Impact of COVID-19 on patient and healthcare professional attitudes, beliefs, and behaviors toward the healthcare system and on the dynamics of the healthcare pathway

Background COVID-19 has dramatically changed how healthcare is delivered and experienced. Methods One-on-one interviews and a virtual ethnographic roundtable were conducted among 45 patients, caregivers, and healthcare professionals (HCPs) in 4 therapeutic areas from the United States and Japan: overactive bladder, vasomotor symptoms, prostate cancer, and metastatic urothelial carcinoma. The goal was to identify the impact of COVID-19 on patient/caregiver and HCP attitudes, interactions, beliefs, and behaviors toward the healthcare system and care pathway. Results Four foundational themes were identified: 1) COVID-19 risk is relative; 2) isolation is collateral damage; 3) telehealth is a parallel universe; and 4) COVID-19 is destabilizing the foundations of healthcare. Numerous insights, influenced by diverse cultural, social, and psychological factors, were identified within each theme. Conclusions The impacts of COVID-19 were noticeable at multiple points of care during the “universal” care pathway, including at initial screening, referral to specialists, diagnosis, treatment initiation/surgery, and during ongoing care. Greater appreciation of the short- and long-term impacts of COVID-19 and resulting gaps in care may act as a catalyst for positive change in future patient care.

An Introduction to Robotically Assisted Surgical Systems: Current Developments and Focus Areas of Research

Purpose of Review Robotic assistance systems for diagnosis and therapy have become technically mature and widely available. Thus, they play an increasingly important role in patient care. This paper provides an overview of the general concepts of robotically assisted surgical systems, briefly revisiting historical and current developments in the surgical robotics market and discussing current focus areas of research. Comprehensiveness cannot be achieved in this format, but besides the general overview, references to further readings and more comprehensive reviews with regard to particular aspects are given. Therefore, the work at hand is considered as an introductory paper into the topic and especially addresses investigators, researchers, medical device manufacturers, and clinicians, who are new to this field. Recent Findings The current research in Robotically Assisted Surgical Systems (RASS) increasingly uses established robotic platforms. To minimize the patient trauma while optimizing the dexterity of the surgeon, miniaturized instruments and semi-autonomous assistance functions are developed. To provide the surgeon with all necessary information in an adequate manner, novel imaging sensors as well as techniques for multimodal sensory feedback and augmented reality are investigated. The Surgical Data Science applies data management and processing approaches including machine learning on medical data to provide optimal, individualized and contextual support to the surgeon. Summary Robotic systems will significantly influence future patient care. Since they must fulfill manifold medical, technical, regulatory and economic requirements, their development calls for a close, active and interdisciplinary cooperation between stakeholders from hospitals, industry and science.

Belatacept dosing in Lung Transplantation: is there a Method to the Madness?

Data supporting the use of belatacept in non-abdominal organs are limited to case series and small cohorts involving patients requiring conversion due to CNI intolerance or contraindication. Review articles summarizing the efficacy of belatacept salvage therapy in lung transplantation have previously been published, however, dosing regimens are highly variable and uniform guidance is lacking. In this article, indications and considerations for belatacept use in lung transplant recipients are reviewed with a specific focus on dosing regimens. Utilization of standardized dosing protocols to guide belatacept conversion will both improve the ability to directly assess outcomes and provide the opportunity to improve future patient care. A suggested framework for dosing selection and timeline for cross titration is proposed herein.

Predicting Inpatient Status for the Next 30/60/90 Days With Machine Learning

In this paper, we report the development of machine learning techniques which can help hospital authorities assess a patients' medical condition and also calculate the probability of readmission of the patient as inpatient, and thus identify patients with higher risks for readmissions. Factor Analysis is performed on patient data to understand the severity of mental health, and Random Forest models are used to determine the probability of a patient becoming an inpatient for the next 30/60/90 days from their last visit to the physician’s office. The Random Forest model fits the data with an overall OOB Error rate of 3.69% and an accuracy of 97.65%. The accuracy on the test data was 96.11%. A web application is also developed to provide a user-friendly interface for physicians and administrators to interact with and obtain relevant information for a given patient and or a group of patients. The web application affords physicians additional inputs to assist in their diagnosis and administrators, a window into anticipating and preparing for future patient needs.

