Lessons from SARS: A retrospective study of outpatient care during an infectious disease outbreak
Bibliographic record
Abstract
BACKGROUND: During severe acute respiratory syndrome (SARS) outbreak in Toronto, outpatient clinics at SickKids Hospital were closed to prevent further disease transmission. In response, a decision was made by the neonatal neuro-developmental follow up (NNFU) clinic staff to select patients with scheduled appointments to have a mail/telephone assessment using Ages and Stages Questionnaire (ASQ) or to postpone/skip their visit. The objective of this study was to compare the developmental assessment and its outcome in two groups of NNFU clinic patients, SARS versus non-SARS, over three standard clinic appointments. METHODS: We compared the diagnostic accuracy (identification of developmental delay), and patient management (referral for therapy or communication of a new diagnosis) of the strategies used during SARS, April/May 2003, to the standard assessment methods used for patients seen in April/May 2005 (non-SARS). In all cases data were obtained for 3 patient visits: before, during and after these 2 months and were compared using descriptive statistics. RESULTS: There were 95 patients in the SARS group and 99 non-SARS patients. The gestational age, sex, entry diagnosis and age at the clinic visit was not different between the groups. The NNFU clinic staff mailed ASQ to 27 families during SARS, 17 (63%) were returned, and 8 of the 17 were then contacted by telephone. Criteria used to identify infants at risk selected for either mailed ASQ or phone interviews were not clearly defined in the patients' charts. There was a significant under identification of developmental delay during SARS (18% versus 45%). Of those who responded to the mailed questionnaire, referrals for therapy rates were similar to non-SARS group. The lost to follow up rate was 24% for the SARS group compared with 7% for non-SARS. There was no difference in the overall rate of developmental delay in the two groups as identified at the 'after' visit. CONCLUSIONS: Poor advanced planning led to a haphazard assessment of patients during this infectious disease outbreak. Future pandemic plans should consider planning for outpatient care as well as in hospital management of patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".