Biomedica[JOURNAL]
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200 papers
Evaluation of the quality of vaginal discharge smear analysis reporting in five clinical laboratories in the Colombian Pacific Region.
Salcedo-Cifuentes M, Fonseca-Pérez JE
Biomedica · 2026 Mar · PMID 41875458 · Publisher ↗
INTRODUCTION: Vaginal flow analysis plays a key role in clinical diagnosis and medical decision-making. Standardizing report formats remains essential to ensure diagnostic reliability. OBJECTIVE: To assess the quality of...
INTRODUCTION: Vaginal flow analysis plays a key role in clinical diagnosis and medical decision-making. Standardizing report formats remains essential to ensure diagnostic reliability. OBJECTIVE: To assess the quality of vaginal smear reporting in five clinical laboratories located in Colombia’s Pacific region. MATERIALS AND METHODS: This descriptive, retrospective study examined records from five laboratories (three public, two private) across three cities in the Colombian Pacific region. The evaluation followed the BACOVA ERIGE guidelines to assess the completeness of the analytical components. Researchers used XLSTAT Premium, version 2024, to compute means, standard deviations, proportions, and ratios. They applied the chi square test to compare reporting compliance across laboratories and used multiple correspondence analysis and discriminant analysis to identify reporting patterns and inter-city differences. RESULTS: The study analyzed 1260 records from women aged 18 to 60 years. Of these, 56.8% were pregnant, and 57% were affiliated to the subsidized healthcare system. Compliance with the BACOVA ERIGE guidelines was higher in Ipiales (54.44%) compared to Cali (24.21%) and Quibdó (21.35%) (c², p = 0.047). The multiple correspondence analysis and discriminant analysis identified three distinct reporting profiles by city. CONCLUSIONS: The variability in vaginal smear reports underscores the need to standardize post-analytical procedures. Unifying technical criteria among laboratories would improve the diagnostic quality of vaginal flora imbalance and enhance clinical decision-making.
Exploring the challenges: main contraindications in organ donation in Colombia.
Gómez-Montero A, García-López A, Cruz-Mususú W … +5 more , Vargas L, Escobar X, Orellano-Salas M, Cabas S, Girón-Luque F
Biomedica · 2026 Mar · PMID 41875457 · Publisher ↗
Introduction. Organ transplantation is crucial for improving the quality of life of patients with organ failure, but the shortage of donors is a global challenge. In Colombia, the demand exceeds the supply, increasing mo...
Introduction. Organ transplantation is crucial for improving the quality of life of patients with organ failure, but the shortage of donors is a global challenge. In Colombia, the demand exceeds the supply, increasing mortality rates on waiting lists. Objective. To evaluate the causes of contraindications in potential organ donors assessed by Fundonar across three regional centers in the country during 2022. Materials and methods. A descriptive cross-sectional study was conducted based on retrospective data from potential donors reported to the Red de Donación y Trasplantes de Colombia. A total of 1451 cases were evaluated. The causes of contraindications were categorized into medical, medico-legal, and logistical categories. Descriptive statistics were used, the normality of the variables was assessed, and contraindicated donors from each regional center were compared using ANOVA. R software, version 4.0.3, was used. Results. Of the 1451 donors evaluated, 849 had contraindications. Among these, 29.8% presented multiple organ failure, 20.8% had a comorbidity, and 15.3% did not meet the diagnostic criteria for brain death. Conclusion. Most of the medical contraindications could be reconsidered by balancing risks and benefits for the recipients. A personalized and multidisciplinary approach, with evidence-based criteria and real-time decisions tailored to Colombia, could improve organ donation approval rates.
Dramatic increase in consumption of antibiotics in Colombia, 2020-2023.
López-Mejía Y, Nelson Alvis Guzmán N, Paternina D … +6 more , Guzmán C, Camargo F, Beltrán M, Sanjuan A, León-Rosso A, Mattar S
Biomedica · 2026 Mar · PMID 41875456 · Publisher ↗
INTRODUCTION: Antibiotic consumption and resistance have increased worldwide. Antibiotic resistance results in longer hospital stays and higher healthcare costs. OBJECTIVE: To describe the consumption of antibiotics and...
