104 New Presentations of Anorexia Nervosa and Atypical Anorexia Nervosa In Adolescents During the COVID-19 Pandemic
Bibliographic record
Abstract
Abstract Primary Subject area Adolescent Medicine Background The coronavirus (COVID-19) pandemic has had profound effects on adolescent mental health. Beginning in mid-March 2020, public health measures were implemented throughout the province of Quebec, including full school closure and confinement. Previous studies have demonstrated the association between stressful events and the exacerbation of anorexia nervosa (AN), however the association of the COVID-19 pandemic on new AN diagnoses remains unknown. Objectives To assess the incidence and severity of newly diagnosed AN or atypical AN (AAN) cases among adolescents during the COVID-19 pandemic compared to the five preceding years. Design/Methods We performed a retrospective analysis from Jan 1 2015 to Nov 15 2020 of new eating disorder assessments at an urban tertiary pediatric hospital. Baseline demographic information and clinical assessment variables were collected. The primary outcomes were the incidence of de novo AN or AAN diagnoses and hospitalization within 7 days of diagnosis. Event rate time trends were compared during the period of pandemic public health measures (March 2020 to November 2020) to the proceeding 5-years (January 2015 to February 2020) using an interrupted time series and logistic mixed modeling. Results Overall, 353 patients met inclusion criteria during the study period. Median patient age was 15.9 (IQR 13.8-16.9) years, 93% were female, and 65% of patients were diagnosed with atypical AN. For the full cohort at diagnosis, %mBMI was 92% (SD ±15%) and mean weight loss was 11 Kg (SD ±7Kg). In the 5 years preceding the pandemic, there were 4.5 new AN/AAN cases per month with a modest downward trend (ßcoeff=-0.016). During confinement, new diagnoses rose to 8.0/month with a steep upward trend (ßcoeff=1.417, p < 0 .001). Similarly, hospitalizations for new cases increased from 0.8 to 2.6/month with a significant increase in linear tend (ßcoeff -0.012 vs. 0.500, p < 0 .001). Moreover, patients diagnosed during COVID-19 confinement had a shorter duration of symptoms (6 months vs. 10 months, p=0.001), with a higher percentage of body weight loss (19% vs. 16%, p=0.03) at a faster rate (2.3kg/mo vs. 1.5Kg/mo, p=0.001). Bradycardia was more pronounced at diagnosis during the pandemic (55 bpm vs. 62 bpm, p=0.001) with a greater proportion meeting threshold for admission (38% vs. 19%, p=0.001). Conclusion During the COVID-19 confinement, new diagnoses of AN and AAN nearly doubled and hospitalizations for these patients more than tripled. Markers for disease severity were more pronounced and evolved more rapidly. Findings highlight the urgent need for increased community resources during the pandemic, as well as prospective research to understand drivers and prognosis for these patients more effectively.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".