BACKGROUND: The aim of this work is to develop a deep learning (DL) system for rapidly and accurately screening for intraocular tumor (IOT), retinal detachment (RD), vitreous hemorrhage (VH), and posterior scleral staphyloma (PSS) using ocular B-scan ultrasound images.
METHODS: Ultrasound images from five clinically confirmed categories, including vitreous hemorrhage, retinal detachment, intraocular tumor, posterior scleral staphyloma, and normal eyes, were used to develop and evaluate a fine-grained classification system (the Dual-Path Lesion Attention Network, DPLA-Net). Images were derived from five centers scanned by different sonographers and divided into training, validation, and test sets in a ratio of 7:1:2. Two senior ophthalmologists and four junior ophthalmologists were recruited to evaluate the system\'s performance.
RESULTS: This multi-center cross-sectional study was conducted in six hospitals in China. A total of 6054 ultrasound images were collected; 4758 images were used for the training and validation of the system, and 1296 images were used as a testing set. DPLA-Net achieved a mean accuracy of 0.943 in the testing set, and the area under the curve was 0.988 for IOT, 0.997 for RD, 0.994 for PSS, 0.988 for VH, and 0.993 for normal. With the help of DPLA-Net, the accuracy of the four junior ophthalmologists improved from 0.696 (95% confidence interval [CI] 0.684-0.707) to 0.919 (95% CI 0.912-0.926, p < 0.001), and the time used for classifying each image reduced from 16.84 ± 2.34 s to 10.09 ± 1.79 s.
CONCLUSIONS: The proposed DPLA-Net showed high accuracy for screening and classifying multiple ophthalmic diseases using B-scan ultrasound images across mutiple centers. Moreover, the system can promote the efficiency of classification by ophthalmologists.

UNASSIGNED: This study aimed to assess the long-term outcomes in patients treated by thoracic endovascular aortic repair (TEVAR) for blunt thoracic aortic injuries (BTAI).
UNASSIGNED: From January 2010 to December 2019, this retrospective observational study was conducted at 3 centers, involving 62 consecutive BTAI patients who underwent TEVAR. Computed tomography angiography scans were planned to be conducted at 6 months post-procedure, and annually thereafter.
UNASSIGNED: Technical success was achieved in all 62 procedures (100%), which included cases of dissection (n=35, 56.45%), pseudoaneurysm (n=20, 32.26%), and rupture (n=7, 11.29%). Mean injury severity score was 31.66±8.30. A total of 21 supra-arch branches were revascularized by chimney technique, with 12 cases involving the left subclavian artery (LSA) and 9 cases involving the left common carotid artery. In addition, 11 LSAs were covered during the procedure. The in-hospital mortality rate was 1.61% (n=1). The mean follow-up time was 86.82±30.58 months. The all-cause follow-up mortality rate was 3.28% (n=2). Stenosis or occlusion of 3 supra-arch branches (4.92%) was identified at follow-up, with 2 cases (3.28%) requiring re-intervention. No spinal cord ischemia, endoleak, or migration was observed.
UNASSIGNED: Despite only including patients with long-term follow-up, this study confirms the long-term safety and effectiveness of TEVAR for BTAI. For young BTAI patients, as the thoracic aorta increases with age, longer follow-up is needed to observe the potential mismatch between the endograft and the aorta.
CONCLUSIONS: This study confirms the long-term safety and effectiveness of endovascular treatment for blunt thoracic aortic injury (BTAI). For young BTAI patients, as the thoracic aorta increases with age, longer follow-up is needed to observe the potential mismatch between the endograft and the aorta. Through a remarkably extended follow-up period (86.82±30.58 months) conducted at multiple centers in China, this study confirms the long-term safety and effectiveness of endovascular treatment for BTAI.

