Evaluation of a Remote Patient Monitoring Program During the COVID-19 Pandemic: Retrospective Case Study With a Mixed Methods Explanatory Sequential Design.

BACKGROUND: Community health center (CHC) patients experience a disproportionately high prevalence of chronic conditions and barriers to accessing technologies that might support the management of these conditions. One such technology includes tools used for remote patient monitoring (RPM), the use of which surged during the COVID-19 pandemic. OBJECTIVE: The aim of this study was to assess how a CHC implemented an RPM program during the COVID-19 pandemic. METHODS: This retrospective case study used a mixed methods explanatory sequential design to evaluate a CHC's implementation of a suite of RPM tools during the COVID-19 pandemic. Analyses used electronic health record-extracted health outcomes data and semistructured interviews with the CHC's staff and patients participating in the RPM program. RESULTS: The CHC enrolled 147 patients in a hypertension RPM program. After 6 months of RPM use, mean systolic blood pressure (BP) was 13.4 mm Hg lower and mean diastolic BP 6.4 mm Hg lower, corresponding with an increase in hypertension control (BP<140/90 mm Hg) from 33.3% of patients to 81.5%. Considerable effort was dedicated to standing up the program, reinforced by organizational prioritization of chronic disease management, and by a clinician who championed program implementation. Noted barriers to implementation of the RPM program were limited initial training, lack of sustained support, and complexities related to the RPM device technology. CONCLUSIONS: While RPM technology holds promise for addressing chronic disease management, successful RPM program requires substantial investment in implementation support and technical assistance.

Long-Term Follow-up (14 to 25 Years) Following Closed Reduction and Early Movement for Simple Dislocation of the Elbow.

BACKGROUND: We have previously reported on the midterm outcomes after a nonoperative protocol to treat simple dislocations of the elbow that included a short period of splinting followed by early movement. We have now performed extended follow-up of the original patient group from the prior study to determine whether the excellent results that previously had been reported were maintained in the long term and also to determine the rate of and need for any late surgical intervention. METHODS: We attempted to contact all of the patients from the original study group. We requested that they complete the Oxford Elbow Score (OES) survey, the Disabilities of the Arm, Shoulder and Hand (DASH) questionnaire, and a validated patient satisfaction questionnaire. Patients also were requested to attend a face-to-face assessment to have a clinical examination that included neurovascular, range-of-motion, and ligamentous stability assessments. RESULTS: Seventy-one patients from the original patient group agreed to participate in the new study. The mean duration of follow-up was 19.3 years. At the time of the final follow-up, patients reported excellent functional outcome scores and a preserved functional range of movement in the injured elbow. The mean OES was 91.6 points, the mean DASH score was 5.22 points, and the mean satisfaction score was 90.9 points. None of the patients had undergone delayed or secondary surgery for instability during the interval period. CONCLUSIONS: This study demonstrated that the original excellent outcomes following treatment with a protocol of a short period of splinting and early movement remained excellent and were maintained into the very long term. LEVEL OF EVIDENCE: Therapeutic Level IV . See Instructions for Authors for a complete description of levels of evidence.

EHR-Safe: generating high-fidelity and privacy-preserving synthetic electronic health records.

Privacy concerns often arise as the key bottleneck for the sharing of data between consumers and data holders, particularly for sensitive data such as Electronic Health Records (EHR). This impedes the application of data analytics and ML-based innovations with tremendous potential. One promising approach for such privacy concerns is to instead use synthetic data. We propose a generative modeling framework, EHR-Safe, for generating highly realistic and privacy-preserving synthetic EHR data. EHR-Safe is based on a two-stage model that consists of sequential encoder-decoder networks and generative adversarial networks. Our innovations focus on the key challenging aspects of real-world EHR data: heterogeneity, sparsity, coexistence of numerical and categorical features with distinct characteristics, and time-varying features with highly-varying sequence lengths. Under numerous evaluations, we demonstrate that the fidelity of EHR-Safe is almost-identical with real data (<3% accuracy difference for the models trained on them) while yielding almost-ideal performance in practical privacy metrics.

Acute Carpal Tunnel Syndrome: Early Nerve Decompression and Surgical Stabilization for Bony Wrist Trauma.

