Long-term Outcomes of Intensive Inpatient Care for Severe, Resistant Obsessive-Compulsive Disorder: Résultats à long terme de soins intensifs à des patients hospitalisés pour un trouble obsessionnel-compulsif grave et résistant
Bibliographic record
Abstract
OBJECTIVE: A substantial proportion of severely ill patients with obsessive-compulsive disorder (OCD) do not respond to serotonin reuptake inhibitors (SRIs) and are unable to practice cognitive behavioral therapy (CBT) on an out-patient basis. We report the short-term (at discharge) and long-term (up to 2 years) outcome of a multimodal inpatient treatment program that included therapist-assisted intensive CBT with adjunctive pharmacotherapy for severely ill OCD patients who are often resistant to SRIs and are either unresponsive or unable to practice outpatient CBT. METHODS: A total of 420 patients, admitted between January 2012 and December 2017 were eligible for the analysis. They were evaluated using the Mini International Neuropsychiatric Interview, the Yale-Brown Obsessive Compulsive Scale (YBOCS), and the Clinical Global Impression (CGI) scale. All patients received 4 to 5 therapist-assisted CBT sessions per week along with standard pharmacotherapy. Naturalistic follow-up information at 3, 6, 12, and 24 months were recorded. RESULTS: = 1.64); 211/420 (50%) were responders (≥35% YBOCS reduction and CGI-I≤2) and an additional 86/420 (21%) were partial responders (25% to 35% YBOCS reduction and CGI-I≤3). Using latent class growth modeling of the follow-up data, 4 distinct classes were identified, which include "remitters" (14.5%), "responders" (36.5%), "minimal responders" (34.7%), and "nonresponders" (14.6%). Shorter duration of illness, better insight, and lesser contamination/washing symptoms predicted better response in both short- and long-term follow-up. CONCLUSION: Intensive, inpatient-based care for OCD may be an effective option for patients with severe OCD and should be considered routinely in those who do not respond with outpatient treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".