42. Heterogeneity of Neuropsychological Profiles in the Prodrome to Psychosis: An Examination of the Association Between Cognition and Clinical Outcomes in NAPLS-1
Bibliographic record
Abstract
Background: The vast majority of studies of neuropsychological (NP) functioning in Clinical High Risk (CHR) cohorts have examined group averages, possibly concealing a range of subgroups ranging from very impaired to high functioning. Our objective was to assess NP profiles and to explore associations with conversion to psychosis, functional and diagnostic outcome. Methods: Data were acquired from individuals (mean age 18.4, SD = 4.6) participating in the longitudinal North American Prodrome Longitudinal Study-I (NAPLS-I), a multi-site consortium following individuals at CHR for developing psychosis for up to 2½ years. By applying the Hierarchical Clustering Ward’s method including 8 different neuropsychological tests, we clustered data of 166 CHR individuals, 49 persons with a family history of psychosis without prodromal symptoms, and 109 healthy controls. We then tested whether cluster profiles with more severe NP impairments were associated with higher conversion rates, lower social and role functioning scores, and/or more chronic diagnostic outcomes compared to the lesser-impaired profiles. To examine clinical utility, analyses were repeated after data were clustered based on clinical decision rules that were established by clinical experts in the field. Results: Four distinctive profile clusters best described the level of NP performance in our CHR cohort: Severely Impaired (n = 33); Clearly Abnormal (n = 82); Borderline (n = 145) and Normal (n = 64). The Severely Impaired cluster largely distinguished itself from the rest of the clusters by larger deviations on processing speed and memory tasks. We found compelling differences in outcome between cluster profiles. Importantly, those assigned to the most impaired profile had a conversion rate of 42.4%, had a 40% chance of developing a diagnosis in the schizophrenia spectrum (as compared to 24.4% in the Clearly impaired, 7.4 % in the Borderline impaired and 2.9% in the Normal functioning group), and had significantly worse social (P < .001) and role (P < .001) functioning scores at baseline and 12-month follow-up. Similar results were obtained when data were clustered following clinical decision rules. Conclusion: Despite extensive neuropsychological investigations within CHR cohorts, this is one of the first studies to investigate NP clustering profiles as a contributor to heterogeneity in outcome. Our results indicate that the four NP profiles vary substantially in their outcome, underscoring the relevance of cognitive functioning in the prediction of illness progression. Our findings may tentatively suggest that individualized cognitive profiling should be explored in clinical settings, and my point to important directions for personalized treatment.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".