Predicting Inpatient Status for the next 30/60/90 Days with Machine Learning

In this paper, we report the development of machine learning techniques which can help hospital authorities assess a patients' medical condition and also calculate the probability of readmission of the patient as inpatient, and thus identify patients with higher risks for readmissions. Factor Analysis is performed on patient data to understand the severity of mental health, and Random Forest models are used to determine the probability of a patient becoming an inpatient for the next 30/60/90 days from their last visit to the physician’s office. The Random Forest model fits the data with an overall OOB Error rate of 3.69% and an accuracy of 97.65%. The accuracy on the test data was 96.11%. A web application is also developed to provide a user-friendly interface for physicians and administrators to interact with and obtain relevant information for a given patient and or a group of patients. The web application affords physicians additional inputs to assist in their diagnosis and administrators, a window into anticipating and preparing for future patient needs.

A Sex Perspective in Neurodegenerative Diseases: microRNAs as Possible Peripheral Biomarkers

Sex is a significant variable in the prevalence and incidence of neurological disorders. Sex differences exist in neurodegenerative disorders (NDs), where sex dimorphisms play important roles in the development and progression of Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. In the last few years, some sex specific biomarkers for the identification of NDs have been described and recent studies have suggested that microRNA (miRNA) could be included among these, as influenced by the hormonal and genetic background. Failing to consider the possible differences between males and females in miRNA evaluation could introduce a sex bias in studies by not considering some of these sex-related biomarkers. In this review, we recapitulate what is known about the sex-specific differences in peripheral miRNA levels in neurodegenerative diseases. Several studies have reported sex-linked disparities, and from the literature analysis miR-206 particularly has been shown to have a sex-specific involvement. Hopefully, in the near future, patient stratification will provide important additional clues in diagnosis, prognosis, and tailoring of the best therapeutic approaches for each patient. Sex-specific biomarkers, such as miRNAs, could represent a useful tool for characterizing subgroups of patients.

True Umbilical Cord Knot in a Primigravida

Umbilical cord knots occur in 1-2% of all deliveries can lead to increase in fetal death and asphyxia. A thorough cord examination is important to discern abnormalities. Although there are not set guidelines for diagnosing and managing umbilical cord knots; increase of reporting with complications will aid in decision making for better future patient management. We describe one such case in a primigravida who was found to have an umbilical cord knot.

Comparison of programmed death-ligand 1 protein expression between primary and metastatic lesions in patients with lung cancer

Assessment of programmed cell death-ligand 1 (PD-L1) expression by immunohistochemistry (IHC) is the definite diagnostic test to guide treatment for patients with advanced-stage non-small cell lung cancer. Intratumoral heterogeneity and discrepancy of PD-L1 expression between primary and metastatic lesions may increase the risk of tumor misclassification. We performed a retrospective study of the Foundation Medicine, Inc clinical database on lung cancer cases that were evaluated for PD-L1 expression by IHC in the context of routine care. All cases were assessed with the Food and Drug Administration-approved 22C3 pharmDx assay and scoring system. 15,028 lung cancer cases, including 8285 primary tumors and 6743 unmatched metastatic lesions were analyzed. Metastatic lesions (mets) were more frequently high positive (tumor proportion score (TPS) ≥50%) for PD-L1 expression than primary lesions (33.8% vs 28.4%; OR, 1.28; 95% CI, 1.19 to 1.37; p<0.001). Higher levels in mets than primaries were seen in samples from lymph nodes, pleural fluid, soft tissue and adrenal gland but not in those from liver, brain and bone. Metastatic lesions of patients with non-squamous histology were more likely to have TPS ≥50% in comparison with primary (OR, 1.37; 95% CI, 1.27 to 1.49; p<0.001), but this was not the case for patients with squamous histology (OR, 0.89; 95% CI, 0.74 to 1.06; p=0.197). PD-L1 expression varies with respect to histologic subtype, sampling site and gender, but is generally higher in metastatic sites. This observation may affect future patient management and trial design.