Patterns of Pediatric Ear, Nose and Throat Disorders in a Tertiary Care Hospital of Western Nepal: A Cross-Sectional Study
Bibliographic record
Abstract
INTRODUCTION: In outpatient department (OPD) of hospital in low and middle income countries (LMICs), pediatric ear, nose and throat (ENT) disorders are common and huge variation in number is being reported in different seasons. This study aimed to study the prevalence and seasonal effect of ENT disorder in children.
 MATERIAL AND METHODS: One year (Jan-Dec, 2015) retrospective data of children (0 months-17 years) visiting ENT outpatient (ENT-OPD) department at Universal College of Medical Sciences-Teaching Hospital, Nepal was analysed. Descriptive statistics were calculated to report the prevalence of ENT disorders for various sub-groups including season. In addition to quantifying the prevalence of ENT disorders in children, the seasonal influence of each disorder was analysed.
 RESULTS: Out of 14,126 patients visiting the ENT-OPD, 3,423 (24.23%) were children. The mean age of children having ENT- disorders were 8.4±5.1, 10.6±4.6 and 10.7±4.7 years respectively with male-female ratio of 1.3:1.
 During all seasons 2,645 (77.3%) had ear problems, 328 (9.6%) nose disorders and 450 (13.14%) throat disorders. The percentage of children with ear disorders declined significantly with increase in age unlike those with nose and throat disorders (P < 0.001). Seasonal trend analysis showed that children had significantly higher number of ear disorders during summer and autumn seasons (P <0.001) whereas nose disorders were more common in spring and winter seasons (P<0.001) with chronic otitis media and wax being the main types of ear disorders and deviated nasal septum (DNS) for nose disorders. Among the throat disorders, tonsillitis was most prevalent in all seasons followed by pharyngitis.
 CONCLUSION:- The study suggests a clear seasonal trend in the prevalence of ENT disorders that can be used for advanced planning and management of the conditions in hospitals.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".