Long-term Outcomes of Endovascular Repair for Blunt Thoracic Aortic Injury: A 10 Year Multi-center Experience.

OBJECTIVE: This study aimed to assess the long-term outcomes in patients treated by thoracic endovascular aortic repair (TEVAR) for blunt thoracic aortic injuries (BTAI). MATERIALS AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. CLINICAL IMPACT: 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.

Detection of iodixanol-induced allergic reaction signals in Chinese inpatients: a multi-center retrospective database study using prescription sequence symmetry analysis.

Objective: This study aimed to explore the signal detection method for allergic reactions induced by inpatient iodixanol injection. Methods: 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. Results: 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%). Conclusion: 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.

A multi-center study to predict the risk of intraoperative hypothermia in gynecological surgery patients using preoperative variables.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: We established a practical predictive model that can be used to preoperatively predict the occurrence of hypothermia in gynecological surgery patients. CLINICAL TRIAL REGISTRATION: chictr.org.cn, identifier ChiCTR2300071859.

Factors influencing witnesses' perception of patient safety during pre-hospital health care from emergency medical services: A multi-center cross-sectional study.

AIM: 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). INCLUSION CRITERIA: witnesses of health care by emergency medical services. EXCLUSION CRITERIA: minors, or communication barriers. OUTCOME VARIABLE: 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.

Use of cystic fibrosis inhaled medication before and after elexacaftor/tezacaftor/ivacaftor initiation.

Elexacator/tezacaftor/ivacaftor (ETI) has improved cystic fibrosis (CF) outcomes. A reduction in use of maintenance medication after its initiation has been reported. Seventy-one adult people with CF (PwCF) who are followed in three CF centers and completed one year of treatment with ETI were included in this study. Their use of inhaled dornase-α, colistin, tobramycin, aztreonam and levofloxacin during this period was compared with the corresponding use during one year without ETI, using the Medication Possession Ratio (MPR). MPR was significantly decreased after ETI initiation for dornase-α (67±35% vs 48±40%, p<0.001) and for all four inhaled antibiotics together (62±33% vs 41±37%, p<0.001). The findings of this multi-center, retrospective, study suggest that the initiation of ETI significantly leads to decrease in use of standard inhaled medication in PwCF. The significance of this finding in the course of the disease is yet to be investigated by larger prospective clinical trials.

Virulence profiling of Cryptococcus gattii isolates in China: insights from a multi-center study.

IMPORTANCE: 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.

Causes of death and treatment-related mortality in newly diagnosed childhood acute lymphoblastic leukemia treatment with Chinese Children's Cancer Group study ALL-2015.

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).

The development of the pediatric stroke neuroimaging platform (PEDSNIP).

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.

A novel prognostic model based on pretreatment serum albumin and ECOG PS for primary CNS lymphoma: an international, multi-center study.

BACKGROUND: Serum albumin has been demonstrated as prognostic parameter in non-Hodgkin lymphoma (NHL). Primary central nervous system lymphoma (PCNSL) is a rare extranodal NHL with highly aggressive behavior. In this study, we aimed at creating a novel prognostic model for PCNSL based on serum albumin levels. METHODS: We compared several commonly used laboratory nutritional parameters for predicting the survival of PCNSL patients using overall survival (OS) for outcome analysis and receiver operating characteristic curve analysis to determine the optimal cut-off values. Parameters associated with OS were evaluated by univariate and multivariate analyses. Independent prognostic parameters for OS were selected for risk stratification, including albumin ≤ 4.1 g/dL, ECOG PS > 1, and LLR > 166.8, which were associated with shorter OS; albumin > 4.1 g/dL, ECOG PS 0-1 and LLR ≤ 166.8, which were associated with longer OS, and five-fold cross-validation was used for evaluating predictive accuracy of identified prognostic model. RESULTS: By univariate analysis, age, ECOG PS, MSKCC score, Lactate dehydrogenase-to-lymphocyte ratio (LLR), total protein, albumin, hemoglobin, and albumin to globulin ratio (AGR) resulted statistically associated with the OS of PCNSL. By multivariate analysis, albumin ≤ 4.1 g/dL, ECOG PS > 1, and LLR > 166.8 were confirmed to be significant predictors of inferior OS. We explored several PCNSL prognostic models based on albumin, ECOG PS and LLR with 1 point assigned to each parameter. Eventually, a novel and effective PCNSL prognostic model based on albumin and ECOG PS successfully classified patients into three risk groups with 5-year survival rates of 47.5%, 36.9%, and 11.9%, respectively. CONCLUSIONS: The novel two-factor prognostic model based on albumin and ECOG PS we propose represents a simple but significant prognostic tool for assessing newly diagnosed patients with PCNSL.

