Background Mycoplasma pneumoniae （M. pneumoniae） is a frequent cause of respiratory tract infections. However,there is deficient knowledge about the clinical manifestations of M. pneumoniae infection. We described t...Background Mycoplasma pneumoniae （M. pneumoniae） is a frequent cause of respiratory tract infections. However,there is deficient knowledge about the clinical manifestations of M. pneumoniae infection. We described the clinical and laboratory findings of M. pneumoniae pneumonia in hospitalized children who were all diagnosed by a ≥ fourfold increase in antibody titer.Methods M. pneumoniae antibodies were routinely detected in children admitted with acute respiratory infection during a one-year period. The medical history was re-collected from children whose M. pneumoniae antibody titer increased≥fourfold at the bedside by a single person, and their frozen paired serum samples were measured again for the M.pneumoniae antibody titer.Results Of the 635 children whose sera were detected for the M. pneumoniae antibody, paired sera were obtained from 82 and 29.3% （24/82） showed a ≥ fourfold increase in antibody titer. There were 24 cases, nine boys and 15 girls, aged from two to 14 years, whose second serum samples were taken on day 9 at the earliest after symptom onset; the shortest interval was three days. All children presented with a high fever （≥38.5℃） and coughing. Twenty-one had no nasal obstruction or a runny nose, and five had mild headaches which all were associated with the high fever. The disease was comparatively severe if the peak temperature was ＞39.5℃. All were diagnosed as having pneumonia through chest X-rays. Four had bilateral or multilobar involvement and their peak temperatures were all ≤ 39.5℃. None of the children had difficulty in breathing and all showed no signs of wheezing.Conclusions The second serum sample could be taken on day 9 at the earliest after symptom onset meant that paired sera could be used for the clinical diagnosis of M. pneumoniae pneumonia in children at the acute stage. M. pneumoniae is a lower respiratory tract pathogen. Extrapulmonary complications were rare and minor in our study. High peak temperature （＞39.5℃） is correlated with the severity of M. pneumoniae pneumonia in children.展开更多
Background Various methods can be applied to build predictive models for the clinical data with binary outcome variable. This research aims to explore the process of constructing common predictive models, Logistic reg...Background Various methods can be applied to build predictive models for the clinical data with binary outcome variable. This research aims to explore the process of constructing common predictive models, Logistic regression （LR）, decision tree （DT） and multilayer perceptron （MLP）, as well as focus on specific details when applying the methods mentioned above： what preconditions should be satisfied, how to set parameters of the model, how to screen variables and build accuracy models quickly and efficiently, and how to assess the generalization ability （that is, prediction performance） reliably by Monte Carlo method in the case of small sample size.展开更多
文摘Background Mycoplasma pneumoniae （M. pneumoniae） is a frequent cause of respiratory tract infections. However,there is deficient knowledge about the clinical manifestations of M. pneumoniae infection. We described the clinical and laboratory findings of M. pneumoniae pneumonia in hospitalized children who were all diagnosed by a ≥ fourfold increase in antibody titer.Methods M. pneumoniae antibodies were routinely detected in children admitted with acute respiratory infection during a one-year period. The medical history was re-collected from children whose M. pneumoniae antibody titer increased≥fourfold at the bedside by a single person, and their frozen paired serum samples were measured again for the M.pneumoniae antibody titer.Results Of the 635 children whose sera were detected for the M. pneumoniae antibody, paired sera were obtained from 82 and 29.3% （24/82） showed a ≥ fourfold increase in antibody titer. There were 24 cases, nine boys and 15 girls, aged from two to 14 years, whose second serum samples were taken on day 9 at the earliest after symptom onset; the shortest interval was three days. All children presented with a high fever （≥38.5℃） and coughing. Twenty-one had no nasal obstruction or a runny nose, and five had mild headaches which all were associated with the high fever. The disease was comparatively severe if the peak temperature was ＞39.5℃. All were diagnosed as having pneumonia through chest X-rays. Four had bilateral or multilobar involvement and their peak temperatures were all ≤ 39.5℃. None of the children had difficulty in breathing and all showed no signs of wheezing.Conclusions The second serum sample could be taken on day 9 at the earliest after symptom onset meant that paired sera could be used for the clinical diagnosis of M. pneumoniae pneumonia in children at the acute stage. M. pneumoniae is a lower respiratory tract pathogen. Extrapulmonary complications were rare and minor in our study. High peak temperature （＞39.5℃） is correlated with the severity of M. pneumoniae pneumonia in children.
基金This work was supported by the grants from National Natural Science Foundation of China （No. 21003077）, College of Public Health of Tianjin Medical University in China （No. GWKY-2010-01）, the Open Project of Key Laboratory of Advanced Energy Materials Chemistry （No. KLAEMC- OP201101） and Natural Science Foundation of Tianjin China （No. 08JCZDJC21400）.
文摘Background Various methods can be applied to build predictive models for the clinical data with binary outcome variable. This research aims to explore the process of constructing common predictive models, Logistic regression （LR）, decision tree （DT） and multilayer perceptron （MLP）, as well as focus on specific details when applying the methods mentioned above： what preconditions should be satisfied, how to set parameters of the model, how to screen variables and build accuracy models quickly and efficiently, and how to assess the generalization ability （that is, prediction performance） reliably by Monte Carlo method in the case of small sample size.
