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Of 141 women with twin pregnancies, 72 were randomly assigned to outpatient care and 69 to hospital admission between 26 and 30 weeks' gestation. There were no differences between the groups in the frequencies of major maternal complications in pregnancy and labour but more of those admitted to hospital than of the outpatient group had to be admitted after 30 weeks. There were no differences between the groups in the mean birthweights of the twins by birth order, or in their mean gestation at birth whether analysed by intention to treat or by the treatment given. 22 infants were delivered before 32 weeks' gestation in the inpatient group compared with 10 in the outpatient group. With the exception of small-for-dates infants, any trend towards greater morbidity or mortality was seen in the inpatient group. The policy of routine hospital admission of women with twin pregnancies from 26 weeks' gestation is not beneficial to mother or babies and should be abandoned. [ABSTRACT FROM AUTHOR]

Background: Personalising management of primary oesophageal adenocarcinoma requires better risk stratification. Lack of independent validation of proposed imaging biomarkers has hampered clinical translation. We aimed to prospectively validate previously identified prognostic grey-level co-occurrence matrix (GLCM) CT features for 3-year overall survival., Methods: Following ethical approval, clinical and contrast-enhanced CT data were acquired from participants from five institutions. Data from three institutions were used for training and two for testing. Survival classifiers were modelled on prespecified variables ('Clinical' model: age, clinical T-stage, clinical N-stage; 'ClinVol' model: clinical features + CT tumour volume; 'ClinRad' model: ClinVol features + GLCM_Correlation and GLCM_Contrast). To reflect current clinical practice, baseline stage was also modelled as a univariate predictor ('Stage'). Discrimination was assessed by area under the receiver operating curve (AUC) analysis; calibration by Brier scores; and clinical relevance by thresholding risk scores to achieve 90% sensitivity for 3-year mortality., Results: A total of 162 participants were included (144 male; median 67 years [IQR 59, 72]; training, 95 participants; testing, 67 participants). Median survival was 998 days [IQR 486, 1594]. The ClinRad model yielded the greatest test discrimination (AUC, 0.68 [95% CI 0.54, 0.81]) that outperformed Stage (ΔAUC, 0.12 [95% CI 0.01, 0.23]; p = .04). The Clinical and ClinVol models yielded comparable test discrimination (AUC, 0.66 [95% CI 0.51, 0.80] vs. 0.65 [95% CI 0.50, 0.79]; p > .05). Test sensitivity of 90% was achieved by ClinRad and Stage models only., Conclusions: Compared to Stage, multivariable models of prespecified clinical and radiomic variables yielded improved prediction of 3-year overall survival., Clinical Relevance Statement: Previously identified radiomic features are prognostic but may not substantially improve risk stratification on their own., Key Points: • Better risk stratification is needed in primary oesophageal cancer to personalise management. • Previously identified CT features-GLCM_Correlation and GLCM_Contrast-contain incremental prognostic information to age and clinical stage. • Compared to staging, multivariable clinicoradiomic models improve discrimination of 3-year overall survival., (© 2024. The Author(s).)

