Assuntos
Anticorpos Monoclonais Humanizados , Artrite Psoriásica , Penfigoide Bolhoso , Psoríase , Humanos , Anticorpos Monoclonais Humanizados/uso terapêutico , Artrite Psoriásica/tratamento farmacológico , Penfigoide Bolhoso/tratamento farmacológico , Penfigoide Bolhoso/patologia , Psoríase/tratamento farmacológico , Resultado do Tratamento , Masculino , Feminino , Pessoa de Meia-IdadeRESUMO
OBJECTIVES: Identify risk factors associated with increased hospital admission and mortality due to dengue fever (DF), and estimate the risk magnitude associated with each individual variable. METHODS: Records of patients diagnosed with dengue were obtained from the Mexican National Epidemiological Surveillance System. Descriptive statistics were performed in all variables. Demographic characteristics and comorbidities were compared between patients based on type of care and mortality. Multivariable analysis was done with a logistic regression model, using two different outcomes: hospitalization and mortality. RESULTS: A total of 24,495 patients were included in the analysis, with a DF case fatality rate of 0.58%. Patients younger than 10 and older than 60, were found to have a greater risk of both hospitalization and mortality due to DF. Comorbidities associated with a higher risk for hospital admission include cirrhosis, CKD, immunosuppression, diabetes, and hypertension. For mortality, CKD, diabetes, and hypertension were identified as risk factors, along with pregnancy. CONCLUSION: Identification of risk factors associated with increased hospitalization and mortality due to DF can help categorize patients that require close monitoring and inpatient care. Early identification of warning signs and patients at increased risk is key to avoiding delay of supportive care.
Assuntos
Dengue , Comorbidade , Dengue/epidemiologia , Feminino , Hospitalização , Humanos , Gravidez , Estudos Retrospectivos , Fatores de RiscoRESUMO
BACKGROUND: Early identification of different COVID-19 clinical presentations may depict distinct pathophysiological mechanisms and guide management strategies. OBJECTIVE: To determine the aggressiveness of SARS-CoV-2 using symptom progression in COVID-19 patients. DESIGN: Historic cohort study of Mexican patients. Data from January-April 2020 were provided by the Health Ministry. SETTING: Population-based. Patients registered in the Epidemiologic Surveillance System in Mexico. PARTICIPANTS: Subjects who sought medical attention for clinical suspicion of COVID-19. All patients were subjected to RT-PCR testing for SARS-CoV-2. MEASUREMENTS: We measured the Period between initial symptoms and clinical progression to COVID-19 suspicion (PISYCS) and compared it to the primary outcomes (mortality and pneumonia). RESULTS: 65,500 patients were included. Reported fatalities and pneumonia were 2176 (3.32%), and 11568 (17.66%), respectively. According to the PISYCS, patients were distributed as follows: 14.89% in <24 hours, 43.25% between 1-3 days, 31.87% between 4-7 days and 9.97% >7 days. The distribution for mortality and pneumonia was 5.2% and 22.5% in <24 hours, 2.5% and 14% between 1-3 days, 3.6% and 19.5% between 4-7 days, 4.1% and 20.6% >7 days, respectively (p<0.001). Adjusted-risk of mortality was (OR [95% CI], p-value): <24 hours = 1.75 [1.55-1.98], p<0.001; 1-3 days = 1 (reference value); 4-7 days = 1.53 [1.37-1.70], p<0.001; >7 days = 1.67 [1.44-1.94], p<0.001. For pneumonia: <24 hours = 1.49 [1.39-1.58], p<0.001; 1-3 days = 1; 4-7 days = 1.48 [1.41-1.56], p<0.001; >7 days = 1.57 [1.46-1.69], p<0.001. LIMITATIONS: Using a database fed by large numbers of people carries the risk of data inaccuracy. However, this imprecision is expected to be random and data are consistent with previous studies. CONCLUSION: The PISYCS shows a U-shaped SARS-CoV-2 aggressiveness pattern. Further studies are needed to corroborate the time-related pathophysiology behind these findings.
Assuntos
COVID-19/patologia , Adulto , Idoso , Idoso de 80 Anos ou mais , COVID-19/epidemiologia , COVID-19/mortalidade , Estudos de Coortes , Progressão da Doença , Feminino , Humanos , Masculino , México , Pessoa de Meia-Idade , Mortalidade/tendências , Pacientes/estatística & dados numéricosRESUMO
Chlorosis level is a useful parameter to assess imidazolinone resistance in sunflower (Helianthus annuus L.). The aim of this study was to quantify chlorosis through two different methods in sunflower plantlets treated with imazapyr. The genotypes used in this study were two inbred lines reported to be different in their resistance to imidazolinones. Chlorosis was evaluated by spectrophotometrical quantification of photosynthetic leaf pigments and by a bioinformatics-based color analysis. A protocol for pigment extraction was presented which improved pigment stability. Chlorophyll amount decreased significantly when both genotypes were treated with 10 µM of imazapyr. Leaf color was characterized using Tomato Analyzer(®) color test software. A significant positive correlation between color reduction and chlorophyll concentration was found. It suggests that leaf color measurement could be an accurate method to estimate chlorosis and infer chlorophyll levels in sunflower plants. These results highlight a strong relationship between imidazolinone-induced chlorosis and variations in leaf color and in chlorophyll concentration. Both methods are quantitative, rapid, simple, and reproducible. Thus, they could be useful tools for phenotyping and screening large number of plants when breeding for imidazolinone resistance in this species.
RESUMO
El presente trabajo se realizó con el fin de construir un algoritmo para detectar estudiantes con alto riesgo de fracaso académico e identificar los mejores predictores del rendimiento. Se caracterizaron los estudiantes que ingresaron en el primer año en el ICBP "Victoria de Girón" durante el curso 2001-2002 de acuerdo con su índice académico del preuniversitario, índice escalafonario, exámenes de ingreso, prueba de inteligencia y un indicador de su motivación profesional. Se emplearon árboles de clasificación para identificar los predictores relevantes y sus puntos de corte óptimos. Se utilizó un modelo de regresión ordinal para evaluar la importancia relativa de los predictores y proponer el algoritmo de predicción. A partir del índice escalafonario, exclusivamente, se obtuvo un procedimiento de clasificación, que permitió identificar a los estudiantes de mayor riesgo de fracaso académico. Los puntos de corte fueron 87 y 91 puntos, que definen una tricotomía para el pronóstico del rendimiento
This paper is aimed at constructing an algorithm to detect students at high risk for academic failure and at identifying the best preformance predictors. The students that were admitted in the first year at Victoria de Girón Institute of Preclinical Basic Sciences during the course 2001-2002 were characterized according to their preuniversity academic index, roster index, admission test, intelligence test and an indicator of their professional motivation. Classification trees were used to identify the relevant predictors and their optimal cut-off points. A model of ordinal regression was used to evaluate the relative importance of the predictors and to propose the prediction algorithm.Starting only from the roster index, it was obtained a classification procedure that allowed to identify students at the highest risk for academic failure. The cut-offs were 87 and 91 points, which define a trichotomy for the performance prognosis.