Frequency and correlates of subjective cognitive complaints and objective cognitive screening results in African American adults following COVID-19 infection
Bibliographic record
Abstract
Background: Subjective cognitive complaints are frequent following COVID-19 infection, but assessment of whether these complaints map onto objective cognitive findings may not be routine in busy clinical settings. Consequently, opportunities to confirm these complaints and to provide follow-up referrals and appropriate care may be missed, thereby impacting patients' functional independence and quality of life. African Americans are vulnerable to poor outcomes from COVID-19, and thus represent a minority group in whom subjective concerns are especially important to investigate. Towards this end, we examined the frequency and correlates of subjective complaints and objective screening results of African American patients referred to the Post-Acute Sequelae of SARS-CoV-2 (PASC) Clinic at Grady Memorial Hospital, a large county teaching hospital in Atlanta, Georgia. Methods: Eighty seven African American patients (mean age = 52.5, SD = 10.5, range = 30-73) were evaluated between January 28, 2021-October 14, 2021 in the Grady PASC clinic. They ranged from 1 to 17 months post positive SARS-COV-2 antigen testing. Patients were administered a subjective cognitive complaint questionnaire (PROMIS Cognitive Function Scale Short Form 8a) as well as cognitive screening measures including the Mini-Cog (3 item recall, clock) and the Digit Symbol Substitution Test (timed visuomotor sequencing). Mood was assessed via the Patient Health Questionnaire-9, and anxiety via the Generalized Anxiety Disorders Scale. Published norms were used to identify clinically elevated scores. Results: Sixty six (76%) patients denied experiencing meaningful cognitive concerns, and of these, 25 (38%) had positive cognitive screens indicating impaired performance on objective testing. Of 21 patients with subjectively elevated cognitive concerns, 17 (81%) also had positive cognitive screens. There were no significant differences in sociodemographic factors (p values = .07-.71), days post-acute positive SARS-COV-2 Antigen Test (p = .99), disease severity (p values = .67-.75), or COVID-19 comorbidity indices (medical conditions (p values = .20-.77), substance abuse (p = .79), psychiatric history (p values = .11-.99) in those with or without subjective complaints and objective cognitive findings. However, patients with subjective complaints and objective cognitive findings reported more post-COVID-19 anxiety (p = .02) and depression (p = .001). Conclusions: Findings indicate a high concordance between subjective complaints on the PROMIS Cognitive Scale and objectively confirmed cognitive impairments in African Americans. Further, almost 40% who reported no cognitive complaints screened positive for cognitive impairment. Although depression and anxiety are associated with subjective complaints, they do not account for positive cognitive screening results, as those patients without depressive complaints also had similar rates of positive objective screens. The findings suggest that cognitive screening using assessment tools should be routinely performed in African Americans, especially those reporting cognitive symptoms on outcome scales. While future studies are needed to assess long-term outcomes, we highly recommend follow-ups in those with positive screens to characterize the specific domains that are impacted and that could affect activities of daily living and quality of life.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".