UNASSIGNED: This study aimed to explore the signal detection method for allergic reactions induced by inpatient iodixanol injection.
UNASSIGNED: A database of 3,719,217 hospitalized patients from 20 large Chinese general hospitals was processed and analyzed using the prescription sequence symmetry analysis (PSSA) method.
UNASSIGNED: 126,680 inpatients who used iodixanol and were concurrently treated with anti-allergic drugs were analyzed. In the medical records of these patients, only 32 had documented iodixanol allergies. Statistical analysis identified 22 drugs in 4 categories-calcium preparations, adrenergic/dopaminergic agents, glucocorticoids, and antihistamines-as marker drugs. With time intervals of 3, 7, and 28 days, the adjusted sequence ratios (aSRs) for all anti-allergics and the 4 categories were greater than 1. The 7-day aSRs were 2.12 (95% CI: 2.08-2.15), 1.70 (95% CI: 1.68-1.73), 3.85 (95% confidence interval [CI]: 3.75-2.30), 2.30 (95% CI: 2.26-2.35), and 1.95 (95% CI: 1.89-2.02), respectively. The proportions of adverse drug events indicated by each signal were as follows: all anti-allergics (2.92%-3%), calcium gluconate (0.19%-0.52%), adrenergic/dopaminergic agents (2.20%-3.37%), glucocorticoids (3.13%-3.76%), and antihistamines (1.05%-1.32%).
UNASSIGNED: This first multi-center Chinese inpatient database study detected iodixanol-induced allergy signals, revealing that reactions may be much higher than those in collected spontaneous reports. Iodixanol risk exposure was closer to actual pharmaceutical care findings. PSSA application with ≤7-day intervals appears better suited for monitoring late allergic reaction signals with these drugs.

Hypothermia is highly common in patients undergoing gynecological surgeries under general anesthesia, so the length of hospitalization and even the risk of mortality are substantially increased. Our aim was to develop a simple and practical model to preoperatively identify gynecological surgery patients at risk of intraoperative hypothermia.
In this retrospective study, we collected data from 802 patients who underwent gynecological surgery at three medical centers from June 2022 to August 2023. We further allocated the patients to a training group, an internal validation group, or an external validation group. The preliminary predictive factors for intraoperative hypothermia in gynecological patients were determined using the least absolute shrinkage and selection operator (LASSO) method. The final predictive factors were subsequently identified through multivariate logistic regression analysis, and a nomogram for predicting the occurrence of hypothermia was established.
A total of 802 patients were included, with 314 patients in the training cohort (mean age 48.5 ± 12.6 years), 130 patients in the internal validation cohort (mean age 49.9 ± 12.5 years), and 358 patients in the external validation cohort (mean age 47.6 ± 14.0 years). LASSO regression and multivariate logistic regression analyses indicated that body mass index, minimally invasive surgery, baseline heart rate, baseline body temperature, history of previous surgery, and aspartate aminotransferase level were associated with intraoperative hypothermia in gynecological surgery patients. This nomogram was constructed based on these six variables, with a C-index of 0.712 for the training cohort.
We established a practical predictive model that can be used to preoperatively predict the occurrence of hypothermia in gynecological surgery patients.
chictr.org.cn, identifier ChiCTR2300071859.

The design of multi-center study is increasingly used for borrowing strength from multiple research groups to obtain broadly applicable and reproducible study findings. Regression analysis is widely used for analyzing multi-group studies, however, some of the large number of regression predictors are nonlinear and/or often measured with batch effects in many large scale collaborative studies. Also, the group compositions of the nonlinear predictors are potentially heterogeneous across different centers. The conventional pooled data analysis ignores the interplay between nonlinearity and batch effect, group composition heterogeneity, measurement error and other data incoherence in multi-center setting that can cause biased regression estimates and misleading outcomes. In this paper, we propose an integrated partially linear regression model (IPLM) based analysis to account for the predictor\'s nonlinearity, general batch effect, group composition heterogeneity, high-dimensional covariates, potential measurement-error in covariates, and combinations of these complexities simultaneously. A local linear regression based approach is employed to estimate the nonlinear component and a regularization procedure is introduced to identify the predictors\' effects that can be either homogeneous or heterogeneous across groups. In particular, when the effects of all predictors are homogeneous across the study centers, the proposed IPLM can automatically reduce to one single parsimonious partially linear model for all centers. The proposed method has asymptotic estimation and variable selection consistency including high-dimensional covariates. Moreover, it has a fast computing algorithm and its effectiveness is supported by numerical simulation studies. A multi-center Alzheimer\'s disease research project is provided to illustrate the proposed IPLM based analysis.

