Low birth weight is associated with lower respiratory tract infections in children with hand, foot, and mouth disease.

BACKGROUND: Low birth weight (LBW) might be a risk factor for acquiring lower respiratory tract infections (LRTIs) associated with disease related complications in early childhood. HFMD, a frequent viral infection in southern China, is a leading cause of lower respiratory tract infections in children. We analyzed whether LBW is a risk factor for children with HFMD to develop lower respiratory tract infections. METHODS: A total of 298 children with HFMD, admitted to a hospital in Qingyuan city, Guangdong province, were recruited. Demographic data and clinical parameters such as serum glucose level and inflammatory markers including peripheral white blood cell count, serum C-reactive protein, and erythrocyte sedimentation rate were routinely collected on admission. Birth weight data were derived from birth records. RESULTS: Mean birth weight (BW) was 167 g lower in patients with HFMD and LRTIs as compared to patients with solely HFMD (p = 0.022) and the frequency of birth weight below the tenth percentile was significantly higher in patients with HFMD and LRTIs (p = 0.002). CONCLUSIONS: The results of the study show that low birth weight is associated with a higher incidence of lower respiratory tract infections in young children with HFMD.

Discrimination of ground-glass nodular lung adenocarcinoma pathological subtypes via transfer learning: A multicenter study.

BACKGROUND: The surgical approach and prognosis for invasive adenocarcinoma (IAC) and minimally invasive adenocarcinoma (MIA) of the lung differ. However, they both manifest as identical ground-glass nodules (GGNs) in computed tomography images, and no effective method exists to discriminate them. METHODS: We developed and validated a three-dimensional (3D) deep transfer learning model to discriminate IAC from MIA based on CT images of GGNs. This model uses a 3D medical image pre-training model (MedicalNet) and a fusion model to build a classification network. Transfer learning was utilized for end-to-end predictive modeling of the cohort data of the first center, and the cohort data of the other two centers were used as independent external validation data. This study included 999 lung GGN images of 921 patients pathologically diagnosed with IAC or MIA at three cohort centers. RESULTS: The predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). The model had high diagnostic efficacy for the training and validation groups (accuracy: 89%, sensitivity: 95%, specificity: 84%, and AUC: 95% in the training group; accuracy: 88%, sensitivity: 84%, specificity: 93%, and AUC: 92% in the internal validation group; accuracy: 83%, sensitivity: 83%, specificity: 83%, and AUC: 89% in one external validation group; accuracy: 78%, sensitivity: 80%, specificity: 77%, and AUC: 82% in the other external validation group). CONCLUSIONS: Our 3D deep transfer learning model provides a noninvasive, low-cost, rapid, and reproducible method for preoperative prediction of IAC and MIA in lung cancer patients with GGNs. It can help clinicians to choose the optimal surgical strategy and improve the prognosis of patients.

[Metrorrhagia treated by radio frequency ablation: report of 36 cases].

OBJECTIVE: To observe the effect of radio frequency ablation (RFA) for treating metrorrhagia. METHOD: In-36 metrorrhagia patients, who failed to respond to both traditional Chinese medicine and western medicine, and who did not seek child-bearing with malignant changes of the uterus shown by gynecological examination, B-ultrasonic, diagnostic curettage, and pathological examination, the width and depth of the uterine cavity were measured while sending the coagulator to the bottom of the uterus, followed by coagulation of the uterine cavity for two times. The whole process was carried out under the supervision of B-ultrasonic, whose strong echo-band was between 0.8 and 1.0 cm. RESULT: Within one year, the effective rate was 100%, and no recurrence was found. CONCLUSION: RFA is easy, economical, safe and efficient in treating metrorrhagia.

[Experience with laparoscopic management of internal hemorrhage in tubal pregnancy in middle-sized and small hospitals: report of 76 cases].

The authors examine the application of laparoscopy in the management of internal hemorrhage in tubal pregnancy in middle-sized and small hospitals. Altogether 76 such cases were collected for a review of the effects of laparoscopic management, and all were treated successfully without any complications. Laparoscopy causes minimal invasion in the management of internal hemorrhage in tubal pregnancy and may bring about rapid recovery of the patients, but the curative effects depend on the technical competence of the surgeon and the laparoscopic equipment.