Predicting intraoperative major blood loss in microsurgery for brain arteriovenous malformations

ObjectiveIntraoperative blood loss poses a great challenge for brain arteriovenous malformation (AVM) microsurgery, although systematic researches are still lacking. This study aimed to identify factors predicting intraoperative major blood loss in brain AVM microsurgery and to investigate its impact on patient outcome. To deal with the fierce bleeding, we introduced a modified hemostatic method, bone-wax (BW) coated bipolar electrocoagulation.MethodsThe authors retrospectively analyzed the clinical data of 131 patients (50/81 in intraoperative major/non-major blood loss cohort) with brain AVMs who underwent microsurgery in our center during the period between January 2018 and April 2023. According to previous studies, major blood loss was defined as blood loss of at least 1,000 mL. The accuracy and objectivity of our grouping methodology were validated by comparing the hemoglobin mass loss, hematocrit loss and factors associated with intraoperative bleeding. Potential clinical and radiological predictors for intraoperative major blood loss were evaluated using a multivariate stepwise logistic regression. And outcomes of patients in the two cohorts were also compared. At last, the performance of BW coated bipolar electrocoagulation in brain AVM microsurgery was illustrated by the case presentation, histological staining and transmission electron microscopy of the coagulated nidus vessels.ResultsHemoglobin mass loss, hematocrit loss and factors associated with intraoperative bleeding were significant different between the two cohorts. five independent factors predicting intraoperative major blood loss were identified: (1) clinical manifestations; (2,3) location and size of the nidus; (4) deep venous drainage; and (5) the number of draining veins. And the intraoperative major blood loss can not only adversely affect the surgical progression, but also predict poor perioperative outcomes for patients. Regarding the application of BW coated bipolar electrocoagulation, we found the novel hemostatic method exerted efficient hemostatic effect and reduced the damage to the vascular structure in brain AVM microsurgery.ConclusionThis study proposed a nomogram for neurosurgeons to predict intraoperative major blood loss in brain AVM microsurgery preoperatively. And intraoperative major blood loss is associated with poor patient outcomes. In addition, BW coated bipolar electrocoagulation, can be applied to control ferocious bleeding during brain AVM microsurgery, which still remains further researches

Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma

Objective: We aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC. Methods: 170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics. Results: Using quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance. Conclusion: The use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment. © Copyright © 2021 Xu, Ji, Hou, Lin, Shi, Zhou, Meng, Wang, Chen, Wang and Yang.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Correlation research of susceptibility single nucleotide polymorphisms and the severity of clinical symptoms in attention deficit hyperactivity disorder

Objective To analyze the correlation between susceptibility single nucleotide polymorphisms (SNPs) and the severity of clinical symptoms in children with attention deficit hyperactivity disorder (ADHD), so as to supplement the clinical significance of gene polymorphism and increase our understanding of the association between genetic mutations and ADHD phenotypes. Methods 193 children with ADHD were included in our study from February 2017 to February 2020 in the Children’s ADHD Clinic of the author’s medical institution. 23 ADHD susceptibility SNPs were selected based on the literature, and multiple polymerase chain reaction (PCR) targeted capture sequencing technology was used for gene analysis. A series of ADHD-related questionnaires were used to reflect the severity of the disease, and the correlation between the SNPs of specific sites and the severity of clinical symptoms was evaluated. R software was used to search for independent risk factors by multivariate logistic regression and the “corplot” package was used for correlation analysis. Results Among the 23 SNP loci of ADHD children, no mutation was detected in 6 loci, and 2 loci did not conform to Hardy-Weinberg equilibrium. Of the remaining 15 loci, there were 9 SNPs, rs2652511 (SLC6A3 locus), rs1410739 (OBI1-AS1 locus), rs3768046 (TIE1 locus), rs223508 (MANBA locus), rs2906457 (ST3GAL3 locus), rs4916723 (LINC00461 locus), rs9677504 (SPAG16 locus), rs1427829 (intron) and rs11210892 (intron), correlated with the severity of clinical symptoms of ADHD. Specifically, rs1410739 (OBI1-AS1 locus) was found to simultaneously affect conduct problems, control ability and abstract thinking ability of children with ADHD. Conclusion There were 9 SNPs significantly correlated with the severity of clinical symptoms in children with ADHD, and the rs1410739 (OBI1-AS1 locus) may provide a new direction for ADHD research. Our study builds on previous susceptibility research and further investigates the impact of a single SNP on the severity of clinical symptoms of ADHD. This can help improve the diagnosis, prognosis and treatment of ADHD

Data_Sheet_1_Correlation research of susceptibility single nucleotide polymorphisms and the severity of clinical symptoms in attention deficit hyperactivity disorder.docx

ObjectiveTo analyze the correlation between susceptibility single nucleotide polymorphisms (SNPs) and the severity of clinical symptoms in children with attention deficit hyperactivity disorder (ADHD), so as to supplement the clinical significance of gene polymorphism and increase our understanding of the association between genetic mutations and ADHD phenotypes.Methods193 children with ADHD were included in our study from February 2017 to February 2020 in the Children’s ADHD Clinic of the author’s medical institution. 23 ADHD susceptibility SNPs were selected based on the literature, and multiple polymerase chain reaction (PCR) targeted capture sequencing technology was used for gene analysis. A series of ADHD-related questionnaires were used to reflect the severity of the disease, and the correlation between the SNPs of specific sites and the severity of clinical symptoms was evaluated. R software was used to search for independent risk factors by multivariate logistic regression and the “corplot” package was used for correlation analysis.ResultsAmong the 23 SNP loci of ADHD children, no mutation was detected in 6 loci, and 2 loci did not conform to Hardy-Weinberg equilibrium. Of the remaining 15 loci, there were 9 SNPs, rs2652511 (SLC6A3 locus), rs1410739 (OBI1-AS1 locus), rs3768046 (TIE1 locus), rs223508 (MANBA locus), rs2906457 (ST3GAL3 locus), rs4916723 (LINC00461 locus), rs9677504 (SPAG16 locus), rs1427829 (intron) and rs11210892 (intron), correlated with the severity of clinical symptoms of ADHD. Specifically, rs1410739 (OBI1-AS1 locus) was found to simultaneously affect conduct problems, control ability and abstract thinking ability of children with ADHD.ConclusionThere were 9 SNPs significantly correlated with the severity of clinical symptoms in children with ADHD, and the rs1410739 (OBI1-AS1 locus) may provide a new direction for ADHD research. Our study builds on previous susceptibility research and further investigates the impact of a single SNP on the severity of clinical symptoms of ADHD. This can help improve the diagnosis, prognosis and treatment of ADHD.</p