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Query: UMLS:C0019079 (hemoptysis)
 6,129 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

This study developed a clinical score based on clinical and radiographic data for the diagnosis of smear-negative pulmonary tuberculosis (SNPT). SNPT was defined as a positive culture in Ogawa in a patient with two negative sputum smears. Data from patients admitted to the emergency ward with respiratory symptoms and negative acid-fast bacilli (AFB) smears was analyzed by means of logistic regression to develop the predictive score.Two hundred and sixty two patients were included. Twenty patients had SNPT. The variables included in the final model were hemoptysis, weight loss, age > 45 years old, productive cough, upper-lobe infiltrate, and miliary infiltrate. With those, a score was constructed. The score values ranged from -2 to 6. The area under the curve for the ROC curve was 0.83 (95% CI 0.74-0.90). A score of value 0 or less was associated with a sensitivity of 93% and a score of more than 4 points was associated with a specificity of 92% for SNPT. Fifty-two point twenty-nine percent of patients had scores of less than one or more than four, what provided strong evidence against and in favor, respectively, for the diagnosis of SNPT. The score developed is a cheap and useful clinical tool for the diagnosis of SNPT and can be used to help therapeutic decisions in patients with suspicion of having SNPT.
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PMID:Development of a clinical scoring system for the diagnosis of smear-negative pulmonary tuberculosis. 1864 49

OBJECTIVE. The purpose of this study was to develop an effective nomogram and artificial neural network (ANN) model for predicting recurrent hemoptysis after bronchial artery embolization (BAE). MATERIALS AND METHODS. The institutional ethics review boards of the two participating hospitals approved this study. Patients with hemoptysis who were treated with BAE were allocated to either the training cohort (Hospital A) or the validation cohort (Hospital B). The predictors of recurrent hemoptysis were identified by univariable and multivariable analyses in the training cohort. A nomogram and ANN model were then developed, and the accuracy was validated by the Harrell C statistic and ROC curves in both the training and validation cohorts. RESULTS. A total of 242 patients (training cohort, 141; validation cohort, 101) were enrolled in this study. The univariable and multivariable analyses revealed that age of 60 years old or older (hazard ratio [HR], 3.921; 95% CI, 1.267-12.127; p = 0.018), lung cancer (HR, 18.057; 95% CI, 4.124-79.068; p < 0.001), bronchial-pulmonary shunts (HR, 11.981; 95% CI, 2.593-55.356; p = 0.001), and nonbronchial systemic artery involvement (HR, 4.194; 95% CI, 1.596-11.024; p = 0.004) were predictors of recurrent hemoptysis. The developed nomogram and ANN model had high accuracy, with a Harrell C statistic of 0.849 (95% CI, 0.778-0.919) internally (for the training cohort) and 0.799 (95% CI, 0.701-0.897) externally (for the validation cohort). The optimal cutoff value of the recurrent hemoptysis risk was 0.16. CONCLUSION. The nomogram and ANN model could effectively predict the risk for recurrent hemoptysis after BAE. Further interventions should be considered for patients with a high suspicion of risk (> 0.16) according to the nomogram.
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PMID:Recurrent Hemoptysis After Bronchial Artery Embolization: Prediction Using a Nomogram and Artificial Neural Network Model. 3305 41