INTRODUCTION: Antibiotic consumption and resistance have increased worldwide. Antibiotic resistance results in longer hospital stays and higher healthcare costs. OBJECTIVE: To describe the consumption of antibiotics and associated expenses in Colombia. MATERIALS AND METHODS: A meticulous descriptive cross-sectional study of antibiotic consumption and expenditure in Colombia from 2020 to 2023 was conducted. Between 2020 and 2023, a description of the consumption and expenditure of antibiotics in Colombia was made. Data were obtained from IQVIA™ (IMS Health and Quintiles). The prominent families of antimicrobials used in Colombia were selected. Twelve pharmacological families were classified, including 27 antimicrobials and three β-lactamase inhibitors. The defined daily dose was used to measure antibiotic consumption, identify variations, and evaluate medical prescription practices. The defined daily dose per 1,000 inhabitants per day was estimated to obtain information from the population receiving daily antibiotic treatment. The amount of antibiotics used was estimated in grams and tons per year. RESULTS: The top 10 most consumed antimicrobials by defined daily dose per 1,000 inhabitants per day in Colombia were amoxicillin, azithromycin, metronidazole, cephalexin, ciprofloxacin, trimethoprim-sulfamethoxazole, ampicillin, sulbactam, clarithromycin, cefazolin, and dicloxacillin. The total consumption of antibiotics was 2,139 tons, which represented an expense of USD$ 708,112,587, for an increase of 17 and 8%, respectively, during the period. CONCLUSIONS: The progressive increase in consumption and spending on antimicrobials in Colombia requires a set of interventions that include promoting changes in medical prescribing behaviour and a public education campaign that leads to the adoption of a sustainable public health policy.
Genomic surveillance of SARS-CoV-2 variants in hospitalized patients: a cohort study from the metropolitan area of valle de Aburrá, Colombia.
Hernández-Ortiz OH, Pérez-Restrepo L, Úsuga J … +8 more , Moreno M, Naranjo A, Vélez J, Sará J, Molina-Saldarriaga F, Jaimes F, Osorio J, Hernández-Ortiz JP
Biomedica · 2026 Mar · PMID 41875455 · Publisher ↗
Introduction. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been one of the most significant pandemics of the modern era. This coronavirus has a high mutation rate, resulting in variants with changes i...
Introduction. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been one of the most significant pandemics of the modern era. This coronavirus has a high mutation rate, resulting in variants with changes in the spike protein, which hinder containment efforts. Genomic surveillance is crucial for public health and vaccination strategies, especially in lowand middle-income countries, where the impact has been considerable. Objective. To identify viral variants and their clinical presentations in a prospective cohort of hospitalized patients with SARS-CoV-2 infection between October 2021 and February 2023. Materials and methods. We collected patients’ demographic data, medical histories, vaccination status, and clinical progression. Viral genome sequencing was performed on nasopharyngeal swab samples confirmed by real-time reverse transcription polymerase chain reaction to classify strains and detect variants. Results. The predominant variant in the 63 SARS-CoV-2-positive samples was omicron (84%), followed by delta (14%). A higher proportion of critical illness was observed in delta cases (100%) compared to omicron (30%). Mutations in the spike protein were identified and classified into four categories (A-D), along with specific mutations in the S gene. Conclusion. The mutational patterns observed in this study are consistent with global reports, with delta cases presenting greater clinical severity. We identified spike protein mutations that may confer distinctive properties to the virus. These findings underscore the need for ongoing genomic surveillance to better understand viral dynamics and guide public health strategies.
Relationship between susceptibility to neurodegenerative diseases and genetic factors in populations exposed to mercury in Medellín, Colombia.
Avendaño EJ, Castillo AP
Biomedica · 2026 Mar · PMID 41875454 · Publisher ↗
INTRODUCTION: Neurodegenerative diseases such as Alzheimer’s and Parkinson’s are associated with genetic and environmental factors, including exposure to mercury, a heavy metal with neurotoxic effects. OBJECTIVES: To ide...
