Impact of COVID-19 pandemic on rates of congenital heart disease procedures among children: prospective cohort analyses of 26 270 procedures in 17 860 children using CVD-COVID-UK consortium record linkage data
Bibliographic record
Abstract
Abstract Background The COVID-19 pandemic necessitated major re-allocation of health care services. Our aim was to assess the impact on paediatric congenital heart disease procedures during different pandemic periods compared to the pre-pandemic period, to inform appropriate responses to future major health services disruptions. Methods and Results We analysed 26,270 procedures from 17,860 children between 01-Jan-2018 and 31-Mar-2022 in England, linking them to primary/secondary care data. The study period included pre-pandemic and pandemic phases, with latter including three restriction periods and corresponding relaxation periods. We compared procedure characteristics and outcomes between each pandemic periods and the pre-pandemic period. There was a reduction in all procedures across all pandemic period with the largest reductions during the first, most severe restriction period (23-Mar-2020 to 23-Jun-2020), and the relaxation period following second restrictions (03-Dec-2020 to 04-Jan-2021) coinciding with winter pressures. During the first restrictions, median procedures per week dropped by 51 compared with the pre-pandemic period(80 vs 131 per week, p = 4.98×10 -08 ). Elective procedures drove these reductions, falling from 96 to 44 per week, (p = 1.89×10 -06 ), while urgent (28 vs 27 per week, p = 0.649) and life-saving/emergency procedures (7 vs 6 per week, p = 0.198) remained unchanged. Cardiac surgery rates increased, and catheter-based procedure rates reduced during the pandemic. Procedures for children under 1-year were prioritized, especially during the first four pandemic periods. No evidence was found for differences in post procedure complications (age adjusted odds ratio 1.1 (95%CI: 0.9, 1.4) or post procedure mortality (age and case mix adjusted odds ratio 0.9 (0.6, 1.3)). Conclusions Prioritization of urgent, emergency and life-saving procedures during the pandemic, particularly in infants, did not impact paediatric CHD post procedure complications or mortality. This information is valuable for future major health services disruptions, though longer-term follow-up of the effects of delaying elective surgery is needed.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".