Frequency of Dengue virus Infection among Febrile Patients of Lahore
Bibliographic record
Abstract
BACKGROUND: Dengue virus infection is one of the major global public health problems. The infection usually occurs with clinical manifestations ranging from an asymptomatic or mild febrile illness as classical dengue fever to the potentially life-threatening illness, dengue hemorrhagic fever and dengue shock syndrome. The objective of the current study was to observe the frequency and diagnosis of primary or secondary dengue viral infection among individuals in Lahore city, Pakistan.METHODS: Study subjects were identified for the presence of dengue diagnostic markers including NS1 antigen, IgM and IgG antibody. The dengue specific antigen NS1 was detected by immonochromatography, while dengue specific antibodies (IgM and IgG) were measured through ELISA.RESULTS: Total 98 (56%) out of 175 febrile cases were found infected by dengue virus. From total 98 confirmed dengue cases, NS1 antigen was detected in 59 (60.20%), IgM antibodies were present in 74 (75.51%) and IgG antibodies were detected in 40 (40.81%) individuals. Statistical analysis reveals correlation of NS1 antigen and IgM antibody among dengue patients with significant P-value (P < 0.01). Results indicated that 58 (59%) were infected by primary infection and 40 (41%) were infected by secondary infection. The most effected age group was 21-30 years (51.02%) and least effected age group was <10 years (3.06%). Males were observed higher in number 61 (62%) as compare to females 37 (38%). Overall, the frequency of dengue virus infections were 56% among undifferentiated febrile patients in Lahore city, Pakistan.CONCLUSION: Dengue is found endemic in city population with increased incidence in monsoon and post monsoon. Constant vigilance of patients and dengue vector control awareness programs among public and health care officials could support in combating dengue.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".