INTRODUCTION: Neurodegenerative diseases such as Alzheimer’s and Parkinson’s are associated with genetic and environmental factors, including exposure to mercury, a heavy metal with neurotoxic effects. OBJECTIVES: To identify and analyze alleles and genes linked to neurodegenerative diseases in relation to mercury exposure in Colombia. MATERIALS AND METHODS: Scientific literature and population genotype data from public databases were reviewed, covering 94 Colombian adults genotyped under the CLM (Colombians from Medellín) reference. Data traceability was ensured through ID registration in the 1000 Genomes project database, guaranteeing informed consent and bioethical approval. Eleven genes (GSTP1, ATP7B, BDNF, GCLC, GCLM, MT1A, MT4, ABCC2, ABCB1, GPX1 y GPX4) with 18 polymorphisms distributed across ten chromosomes were analyzed using the SNPstatsTM program. The c² test was applied to evaluate the Hardy-Weinberg equilibrium, considering deviations with p < 0.05 as significant. RESULTS: The results showed a high probability of an association between neurodegenerative diseases such as Alzheimer’s and Parkinson’s and mercury exposure in individuals with genetic variants related to glutathione metabolism and mercury transport and excretion pathways. CONCLUSIONS: Genetic alterations or their expression involving mercury bioaccumulation, its crossing of the blood-brain barrier, central nervous system inflammation, and oxidative stress from reactive oxygen and nitrogen species increase the risk of developing Alzheimer’s and Parkinson’s disease.
Crataegus mexicana root-based supplement intoxication in a woman with weight loss persistent preoccupation: Case report.
Abad-Cuenca S
Biomedica · 2026 Mar · PMID 41875453 · Publisher ↗
Body image preoccupation is increasingly common, particularly among Latin American women, influenced by societal beauty standards favoring thinness. This often drives individuals to use unregulated weight loss supplement...
Body image preoccupation is increasingly common, particularly among Latin American women, influenced by societal beauty standards favoring thinness. This often drives individuals to use unregulated weight loss supplements, which can lead to serious health risks. This case reports a rare instance of acute diarrhea resulting from the unsupervised use of a Crataegus mexicana root-based supplement, a product frequently marketed for weight loss. A 41-year-old Hispanic woman presented to the emergency department with a 15-day history of daily diarrhea, epigastric pain, and malaise. She reported using the supplement for weight loss. Physical examination revealed moderate dehydration and localized tenderness in the precordial and epigastric regions. The diagnosis was acute diarrhea related to the herbal supplement, with moderate dehydration. The patient received intravenous saline and analgesics and was discharged in stable condition after 48 hours. Follow-up showed no recurrence of symptoms, but persistent body image concerns. This case highlights the dangers of unsupervised herbal supplement use for weight los and underscores the need for proper medical guidance when using supplements.
Acute pancreatitis due to Leptospira spp.: An uncommon case report of a common zoonosis.
López JP, Salgado CA, Morales CD
Biomedica · 2026 Mar · PMID 41875452 · Publisher ↗
Leptospirosis, a widespread zoonotic disease prevalent in tropical and subtropical regions, causes over one million cases and about 59,000 deaths annually. It is transmitted through contact with infected animal urine, pr...
Leptospirosis, a widespread zoonotic disease prevalent in tropical and subtropical regions, causes over one million cases and about 59,000 deaths annually. It is transmitted through contact with infected animal urine, primarily from rodents, and worsened by poor sanitation and favorable climate. Although in Colombia there was a significant decline in cases from 2018 to 2022, severe forms of the disease, including rare complications like acute pancreatitis, still pose significant health risks. A 49-year-old male presented with symptoms including abdominal pain, jaundice, and severe thrombocytopenia. Despite initial normal tests, leptospirosis was eventually diagnosed after further testing revealed elevated lipase levels and medical imaging confirmed severe pancreatitis. The patient received antibiotics and intensive care, which led to recovery and confirmation of leptospirosis through serology. Leptospirosis can cause severe multi-organ complications, including rare cases of pancreatitis. This case underscores the need for early diagnosis and treatment of leptospirosis to manage such complications effectively. Environmental factors and rodent control are crucial for prevention, emphasizing the importance of comprehensive management and preventive measures.
Outbreak of toxoplasmosis with pulmonary involvement in immunocompetent military population.
