Journal of investigative medicine : the official publication of the American Federation for Clinical Research
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Erythropoietin (EPO) resistance is frequently reported in hemodialysis (HD) patients. Metabolic syndrome (MetS) is a common biochemical condition that comprises central obesity, dyslipidemia, hypertension, and hyperglycemia. The present study aimed to assess the relation between MetS and EPO resistance in HD patients. ⋯ Multivariate logistic regression analysis identified lower albumin levels (OR (95% CI): 0.072 (0.016-0.313), p < 0.001), higher ferritin levels (OR (95% CI): 1.05 (1.033-1.066), p< 0.001), higher hsCRP levels (OR (95% CI): 1.041 (1.007-1.077), p = 0.018), and MetS (OR (95% CI): 36.68 (2.893-465.05), p = 0.005) as predictors of EPO resistance in the studied patients. The present study identified MetS as a predictor of EPO resistance in HD patients. Other predictors include serum ferritin, hsCRP, and albumin levels.
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Multicenter Study Clinical Trial Observational Study
A prospective observational multicentric clinical trial to evaluate microscopic examination of acid-fast bacilli in sputum by artificial intelligence-based microscopy system.
Microscopy-based tuberculosis (TB) diagnosis i.e., Ziehl-Neelsen (ZN) stained smear screening still remains the primary diagnostic method in resource poor and high TB burden countries, however itrequires considerable experience and is bound to human errors. In remote areas, wherever expert microscopist is not available, timely diagnosis at initial level is not possible. Artificial intelligence (AI)-based microscopy may be a solution to this problem. ⋯ All the smears were observed by 3 microscopist and the AI based microscopy system. AI based microscopy was found to have a sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy of 89.25%, 92.15%, 75.45%, 96.94%, 91.53% respectively. AI based sputum microscopy has an acceptable degree of accuracy, PPV, NPV, specificity and sensitivity and thus may be used as a screening tool for the diagnosis of pulmonary tuberculosis.
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There is little information on the differential diagnosis and prognosis of hospitalized patients with hyperbilirubinemia. Here, we hypothesized that hyperbilirubinemia in hospitalized patients is associated with specific diseases and outcomes. This retrospective cohort analysis included patients admitted to the Medical University of South Carolina with a total bilirubin >3 mg/dL from January 9, 2015 to August 25, 2017. ⋯ Overall, the mortality/discharge to hospice rate in patients with a bilirubin >3 mg/dL was 30%, and was proportional to the severity of hyperbilirubinemia, including when controlling for the underlying severity of illness. Mortality was highest in patients with primary liver disease and malignancy and was lowest in patients with non-cancerous obstruction or hemolytic jaundice. Hyperbilirubinemia in hospitalized patients is most often due to primary liver disease, and identifies patients with a poor prognosis, particularly when caused by primary liver disease or cancer.
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Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects several organs and causes variable clinical symptoms. Early diagnosis is currently the most effective way to save the lives of patients with SLE. But it is very difficult to detect in the early stages of the disease. ⋯ It should be noted that the proposed system showed a higher area under the curve (90%) and a balanced accuracy (90%) than the other machine learning methods. This study shows the usefulness of ML techniques for identifying and predicting SLE patients. These results demonstrate the possibility of developing automatic diagnostic support systems for SLE patients based on machine learning techniques.
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This study aimed to develop and validate a simple-to-use nomogram for predicting the delayed radiographic recovery in children with mycoplasma pneumoniae pneumonia (MPP) complicated with atelectasis. A retrospective study of 306 children with MPP complicated with atelectasis was performed at the Children's Hospital of Chongqing Medical University from February 2017 to March 2020. The patients were divided into recovery group and delayed recovery group based on chest CT scan 1 month after discharge. ⋯ The calibration curve demonstrated that the nomogram was well-fitted, and decision curve analysis (DCA) showed that the nomogram was clinically beneficial. This study developed and validated a simple-to-use nomogram for predicting delayed radiographic recovery in children with MPP complicated with atelectasis. This might be generally applied in clinical practice.