BACKGROUND: Precleaning is a key step in endoscopic reprocessing.
OBJECTIVE: To develop an effective and economic endoscope cleaning method by using a disposable endoscope bedside precleaning kit.
METHODS: Altogether, 228 used gastrointestinal endoscopes were selected from five high-volume endoscopy units and precleaned by a traditional precleaning bucket (group T) or a disposable endoscope bedside precleaning kit (group D). Each group was further subdivided based on the replacement frequency of the cleaning solution, which was replaced every time in subgroups T1 and D1 and every several times in subgroups Ts and Ds. The adenosine triphosphate (ATP) level and residual proteins were measured three times: Before and after precleaning and after manual cleaning.
RESULTS: After precleaning, the precleaning kit significantly reduced the ATP levels (P = 0.034) and has a more stable ATP clearance rate than the traditional precleaning bucket. The precleaning kit also saved a quarter of the cost of enzymatic detergent used during the precleaning process. After manual cleaning, the ATP levels were also significantly lower in the precleaning kit group than in the traditional precleaning bucket group (P < 0.05). Meanwhile, the number of uses of the cleaning solution (up to four times) has no significant impact on the cleaning effect (P > 0.05).
CONCLUSIONS: Considering its economic cost and cleaning effect, the use of a disposable endoscope bedside precleaning kit can be an optimal option in the precleaning stage with the cleaning solution being replaced several times in the manual cleaning stage.

OBJECTIVE: To determine the factors related with the perception of feeling safe during pre-hospital emergency care.
METHODS: A multi-centred, cross-sectional study. Data collection from April 2021 to March 2022, in the Centro de Emergencias Sanitarias 061 (Andalusia, Spain).
METHODS: witnesses of health care by emergency medical services.
METHODS: minors, or communication barriers.
METHODS: Witness Perceived Safety Scale ESPT10. The variables studied were related with sociodemographic data, the request for health care, the patient, the hospital transfer and patient safety incidents. A multivariate linear regression model was constructed for the dependent variable. The study followed STROBE statement.
RESULTS: Responses were obtained from 1400 witnesses. The linear regression model showed that the score on the scale increased as the witnesses felt more satisfied (B = 1.302; p < 0.001). On the contrary, the score was lower when the witness reported a patient safety incident (B = -2.856; p < 0.001 and B = -3.166; p < 0.001), or when the assistance took place in a public space (B = -0.722; p = 0.017).
CONCLUSIONS: The level of satisfaction, the occurrence of a patient safety incident, and the place of health care are related factors with the perception of the witnesses. The Witness Perceived Safety Scale ESPT10 could be considered a valid and useful patient safety indicator.

OBJECTIVE: Our study indicates that the molecular typing of Cryptococcus gattii is unrelated to virulence. The integration of animal experiments and clinical prognosis demonstrated that pathogenicity did not exhibit a direct correlation with in vitro virulence phenotypes or molecular genotypes, emphasizing the intricate nature of virulence. In conclusion, our research holds the potential to provide valuable insights into understanding the microbiological attributes of C. gattii in China.

