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The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage
https://ir.cnu.edu.tw/handle/310902800/34571
title: The Added Value of Intraventricular Hemorrhage on the Radiomics Analysis for the Prediction of Hematoma Expansion of Spontaneous Intracerebral Hemorrhage abstract: Background: Among patients undergoing head computed tomography (CT) scans within 3 h of spontaneous intracerebral hemorrhage (sICH), 28% to 38% have hematoma expansion (HE) on follow-up CT. This study aimed to predict HE using radiomics analysis and investigate the impact of intraventricular hemorrhage (IVH) compared with the conventional approach based on intraparenchymal hemorrhage (IPH) alone. Methods: This retrospective study enrolled 127 patients with baseline and follow-up non-contrast CT (NCCT) within 4 similar to 72 h of sICH. IPH and IVH were outlined separately for performing radiomics analysis. HE was defined as an absolute hematoma growth > 6 mL or percentage growth > 33% of either IPH (HEP) or a combination of IPH and IVH (HEP+V) at follow-up. Radiomic features were extracted using PyRadiomics, and then the support vector machine (SVM) was used to build the classification model. For each case, a radiomics score was generated to indicate the probability of HE. Results: There were 57 (44.9%) HEP and 70 (55.1%) non-HEP based on IPH alone, and 58 (45.7%) HEP+V and 69 (54.3%) non-HEP+V based on IPH + IVH. The majority (>94%) of HE patients had poor early outcomes (death or modified Rankin Scale > 3 at discharge). The radiomics model built using baseline IPH to predict HEP (RMP) showed 76.4% accuracy and 0.73 area under the ROC curve (AUC). The other model using IPH + IVH to predict HEP+V (RMP+V) had higher accuracy (81.9%) with AUC = 0.80, and this model could predict poor outcomes. The sensitivity/specificity of RMP and RMP+V for HE prediction were 71.9%/80.0% and 79.3%/84.1%, respectively. Conclusion: The proposed radiomics approach with additional IVH information can improve the accuracy in prediction of HE, which is associated with poor clinical outcomes. A reliable radiomics model may provide a robust tool to help manage ICH patients and to enroll high-risk ICH cases into anti-expansion or neuroprotection drug trials.
<br>Association of labor epidural analgesia exposure with long-term risk of autism spectrum disorder in offspring: A meta-analysis of observational studies
https://ir.cnu.edu.tw/handle/310902800/34540
title: Association of labor epidural analgesia exposure with long-term risk of autism spectrum disorder in offspring: A meta-analysis of observational studies abstract: To investigate the association between labor epidural analgesia exposure and the risk of autism spectrum disorder in offspring, this meta-analysis reviewed relevant literature from Medline, Cochrane Library, Google Scholar, and EMBASE databases from inception to May 2022 to evaluate the overall adjusted risk of autism spectrum disorder in offspring (primary outcome) and adjusted risks of autism spectrum disorder focusing on sibling-matched data, children who were delivered vaginally, and duration of labor epidural analgesia exposure (secondary outcomes). Pooled results of seven eligible observational studies involving 4,021,406 children revealed slightly higher risks of autism spectrum disorder in children with labor epidural analgesia exposure than those without (hazard ratio = 1.11, 95% confidence interval: 1.06-1.16, I-2 = 67%, seven studies, level of evidence: very low). Consistent findings were found in subgroup analysis focusing on sibling data (hazard ratio: 1.10, 95% confidence interval: 1.02-1.18, I-2 = 0%, five studies) and children delivered vaginally (hazard ratio: 1.11, 95% confidence interval: 1.06-1.17, I-2 = 64%, seven studies). The tendency of an increased risk of autism spectrum disorder in children exposed to labor epidural analgesia 8 h (two studies). Although our results demonstrated a slightly increased risk of autism spectrum disorder in offspring with previous labor epidural analgesia exposure, the small effect size and lack of cumulative dose-response effect precluded tangible evidence supporting the association. Lay abstract A previous meta-analysis has demonstrated a superior analgesic efficacy of epidural analgesia (e.g. labor epidural analgesia) in comparison with non-epidural approaches. The widely accepted safety of labor epidural analgesia also endorses its current popularity in obstetric