A snapshot of pediatric inpatients and outpatients with COVID-19: a point prevalence study from Turkey.

This multi-center point prevalence study evaluated children who were diagnosed as having coronavirus disease 2019 (COVID-19). On February 2nd, 2022, inpatients and outpatients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were included in the study from 12 cities and 24 centers in Turkey. Of 8605 patients on February 2nd, 2022, in participating centers, 706 (8.2%) had COVID-19. The median age of the 706 patients was 92.50 months, 53.4% were female, and 76.7% were inpatients. The three most common symptoms of the patients with COVID-19 were fever (56.6%), cough (41.3%), and fatigue (27.5%). The three most common underlying chronic diseases (UCDs) were asthma (3.4%), neurologic disorders (3.3%), and obesity (2.6%). The SARS-CoV-2-related pneumoniae rate was 10.7%. The COVID-19 vaccination rate was 12.5% in all patients. Among patients aged over 12 years with access to the vaccine given by the Republic of Turkey Ministry of Health, the vaccination rate was 38.7%. Patients with UCDs presented with dyspnea and pneumoniae more frequently than those without UCDs (p < 0.001 for both). The rates of fever, diarrhea, and pneumoniae were higher in patients without COVID-19 vaccinations (p = 0.001, p = 0.012, and p = 0.027).  Conclusion: To lessen the effects of the disease, all eligible children should receive the COVID-19 vaccine. The illness may specifically endanger children with UCDs. What is Known: • Children with COVID-19 mainly present with fever and cough, as in adults. • COVID-19 may specifically threaten children with underlying chronic diseases. What is New: • Children with obesity have a higher vaccination rate against COVID-19 than children without obesity. • Among unvaccinated children, fever and pneumoniae might be seen at a higher ratio than among vaccinated children.

A prediction nomogram for moderate-to-severe bronchopulmonary dysplasia in preterm infants < 32 weeks of gestation: A multicenter retrospective study.

Background: Moderate-to-severe bronchopulmonary dysplasia (msBPD) is a serious complication in preterm infants. We aimed to develop a dynamic nomogram for early prediction of msBPD using perinatal factors in preterm infants born at <32 weeks' gestation. Methods: This multicenter retrospective study conducted at three hospitals in China between January 2017 and December 2021 included data on preterm infants with gestational age (GA) < 32 weeks. All infants were randomly divided into training and validation cohorts (3:1 ratio). Variables were selected by Lasso regression. Multivariate logistic regression was used to build a dynamic nomogram to predict msBPD. The discrimination was verified by receiver operating characteristic curves. Hosmer-Lemeshow test and decision curve analysis (DCA) were used for evaluating calibration and clinical applicability. Results: A total of 2,067 preterm infants. GA, Apgar 5-min score, small for gestational age (SGA), early onset sepsis, and duration of invasive ventilation were predictors for msBPD by Lasso regression. The area under the curve was 0.894 (95% CI 0.869-0.919) and 0.893 (95% CI 0.855-0.931) in training and validation cohorts. The Hosmer-Lemeshow test calculated P value of 0.059 showing a good fit of the nomogram. The DCA demonstrated significantly clinical benefit of the model in both cohorts. A dynamic nomogram predicting msBPD by perinatal days within postnatal day 7 is available at https://sdxxbxzz.shinyapps.io/BPDpredict/. Conclusion: We assessed the perinatal predictors of msBPD in preterm infants with GA < 32 weeks and built a dynamic nomogram for early risk prediction, providing clinicians a visual tool for early identification of msBPD.

A multi-center international study on the spinal cord independence measure, version IV: Rasch psychometric validation.