We undertook this study to investigate the outcomes of surgical treatment for acute carpal tunnel syndrome following our protocol for concurrent nerve decompression and skeletal stabilization for bony wrist trauma to be undertaken within 48 hours. Methods: We identified all patients treated at our trauma center following this protocol between January 1, 2014 and December 31, 2019. All patients were clinically reviewed at least 12 months after surgery and assessed using the Brief Michigan Hand Outcomes Questionnaire, the Boston Carpal Tunnel Questionnaire, and sensory assessment with Semmes-Weinstein monofilament testing. Results: The study group was made up of 35 patients. Thirty-three patients were treated within 36 hours. Patients treated with our unit protocol for early surgery comprising nerve decompression and bony stabilization within 36 hours report excellent outcomes at medium term follow-up. Conclusions: We propose that nerve decompression and bony surgical stabilization should be undertaken as soon as practically possible once the diagnosis is made. This is emergent treatment to protect and preserve nerve function. In our experience, the vast majority of patients were treated within 24 hours; however, where a short period of observation was required, excellent results were generally achieved when treatment was completed within 36 hours.

Understanding and Addressing the Digital Health Literacy Needs of Low-Income Limited English Proficient Asian American Patients.

Introduction: During the pandemic, Asian Health Services (AHS), a federally qualified health center serving patients in 14 Asian languages, transformed rapidly to provide telehealth visits, developed an intensive remote patient monitoring program, and conducted a digital health literacy survey. Method: This article describes how AHS collected and utilized descriptive data on our patient population to inform our rapid adoption of telehealth and assess our patients' response to these changes. Results: Our experiences show that audio visits are invaluable for our patients. In addition, our remote monitoring program resulted in 96% of patients improving their blood pressure control. Conclusion: Many barriers to widespread adoption of telehealth exist, including low digital literacy and the need for in-language digital training. Disaggregated data by ethnicity and language are needed to inform future work.

Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab.

Assessment of programmed death ligand 1 (PD-L1) expression by immunohistochemistry (IHC) has emerged as an important predictive biomarker across multiple tumor types. However, manual quantitation of PD-L1 positivity can be difficult and leads to substantial inter-observer variability. Although the development of artificial intelligence (AI) algorithms may mitigate some of the challenges associated with manual assessment and improve the accuracy of PD-L1 expression scoring, use of AI-based approaches to oncology biomarker scoring and drug development has been sparse, primarily due to the lack of large-scale clinical validation studies across multiple cohorts and tumor types. We developed AI-powered algorithms to evaluate PD-L1 expression on tumor cells by IHC and compared it with manual IHC scoring in urothelial carcinoma, non-small cell lung cancer, melanoma, and squamous cell carcinoma of the head and neck (prospectively determined during the phase II and III CheckMate clinical trials). 1,746 slides were retrospectively analyzed, the largest investigation of digital pathology algorithms on clinical trial datasets performed to date. AI-powered quantification of PD-L1 expression on tumor cells identified more PD-L1-positive samples compared with manual scoring at cutoffs of ≥1% and ≥5% in most tumor types. Additionally, similar improvements in response and survival were observed in patients identified as PD-L1-positive compared with PD-L1-negative using both AI-powered and manual methods, while improved associations with survival were observed in patients with certain tumor types identified as PD-L1-positive using AI-powered scoring only. Our study demonstrates the potential for implementation of digital pathology-based methods in future clinical practice to identify more patients who would benefit from treatment with immuno-oncology therapy compared with current guidelines using manual assessment.

Embracing virtual outpatient clinics in the era of COVID-19.

The response to the COVID-19 pandemic has raised the profile and level of interest in the use, acceptability, safety, and effectiveness of virtual outpatient consultations and telemedicine. These models of care are not new but a number of challenges have so far hindered widespread take-up and endorsement of these ways of working. With the response to the COVID-19 pandemic, remote and virtual working and consultation have become the default. This paper explores our experience of and learning from virtual and remote consultation and questions how this experience can be retained and developed for the future. Cite this article: Bone Jt Open 2021;2(5):301-304.

The perception of patient safety in an alternate site of care for elective surgery during the first wave of the novel coronavirus pandemic in the United Kingdom: a survey of 158 patients.

