Demographic and clinical variables in the dengue epidemic in Punjab, Pakistan
Bibliographic record
Abstract
Objectives: To identify the latest trends in the clinical picture and severity of the disease, which will help better understand and manage dengue. Methodology: It was a cross-sectional, hospital-based study performed in the tertiary care hospitals of Punjab from August 21 to December 2022, in which serologically and polymerase chain reaction (PCR) confirmed patients with dengue infection, were enrolled. Demographic and clinical variables were recorded on a pre-tested Performa, processed and presented in frequency and percentages, and graphs were generated. Mean and standard deviation was used to present continuous variables. Results: Out of a total of 580 patients, 472 were diagnosed with Dengue Fever (DF) and 108 with Dengue Hemorrhagic Fever (DHF). About 79.31% of the patients were male and 20.69% were females. The mean age of patients was 32.5±9 years. Among the clinical features the percentage of high-grade fever, body aches, and vomiting were the highest. The liver function profile showed that serum bilirubin, Serum aspartate transaminase (AST), serum alanine transaminase (ALT,) and alkaline phosphatase (ALP) levels were markedly raised. Conclusion: This study showed that with time the trends in the presentation of dengue are slowly shifting, which will help us better manage the disease burden in the future. doi: https://doi.org/10.12669/pjms.39.6.7383 How to cite this: Mushtaq S, Khan MIU, Khan MT, Husain A. Demographic and clinical variables in the dengue epidemic in Punjab, Pakistan. Pak J Med Sci. 2023;39(6):1742-1746. doi: https://doi.org/10.12669/pjms.39.6.7383 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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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 | 0.022 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".