CONTEXT: The Spinal Cord Independence Measure is a comprehensive functional rating scale for individuals with spinal cord lesion (SCL). OBJECTIVE: To validate the scores of the three subscales of SCIM IV, the fourth version of SCIM, using advanced statistical methods. STUDY DESIGN: Multi-center cohort study. SETTING: Nineteen SCL units in 11 countries. METHODS: SCIM developers created SCIM IV following comments by experts, included more accurate definitions of scoring criteria in the SCIM IV form, and adjusted it to assess specific conditions or situations that the third version, SCIM III, does not address. Professional staff members assessed 648 SCL inpatients, using SCIM IV and SCIM III, at admission to rehabilitation, and at discharge. The authors examined the validity and reliability of SCIM IV subscale scores using Rasch analysis. RESULTS: The study included inpatients aged 16-87 years old. SCIM IV subscale scores fit the Rasch model. All item infit and most item outfit mean-square indices were below 1.4; statistically distinct strata of abilities were 2.6-6; most categories were properly ordered; item hierarchy was stable across most clinical subgroups and countries. In a few items, however, we found misfit or category threshold disordering. We found SCIM III and SCIM IV Rasch properties to be comparable. CONCLUSIONS: Rasch analysis suggests that the scores of each SCIM IV subscale are reliable and valid. This reinforces the justification for using SCIM IV in clinical practice and research.

Blunt Cerebrovascular Injury in the Elderly With Traumatic Cervical Spine Injuries: Results of a Retrospective Multi-Center Study of 1512 Cases in Japan.

This study is nationwide retrospective multi-center study to investigate the incidence and characteristics of blunt cerebrovascular injury (BCVI) in elderly Japanese patients with traumatic cervical spine injuries (CSI) including spinal cord injury (SCI) without major bone injury. The study enrolled 1512 patients (average age: 75.8 ± 6.9 years; 1007 males, 505 females) from 33 nationwide institutions, and 391 (26%) of the participants had digital subtraction angiography and/or computed tomography angiography. Fifty-three patients were diagnosed as having BCVI by angiography. We assessed neurological evaluation, comorbidities and classification of CSI in the elderly patients with/without BCVI and collected 6-month follow-up data on treatment, complications, and patient outcome. We also statistically analyzed the relative risk (RR) and relationship between BCVI and other factors. Significant differences were identified between BCVI (+) (n = 53) and (-) (n = 1459) patients with American Spinal Injury Association Impairment Scale (ASIA) A, C, D, cervical fracture, C3-7 injury level (AO type F and/or C), cervical dislocation, spinal surgery for CSI, tetraplegia type of SCI, and/or head injury. Fifty-three (3.5%) elderly patients had CSI complicated by BCVI including 10 (19%) cases of Denver grade I, four (7%) of grade II, 1 (2%) of grade III, 29 (55%) of grade IV, and nine (17%) of grade V. Sixteen cases were treated by interventional radiology. Rates of mortality and brain infarction from BCVI were 0.13% and 0.40%, respectively. RR of BCVI was significantly higher in the elderly cervical injury patients with head injury, severe neurological deficit, ASIA A (RR: 4.33), cervical fracture at the C3-7 level (RR: 7.39), and cervical dislocation at the C1-6 level (RR: 3.06-7.18). In conclusion, 53 (3.5%) elderly patients were complicated with BCVI. BCVI more frequently complicated head injury, severe neurological deficit (ASIA A or tetraplegia), AO type F, and/or C fractures and cervical dislocation in these patients. Six patients (11%) suffered brain infarction and two patients died from BCVI.

A multi-center study on evaluation of leukocyte differential performance by an artificial intelligence-based Digital Cell Morphology Analyzer / 中华检验医学杂志

