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BackgroundThe COVID-19 outbreak has increased challenges associated with health management, especially cancer management. In an effort to provide continuous pharmaceutical care to cancer patients, Sun Yat-sen University Cancer Center (SYSUCC) implemented a remote pharmacy service platform based on its already existing web-based hospital app known as Cloud SYSUCC. ObjectiveThe aim of this study was to investigate the characteristics, acceptance, and initial impact of the Cloud SYSUCC app during a COVID-19 outbreak in a tertiary cancer hospital in China. MethodsThe total number of online prescriptions and detailed information on the service were obtained during the first 6 months after the remote service platform was successfully set up. The patients’ gender, age, residence, primary diagnosis, drug classification, weekly number of prescriptions, and prescribed drugs were analyzed. In addition, a follow-up telephonic survey was conducted to evaluate patients’ satisfaction in using the remote prescription service. ResultsA total of 1718 prescriptions, including 2022 drugs for 1212 patients, were delivered to 24 provinces and municipalities directly under the Central Government of China between February 12, 2020, and August 11, 2020. The majority of patients were female (841/1212, 69.39%), and 90.18% (1093/1212) of them were aged 31-70 years old. The top 3 primary diagnoses for which remote medical prescriptions were made included breast cancer (599/1212, 49.42%), liver cancer (249/1212, 20.54%), and thyroid cancer (125/1212, 10.31%). Of the 1718 prescriptions delivered, 1435 (83.5%) were sent to Guangdong Province and 283 (16.5%) were sent to other provinces in China. Of the 2022 drugs delivered, 1012 (50.05%) were hormonal drugs. The general trend in the use of the remote prescription service declined since the 10th week. A follow-up telephonic survey found that 88% (88/100) of the patients were very satisfied, and 12% (12/100) of the patients were somewhat satisfied with the remote pharmacy service platform. ConclusionsThe remote pharmacy platform Cloud SYSUCC is efficient and convenient for providing continuous pharmaceutical care to patients with cancer during the COVID-19 crisis. The widespread use of this platform can help to reduce person-to-person transmission as well as infection risk for these patients. Further efforts are needed to improve the quality and acceptance of the Cloud SYSUCC platform, as well as to regulate and standardize the management of this novel service.

Abstract Background Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance imaging (MRI) to diagnose FCD and identify laterality early. Methods Forty-three patients treated between July 2017 and May 2022 with histopathologically confirmed FCD were retrospectively enrolled. The contralateral unaffected hemispheres were included as the control group. Therefore, 86 ROIs were finally included. Using January 2021 as the time cutoff, those admitted after January 2021 were included in the hold-out set (n = 20). The remaining patients were separated randomly (8:2 ratio) into training (n = 55) and validation (n = 11) sets. All preoperative and postoperative MR images, including T1-weighted (T1w), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR), and combined (T1w + T2w + FLAIR) images, were included. The least absolute shrinkage and selection operator (LASSO) was used to select features. Multivariable logistic regression analysis was used to develop the diagnosis model. The performance of the radiomic nomogram was evaluated with an area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration and clinical utility. Results The model-based radiomics features that were selected from combined sequences (T1w + T2w + FLAIR) had the highest performances in all models and showed better diagnostic performance than inexperienced radiologists in the training (AUCs: 0.847 VS. 0.664, p = 0.008), validation (AUC: 0.857 VS. 0.521, p = 0.155), and hold-out sets (AUCs: 0.828 VS. 0.571, p = 0.080). The positive values of NRI (0.402, 0.607, 0.424) and IDI (0.158, 0.264, 0.264) in the three sets indicated that the diagnostic performance of Model-Combined improved significantly. The radiomics nomogram fit well in calibration curves (p > 0.05), and decision curve analysis further confirmed the clinical usefulness of the nomogram. Additionally, the contrast (the radiomics feature) of the FCD lesions not only played a crucial role in the classifier but also had a significant correlation (r = -0.319, p

Based on the waterflooding development in carbonate reservoirs in the Middle East, in order to solve the problem of the poor development effects caused by commingled injection and production, taking the thick bioclastic limestone reservoirs of Cretaceous in Iran-Iraq as an example, this paper proposes a balanced waterflooding development technology for thick and complex carbonate reservoirs. This technology includes the fine division of development units by concealed baffles and barriers, the combination of multi well type and multi well pattern, and the construction of balanced water injection and recovery system. Thick carbonate reservoirs in Iran-Iraq are characterized by extremely vertical heterogeneity, development of multi-genesis ultra-high permeability zones, and highly concealed baffles and barriers. Based on the technologies of identification, characterization, and sealing evaluation for concealed baffles and barriers, the balanced waterflooding development technology is proposed, and three types of balanced waterflooding development modes/techniques are formed, namely, conventional stratigraphic framework, fine stratigraphic framework, and deepened stratigraphic framework. Numerical simulations show that this technology is able to realize a fine and efficient waterflooding development to recover, in a balanced manner, the reserves of thick and complex carbonate reservoirs in Iran and Iraq. The proposed technology provides a reference for the development optimization of similar reservoirs.