564 The Impact of COVID-19 on the Provision of Pediatric Burn Care
Bibliographic record
Abstract
Abstract Introduction The WHO declared the outbreak of COVID-19 a pandemic in the spring of 2020 which led to widespread restrictions on daily life activities as people were instructed to isolate at home. Given that 75 – 85% of pediatric burns occur in the home, it is likely that these measures had an impact on pediatric burn care. Thus, the aim of this study was to investigate the impact of the COVID-19 pandemic on the provision of pediatric burn care at an American Burn Association-verified pediatric burn center. Methods Data was retrospectively extracted from all new burn patients aged 0-18 years during a pre-pandemic period (April 2019 – August 2019) and a pandemic period (April 2020 – August 2020). Continuous data was examined using 2 tailed t-tests (p < 0.05), while non-continuous data was examined using Pearson chi-squared tests (p < 0.05). These analyses were used to analyze burn demographics and examine changes in the delivery of acute and follow-up burn care before and during the pandemic. Results During the pre-pandemic period, 213 new burns were identified, compared to 172 new burns during the pandemic period. No clinically significant changes were observed in patient age at presentation (p = 0.54), total body surface area of burn (p = 0.85), and time to presentation following the injury (p = 0.24). Interestingly, a significant increase in friction burns (p = 0.023) was observed, which mainly consisted of treadmill burns. During the pandemic, burn operating room utilization remained high and represented approximately 25% of the hospital's total surgical capacity. In addition, there were no significant changes to inpatient and outpatient encounters (p = 0.56 and p = 1.00) between the two periods thereby highlighting the need for these essential services during the pandemic. Conclusions Burn-related service needs remained consistent across the pre-pandemic and pandemic cohorts as demonstrated by the number of new burns as well as the continued provision of burn care. Overall, no clinically significant changes to patient demographics, aside from the increase in friction burns, were observed. Furthermore, the ability to provide all aspects of pediatric burn care at this tertiary pediatric hospital remained consistent across the pre-pandemic and pandemic cohorts. Although this study presents data from the first five months on the pandemic, further analysis of the entire year will be carried out in order to identify additional trends.
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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".