Prenatal MRI assessment of mediastinal shift angle as a feasible and effective risk stratification tool in isolated right-sided congenital diaphragmatic hernia.

OBJECTIVES: To develop a mediastinal shift angle (MSA) measurement method applicable to right-sided congenital diaphragmatic hernia (RCDH) in fetal MRI and to validate the predictive value of MSA in RCDH. METHODS: Twenty-seven fetuses with isolated RCDH and 53 controls were included in our study. MSA was measured on MRI axial image at the level of four-chamber view of the fetal heart. The angle between the sagittal midline landmark line and the left boundary landmark line touching tangentially the lateral wall of the left ventricle was used to quantify MSA for RCDH. Appropriate statistical analyses were performed to determine whether MSA can be regarded as a valid predictive tool for postnatal outcomes. Furthermore, predictive performance of MSA was compared with that of lung area to head circumference ratio (LHR), observed/expected LHR (O/E LHR), total fetal lung volume (TFLV), and observed/expected TFLV (O/E TFLV). RESULTS: MSA was significantly higher in the RCDH group than in the control group. MSA, LHR, O/E LHR, TFLV, and O/E TFLV were all correlated with postnatal survival, pulmonary hypertension (PH), and extracorporeal membrane oxygenation (ECMO) therapy (p < 0.05). Value of the AUC demonstrated good predictive performance of MSA for postnatal survival (0.901, 95%CI: (0.781-1.000)), PH (0.828, 95%CI: (0.661-0.994)), and ECMO therapy (0.813, 95%CI: (0.645-0.980)), which was similar to O/E TFLV but slightly better than TFLV, O/E LHR, and LHR. CONCLUSIONS: We developed a measurement method of MSA for RCDH for the first time and demonstrated that MSA could be used to predict postnatal survival, PH, and ECMO therapy in RCDH. CLINICAL RELEVANCE STATEMENT: Newly developed MRI assessment method of fetal MSA in RCDH offers a simple and effective risk stratification tool for patients with RCDH. KEY POINTS: • We developed a measurement method of mediastinal shift angle for right-sided congenital diaphragmatic hernia for the first time and demonstrated its feasibility and reproducibility. • Mediastinal shift angle can predict more prognostic information other than survival in right-sided congenital diaphragmatic hernia with good performance. • Mediastinal shift angle can be used as a simple and effective risk stratification tool in right-sided congenital diaphragmatic hernia to improve planning of postnatal management.

Patient Welfare Implications of Indication-Specific Value-Based Pricing of Multi-Indication Drugs.

OBJECTIVES: Indication-specific value-based pricing (ISVBP) is a mechanism that allows the prices of multi-indication drugs to vary across indications by aligning the drug prices with value. However, the overall impact of ISVBP on patients across indications is uncertain. This study examines the theoretical welfare effects of ISVBP for multi-indication drugs and compares consumer surplus under ISVBP and single pricing, the latter of which is based on the weighted average value. METHODS: We considered a healthcare system with government-negotiated drug prices based on the value of drugs. We assumed a drug with 2 indications and 1 relevant comparator for each indication. The value of the drug was uniformly distributed among the patients of each indication in the base case. We also considered alternative scenarios with exponentially and Pareto distributed drug values. Numerical simulations were conducted to explore potential settings where ISVBP was welfare-improving for patients compared with single pricing. RESULTS: The theoretical analysis showed that the consumer surplus change was strictly non-positive from single pricing to ISVBP. Therefore, it was not welfare-improving for patients in the settings of interest. Numerical simulations confirmed this result across various scenarios of value distributions. CONCLUSIONS: This study provides insights into the patient welfare implications of ISVBP for multi-indication drugs. We did not identify conditions under which ISVBP can enhance overall patient well-being, suggesting that it should be implemented cautiously. Future research should examine dynamic welfare implications related to innovation incentives because they may significantly affect population health in the future.

Impact of CYP2A6 Gene Polymorphism on the Efficacy and Safety of S-1 Therapy in Patients with Gastric Cancer: A Systematic Review and Meta-Analysis.