Objective:To evaluate the performance of an artificial intelligent (AI)-based automated digital cell morphology analyzer (hereinafter referred as AI morphology analyzer) in detecting peripheral white blood cells (WBCs).Methods:A multi-center study. 1. A total of 3010 venous blood samples were collected from 11 tertiary hospitals nationwide, and 14 types of WBCs were analyzed with the AI morphology analyzers. The pre-classification results were compared with the post-classification results reviewed by senior morphological experts in evaluate the accuracy, sensitivity, specificity, and agreement of the AI morphology analyzers on the WBC pre-classification. 2. 400 blood samples (no less than 50% of the samples with abnormal WBCs after pre-classification and manual review) were selected from 3 010 samples, and the morphologists conducted manual microscopic examinations to differentiate different types of WBCs. The correlation between the post-classification and the manual microscopic examination results was analyzed. 3. Blood samples of patients diagnosed with lymphoma, acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndrome, or myeloproliferative neoplasms were selected from the 3 010 blood samples. The performance of the AI morphology analyzers in these five hematological malignancies was evaluated by comparing the pre-classification and post-classification results. Cohen′s kappa test was used to analyze the consistency of WBC pre-classification and expert audit results, and Passing-Bablock regression analysis was used for comparison test, and accuracy, sensitivity, specificity, and agreement were calculated according to the formula.Results:1. AI morphology analyzers can pre-classify 14 types of WBCs and nucleated red blood cells. Compared with the post-classification results reviewed by senior morphological experts, the pre-classification accuracy of total WBCs reached 97.97%, of which the pre-classification accuracies of normal WBCs and abnormal WBCs were more than 96% and 87%, respectively. 2. The post-classification results reviewed by senior morphological experts correlated well with the manual differential results for all types of WBCs and nucleated red blood cells (neutrophils, lymphocytes, monocytes, eosinophils, basophils, immature granulocytes, blast cells, nucleated erythrocytes and malignant cells r>0.90 respectively, reactive lymphocytes r=0.85). With reference, the positive smear of abnormal cell types defined by The International Consensus Group for Hematology, the AI morphology analyzer has the similar screening ability for abnormal WBC samples as the manual microscopic examination. 3. For the blood samples with malignant hematologic diseases, the AI morphology analyzers showed accuracies higher than 84% on blast cells pre-classification, and the sensitivities were higher than 94%. In acute myeloid leukemia, the sensitivity of abnormal promyelocytes pre-classification exceeded 95%. Conclusion:The AI morphology analyzer showed high pre-classification accuracies and sensitivities on all types of leukocytes in peripheral blood when comparing with the post-classification results reviewed by experts. The post-classification results also showed a good correlation with the manual differential results. The AI morphology analyzer provides an efficient adjunctive white blood cell detection method for screening malignant hematological diseases.

A multi-center study of biochemical and hotspot gene screening for neonatal genetic metabolic diseases / 中华实用儿科临床杂志

Objective:To investigate the efficiency of biochemical screening and hotspot gene screening in the detection of neonatal inherited metabolic diseases.Methods:This was a prospective multi-center study.The study was carried out on 21 442 neonatal samples collected from 12 hospitals in 10 provinces from November 2020 to November 2021.The results of biochemical screening and hotspot gene screening were analyzed jointly.Biochemical screening methods included glucose-6-phosphate dehydrogenase deficiency enzyme activity assay and neonatal tandem mass spectrometry.Genetic screening analysis involved 135 genes associated with 75 neonatal diseases.Results:Of all the 21 442 neonates enrolled in the study, 21 205 were subject to biochemical screening.A total of 813 cases were positive in the initial screening, and 0.45% of them (95 cases) were diagnosed after recall.All the 21 442 neonates underwent gene screening.About 168 positive cases were detected in the initial screening, and 0.73% (156 cases) of them were confirmed finally.Biochemical and genetic screening improved the detection sensitivity of such diseases as primary carnitine deficiency, neonatal intrahepatic cholestasis caused by citrin deficiency, and 2-methylbutyrylglycinemia.Moreover, biochemical and genetic screening enabled the detection of more diseases, including the common single-gene genetic diseases such as thalassemia and Wilson disease.Conclusions:In neonatal screening, the combination of biochemical screening and gene screening expands the number of diseases detected and improve screening efficiency.

Integrated partially linear model for multi-center studies with heterogeneity and batch effect in covariates.

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.

Effect of a disposable endoscope precleaning kit in the cleaning procedure of gastrointestinal endoscope: A multi-center observational study.

BACKGROUND: Precleaning is a key step in endoscopic reprocessing. AIM: 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). CONCLUSION: 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.

Improving the diagnosis of acute ischemic stroke on non-contrast CT using deep learning: a multicenter study.

