Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

Long-term efficacy of a rural community-based integrated intervention for prevention and management of chronic obstructive pulmonary disease: a cluster randomized controlled trial in China's rural areas

This study aimed to assess the efficacy of a rural community-based integrated intervention for early prevention and management of chronic obstructive pulmonary disease (COPD) in China. This 18-year cluster-randomized controlled trial encompassing 15 villages included 1008 patients (454 men and 40 women in the intervention group [mean age, 54 ± 10 years]; 482 men and 32 women in the control group [mean age, 53 ± 10 years]) with confirmed COPD or at risk for COPD. Villages were randomly assigned to the intervention or the control group, and study participants residing within the villages received treatment accordingly. Intervention group patients took part in a program that included systematic health education, smoking cessation counseling, and education on management of COPD. Control group patients received usual care. The groups were compared after 18 years regarding the incidence of COPD, decline in lung function, and mortality of COPD. COPD incidence was lower in the intervention group than in the control group (10% vs 16%, <0.05). A decline in lung function was also significantly delayed in the intervention group compared to the control group of COPD and high-risk patients. The intervention group showed significant improvement in smoking cessation compared with the control group, and smokers in the intervention group had lower smoking indices than in the control group (350 vs 450, <0.05). The intervention group also had a significantly lower cumulative COPD-related death rate than the control group (37% vs 47%, <0.05). A rural community-based integrated intervention is effective in reducing the incidence of COPD among those at risk, delaying a decline in lung function in COPD patients and those at risk, and reducing mortality of COPD.