BACKGROUND: We undertook a prospective qualitative survey to ascertain the perceptions and experience of National Health Service patients in the United Kingdom who underwent planned or elective procedures and surgery at alternate 'clean' hospital sites during the coronavirus disease 2019 (COVID-19) pandemic. These alternate 'clean' hospital sites were independent hospitals running active staff and patient testing programmes for COVID-19 and which did not admit or treat patients suffering with COVID-19. METHODS: A prospective survey was undertaken to include patients at least 30 days after a planned surgery or procedure conducted at a 'clean' alternate hospital site during the COVID-19 pandemic. The study was conducted using structured interviews undertaken by trained assessors. A 20% sample group of patients were randomly selected to participate in this study. Qualitative data related to confidence, safety and perceptions of safety were collected. RESULTS: Ninety-five patients (60%) reported that they had prior worries or concerns about undergoing an elective procedure during the COVID-19 pandemic. A total of 47 patients (30%) had delayed their surgery at least once because of these concerns. A total of 150 patients (95%) felt that the precautions in place to protect their safety in the setting of an alternate 'clean' hospital site were well thought out and proportionate. Patients reported high levels of confidence in the measures undertaken. Separation of patient pathways using the independent sector and patient testing were identified by patients as having the greatest impact on their perception of safety. CONCLUSIONS: Patient confidence will be key to ensuring uptake of planned and elective procedures and surgery during the COVID-19 pandemic. Perceptions of safety will be key to this confidence and efforts to demonstrably enhance safety are well received by patients. In particular, patients felt that a dedicated programme of patient testing and separation of patient pathways provided the greatest levels of confidence in the safety of their treatment.

Targeted sonodynamic destruction of glioblastoma cells using antibody-titanium dioxide nanoparticle conjugates.

Aim: We present data on sonodynamic therapy (SDT) against glioblastoma cells utilizing titanium dioxide (TiO2) nanoparticles conjugated to anti-EGFR antibody. Materials & methods: TiO2 nanoparticles were bound to anti-EGFR antibody to form antibody-nanoparticle conjugates (ANCs), then characterized by x-ray photoelectron spectroscopy and transmission electron microscopy. Cells underwent ultrasound and assessment on viability, reactive oxygen species and apoptosis were performed. Results: X-ray photoelectron spectroscopy analysis revealed the formation of an ANC. Transmission electron microscopy showed internalization of the ANCs by glioblastoma cells. With SDT, cell viabilities were reduced in the presence of ANCs, reactive oxygen species production was formed, but minimal effect on apoptosis was seen. Conclusion: For the first time, an ANC can be used with SDT to kill glioblastoma cells.

Surgery with the Motec total wrist replacement: learning from earlier designs.

The design of and applications for wrist arthroplasty continue to evolve but lag behind the results for hip and knee arthroplasty with respect to demonstrable durability and effectiveness. As we develop our knowledge, experience and the indications for wrist replacement surgery, it is important that we learn from past design and surgical experience. We report the case of a female patient treated with a Motec cementless metal-on-metal wrist replacement (Swemac Orthopaedics AB, Linköping, Sweden) for post-traumatic arthritis of the radiocarpal joint. Based on our experience with this case and others, we make two specific technical recommendations to improve the success and longevity of this implant.

Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance.

In this work, we assessed the ability of computerized features of nuclear morphology from diagnostic biopsy images to predict prostate cancer (CaP) progression in active surveillance (AS) patients. Improved risk characterization of AS patients could reduce over-testing of low-risk patients while directing high-risk patients to therapy. A total of 191 (125 progressors, 66 non-progressors) AS patients from a single site were identified using The Johns Hopkins University's (JHU) AS-eligibility criteria. Progression was determined by pathologists at JHU. 30 progressors and 30 non-progressors were randomly selected to create the training cohort D1 (n = 60). The remaining patients comprised the validation cohort D2 (n = 131). Digitized Hematoxylin & Eosin (H&E) biopsies were annotated by a pathologist for CaP regions. Nuclei within the cancer regions were segmented using a watershed method and 216 nuclear features describing position, shape, orientation, and clustering were extracted. Six features associated with disease progression were identified using D1 and then used to train a machine learning classifier. The classifier was validated on D2. The classifier was further compared on a subset of D2 (n = 47) against pro-PSA, an isoform of prostate specific antigen (PSA) more linked with CaP, in predicting progression. Performance was evaluated with area under the curve (AUC). A combination of nuclear spatial arrangement, shape, and disorder features were associated with progression. The classifier using these features yielded an AUC of 0.75 in D2. On the 47 patient subset with pro-PSA measurements, the classifier yielded an AUC of 0.79 compared to an AUC of 0.42 for pro-PSA. Nuclear morphometric features from digitized H&E biopsies predicted progression in AS patients. This may be useful for identifying AS-eligible patients who could benefit from immediate curative therapy. However, additional multi-site validation is needed.

