Disease Spectrum and Triage Assessment among Children Presenting to the Paediatric Emergency Department at a Tertiary Care Centre in Telangana, India
Bibliographic record
Abstract
Introduction: Triage is a sorting process to quickly assess patients upon their arrival in the emergency department which helps to stream them to an appropriate location and adequate treatment. Triage assessment helps in recognising the commonly presenting childhood emergencies to optimise quality of care delivered in the Paediatric Emergency Department. Priority attention can be given to the critically ill or injured patients as how long the patient can safely wait, is predicted by triage. Aim: To provide data on disease spectrum and triage assessment of children presenting to an exclusive Paediatric Emergency Department. Materials and Methods: This was a cross-sectional study which was conducted from October 2020 to September 2021 over a period of one year in the Paediatric Emergency Department at Niloufer Hospital, a tertiary care children hospital in Hyderabad, Telangana, India. All children in the age group of one month to twelve years triaged by fivelevel Canadian triage and acute scale were included in the study. Data was collected from the register maintained at the Emergency Department. Descriptive statistics was used to analyse the data. Micosoft excel sheets were used for recording data. Results: During the study period, 7986 children were admitted with 5718 (71.6%) males and 2268 (28.4%) females. A total of 4352 (54.5%) patients were less than one year age. Neurological emergencies, acute febrile illnesses, respiratory illnesses were most common reasons for emergency visits. The number of chidren presenting with triage level 1,2,3 were n=4369 (54.71%). Conclusion: Majority of the patients attending the Emergency Department were less than one year old and acute febrile illnesses and seizures were the most common causes for admissions. Triaging and priorisation of pediatric emergencies is strogly recommended for early recognition of life threatening illnesses and to improve outcomes. Specially trained nurses, healthcare professionals trained in Basic Life Support (BLS) and Paediatric Advanced Life Support (PALS) will go a long way in reducing morbidity and mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".