OBJECTIVE: To identify early potential risk factors for hospital-acquired pneumonia (HAP) in patients with mild traumatic brain injury (mTBI), construct a risk prediction model, and evaluate its predictive efficacy. METHODS: A case-control study was conducted using clinical data from mTBI patients admitted to the neurosurgery department of Changzhou Second People's Hospital from September 2021 to September 2023. The patients were divided into two groups based on whether they developed HAP. Clinical data within 48 hours of admission were statistically analyzed to identify factors influencing HAP occurrence through univariate analysis. Least absolute shrinkage and selection operator (LASSO) regression analysis was employed for feature selection to identify the most influential variables. The dataset was divided into training and validation sets in a 7:3 ratio. A multivariate Logistic regression analysis was then performed using the training set to construct the prediction model, exploring the risk factors for HAP in mTBI patients and conducting internal validation in the validation set. Receiver operator characteristic curve (ROC curve), decision curve analysis (DCA), and calibration curve were utilized to assess the sensitivity, specificity, decision value, and predictive accuracy of the prediction model. RESULTS: A total of 677 mTBI patients were included, with 257 in the HAP group and 420 in the non-HAP group. The significant differences were found between the two groups in terms of age, maximum body temperature (MaxT), maximum heart rate (MaxHR), maximum systolic blood pressure (MaxSBP), minimum systolic blood pressure (MinSBP), maximum respiratory rate (MaxRR), cause of injury, and laboratory indicators [C-reactive protein (CRP), procalcitonin (PCT), neutrophil count (NEUT), erythrocyte sedimentation rate (ESR), fibrinogen (FBG), fibrinogen equivalent units (FEU), prothrombin time (PT), activated partial thromboplastin time (APTT), total cholesterol (TC), lactate dehydrogenase (LDH), prealbumin (PAB), albumin (Alb), blood urea nitrogen (BUN), serum creatinine (SCr), hematocrit (HCT), hemoglobin (Hb), platelet count (PLT), glucose (Glu), K⁺, Na⁺], suggesting they could be potential risk factors for HAP in mTBI patients. After LASSO regression analysis, the key risk factors were enrolled in the multivariate Logistic regression analysis. The results revealed that the cause of injury being a traffic accident [odds ratio (OR) = 2.199, 95% confidence interval (95%CI) was 1.124-4.398, P = 0.023], NEUT (OR = 1.330, 95%CI was 1.214-1.469, P < 0.001), ESR (OR = 1.053, 95%CI was 1.019-1.090, P = 0.003), FBG (OR = 0.272, 95%CI was 0.158-0.445, P < 0.001), PT (OR = 0.253, 95%CI was 0.144-0.422, P < 0.001), APTT (OR = 0.689, 95%CI was 0.578-0.811, P < 0.001), Alb (OR = 0.734, 95%CI was 0.654-0.815, P < 0.001), BUN (OR = 0.720, 95%CI was 0.547-0.934, P = 0.016), and Na⁺ (OR = 0.756, 95%CI was 0.670-0.843, P < 0.001) could serve as main risk factors for constructing the prediction model. Calibration curves demonstrated good calibration of the prediction model in both training and validation sets with no evident over fitting. ROC curve analysis showed that the area under the ROC curve (AUC) of the prediction model in the training set was 0.943 (95%CI was 0.921-0.965, P < 0.001), with a sensitivity of 83.6% and a specificity of 91.5%. In the validation set, the AUC was 0.917 (95%CI was 0.878-0.957, P < 0.001), with a sensitivity of 90.1% and a specificity of 85.0%. DCA indicated that the prediction model had a high net benefit, suggesting practical clinical applicability. CONCLUSIONS The cause of injury being a traffic accident, NEUT, ESR, FBG, PT, APTT, Alb, BUN, and Na⁺ are identified as major risk factors influencing the occurrence of HAP in mTBI patients. The prediction model constructed using these parameters effectively assesses the likelihood of HAP in mTBI patients.
Humans ; Risk Factors ; Case-Control Studies ; Logistic Models ; Healthcare-Associated Pneumonia/epidemiology* ; Brain Injuries, Traumatic/complications* ; Male ; Female ; ROC Curve ; Pneumonia/etiology* ; Middle Aged ; Adult

Objective To establish a scientific and rational nurse scheduling model for saving nursing human resources and schedule time for head nurses. Methods The nurses and the patients were divided into groups respectively. According to the principle of convention and common multiple, the mathematical logic algorithm was used to calculate working hours, rest and backup scheduling. Results ST basic scheduling model was established and the extension model 1, 2, and merge models 1, 2 was added on the basic of ST scheduling. Conclusions Based on the basic model, free combination and extension model, appropriate scheduling model was selected according to the number of patients and disease condition. It′s convenient which saves the scheduling time of the head nurses. At the same time, it standardizes the backup scheduling, fixes the backup nurses, and saves the nursing resources.

Objective To investigate subtle structural changes of white matter in patients with amnestic mild cognitive impair-ment (aMCI)using a tractography-based method.Methods Thirty patients with clinical diagnosis of aMCI and thirty-one cases of normal control(NC)and undergone diffusion tensor imaging.Cingulum (CG),corpus callosum (CC),uncinate fasciculus (UNC) and inferior occipitofrontal fasciculus (IOFF)were reconstructed,and fractional anisotrophy (FA)values were measured along these tracts using dTV II software.Differences of white matter tracts’FA values were explored between aMCI group and NC group.In addition,correlation analyses were also done between FA values and the MMSE(mini-mental state examination)scores in the aMCI patients.Results ① aMCI patients exhibited significant lower FA values in the bilateral CG,bilateral UNC and CC than NC group. Although there were no statistically significant differences,aMCI patients exhibited lower FA values than NC group in the left IOFF.② The FA values of right CG were positively correlated with MMSE scores.Conclusion Abnormal changes of FA values in CG,UNC and CC of aMCI patients suggest that subtle damages of white matter tracts related to memory exist in the prodromal phase of Alzheimer’s disease (AD).Fiber tractography has high sensitivity in detecting early damages of white matter.

OBJECTIVE: To understand the distribution of allergens in patients with allergic rhinitis (AR) in Quanzhou, for the diagnosis, prevention and treatment. METHOD: Twenty standardized allergen underwent skin prick testing (skin prick test, SPT) were used for 1236 patients with suspected AR patients in Quanzhou, and the different age, gender and severity in patients with allergen distribution differences of positive rate were analyzed. RESULT: The top 5 allergens with positive skin tests were D. pteronyssinus (66.7%), D. farinae (65.5%), Blattodea (32.8%), Sea crab (18.2%), and Sea lobster (16.8%). The positive rate of SPT in the minor groups and adult groups had significant difference (P < 0.05). Gender difference between the positive rate of SPT had no significant difference (P > 0.05). There was significant difference between the positive rate in patients with a family history and history of asthma and patients without above two history (P < 0.05). CONCLUSION Dust Mite, Blattodea, Sea crab. Sea lobster are the most important allergens in quanzhou. Different ages of the patients with SPT positive rates vary, a family history, history of asthma patients with positive rate is higher than patients without a family history of asthma history, high positive rate.
Adolescent ; Adult ; Aged ; Allergens ; analysis ; immunology ; Animals ; Child ; Child, Preschool ; China ; epidemiology ; Female ; Humans ; Male ; Middle Aged ; Rhinitis, Allergic ; Rhinitis, Allergic, Perennial ; diagnosis ; epidemiology ; immunology ; Skin Tests ; Young Adult