Reyes-Toledo R, Culma-Roa L, López MJ … +2 more , Pérez JE, Suárez-Silva D
Biomedica · 2026 Mar · PMID 41875451 · Publisher ↗
Toxoplasmosis is a common zoonotic infection with various transmission mechanisms and wide distribution worldwide. Its probability of causing disease is related to alterations in the immune system as well as the parasite...
Toxoplasmosis is a common zoonotic infection with various transmission mechanisms and wide distribution worldwide. Its probability of causing disease is related to alterations in the immune system as well as the parasite’s virulence. This study presents four cases of patients from rainforest areas in Colombia who did not have any known immunosuppression but do have a diagnosis of toxoplasmosis with pulmonary involvement, confirmed by serology. One of them also developed hypoxemic ventilatory failure and myocarditis. This outbreak of toxoplasmosis occurred in military personnel after coming into contact with common sources of exposure in the Colombian Amazon during a military training exercise. This article includes the diagnostic process, clinical manifestations, treatment, and importance of the parasite’s genotypic variants.
Current challenges in the diagnosis of neurodegenerative diseases in neurological practice.
Pardo-Turriago R
Biomedica · 2026 Mar · PMID 41875450 · Publisher ↗
Abstract loading — click title to view on PubMed.
Classification of human epidermal growth factor receptor 2 expression in cancerous breast tissue through artificial intelligence.
Villota LV, Lasso JJ, Muñoz EN … +1 more , Vargas R
Biomedica · 2025 Dec · PMID 41410332 · Full text
Introduction. Histological and molecular analysis of breast tissue is essential for the diagnosis, prognosis, and treatment of breast cancer. Key biomarkers include progesterone and estrogen receptors, as well as the hum...
Introduction. Histological and molecular analysis of breast tissue is essential for the diagnosis, prognosis, and treatment of breast cancer. Key biomarkers include progesterone and estrogen receptors, as well as the human epidermal growth factor receptor 2 (HER2). HER2 overexpression indicates an aggressive subtype of breast cancer but enables targeted therapies that improve survival rates. However, its evaluation faces challenges, ranging from sample quality to interpretation variability. The College of American Pathologists classifies HER2 overexpression into four categories, but variations around the 10% expression threshold can lead to misinterpretations. Objective. To present an automated technique for classifying HER2-overexpressing cells in histological slides. Materials and methods. The Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology was applied using samples of 89 patients from the Unidad de Diagnóstico en Patología, covering all four HER2 expression levels. Deep learning techniques were employed, leveraging neural networks and vision transformer models through transfer learning. Additionally, a usability evaluation was conducted on the final version of the software. Results. The ViT-B/16 model achieved a classification accuracy of 90,65%, while the tool was evaluated with an acceptable level of satisfaction in its clinical application. Conclusion. Artificial intelligence demonstrated high accuracy and consistency in HER2 classification, reducing diagnostic variability and improving objectivity. However, further optimization of processing efficiency is required for broader applicability.
Synthetic data within a common data model for artificial intelligence applications in maternal health: experience report in the Colombian context.
Torres-Silva EA, Gaviria-Jiménez JJ, Guevara-Zambrano AM … +2 more , Herrera-Almanza L, Flórez-Arango J
Biomedica · 2025 Dec · PMID 41410331 · Full text
INTRODUCTION: Synthetic data in healthcare is an alternative for generating clinical records that resemble those registered in real clinical scenarios. The benefits of synthetic data are: greater volume of data, the poss...
INTRODUCTION: Synthetic data in healthcare is an alternative for generating clinical records that resemble those registered in real clinical scenarios. The benefits of synthetic data are: greater volume of data, the possibility of representing specific patient populations, protection of real-data privacy, and improved data-sharing among different actors. OBJECTIVE: To formulate a synthetic data generation model for the gestational care process in Colombia and adapt it to the Observational Medical Outcomes Partnership (OMOP) common data model to facilitate its integration into artificial intelligence applications in maternal health. MATERIALS AND METHODS: We conducted a case study of fully synthetic data formulation that included some of the most frequent outcomes and conditions during gestation based on a typical care process for pregnant women in Colombia. This approach was complemented by the generation of a common data model to facilitate data integration in future artificial intelligence applications or complementary systems that benefit from a standardized language, regardless of the system or form of classification. RESULTS: We formulated a model for the synthetic generation of clinical data –applicable to real clinical settings– that spans the entire gestational care until the perinatal period. The model included the most frequent clinical conditions and outcomes, which were diagrammed in the Synthea™ tool with their corresponding clinical probabilities of occurrence based on the reported literature or the usual practice of obstetric specialists in Colombia. CONCLUSIONS: This study demonstrates that the generation of synthetic data applied to the gestational care process in Colombia was feasible and represents a pioneering contribution in the region
Knowledge-based clinical decision support system for the automated classification of anemia in hemodialysis patients.
