Potential and limitations of machine meta-learning (ensemble) methods for predicting COVID-19 mortality in a large inhospital Brazilian dataset.

The majority of early prediction scores and methods to predict COVID-19 mortality are bound by methodological flaws and technological limitations (e.g., the use of a single prediction model). Our aim is to provide a thorough comparative study that tackles those methodological issues, considering multiple techniques to build mortality prediction models, including modern machine learning (neural) algorithms and traditional statistical techniques, as well as meta-learning (ensemble) approaches. This study used a dataset from a multicenter cohort of 10,897 adult Brazilian COVID-19 patients, admitted from March/2020 to November/2021, including patients [median age 60 (interquartile range 48-71), 46% women]. We also proposed new original population-based meta-features that have not been devised in the literature. Stacking has shown to achieve the best results reported in the literature for the death prediction task, improving over previous state-of-the-art by more than 46% in Recall for predicting death, with AUROC 0.826 and MacroF1 of 65.4%. The newly proposed meta-features were highly discriminative of death, but fell short in producing large improvements in final prediction performance, demonstrating that we are possibly on the limits of the prediction capabilities that can be achieved with the current set of ML techniques and (meta-)features. Finally, we investigated how the trained models perform on different hospitals, showing that there are indeed large differences in classifier performance between different hospitals, further making the case that errors are produced by factors that cannot be modeled with the current predictors.

Hypothyroidism does not lead to worse prognosis in COVID-19: findings from the Brazilian COVID-19 registry.

BACKGROUND: It is not clear whether previous thyroid diseases influence the course and outcomes of COVID-19. METHODS: The study is a part of a multicentric cohort of patients with confirmed COVID-19 diagnosis from 37 hospitals. Matching for age, sex, number of comorbidities, and hospital was performed for the paired analysis. RESULTS: Of 7,762 patients with COVID-19, 526 had previously diagnosed hypothyroidism and 526 were matched controls. The median age was 70 years, and 68.3% were females. The prevalence of comorbidities was similar, except for coronary and chronic kidney diseases that were higher in the hypothyroidism group (p=0.015 and p=0.001). D-dimer levels were lower in patients with hypothyroid (p=0.037). In-hospital management was similar, but hospital length-of-stay (p=0.029) and mechanical ventilation requirement (p=0.006) were lower for patients with hypothyroidism. There was a trend of lower in-hospital mortality in patients with hypothyroidism (22.1% vs 27.0%; p=0.062). CONCLUSION: Patients with hypothyroidism had a lower requirement of mechanical ventilation and showed a trend of lower in-hospital mortality. Therefore, hypothyroidism does not seem to be associated with a worse prognosis.

Predictors of venous thromboembolism in COVID-19 patients: results of the COVID-19 Brazilian Registry.

Previous studies that assessed risk factors for venous thromboembolism (VTE) in COVID-19 patients have shown inconsistent results. Our aim was to investigate VTE predictors by both logistic regression (LR) and machine learning (ML) approaches, due to their potential complementarity. This cohort study of a large Brazilian COVID-19 Registry included 4120 COVID-19 adult patients from 16 hospitals. Symptomatic VTE was confirmed by objective imaging. LR analysis, tree-based boosting, and bagging were used to investigate the association of variables upon hospital presentation with VTE. Among 4,120 patients (55.5% men, 39.3% critical patients), VTE was confirmed in 6.7%. In multivariate LR analysis, obesity (OR 1.50, 95% CI 1.11-2.02); being an ex-smoker (OR 1.44, 95% CI 1.03-2.01); surgery ≤ 90 days (OR 2.20, 95% CI 1.14-4.23); axillary temperature (OR 1.41, 95% CI 1.22-1.63); D-dimer ≥ 4 times above the upper limit of reference value (OR 2.16, 95% CI 1.26-3.67), lactate (OR 1.10, 95% CI 1.02-1.19), C-reactive protein levels (CRP, OR 1.09, 95% CI 1.01-1.18); and neutrophil count (OR 1.04, 95% CI 1.005-1.075) were independent predictors of VTE. Atrial fibrillation, peripheral oxygen saturation/inspired oxygen fraction (SF) ratio and prophylactic use of anticoagulants were protective. Temperature at admission, SF ratio, neutrophil count, D-dimer, CRP and lactate levels were also identified as predictors by ML methods. By using ML and LR analyses, we showed that D-dimer, axillary temperature, neutrophil count, CRP and lactate levels are risk factors for VTE in COVID-19 patients.

Tumoural form of Whipple's disease simulating carcinomatosis.

Whipple's disease is a rare disease caused by the actinomycete bacteria Tropheryma whipplei, which cause intestinal infection. The most common symptoms are chronic diarrhoea, weight loss, abdominal pain, arthritis and neurological abnormalities, which can be fatal. This paper reports a case of a 57-year-old Brazilian woman with diarrhoea, vomiting, abdominal pain, appetite loss, intermittent fever, malaise, weight loss and malnutrition. Migratory polyarthralgia and recurrent visual scotomas preceded the symptoms. The retroperitoneal pseudotumour formation finding was associated with prolonged wasting syndrome, which did not respond to usual therapies, thus leading to the investigation of carcinomatosis disease. After laparotomy, biopsy and histochemical study of the lesions with negative results for malignancy, we proceeded to the investigation of Whipple's disease, which was then confirmed. The patient improved clinically and started gaining weight after using ceftriaxone (IV).

Tumoural form of Whipple's disease simulating carcinomatosis

Whipple's disease is a rare disease caused by the actinomycete bacteria Tropheryma whipplei, which cause intestinal infection. The most common symptoms are chronic diarrhoea, weight loss, abdominal pain, arthritis and neurological abnormalities, which can be fatal. This paper reports a case of a 57-year-old Brazilian woman with diarrhoea, vomiting, abdominal pain, appetite loss, intermittent fever, malaise, weight loss and malnutrition. Migratory polyarthralgia and recurrent visual scotomas preceded the symptoms. The retroperitoneal pseudotumour formation finding was associated with prolonged wasting syndrome, which did not respond to usual therapies, thus leading to the investigation of carcinomatosis disease. After laparotomy, biopsy and histochemical study of the lesions with negative results for malignancy, we proceeded to the investigation of Whipple's disease, which was then confirmed. The patient improved clinically and started gaining weight after using ceftriaxone (IV).