Prevalence and Features of Misdiagnosis of Primary Psychiatric Disorders Among bvFTD Patients
Bibliographic record
Abstract
OBJECTIVE: Previous studies have reported misdiagnosis rates of nondegenerative primary psychiatric disorders of up to 50% among patients with behavioral variant frontotemporal dementia (bvFTD). The authors hypothesized that misdiagnosis rates have decreased over time because of an increased awareness and a better understanding of psychiatric prodromes of FTD. METHODS: Retrospective data on past psychiatric trajectories of individuals with probable or definite bvFTD (N=609) were acquired from 12 sites of the Neuropsychiatric International Consortium on FTD. Symptom profiles, primary psychiatric disorder diagnoses, and treatment information were collected from medical records. The authors used descriptive statistics to characterize past diagnostic trajectories, chi-square and t tests to compare groups, and logistic regressions to determine risk factors for diagnostic errors. RESULTS: Of 609 bvFTD patients, 33% received a primary psychiatric disorder diagnosis after the onset of bvFTD symptoms but before a formal bvFTD diagnosis. In 13% (N=80) of all bvFTD cases, the diagnosis was retrospectively considered erroneous. The most common misdiagnosis was major depressive disorder, followed by anxiety disorders and psychosis. The remaining cases were classified as psychiatric prodromes (N=68) and comorbid conditions (N=42). Patients with misdiagnoses were significantly younger, by about 5.5 years, than those without such diagnoses and had higher rates of depressed mood, dietary changes, stereotypy, somatization, and anxiety symptoms. Only younger age predicted erroneous diagnoses. CONCLUSIONS: The rate of patients who were misdiagnosed as having primary psychiatric disorders was much lower than in previous reports, suggesting improvements in the quality of diagnostic assessments. Misdiagnoses were more common among younger patients, with some psychiatric symptoms being overrepresented in such cases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".