Tenorio S, Valderrama LA, Arango-Álvarez JJ … +2 more , Lozano LA, Mojica IL
Biomedica · 2025 Dec · PMID 41410330 · Full text
INTRODUCTION: Anemia is a frequent complication in patients with chronic kidney disease undergoing hemodialysis and is associated with increased morbidity, mortality, and healthcare burden. Accurate classification is ess...
INTRODUCTION: Anemia is a frequent complication in patients with chronic kidney disease undergoing hemodialysis and is associated with increased morbidity, mortality, and healthcare burden. Accurate classification is essential to optimize treatment with intravenous iron and erythropoiesis-stimulating agents. Rule-based clinical decision support systems (CDSS) provide a strategy to standardize this process. OBJECTIVE: To describe the development and implementation of a knowledge-based clinical decision support system for the automated classification of anemia in hemodialysis patients using laboratory data. MATERIALS AND METHODS: This retrospective observational study included 883 adult patients receiving prevalent hemodialysis during 2023. An algorithm was developed based on established clinical guidelines [Sociedad Latinoamericana de Nefrología e Hipertensión (SLANH)], KDIGO, NICE to classify patients with hemoglobin below 12 g/dl into three categories: absolute iron deficiency, functional iron deficiency, and candidates for therapeutic trial with intravenous iron. The system also flagged cases with suspected severe secondary hyperparathyroidism (PTH > 800 pg/ml). Data was obtained from the laboratory information system and the clinical decision support system. We applied a descriptive statistical analysis. RESULTS: The clinical decision support system automatically classified patients into the following categories: functional iron deficiency (39.2%), severe hyperparathyroidism (26.7%), absolute iron deficiency (17.7%), and candidates for intravenous iron trial (16.4%). A subgroup (9.5% within the functional iron deficiency group) also showed elevated PTH levels, suggesting potential resistance to erythropoiesis-stimulating agents. Distinct clinical profiles were observed across the groups. CONCLUSIONS: The clinical decision support system enabled automated and standardized classification of anemia in hemodialysis patients, supporting evidence-based clinical decision-making. Its implementation represents a digital health innovation with the potential to improve the quality and safety of anemia management in chronic kidney disease.
Artificial intelligence-driven clinical guideline recommendations in maternal care: How trustworthy are they?
Pérez JJ, Giraldo-Forero AF, Rúa S … +7 more , Betancur D, Urquina Z, Castañeda P, Arango-Valencia S, Barrientos-Gómez JG, Torres-Silva EA, Orozco-Duque A
Biomedica · 2025 Dec · PMID 41410329 · Full text
INTRODUCTION: Medical staff often face difficulties in consulting and applying clinical guidelines in practice. Large language models, especially when combined with retrieval-augmented generation, may help overcome these...
INTRODUCTION: Medical staff often face difficulties in consulting and applying clinical guidelines in practice. Large language models, especially when combined with retrieval-augmented generation, may help overcome these challenges by producing context-specific outputs with improved adherence to medical guidelines. OBJECTIVES: To assess the performance of commercial large language models in answering maternal health questions within retrieval-augmented generation systems, using both human and automated evaluation metrics. MATERIAL AND METHODS: A controlled experiment was designed to obtain accurate, consistent answers from a retrieval-augmented generation system based on Colombian maternal care guidelines. A physician formulated ten questions and defined the groundtruth answers. Various large language models were tested with a standardized prompt and evaluated through binary answer-concept ranking and retrieval-augmented generation assessment, metrics, judged by two independent large language models. RESULTS: Generative pre-trained transformer 3.5 (GPT-3.5) achieved the highest physicianassessed accuracy (0.90). Claude 3.5 obtained the top faithfulness score (0.78) under GPT-4.o evaluation, while Mistral ranked highest (0.84) under Claude 3.5 evaluation. Regarding answer relevance, GPT-3.5 scored highest across both judges (0.94 and 0.86). CONCLUSIONS: Integrating retrieval-augmented generation into obstetric care has the potential to enhance evidence-based practices and improve patient outcomes. However, rigorous validation of accuracy and context-specific reliability is essential before clinical deployment. The findings of this study indicate that large-scale models (e.g., GPT-3.5, Claude, Llama 70B) consistently outperform lighter models such as Llama 8B.
