Caracterización clínica del dengue y variables predictoras de gravedad en pacientes pediátricos en un hospital de segundo nivel en Chilpancingo, Guerrero, México: serie de casos
Bibliographic record
Abstract
El dengue sigue en incremento a nivel mundial y actualmente la mayor incidencia de primera infección ocurre en población pediátrica. El dengue grave es potencialmente letal en menores de edad. Este estudio caracteriza el perfil clínico de pacientes pediátricos con dengue atendidos en un hospital de segundo nivel en Chilpancingo, Guerrero, México. Serie de casos conformada por 133 pacientes pediátricos hospitalizados con diagnóstico de dengue no grave y dengue grave, de acuerdo a criterios clínicos. Los resultados del análisis univariado de los signos y síntomas clínicos fueron expresados como promedios o porcentajes, y se consideró nivel de significancia estadística de 0.05. Mediante GLMM (Generalised Linear Mixed Models) se estimó la predicción de dengue grave con la presencia de signos y síntomas clínicos. El 58% (77/133) de los pacientes fue clasificado como dengue grave. Hubo diferencias significativas entre los grupos de dengue en los signos y síntomas siguientes: fiebre, dolor abdominal, epistaxis y cuenta plaquetaria. El dengue grave se presentó en mayor proporción en los pacientes mayores de cuatro años de edad (p<0.05). El GLMM identificó un conjunto de cuatro signos y síntomas clínicos (fiebre ≥39 °C, mialgias, artralgias y dolor abdominal) como predictores de la gravedad del dengue. Los resultados de este estudio exploratorio sugieren cambios en la frecuencia de síntomas y signos clínicos del dengue en la población pediátrica. Pacientes pediátricos con diagnóstico presuntivo de dengue que presenten fiebre ≥39 °C, mialgias, artralgias y dolor abdominal deben considerarse como potenciales casos de dengue grave. Dengue continues to increase globally. Currently, the highest incidence of first infection occurs in paediatric population, where severe dengue fever is potentially lethal. This study characterizes the clinical profile of paediatric patients with dengue fever in the South of Mexico. We undertook a series case study of 133 paediatric inpatients who presented clinical diagnosis of non-severe dengue and severe dengue fever. We described univariate analysis as means or percentages, using 0.05 as significance level. We estimated the prediction of severe dengue considering clinical signs and symptoms only using GLMM (Generalised Linear Mixed Models). 58% (77/133) patients had severe dengue. There were significant differences among the dengue groups, in the following signs and symptoms: Fever, abdominal pain, epistaxis and platelet count. Children older than four years old had a higher proportion of severe dengue (p<0.05). GLMM identified a group of four clinical signs and symptoms (fever ≥39 °C, myalgia, arthralgia and abdominal pain) as predictors of severe dengue. The results of this exploratory study suggest changes in the frequency of clinical signs and symptoms among paediatric inpatients. Paediatric patients with a presumptive diagnosis of dengue, showing fever of ≥39° C, myalgia, arthralgia and abdominal pain should be considered as potential cases of severe dengue.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".