practice. However, the results of a recent large-scale longitudinal study that demonstrated a significant increase in risk of autism spectrum disorder in offspring from mothers with labor epidural analgesia exposure have raised some concerns over the safety of its use. The current meta-analysis aimed at examining the strength of evidence regarding this issue based on updated clinical data. Through systematically reviewing seven eligible observational studies involving 4,021,406 children from electronic databases, our results showed a slight but statistically significant increase in risk of autism spectrum disorder in children with exposure to labor epidural analgesia compared with those without. The finding was consistent in subgroup analysis focusing on siblings and children delivered vaginally. Nevertheless, despite the tendency of an increased risk of autism spectrum disorder in children exposed to labor epidural analgesia <4 h, this effect was not observed in those exposed to labor epidural analgesia >8 h (data from two studies). In conclusion, the level of evidence linking labor epidural analgesia to autism spectrum disorder development in offspring was very low based on the latest data because of the small effect size and the finding of a lack of cumulative dose-response effect in the current analysis. Further studies are warranted to provide an insight into this issue.
<br>Comparison between laryngeal handshake and palpation techniques in the identification of cricothyroid membrane: a meta-analysis
https://ir.cnu.edu.tw/handle/310902800/34493
title: Comparison between laryngeal handshake and palpation techniques in the identification of cricothyroid membrane: a meta-analysis abstract: Because the use of conventional digital palpation technique for the identification of cricothyroid membrane (CTM) has been widely believed to be unreliable, the 'laryngeal handshake' technique (LH) has been introduced for CTM identification in the event of cricothyroidotomy. To provide evidence for clinical practice, this pilot meta-analysis aimed at investigating whether identification of CTM with the LH is superior to that with the palpation technique. Studies that evaluated the accuracy of CTM identification by using LH or palpation techniques (i.e., LH group vs. Palpation group) were identified from electronic databases including PubMed, Embase, Medline, google scholar, Cochrane Central Register of Controlled Trials from inception to July 5, 2020. The primary outcome was the accuracy of both techniques. Four studies published from 2018 to 2020 were considered relevant and were read in full. We found no significant difference in success rate of CTM identification [Risk Ratio (RR) 1.09, 95% CI 0.89-1.34, p = 0.41] between the two groups. These preliminary results of the current study demonstrated no significant differences in success rate between the laryngeal handshake and conventional palpation techniques in cricothyroid membrane identification.
<br>A Real-Time Artificial Intelligence-Assisted System to Predict Weaning from Ventilator Immediately after Lung Resection Surgery
https://ir.cnu.edu.tw/handle/310902800/34455
title: A Real-Time Artificial Intelligence-Assisted System to Predict Weaning from Ventilator Immediately after Lung Resection Surgery abstract: Assessment of risk before lung resection surgery can provide anesthesiologists with information about whether a patient can be weaned from the ventilator immediately after surgery. However, it is difficult for anesthesiologists to perform a complete integrated risk assessment in a time-limited pre-anesthetic clinic. We retrospectively collected the electronic medical records of 709 patients who underwent lung resection between 1 January 2017 and 31 July 2019. We used the obtained data to construct an artificial intelligence (AI) prediction model with seven supervised machine learning algorithms to predict whether patients could be weaned immediately after lung resection surgery. The AI model with Naive Bayes Classifier algorithm had the best testing result and was therefore used to develop an application to evaluate risk based on patients' previous medical data, to assist anesthesiologists, and to predict patient outcomes in pre-anesthetic clinics. The individualization and digitalization characteristics of this AI application could improve the effectiveness of risk explanations and physician-patient communication to achieve better patient comprehension.
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