Use of artificial intelligence in the diagnosis of alterations in cervical cytology: A university population-based observational study.
Manzano-Chaya JS, Mendoza-Herrera T, García-Ayala E
Biomedica · 2025 Dec · PMID 41410328 · Full text
INTRODUCTION: Conventional cervical cytology (Pap smear) remains a primary method for cervical cancer screening in Colombia, despite limitations in diagnostic yield and heavy workload. The potential of artificial intelli...
INTRODUCTION: Conventional cervical cytology (Pap smear) remains a primary method for cervical cancer screening in Colombia, despite limitations in diagnostic yield and heavy workload. The potential of artificial intelligence to address these challenges is yet to be evaluated in our population. OBJECTIVE: To evaluate and compare the discriminative ability of four artificial intelligence-based models for the detection of abnormalities in Pap smears. Materials and methods. A total of 650 images of Pap smear cells were obtained from a university cohort in northeastern Colombia. These images were subjected to diagnostic evaluation by an expert pathologist. Four artificial intelligence models (DenseNet, InceptionV3, MobileNet, and VGG19) were trained using data from a publicly available Pap smear database with digital image analysis and deep learning. The discriminative ability of the models was determined by calculating their sensitivity, specificity, and area under the curve. MATERIALS AND METHODS: MobileNet tuvo la mejor capacidad discriminativa [área bajo la curva (AUC) de 0,97) con una especificidad del 0,99 y sensibilidad de 0,78 para la detección de alteraciones en la citología cervicouterina. Por otro lado, InceptionV3 tuvo un mejor desempeño en el tamizaje, con sensibilidad del 0,93, especificidad de 0,82 y área bajo la curva de 0,947. RESULTS: MobileNet showed the highest discriminative ability (AUC = 0.97), with a specificity of 0.99 and sensitivity of 0.78 for the detection of altered cells in Pap smears. On the other hand, InceptionV3 had the best performance capabilities for screening, with a sensitivity of 0.93, specificity of 0.82, and AUC of 0.947. CONCLUSIONS: The results of this study illustrate the advantages and disadvantages of different artificial intelligence models and how their application could help improve the diagnostic performance of manual reading in cervical cancer screening or even serve as a primary screening method to rule out negative cases, by achieving a diagnostic performance comparable to that of manual reading.
Advanced artificial intelligence in piRNA and PIWI-like protein research: A systematic review of recurrent neural networks, long short-term memory, and emerging computational techniques.
Reyes JS, Guevara JD, Picón LT … +4 more , Sánchez IL, Gaona LA, Montoya MP, Pino LE
Biomedica · 2025 Dec · PMID 41410327 · Full text
INTRODUCTION: PIWI-interacting RNAs are small and non-coding RNAs involved in gene regulation and transposable element repression, emerging as critical biomarkers and therapeutic targets in oncology. Advances in artifici...