To investigate the possible risk factors for death at post-treatment in children with acute lymphoblastic leukemia (ALL). A multivariate competing risk analysis was performed to retrospectively analyze the data of children with ALL who died after treatment with CCCG-ALL-2015 in China and to determine the possible risk factors for death at post-treatment in children with ALL. Age at the first diagnosis of ≥10 years; final risk level of high-risk; D19 minimal residual disease (MRD) (≥0.01%) and D46 MRD (≥0.01%); genetic abnormalities, such as KMT2A-rearrangement, c-Myc rearrangement, and PDGFRB rearrangement; and the presence of CNS3 (all P values, <0.05) were identified as independent risk factors, whereas the risk level at the first diagnosis of low-risk (LR) and ETV6::RUNX1 positivity was considered as independent protective factors of death in children with ALL. Among the 471 cases of death, 45 cases were treated with CCCG-ALL-2015 only, and 163 (34.61%) were treatment-related, with 62.42% due to severe infections. 55.83% of treatment-related mortality (TRM) occurred in the early phase of treatment (induction phase). TRM has a significant impact on the overall survival of pediatric patients with ALL. Moreover, the CCCG-ALL-2015 regimen has a better safety profile for treating children with ALL, with rates close to those in developed countries (registration number: ChiCTR-IPR-14005706; date of registration: June 4, 2014).

Childhood stroke occurs from birth to 18 years of age, ranks among the top ten childhood causes of death, and leaves lifelong neurological impairments. Arterial ischemic stroke in infancy and childhood occurs due to arterial occlusion in the brain, resulting in a focal lesion. Our understanding of mechanisms of injury and repair associated with focal injury in the developing brain remains rudimentary. Neuroimaging can reveal important insights into these mechanisms. In adult stroke population, multi-center neuroimaging studies are common and have accelerated the translation process leading to improvements in treatment and outcome. These studies are centered on the growing evidence that neuroimaging measures and other biomarkers (e.g., from blood and cerebrospinal fluid) can enhance our understanding of mechanisms of risk and injury and be used as complementary outcome markers. These factors have yet to be studied in pediatric stroke because most neuroimaging studies in this population have been conducted in single-centred, small cohorts. By pooling neuroimaging data across multiple sites, larger cohorts of patients can significantly boost study feasibility and power in elucidating mechanisms of brain injury, repair and outcomes. These aims are particularly relevant in pediatric stroke because of the decreased incidence rates and the lack of mechanism-targeted trials. Toward these aims, we developed the Pediatric Stroke Neuroimaging Platform (PEDSNIP) in 2015, funded by The Brain Canada Platform Support Grant, to focus on three identified neuroimaging priorities. These were: developing and harmonizing multisite clinical protocols, creating the infrastructure and methods to import, store and organize the large clinical neuroimaging dataset from multiple sites through the International Pediatric Stroke Study (IPSS), and enabling central searchability. To do this, developed a two-pronged approach that included building 1) A Clinical-MRI Data Repository (standard of care imaging) linked to clinical data and longitudinal outcomes and 2) A Research-MRI neuroimaging data set acquired through our extensive collaborative, multi-center, multidisciplinary network. This dataset was collected prospectively in eight North American centers to test the feasibility and implementation of harmonized advanced Research-MRI, with the addition of clinical information, genetic and proteomic studies, in a cohort of children presenting with acute ischemic stroke. Here we describe the process that enabled the development of PEDSNIP built to provide the infrastructure to support neuroimaging research priorities in pediatric stroke. Having built this Platform, we are now able to utilize the largest neuroimaging and clinical data pool on pediatric stroke data worldwide to conduct hypothesis-driven research. We are actively working on a bioinformatics approach to develop predictive models of risk, injury and repair and accelerate breakthrough discoveries leading to mechanism-targeted treatments that improve outcomes and minimize the burden following childhood stroke. This unique transformational resource for scientists and researchers has the potential to result in a paradigm shift in the management, outcomes and quality of life in children with stroke and their families, with far-reaching benefits for other brain conditions of people across the lifespan.