Objective To investigate the diagnostic value of T-SPOT.TB in patients with fever.Methods T-SPOT.TB was carried out in 456 febrile patients who had no determined reason for fever or who could not be excluded from infection with Mycobacterium tuberculosis.These patients were followed up for their final clinical diagnosis and the diagnostic value of T-SPOT.TB was evaluated using the receiver operating characteristic (ROC) curve.Results In the present study,85 patients were clinically diagnosed with tuberculosis (TB) (including 34 cases of pulmonary TB,24 cases of TB infection defined as T-SPOT.TB positive without TB lesion,but effective with anti-TB treatment,10 cases of tuberculous pleurisy and 17 cases of other extrapulmonary TB) and 371 patients had no definite evidence of Mycobacterium tuberculosis infection (including 42 cases of suspected TB and 329 cases of other diseases).T-SPOT.TB had a high sensitivity of 84.3％ in TB patients and a high negative predictive value of 94.2 ％,but the specificity was 68.1％ and the positive predictive value was 41.4 ％.The Kappa value was 0.380 and the area under ROC curve was 0.762 (95％CI:0.707-0.817).T-SPOT.TB had a higher sensitivity in extrapulmonary TB than in pulmonary TB (88.2 ％ vs 78.1 ％),with the negative predictive values of 95.3 ％ and 92.6 ％,Kappa values of 0.438 and 0.299,and the areas under ROC of 0.791 (95 ％ CI:0.724-0.857) and 0.719 (95％CI:0.623-0.815),respectively.Ninety-nine cases were T-SPOT.TB positive out of 329 patients diagnosed with other diseases.Conclusions T-SPOT.TB test can be used as a method for TB diagnosis in patients without obvious TB lesions.Due to its relatively high negative predictive value,T-SPOT.TB can be used to rule out infection with Mycobacterium tuberculosis.

Objective To explore the relationship between meta-mood and learning adaptability of undergraduate nursing students in order to promote the students' academic achievement.Method 225 nursing students participated in the survey using the trait Meta-Mood Scale and the college students' learning adaptability scale.Results The average total scores on meta-mood and learning adaptability were(3.42±0.53)and(3.60±0.52),respectively.They were positively correlated and the 3 dimensions of meta-mood predicted the variance of learning adaptability by 12.7%.Conclusions The meta-mood of undergraduate nursing students is at moderate level,and learning adaptability is at a better level.The nursing administrations or educators should guide students to manage their moods so as to improve the students' learning adaptability.

The analysis of big data in medical field cannot be isolated from the high quality clinical database, and the construction of first aid database in our country is still in the early stage of exploration. This paper introduces the idea and key technology of the construction of multi-parameter first aid database. By combining emergency business flow with information flow, an emergency data integration model was designed with reference to the architecture of the Medical Information Mart for Intensive Care III (MIMIC-III), created by Computational Physiology Laboratory of Massachusetts Institute of Technology (MIT), and a high-quality first-aid database was built. The database currently covers 22 941 medical records for 19 814 different patients from May 2015 to October 2017, including relatively complete information on physiology, biochemistry, treatment, examination, nursing, etc. And based on the database, the first First-Aid Big Data Datathon event, which 13 teams from all over the country participated in, was launched. The First-Aid database provides a reference for the construction and application of clinical database in China. And it could provide powerful data support for scientific research, clinical decision making and the improvement of medical quality, which will further promote secondary analysis of clinical data in our country.
Big Data ; Critical Care ; Databases, Factual ; Humans ; Medical Informatics