Clinical-epidemiological caracterization of patiens with dengue in medical office 11 of puerto padre
Bibliographic record
Abstract
Introduction: dengue is a vector-transmitted infectious disease, considered the arbovirus that most affects humans.Objective: to clinically and epidemiologically characterize the cases with a diagnosis of probable dengue in the period studied.Method: observational, descriptive, prospective and cross-sectional study in office 11 of the health area belonging to the Romárico Oro polyclinic, in the municipality of Puerto Padre, in the period between January 2019-December 2023. The Universe was made up of 196 patients febrile, with confirmatory diagnosis of dengue through the detection of IgM antibodies. The data were obtained from the databases relating to arboviruses of the Municipal Directorate of Hygiene and Epidemiology.Results: the investigation and fight against vectors are of relevant importance, since it was shown that 93,7 % of the cases were caught through this activity. The largest number of diagnosed cases corresponded to the year 2022 (38,8 % of cases). The most representative months were those included in the quarter from October to December (48 %). The female sex (55,6 %) and ages between 40 and 59 years (36,7 %) predominated. There were several clinical manifestations, but the most frequent was fever (100%). The most significant comorbidity was arterial hypertension (66,1 %).Conclusion: even after the efforts of MINSAP (PHM), dengue cases reflect a high increase, and the female population continues to be the most affected; especially in the months of October, November and December.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".