Corno cutâneo: estudo histopatológico retrospectivo de 222 casos

FUNDAMENTOS: O corno cutâneo é lesão acentuadamente hiperqueratótica, cônica e circunscrita, que pode ocultar tanto lesões benignas como malignas. OBJETIVO: Identificar histopatologicamente as principais dermatoses que se apresentam clinicamente como corno cutâneo. MÉTODOS: Estudo histopatológico retrospectivo de 222 cornos cutâneos, a partir de laudos anatomopatológicos do Hospital de Clínicas de Uberlândia entre os anos de 1990 e 2006. RESULTADOS: A média de idade dos pacientes foi de 67,42 anos. O sexo feminino foi mais acometido (64,86%). O tempo médio de evolução foi de 16,92 meses. As localizações mais frequentes das lesões foram: cabeça (35,14%) e membros superiores (31,08%). Observaram-se lesões histopatologicamente benignas em 41,44% e lesões prémalignas ou malignas em 58,56% dos cornos cutâneos estudados. Entre as lesões pré-malignas, a queratose actínica foi encontrada em 83,84% dos casos; entre as malignas, o carcinoma espinocelular correspondeu a 93,75% dos casos. CONCLUSÕES: Este estudo mostrou que a maioria dos cornos cutâneos surgiu sobre áreas do corpo expostas à luz solar, predominantemente, cabeça e membros superiores. Considerando-se a elevada frequência de lesões prémalignas e também a presença de lesões malignas, sugere-se exérese cirúrgica seguida de estudo histopatológico dos cornos cutâneos, para confirmação de diagnóstico específico

Translocation and post-release monitoring of captive-raised Blue-fronted Amazons Amazona aestiva.

Translocation is a useful tool for the conservation of endangered species, because it enables individuals to be moved between wild populations and between captivity and the wild. The use of captive-raised animals in these processes is sometimes the only option to recover a declining population, but captive-raised parrots are commonly seen as the worst candidates for release because they lose their ability to recognize predators, to find food in the wild and to socialize with conspecifics. The Blue-fronted Amazon Amazona aestiva is one of the most popular parrot species in captivity. Thirty-one parrots were soft released and monitored during 13 continuous months in a Cerrado area (savannahlike vegetation) of Minas Gerais State, southeastern Brazil. Three released parrots (10%) were confirmed to die and five (16%) disappeared soon after release and no behavioral recordings or data about their destinations were available. Ten parrots (32%) showed behaviors that suggest adaptation to the wild and 13 individuals (42%) expressed behaviors more typical of captivity. Difficulties in settling were observed for the parrots after release. One released pair, and one female paired with a wild male, reproduced. There was a tendency to decrease in all captive-related behaviors and to increase in wild-related behaviors since time after release. Supplementary food use diminished as the parrots explored natural food resources. This study indicates that confiscated captive-raised parrots can be good candidates for translocation if a training program could be applied prior to their release to reduce undesirable behaviors and the chance of re-capturing by humans. Furthermore, the use of non-endangered species in conservation programs can be useful to create protocols for the conservation programs of rare and endangered species

Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

Abstract Background Acute kidney injury (AKI) is frequently associated with COVID-19, and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalised COVID-19 patients, and to assess the incidence of AKI and KRT requirement. Methods This study is part of a multicentre cohort, the Brazilian COVID-19 Registry. A total of 5212 adult COVID-19 patients were included between March/2020 and September/2020. Variable selection was performed using generalised additive models (GAM), and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. Accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results The median age of the model-derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalisation. The temporal validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. The geographic validation cohort had similar age and sex; however, this cohort had higher rates of ICU admission, AKI, need for KRT and in-hospital mortality. Four predictors of the need for KRT were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation and diabetes. The MMCD score had excellent discrimination in derivation (AUROC 0.929, 95% CI 0.918–0.939) and validation (temporal AUROC 0.927, 95% CI 0.911–0.941; geographic AUROC 0.819, 95% CI 0.792–0.845) cohorts and good overall performance (Brier score: 0.057, 0.056 and 0.122, respectively). The score is implemented in a freely available online risk calculator ( https://www.mmcdscore.com/ ). Conclusions The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalised COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation

ABC-SPH risk score for in-hospital mortality in COVID-19 patients : development, external validation and comparison with other available scores

The majority of available scores to assess mortality risk of coronavirus disease 2019 (COVID-19) patients in the emergency department have high risk of bias. Therefore, this cohort aimed to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients and to compare this score with other existing ones. Consecutive patients (≥ 18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Median (25-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO/FiO ratio, platelet count, and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829-0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833-0.885]) and Spanish (0.894 [95% CI 0.870-0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). An easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation was designed and validated for early stratification of in-hospital mortality risk of patients with COVID-19