INTRODUCTION: The relationship of CYP2A6 polymorphisms with S-1 therapy outcomes in gastric cancer is unclear. This review aimed to assess the association between CYP2A6 gene polymorphisms (CYP2A6*4, *7, *9, *10) and S-1 therapy outcomes in gastric cancer, aiming to identify predictive markers for S-1 efficacy and adverse reactions. METHODS: We searched seven databases, using random or fixed-effect models to calculate hazard ratio (HR) and 95% confidence interval (CI) based on study heterogeneity. RESULTS: A total of 1,143 articles were retrieved from multiple online databases as of March 28, 2023. After screening, seven articles containing seven investigations were included in the meta-analysis. Our results revealed a significant association between the CYP2A6 polymorphism site and the overall survival (OS) of variant/variant group (V/V) patients compared to wild-type/wild-type (W/W) or wild-type/variant (W/V) patients (HR = 2.73, 95% CI: 1.45-5.14, p = 0.002). S-1 was more beneficial for W/W or W/V patients than V/V patients in terms of progression-free survival (PFS) (HR = 3.15, 95% CI: 1.47-6.75, p = 0.003). There was no association between CYP2A6 polymorphism and hematological adverse reactions (OR = 0.52, 95% CI: 0.23-1.15, p = 0.104). CONCLUSION: CYP2A6 polymorphisms correlate with S-1 efficacy (OS and PFS) in gastric cancer, suggesting their potential as predictive markers. However, the generalizability of findings is limited by the small number of studies from Eastern countries and variations in chemotherapy regimens and detection methods. Further, large-scale studies are needed to confirm these associations.

Cerebral circulation time on DSA after thrombectomy associated with hemorrhagic transformation in acute ischemic stroke.

BACKGROUND: To investigate the association between cerebral circulation time (CCT) on digital subtraction angiography immediately after thrombectomy and hemorrhagic transformation (HT) in acute ischemic stroke (AIS). METHODS: Retrospectively enrolled consecutive AIS patients presented with large vessel occlusion who received thrombectomy and achieved successful recanalization between January 2019 and June 2021. The time interval from the beginning of the siphon segment of internal carotid artery visualization until the end of the arterial phase during cerebral angiography was calculated as CCT. The independent association of CCT with HT was evaluated using logistic regression analyses. The receiver operating characteristic curve was analyzed to evaluate the association between CCT and HT. RESULTS: Two hundred and twenty-four patients were included, of whom 86 (38.4%) suffered HT. Compared with patients without HT, patients with HT were of advanced age, less commonly male, had more diabetes mellitus, had higher baseline National Institutes of Health Stroke Scale score, lower Alberta Stroke Program Early Computed Tomographic Score, and shorter CCT (P < 0.05). Multivariable logistic regression suggested that CCT was independently associated with HT (adjusted odds ratio, 0.170; 95% confidence interval, 0.004-0.450; P < 0.001). According to the receiver operating characteristic curve, the optimal cut-off value for the strong correlation between CCT and HT was 1.72 s, which had 76.6% sensitivity, 81.6% specificity, and the area under the curve was 0.846. CONCLUSION: Shorter post-thrombectomy CCT was independently associated with HT.

Manganese promotes α-synuclein amyloid aggregation through the induction of protein phase transition.

α-Synuclein (α-Syn) is the major protein component of Lewy bodies, a key pathological feature of Parkinson's disease (PD). The manganese ion Mn2+ has been identified as an environmental risk factor of PD. However, it remains unclear how Mn2+ regulates α-Syn aggregation. Here, we discovered that Mn2+accelerates α-Syn amyloid aggregation through the regulation of protein phase separation. We found that Mn2+ not only promotes α-Syn liquid-to-solid phase transition but also directly induces soluble α-Syn monomers to form solid-like condensates. Interestingly, the lipid membrane is integrated into condensates during Mn2+-induced α-Syn phase transition; however, the preformed Mn2+/α-syn condensates can only recruit lipids to the surface of condensates. In addition, this phase transition can largely facilitate α-Syn amyloid aggregation. Although the Mn2+-induced condensates do not fuse, our results demonstrated that they could recruit soluble α-Syn monomers into the existing condensates. Furthermore, we observed that a manganese chelator reverses Mn2+-induced α-Syn aggregation during the phase transition stage. However, after maturation, α-Syn aggregation becomes irreversible. These findings demonstrate that Mn2+ facilitates α-Syn phase transition to accelerate the formation of α-Syn aggregates and provide new insights for targeting α-Syn phase separation in PD treatment.

Mediastinal shift angle (MSA) measurement with MRI: a simple and effective tool for prenatal risk stratification in fetuses with congenital diaphragmatic hernia.

