Association of Anxiety and Depression with Objective and Subjective Cognitive Decline in Outpatient Healthcare Consumers with COVID-19: А Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: In addition to the neurological complications affecting people infected with COVID-19, cognitive impairment symptoms and symptoms of anxiety and depression remain a frequent cause of complaints. The specificity of cognitive impairment in patients with COVID-19 is still poorly understood. AIM: An exploratory study of factors that may be associated with cognitive decline during the COVID-19 pandemic. METHODS: The cross-sectional multicentre observational study was conducted in a polyclinic unit in Saint Petersburg and in the regions of the North-Western Federal Region. During the study, socio-demographic parameters and information about the somatic condition of patients who applied for primary health care was collected. Emotional and cognitive state were investigated using the Hospital Anxiety and Depression Scale (HADS) and Montreal Cognitive Assessment (MoCA). Mathematical and statistical data processing was carried out using SPSS and RStudio statistical programs. RESULTS: The study included 515 participants, 60% (n=310) of which were women. The sample was divided into those who did (28.5%, n=147) and did not (71.4%, n=368) complain of cognitive decline. Patients with complaints of cognitive decline were significantly older, had lower levels of education and higher levels of depression and anxiety according to HADS (p 0.05). Patients with complaints of cognitive decline underwent the MoCA test (24.3%, n=125). The median MoCA test scores were within the normal range (Median=27, Q1=25, Q3=28), and cognitive decline (MoCA less than 26 points) was detected in 40% (n=50) of patients with complaints of cognitive decline. No significant correlations were found between the MoCA scores and the levels of anxiety and depression according to the HADS (p 0.05). Patients with mild severity of the COVID-19 course were more successful with MoCA subtests than patients with moderate and severe courses. CONCLUSION: We found no linear association between objective cognitive deficit and the affective state of respondents. Patients subjective complaints about cognitive dysfunction were mostly caused by their emotional state than an objective decrease of their cognitive functions. Therefore, in case of subjective complaints on cognitive decline, it is necessary to assess not only the cognitive but also the affective state of the patient. The severity of the COVID-19 course affects the functions of the cognitive sphere, including attention, regulatory functions and speech fluency. Mild and moderate severity of the COVID-19 correlates with clinically determined depression. The absence of this relationship with the severe course of the disease is probably explained by the significant somatic decompensation of patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".