OBJECTIVE: This study aimed to develop a deep learning (DL) model to improve the diagnostic performance of EIC and ASPECTS in acute ischemic stroke (AIS). METHODS: Acute ischemic stroke patients were retrospectively enrolled from 5 hospitals. We proposed a deep learning model to simultaneously segment the infarct and estimate ASPECTS automatically using baseline CT. The model performance of segmentation and ASPECTS scoring was evaluated using dice similarity coefficient (DSC) and ROC, respectively. Four raters participated in the multi-reader and multicenter (MRMC) experiment to fulfill the region-based ASPECTS reading under the assistance of the model or not. At last, sensitivity, specificity, interpretation time and interrater agreement were used to evaluate the raters' reading performance. RESULTS: In total, 1391 patients were enrolled for model development and 85 patients for external validation with onset to CT scanning time of 176.4 ± 93.6 min and NIHSS of 5 (IQR 2-10). The model achieved a DSC of 0.600 and 0.762 and an AUC of 0.876 (CI 0.846-0.907) and 0.729 (CI 0.679-0.779), in the internal and external validation set, respectively. The assistance of the DL model improved the raters' average sensitivities and specificities from 0.254 (CI 0.22-0.26) and 0.896 (CI 0.884-0.907), to 0.333 (CI 0.301-0.345) and 0.915 (CI 0.904-0.926), respectively. The average interpretation time of the raters was reduced from 219.0 to 175.7 s (p = 0.035). Meanwhile, the interrater agreement increased from 0.741 to 0.980. CONCLUSIONS: With the assistance of our proposed DL model, radiologists got better performance in the detection of AIS lesions on NCCT.

Reliability of multi-parameter mapping (MPM) in the cervical cord: A multi-center multi-vendor quantitative MRI study.

MRI based multicenter studies which target neurological pathologies affecting the spinal cord and brain - including spinal cord injury (SCI) - require standardized acquisition protocols and image processing methods. We have optimized and applied a multi-parameter mapping (MPM) protocol that simultaneously covers the brain and the cervical cord within a traveling heads study across six clinical centers (Leutritz et al., 2020). The MPM protocol includes quantitative maps (magnetization transfer saturation (MT), proton density (PD), longitudinal (R1), and effective transverse (R2*) relaxation rates) sensitive to myelination, water content, iron concentration, and morphometric measures, such as cross-sectional cord area. Previously, we assessed the repeatability and reproducibility of the brain MPM data acquired in the five healthy participants who underwent two scan-rescans (Leutritz et al., 2020). This study focuses on the cervical cord MPM data derived from the same acquisitions to determine its repeatability and reproducibility in the cervical cord. MPM matrices of the cervical cord were generated and processed using the hMRI and the spinal cord toolbox. To determine reliability of the cervical MPM data, the intra-site (i.e., scan-rescan) coefficient of variation (CoV), inter-site CoV, and bias within region of interests (C1, C2 and C3 levels) were determined. The range of the mean intra- and inter-site CoV of MT, R1 and PD was between 2.5% and 12%, and between 1.1% and 4.0% for the morphometric measures. In conclusion, the cervical MPM data showed a high repeatability and reproducibility for key imaging biomarkers and hence can be employed as a standardized tool in multi-center studies, including clinical trials.

Performance comparison of two nucleic acid amplification systems for SARS-CoV-2 detection: A multi-center study.

BACKGROUND: Many rapid nucleic acid testing systems have emerged to halt the development and spread of COVID-19. However, so far relatively few studies have compared the diagnostic performance between these testing systems and conventional detection systems. Here, we performed a retrospective analysis to evaluate the clinical detection performance between SARS-CoV-2 rapid and conventional nucleic acid detection system. METHODS: Clinical detection results of 63,352 oropharyngeal swabs by both systems were finally enrolled in this analysis. Sensitivity (SE), specificity (SP), and positive and negative predictive value (PPV, NPV) of both systems were calculated to evaluate their diagnostic accuracy. Concordance between these two systems were assessed by overall, positive, negative percent agreement (OPA, PPA, NPA) and κ value. Sensitivity of SARS-CoV-2 rapid nucleic acid detection system (Daan Gene) was further analyzed with respect to the viral load of clinical specimens. RESULTS: Sensitivity of Daan Gene was slightly lower than that of conventional detection system (0.86 vs. 0.979), but their specificity was equivalent. Daan Gene had ≥98.0% PPV and NPV for SARS-CoV-2. Moreover, Daan Gene demonstrated an excellent test agreement with conventional detection system (κ = 0.893, p = 0.000). Daan Gene was 99.31% sensitivity for specimens with high viral load (Ct < 35) and 50% for low viral load (Ct ≥ 35). CONCLUSIONS: While showing an analytical sensitivity slightly below than that of conventional detection system, rapid nucleic acid detection system may be a diagnostic alternative to rapidly identify SARS-CoV-2-infected individuals with high viral loads and a powerful complement to current detection methods.