: Dengue is the most common arboviral disease in the world. Traditionally, it has affected more adults, but the incidence in children has increased in recent years. Colombia is no stranger to this change; therefore, we aimed to find the differences in signs, symptoms, and clinical, hematological, and hemogram characteristics between children under 12 years old and individuals aged 12 years and older in an endemic region of Colombia in 2020–2022. The analyses were conducted with baseline data, corresponding to a cross-sectional design. Multiple correspondence analysis was used for general, dermatological, and clinical symptom profiles. Discriminant analysis was used for laboratory profiles. Multiple correspondence analysis was applied to nominal categorical data, employing Euclidean distances to analyze age groups. Discriminant analysis was applied to a training sample and validated on a test sample. The overall agreement of the model’s discrimination, sensitivity, specificity, and fit indicators was calculated. The results indicated that individuals under 12 years exhibited distinct dermatological and clinical features, including rash, pruritus, hypotension, lymphocyte count, and platelet count, compared with those aged 12 years and older. In contrast, those 12 years and older were profiled for general and clinical symptoms such as pain (back pain, retro-orbital pain, headache), dizziness, chills, hematuria, tachypnea, and elevated/high hematocrit, hemoglobin, and basophil values. These findings are crucial to understanding the high incidence in children; they also facilitate rapid understanding of the disease in clinical care settings and differentiate it from other febrile outbreaks. This will affect disease control, particularly in severe cases, and reduce mortality.

Background: Populations exposed to Armed Conflict Experiences (ACE) show different levels of impact in their mental health (i.e. clinical and positive components); however, there is limited evidence related to mental health of general population (civilians not classified as victims) exposed to ACE. Government guided mental health assessments exclude this population. The use of a newly validated Extreme Experiences Scale (EX²) seems appropriate to classify victims, ex-combatants, and civilians for their mental health assessment. Methods: Here, we propose a novel approach to identify relationships between individuals classified with different levels of ACE exposure—independent of their legal role in the armed conflict, and mental health outcomes. According to the cut-off points derived from the scores of EX², we classified the sample in low and high exposure to ACE. Results: The high-level ACE group (scores > 2.5) included 119 subjects, and the low-level ACE was constituted by 66 subjects. Our results evidence that people with high exposure to ACE experiment higher odds to present anxiety disorders, risk of suicide, or post-traumatic stress disorder, as well as increased cognitive empathy (i.e., fantasy dimension). Conclusion: These findings allowed us to identify the influence of ACE on mental health outcomes beyond the conventional frame (victim or ex-combatant), and to discuss effective interventions and implementation of mental health strategies in these communities. We expect to help the health system to focus on key vulnerable subjects by including civilians not recognized as victims, which are neglected from most of the public health screening, assessment, and interventions.

One of the main challenges in the clinical management of dengue is the early identification of cases that could progress to severe forms of the disease. A biomarker that may enable this identification is the presence of genetic polymorphisms in genes associated with immune responses. The objective of this study was to perform a systematic review of the Latin American literature on these genes. An electronic literature search was carried out in PubMed, Scopus, Lilacs, and the Virtual Health Library, and reference lists of systematic reviews in the area. Case-control studies conducted in Latin American countries examining at least one form of genetic polymorphism related to immune responses against severe dengue were included. In total, 424 articles were identified and 26 were included in this systematic review. Of the 26 selected articles, 16 reported polymorphisms associated with the risk of developing severe dengue (Risk); Similarly, 16 articles reported polymorphisms associated with a decreased risk of severe dengue (Protective). The final analysis revealed that multiple polymorphisms in immune system genes were early markers of the progression of dengue in Latin Americans and found that polymorphisms of the TNF-alpha gene may have a critical role in dengue pathogenesis.

Background: Early detection of severe dengue (SD) is crucial in preventing life-threatening complications. Despite its importance, comprehensive knowledge about these early indicators is still limited. This study aimed to identify predictors of SD in a hyperendemic region of Colombia. Methods: A cross-sectional analysis was conducted using data from 2018 to 2022, encompassing 233 patients. By utilizing the 2009 World Health Organization dengue classifications, cases were differentiated between severe dengue (SD) and non-severe dengue (non-SD). Among these, 47 were confirmed as SD. Associations between clinical, demographic, and laboratory data and disease severity were examined using Fisher’s exact tests or the Mann–Whitney U test (p < 0.05). Profiles for SD and non-SD cases were established through multiple correspondence analysis, and a logistic regression-based predictive model was validated using training and test sets. The model’s performance was evaluated using the area under the receiver operating characteristic curve (AUC-ROC), accuracy, sensitivity, F1-score, and precision. Results: Differences in place of residence, comorbidities, type of infection, and signs and symptoms were observed between the severe dengue (SD) and non-severe dengue (non-SD) groups. Median levels of platelets, white blood cells (WBC), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were found to be higher in the SD group compared to the non-SD group. Neutrophils, leukocytes, platelets, AST, and primary infection were significant predictors of SD. The model demonstrated an area under the receiver operating characteristic curve (AUC) of 0.91 (95% CI, 0.85–0.96). Conclusions: The developed predictive model provides significant assistance to clinicians in assessing SD risk and optimizing triage, which is particularly crucial during dengue outbreaks.