OBJECTIVES: To investigate the predictive value of mediastinal shift angle (MSA) in congenital diaphragmatic hernia (CDH). METHODS: A retrospective analysis was performed on 87 fetuses with prenatally diagnosed left-sided CDH (LCDH) and 88 controls. MSA was measured on magnetic resonance imaging (MRI). Lung area to head circumference ratio (LHR), ratio of the observed/expected LHR (O/E LHR), total fetal lung volume (TFLV), and observed/expected total fetal lung volume (O/E TFLV) were also measured. Correlation of MSA with pulmonary hypertension (PH), extracorporeal membrane oxygenation (ECMO) use, duration of hospitalization and survival in neonates with CDH was analyzed. Performance of MSA in prediction of postnatal outcomes was compared with LHR, O/E LHR, TFLV, and O/E TFLV. RESULTS: There were significant differences in MSA values not only between the CDH group and the control group but also in CDH patients with different survival outcomes. MSA was inversely correlated with O/E LHR, O/E TFLV, and TFLV. MSA, LHR, O/E LHR, TFLV, and O/E TFLV could all be used to predict survival of CDH patients. In addition, the receiver operating characteristic (ROC) curve showed that the test performance of MSA was similar to that of TFLV, O/E TFLV, and O/E LHR, but superior to that of LHR. MSA was also correlated with PH, need for ECMO support, and duration of hospitalization. CONCLUSION: MRI measurement of MSA can provide various prognostic information for prenatally diagnosed LCDH, in addition to postnatal survival. The test performance of MSA is similar to TFLV, O/E TFLV, and O/E LHR. KEY POINTS: • Mediastinal shift angle (MSA) can be measured quickly and reproducibly on MRI images. • MSA could provide more prognostic information other than postnatal survival for LCDH with good test performance. • MSA should be incorporated into prenatal risk stratification for LCDH to improve planning of postnatal management.

Pick's disease presenting with corticobasal syndrome: A case report and clinicopathological review.

Pick's disease (PiD) is a rare form of frontal temporal lobar degeneration. The pathognomonic feature is atrophy of the frontotemporal lobes and intraneuronal deposits of 3R-τ inclusions, the Pick body. Corticobasal syndrome (CBS) is an atypical parkinsonian syndrome with a heterogeneous spectrum of underlying pathologies. We report a case of clinically diagnosed CBS with a post-mortem diagnosis of PiD and conduct a clinicopathological review of the literature on this unusual presentation.

Population impact of fine particulate matter on tuberculosis risk in China: a causal inference.

BACKGROUND: Previous studies have suggested the potential association between air pollution and tuberculosis incidence, but this association remains inconclusive and evidence to assess causality is particularly lacking. We aimed to draw causal inference between fine particulate matter less than 2.5 µm in diameter (PM2.5) and tuberculosis in China. METHODS: Granger causality (GC) inference was performed within vector autoregressive models at levels and/or first-differences using annual national aggregated data during 1982-2019, annual provincial aggregated data during 1982-2019 and monthly provincial aggregated data during 2004-2018. Convergent cross-mapping (CCM) approach was used to determine the backbone nonlinear causal association based on the monthly provincial aggregated data during 2004-2018. Moreover, distributed lag nonlinear model (DLNM) was applied to quantify the causal effects. RESULTS: GC tests identified PM2.5 driving tuberculosis dynamics at national and provincial levels in Granger sense. Empirical dynamic modeling provided the CCM causal intensity of PM2.5 effect on tuberculosis at provincial level and demonstrated that PM2.5 had a positive effect on tuberculosis incidence. Then, DLNM estimation demonstrated that the PM2.5 exposure driven tuberculosis risk was concentration- and time-dependent in a nonlinear manner. This result still held in the multi-pollutant model. CONCLUSIONS: Causal inference showed that PM2.5 exposure driving tuberculosis, which showing a concentration gradient change. Air pollutant control may have potential public health benefit of decreasing tuberculosis burden.

Individual differences in contextual threat generalisation and uncertainty: The role of intolerance of uncertainty.

Threat generalisation is an adaptive process that is essential for individual survival. In contrast, over-generalisation is a pathological process that underlies the development of anxiety disorders. Intolerance of uncertainty (IU) is an individual characteristic known to influence threat generalisation by altering the responses to threat in uncertain situations. However, how it affects contextual threat generalisation remains unclear. Here, we used a novel paradigm to investigate whether contextual threat generalisation varied between individuals depending on their IU level (high or low) and the predictability of a situation (predictable or unpredictable). We analysed shock expectancy in 82 participants (age: 18-27 years) during threat acquisition and generalisation. Results showed that compared with the low IU group, the high IU group exhibited increased contextual threat generalisation to threat-related cues in unpredictable situation. These findings suggest that IU could be a marker for anxiety disorder susceptibility, as well as a target for anxiety treatment.

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi-attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost-effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient-Reported Outcomes Measurement Information System Global Health 10 (PROMIS-GH10) to the EuroQol five dimensions (EQ-5D-5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out-performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out-performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.