Puntaje de riesgo finlandés para detección de disglucemia en adultos en Unidad de Medicina Familiar

Establecer la capacidad discriminativa del puntaje de riesgo finlandés para disglucemia en usuarios de una unidad de medicina familiar localizada en zona conurbana del Estado de Guerrero, México. Material y métodos: Realizamos un estudio transversal de marzo a diciembre del 2021 en una Unidad de Medicina Familiar. Previo consentimiento informado aplicamos a 200 personas de 20 a 60 años, el puntaje de riesgo finlandés para detección de disglucemia, obtuvimos medidas somatométricas y cifras de glucosa plasmática en ayuno. Estimamos sensibilidad, especificidad, valor predictivo positivo y negativo, razón de verosimilitud positiva y negativa, y calculamos el área bajo la curva (AUC) para estimar la capacidad discriminativa del puntaje de riesgo, donde la prueba de referencia fue la glucosa en ayuno. Realizamos análisis bivariado para identificar factores asociados a disglucemia, obteniendo Odds Ratio (OR), e intervalos de confianza del 95 % (IC95%). La ocurrencia de disglucemia fue de 26.5 % (53/200). El AUC de la curva ROC del puntaje finlandés para disglucemia fue de 0.65 (IC95% 0.57-0.74). Los factores asociados a diabetes fueron ≥40 años (OR 2.1; IC95% 1.1-3.9), índice de masa corporal ≥25 Kg/m2 (OR 2.8; IC95% 1.2-6.7) y padecer hipertensión arterial (OR 2.2; IC95% 1.1-4.4). El FINDRISC demostró por AUC ser una mala herramienta para detectar personas en riesgo de padecer disglucemia, en población adscrita a unidad médica conurbana.

To establish the discriminative capacity of the Finnish risk score for dysglycemia in users of a family medicine unit located in the suburbs of the State of Guerrero, Mexico. We conducted a cross-sectional study from March to December 2021 in a Family Medicine Unit. With prior informed consent, we applied the Finnish risk score for the detection of dysglycemia to 200 people between the ages of 20 and 60, we obtained somatometric measurements and fasting plasma glucose figures. We estimated sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, and calculated the area under the curve (AUC) to estimate the discriminative ability of the risk score, where the reference test was fasting glucose. We performed bivariate analysis to identify factors associated with dysglycemia, obtaining Odds Ratio (OR) and 95% confidence intervals (95%CI). Result: The occurrence of dysglycemia was 26.5% (53/200). The AUC of the ROC curve of the Finnish score for dysglycemia was 0.65 (95%CI 0.57-0.74). The factors associated with diabetes were ≥40 years (OR 2.1; 95%CI 1.1-3.9), body mass index ≥25 Kg/m2 (OR 2.8; 95%CI 1.2-6.7) and suffering from arterial hypertension (OR 2.2; 95%CI 1.1 -4.4). The FINDRISC was shown by AUC to be a poor tool for detecting people at risk of suffering from dysglycemia, in a population attached to a suburban medical unit

SARS-CoV-2 Reinfection among Healthcare Workers in Mexico: Case Report and Literature Review.

Since the onset of the COVID-19 pandemic, there have been multiple questions regarding reinfections associated with SARS-CoV-2. Healthcare workers on duty, due to overexposure in environments where there are more cases of COVID-19, are more prone to become infected by this virus. Here, we report 4 cases that meet the definition of clinical reinfection by SARS-CoV-2, as well as a literature review on this subject; all occurred in healthcare workers in Acapulco Guerrero, Mexico who provide their services in a hospital that cares for patients with COVID-19. The time between the manifestation of the first and second infection for each case was 134, 129, 107 and 82 days, all patients presented symptomatology in both events. The time between remission of the first infection and onset of second infection was 108, 109, 78 and 67 days for each case, while the time to confirmation by reverse transcription polymerase chain reaction (RT-PCR) between infections was 134, 124, 106 and 77 days. In two of the four cases the reinfection resulted in a more severe case, while in the remaining two cases the manifestation of symptoms and complications was similar to that presented in the first infection. Given this scenario, greater care is needed in the management of the pandemic caused by SARS-CoV-2 to protect healthcare workers and the general public from risks and complications caused by a possible reinfection by SARS-CoV-2.

DISTATIS: A Promising Framework to Integrate Distance Matrices in Molecular Phylogenetics.

BACKGROUND: Molecular phylogenetic algorithms frequently disagree with the approaches considering reproductive compatibility and morphological criteria for species delimitation. The question stems if the resulting species boundaries from molecular, reproductive and/or morphological data are definitively not reconcilable; or if the existing phylogenetic methods are not sensitive enough to agree morphological and genetic variation in species delimitation. OBJECTIVE: We propose DISTATIS as an integrative framework to combine alignment-based (AB) and alignment-free (AF) distance matrices from ITS2 sequences/structures to shed light whether Gelasinospora and Neurospora are sister but independent genera. METHODS: We aimed at addressing this standing issue by harmonizing genus-specific classification based on their ascospore morphology and ITS2 molecular data. To validate our proposal, three phylogenetic approaches: i) traditional alignment-based, ii) alignment-free and iii) novel distance integrative (DI)-based were comparatively evaluated on a set of Gelasinospora and Neurospora species. All considered species have been extensively characterized at both the morphological and reproductive levels and there are known incongruences between their ascospore morphology and molecular data that hampers genus-specific delimitation. RESULTS: Traditional AB phylogenetic analyses fail at resolving the Gelasinospora and Neurospora genera into independent monophyletic clades following ascospore morphology criteria. In contrast, AF and DI approaches produced phylogenetic trees that could properly delimit the expected monophyletic clades. CONCLUSION: The DI approach outperformed the AF one in the sense that it could also divide the Neurospora species according to their reproduction mode.