Neuropsychiatric Symptoms and Psychotropic Medication Use Following SARS-Cov-2 Infection Among Elderly Residents in Long-Term Care Facilities
Bibliographic record
Abstract
Background: SARS-CoV-2 infection can lead to persistent post-acute neuropsychiatric symptoms. Older adults with multimorbidity may be at increased risk of post-acute symptoms after COVID-19. The goals of the present study were to assess the associations of SARS-CoV-2 infection with neuropsychiatric symptoms and psychotropic medication prescription among older adults living in long-term care facilities. Methods: Nursing home residents (n=111) participated in this three-month longitudinal study. Nurse ratings of neuropsychiatric symptoms were conducted at baseline and at the three-month follow-up. SARS-CoV-2 infection status and psychotropic medication prescription were extracted from a medical chart review. Results: About 73.9% of participants were infected with SARS-CoV-2 on average 480.49 (SD= 228) days before study enrollment. There were no significant changes in neuropsychiatric symptoms during the study follow-up period. Participants with a SARS-CoV-2 infection had more agitation compared to those who were never infected. However, this effect disappeared after adjusting for age, sex, history of psychiatric disorder, neurocognitive status, and multimorbidity. Participants with SARS-CoV-2 had a higher number of psychotropic medication prescription. This effect was driven by increased use of antidepressants and antipsychotic medications. Conclusion: Both acute and short-term neuropsychiatric symptoms associated with COVID-19 may contribute to long-term psychoactive polypharmacy among older adults living in long-term facilities.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".