Background: Programmed death-ligand 1 (PD-L1) expression is a predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). PD-L1 and glucose transporter 1 expression are closely associated, and studies demonstrate correlation of PD-L1 with glucose metabolism., Aim: The aim of this study was to investigate the association of fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([ 18 F]FDG-PET/CT) metabolic parameters with PD-L1 expression in primary lung tumour and lymph node metastases in resected NSCLC., Methods: We conducted a retrospective analysis of 210 patients with node-positive resectable stage IIB-IIIB NSCLC. PD-L1 tumour proportion score (TPS) was determined using the DAKO 22C3 immunohistochemical assay. Semi-automated techniques were used to analyse pre-operative [ 18 F]FDG-PET/CT images to determine primary and nodal metabolic parameter scores (including max, mean, peak and peak adjusted for lean body mass standardised uptake values (SUV), metabolic tumour volume (MTV), total lesional glycolysis (TLG) and SUV heterogeneity index (HISUV))., Results: Patients were predominantly male (57%), median age 70 years with non-squamous NSCLC (68%). A majority had negative primary tumour PD-L1 (TPS < 1%; 53%). Mean SUV max , SUV mean , SUV peak and SUL peak values were significantly higher (p < 0.05) in those with TPS ≥ 1% in primary tumour (n = 210) or lymph nodes (n = 91). However, ROC analysis demonstrated only moderate separability at the 1% PD-L1 TPS threshold (AUCs 0.58-0.73). There was no association of MTV, TLG and HISUV with PD-L1 TPS., Conclusion: This study demonstrated the association of SUV-based [ 18 F]FDG-PET/CT metabolic parameters with PD-L1 expression in primary tumour or lymph node metastasis in resectable NSCLC, but with poor sensitivity and specificity for predicting PD-L1 positivity ≥ 1%., Clinical Relevance Statement: Whilst SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography metabolic parameters may not predict programmed death-ligand 1 positivity ≥ 1% in the primary tumour and lymph nodes of resectable non-small cell lung cancer independently, there is a clear association which warrants further investigation in prospective studies., Trial Registration: Non-applicable KEY POINTS: • Programmed death-ligand 1 immunohistochemistry has a predictive role in non-small cell lung cancer immunotherapy; however, it is both heterogenous and dynamic. • SUV-based fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography ([ 18 F]FDG-PET/CT) metabolic parameters were significantly higher in primary tumour or lymph node metastases with positive programmed death-ligand 1 expression. • These SUV-based parameters could potentially play an additive role along with other multi-modal biomarkers in selecting patients within a predictive nomogram., (© 2024. The Author(s).)

Introduction: Diagnostic genomic sequencing is the emerging standard of care in nephrology. There is a growing need to scale up the implementation of genomic diagnostics nationally to improve patient outcomes., Methods: This pragmatic study provided genomic or genetic testing to patients with suspected monogenic kidney disease through a national network of kidney genetics clinics (KGCs). We sought to evaluate the experiences of implementing genomic diagnostics across Australia and associated diagnostic outcomes between 2013 and 2022., Results: We successfully established and expanded a nationwide network of 20 clinics as of 2022; concurrently developing laboratory, research, and education programs to scale the clinical application of genomics in nephrology. We report on an Australian cohort of 1506 kidney patients, of whom 1322 received their test results. We assessed barriers to implementation in the nephrology context, and where possible, applied real-time solutions to improve clinical processes over 10 years., Conclusion: Developing a multidisciplinary kidney genetics model across multiple health services nationally was highly successful. This model supported optimal care of individuals with monogenic kidney disease in an economically responsible way. It has continued to evolve with technological and service developments and is now set to scale further as genomic testing for kidney patients transitions to health care system funding., (© 2024 International Society of Nephrology. Published by Elsevier Inc.)

The offshore Multi-use Setting (MUS) is a concept that aims to co-locate marine industrial activities, including wind farms and aquaculture. MUS is considered an innovative approach to promoting efficiency in space and resource use whilst contributing global policy priorities. However, the impacts of MUS development across social, economic, and environmental domains are uncertain, hindering the commercialisation of the concept. In this study, we initially demonstrate the potential consequences of co-locating seaweed aquaculture and a wind farm as a step towards MUS. Using a hypothetical case study and modified Delphi methodology, 14 subject matter experts predicted potential outcomes across social and environmental objectives. Five Cognitive maps and impact tables of 58 potential consequences were generated based on experts' perspective on co-locating seaweed aquaculture and a wind farm. The findings highlight the potential to exasperate pressures in the area, including those already attributed to wind farm operations, such as species mortality and stakeholder conflict. However, it may also enhance social-ecological conditions, such as resource provisioning and promoting habitat functionality in the region, through the addition of seaweed aquaculture. The cognitive maps demonstrate the complexity of managing MUS implementation, where high degree of variability and uncertainty about the outcomes is present. The findings of this study provide the vital entry point to performing further integrative assessment and modelling approaches, such as probabilistic analysis and simulations, in support of MUS decision-making. The research also strongly recommends alternative strategies in the pursuit of combining seaweed production and wind farms to avoid significant financial (among many other) trade-offs and risks. More broadly, we have found that our approach's ability to visually represent a complex situation while considering multiple objectives could be immensely valuable for other bioeconomy innovations or nature-based solutions. It helps mitigate the potential for expensive investments without a comprehensive evaluation of the associated risks and negative impacts, as necessitated by the principles of sustainability in decision-making., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)