An Observational Study on Changes in Psychological Parameters in Covid 19 Recovered Patients
Bibliographic record
Abstract
The rapid escalation of COVID-19 pandemic resulted in a World Health Organization (WHO)-declaring public health emergency of international concern. The present study aimed to measure the prevalence of depression, anxiety, stress, post-traumatic stress disorder and cognitive impairment among the covid19 recovered patients. This observational study included patients with a history of COVID-19 who were admitted in the IPD of Medical College & Hospital, Kolkata. Data was collected from the patients after 14 days from recovering from COVID Patients were assessed through three questionnaire, Depression, Anxiety and Stress Scale - 21 (DASS-21), PTSD Checklist PCL-5 and Montreal Cognitive Assessment (MOCA). Statistical analysis showed significant differences between Anxiety and PTSD score of male and female patients. Significant difference was found in the depression, anxiety and PTSD score, when comparison was made on the basis severity level of Covid. Significant difference was found in the depression, stress and MOCA score, when comparison was made on the basis of educational status of patients. Duration of hospital stay and oxygen therapy were positively associated with anxiety, depression, stress and score while MOCA scores were found to be negatively associated. The result of the present study showed that no significant difference in the psychological variables was observed when comparison was made in terms of comorbidity. In conclusion, we should pay special attention to the mental health status of female patients, severe type individuals as we provide treatments to the COVID-19 patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".