these patients (OR =1.6316; CL = 0.9857-2.7007; p=0.0514). We found that cases were statistically much more likely than controls to have received a diagnosis for neurotic disorders (17% of cases), depression (16%), personality disorders (3%) and adjustment reaction (4%). Although the cases had twice as many doctor visits as the controls (9.3 +/- 0.97 (sem) vs. 4.8 +/- 0.17 p<0.0001), only 38% of them had received a diagnosis of narcolepsy in the year prior to sleep specialist evaluation. Neurologists had the highest "success rate" for correct diagnosis: neurologists diagnosed narcolepsy in 55% of the cases they had seen. The other medical practitioners diagnosed narcolepsy in a much smaller percentage of the cases they had seen: 23.5% for internists (excluding neurologists), 21.9% for general practitioners, 11.1% for psychiatrists, and 0% for pediatricians. CONCLUSIONS: In the year prior to documentation of narcolepsy in a sleep disorders center, patients with narcolepsy were diagnosed with a wide variety of mental and neurologic disorders. Our findings are supportive of either the coexistence of these disorders in narcolepsy patients or a high frequency of missed diagnosis by their clinicians. The latter may help explain the very long interval between onset of symptoms and correct diagnosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".