INTRODUCTION: PIWI-interacting RNAs are small and non-coding RNAs involved in gene regulation and transposable element repression, emerging as critical biomarkers and therapeutic targets in oncology. Advances in artificial intelligence, such as recurrent neural networks, long short-term memory networks, and graph convolutional networks, offer significant improvements in PIWI-interacting RNA detection. OBJECTIVES: To evaluate the performance of artificial intelligence models, including recurrent neural networks, long short-term memory, and graph convolutional networks, in detecting PIWI-interacting RNAs and assessing their implications for cancer diagnostics and prognosis. MATERIALS AND METHODS: A systematic review of 24 studies was conducted across PubMed, ScienceDirect, Scopus, and Web of Science, focusing on artificial intelligence-based approaches for PIWI-interacting RNA detection. Inclusion criteria were original articles published in English or Spanish using artificial intelligence models in clinical or experimental settings. Performance metrics such as accuracy, sensitivity, and specificity were analyzed. RESULTS: Long short-term memory models achieved the highest overall accuracy (92.3%), followed by graph convolutional networks (91.4%), support vector machines (88%), and recurrent neural networks (85.7%). Sensitivity and specificity were also highest in long short-term memory (94% and 91%, respectively). Graph convolutional networks showed superior performance in identifying PIWI-interacting RNA-disease associations with complex datasets. Support vector machine models were effective in smaller datasets but exhibited scalability limitations. CONCLUSION: Artificial intelligence models, especially long short-term memory and graph convolutional networks, significantly enhance PIWI-interacting RNA detection, supporting their application in cancer diagnostics and personalized medicine. Future studies should refine these models, address dataset biases, and explore their integration into clinical workflows.
Artificial intelligence and digital health in Colombia: outlook of the most recent advances and future challenges.
López DM, Osorio JS
Biomedica · 2025 Dec · PMID 41410326 · Full text
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Exploring the intersection of climate change, gender, and food security in Latin America.
Cediel-Becerra N, Sánchez-Arévalo D
Biomedica · 2025 Nov · PMID 41325570 · Full text
INTRODUCTION: The consequences of climate change for women in Latin American countries are more severe due to persistent gaps in education, land ownership and access to information services. These inequities heighten hea...
INTRODUCTION: The consequences of climate change for women in Latin American countries are more severe due to persistent gaps in education, land ownership and access to information services. These inequities heighten health, welfare and livelihood risks among rural women. OBJECTIVE: To describe the relationship between climate change and food security from a gender perspective in Latin America. MATERIALS AND METHODS: An exploratory review was conducted in Redalyc, SciELO, Google Scholar, EBSCO, Web of Science and Scopus. We analyzed 36 documents published between 2010 and 2022 focusing on Latin American countries RESULTS: he most frequently described extreme events were droughts, floods, rising temperatures, and landslides, all of which contributed to food supply shortages. Evidence shows persistent gaps in health, access to resources and information, security and human rights, which perpetuate social vulnerability and hinder the effectiveness of public policies addressing the impacts of climate change and the social consequences of the pandemic. Climate-related risks are particularly severe for indigenous and Afro-descendant women and girls, older women, LGBTIQ+ people, women with disabilities, women in migration contexts, and those living in rural, remote or disaster- and conflict-prone areas. CONCLUSIONS: Climate change is not gender-neutral, and there remains a gap in the implementation of gender-sensitive climate adaptation policies.
Characterization of Colombian departments based on climatic factors, infrastructure, basic service access, and dengue incidence rate.
Portilla J, Tovar-Cuevas J, Manotas D
Biomedica · 2025 Nov · PMID 41325569 · Full text
INTRODUCTION: Dengue is an endemic disease in Colombia, with spatial variations influenced by climatic, socioeconomic, and basic service access factors. Territorial characterization based on these determinants supports a...
INTRODUCTION: Dengue is an endemic disease in Colombia, with spatial variations influenced by climatic, socioeconomic, and basic service access factors. Territorial characterization based on these determinants supports a better understanding of disease distribution and enables the design of more effective control strategies. OBJECTIVES: To identify groups of departments in Colombia based on the relationship between dengue incidence rates and climatic, socioeconomic, and basic service access factors in 2023. MATERIALS AND METHODS: Data were collected from the Instituto Nacional de Salud of Colombia, the Encuesta Nacional de Calidad de Vida, and satellite sources, such as ERA5 and CHIRPS. Variables related to access to basic services (drinking water, sewage, and waste collection), housing deficit, temperature, precipitation, and the normalized difference vegetation index (NDVI) were analyzed. A multiple factor analysis was applied to reduce dimensionality, followed by hierarchical clustering and self-organizing maps to identify department groupings. RESULTS: Three groups of departments with distinct characteristics were identified. The most vulnerable group (group 3) showed an average incidence rate of 1,046.87 cases per 100,000 inhabitants, associated with extreme housing deficits, limited access to basic services, and climatic conditions favorable for vector proliferation. CONCLUSIONS: The analysis identified key territorial patterns in dengue incidence and highlighted the influence of structural factors on disease transmission. These findings provide a foundation to strengthen public policies and design more targeted prevention and control strategies in the most vulnerable regions.
Spatial modeling of soil-transmitted helminthiases in Colombia under climate change scenarios.
Olivera MJ, Porras-Villamil JF, Fuentes MV
Biomedica · 2025 Nov · PMID 41325568 · Full text
INTRODUCTION: Soil-transmitted helminthiases remain a significant public health burden in Colombia, especially in rural and tropical areas. Climate change is expected to alter environmental conditions that favor the surv...
INTRODUCTION: Soil-transmitted helminthiases remain a significant public health burden in Colombia, especially in rural and tropical areas. Climate change is expected to alter environmental conditions that favor the survival and transmission of Ascaris lumbricoides, Trichuris trichiura, and hookworms. OBJECTIVE: To estimate the current spatial distribution of these infections and project prevalence changes by 2035 under climate change scenarios, with and without public health interventions. MATERIALS AND METHODS: An ecological study with spatial modeling was conducted, integrating epidemiological, climatic, and biological data. Baseline prevalence data were obtained from the Encuesta Nacional de Parasitismo Intestinal (2012-2014). Climate projections from the ERA5-Land satellite product (2024-2035) were used alongside generalized additive models to estimate environmental suitability. A systematic review defined optimal temperature and humidity thresholds for the development of infective stages. Two scenarios were modeled: one without intervention and another with mass drug administration and improved sanitation. RESULTS: Baseline prevalence was 11.3% for A. lumbricoides, 18.4% for T. trichiura, and 6.4% for hookworms, with highest rates in Amazonia and the Sierra Nevada de Santa Marta. In a no-intervention scenario, projected prevalences increased to 13.6, 21.2, and 8.0%, respectively. The intervention scenario reduced these to 6.8%, 12.7%, and 5.6%. Temperature and humidity were strong positive predictors (p < 0.01), while altitude and forest cover showed negative associations. CONCLUSIONS: Climate change may intensify soil-transmitted helminthiases transmission in Colombia by 2035. However, sustained control strategies could significantly mitigate this impact. Spatial modeling offers a valuable tool to guide targeted interventions and inform public health planning.
Dengue incidence and its relationship with El Niño oceanic index, as a sensitive variable to anticipate outbreaks in the Colombian Caribbean region.
Salazar-Ceballos A, Álvarez-Miño L
Biomedica · 2025 Nov · PMID 41325567 · Full text
INTRODUCTION: The Lancet Countdown 2023 report for Latin America indicates that rising temperatures influence the transmission of the dengue virus. In Colombia’s Caribbean region, a significant association has been ident...
INTRODUCTION: The Lancet Countdown 2023 report for Latin America indicates that rising temperatures influence the transmission of the dengue virus. In Colombia’s Caribbean region, a significant association has been identified between dengue incidence and climatic variables, such as temperature, humidity, and precipitation. OBJECTIVE: To analyze the relationship between the incidence of dengue and the oceanic Niño index in the departments of the Colombian Caribbean region from 2021 to 2023. MATERIALS AND METHODS: An ecological time series study was conducted using distributed lag non-linear models and autoregressive integrated moving average models in the seven departments of the Caribbean region. Descriptive and autoregressive analyses were performed using JASP and RStudio. Non-linear and lagged analyses were run with the dlnmpackage in RStudio. RESULTS: A positive and significant relationship between the oceanic Niño index and dengue incidence was found for 2023 data, the year when the El Niño - ENSO (El Niño-Southern Oscillation) warm phase occurred. Bolívar, Cesar, Córdoba, and Magdalena departments showed positive correlations. A non-linear relationship between El Niño/La Niña and dengue incidence was also observed, with a higher increase in dengue cases during El Niño events. CONCLUSIONS: The oceanic Niño index appears to be a useful climatic indicator for monitoring increases in the monthly dengue incidence rate in the analyzed departments of Colombia’s Caribbean región.
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