Tracheostomy during COVID-19 pandemic-Novel approach.

BACKGROUND: This study describes a novel approach in reducing SARS-CoV-2 transmission during tracheostomy. METHODS: Five patients underwent tracheostomy between April 1, 2020 and April 17, 2020. A clear and sterile plastic drape was used as an additional physical barrier against droplets and aerosols. Operative diagnosis; droplet count and distribution on plastic sheet and face shields were documented. RESULTS: Tracheostomy was performed for patients with carcinoma of tonsil (n = 2) and nasopharynx (n = 1), and aspiration pneumonia (n = 2). Droplet contamination was noted on all plastic sheets (n = 5). Droplet contamination was most severe over the central surface at 91.5% (86.7%-100.0%) followed by the left and right lateral surfaces at 5.2% (6.7%-10.0%) and 3.3% (6.7%-10.0%), respectively. No droplet contamination was noted on all face shields. CONCLUSION: Plastic drapes can help reduce viral transmission to health care providers during tracheostomy. Face shields may be spared which in turn helps to conserve resources during the novel coronavirus disease 2019 pandemic.

Conservation of personal protective equipment for head and neck cancer surgery during COVID-19 pandemic.

BACKGROUND: COVID-19 pandemic has led to a global shortage of personal protective equipment (PPE). This study aims to stratify face shield needs when performing head and neck cancer surgery. METHODS: Fifteen patients underwent surgery between March 1, 2020 and April 9, 2020. Operative diagnosis and procedure; droplet count and distribution on face shields were documented. RESULTS: Forty-five surgical procedures were performed for neck nodal metastatic carcinoma of unknown origin (n = 3); carcinoma of tonsil (n = 2), tongue (n = 2), nasopharynx (n = 3), maxilla (n = 1), and laryngopharynx (n = 4). Droplet contamination was 57.8%, 59.5%, 8.0%, and 0% for operating, first and second assistant surgeons, and scrub nurse respectively. Droplet count was highest and most widespread during osteotomies. No droplet splash was noted for transoral robotic surgery. CONCLUSION: Face shield is not a mandatory adjunctive PPE for all head and neck surgical procedures and health care providers. Judicious use helps to conserve resources during such difficult times.

New Technologies to Image Tumors.

The premise of this book is the importance of the tumor microenvironment (TME). Until recently, most research on and clinical attention to cancer biology, diagnosis, and prognosis were focused on the malignant (or premalignant) cellular compartment that could be readily appreciated using standard morphology-based imaging.

Applications of machine learning in drug discovery and development.

Drug discovery and development pipelines are long, complex and depend on numerous factors. Machine learning (ML) approaches provide a set of tools that can improve discovery and decision making for well-specified questions with abundant, high-quality data. Opportunities to apply ML occur in all stages of drug discovery. Examples include target validation, identification of prognostic biomarkers and analysis of digital pathology data in clinical trials. Applications have ranged in context and methodology, with some approaches yielding accurate predictions and insights. The challenges of applying ML lie primarily with the lack of interpretability and repeatability of ML-generated results, which may limit their application. In all areas, systematic and comprehensive high-dimensional data still need to be generated. With ongoing efforts to tackle these issues, as well as increasing awareness of the factors needed to validate ML approaches, the application of ML can promote data-driven decision making and has the potential to speed up the process and reduce failure rates in drug discovery and development.

Practice guidelines for the supervising professional: intraoperative neurophysiological monitoring.

The American Society of Neurophysiological Monitoring (ASNM) was founded in 1989 as the American Society of Evoked Potential Monitoring. From the beginning, the Society has been made up of physicians, doctoral degree holders, Technologists, and all those interested in furthering the profession. The Society changed its name to the ASNM and held its first Annual Meeting in 1990. It remains the largest worldwide organization dedicated solely to the scientifically-based advancement of intraoperative neurophysiology. The primary goal of the ASNM is to assure the quality of patient care during procedures monitoring the nervous system. This goal is accomplished primarily through programs in education, advocacy of basic and clinical research, and publication of guidelines, among other endeavors. The ASNM is committed to the development of medically sound and clinically relevant guidelines for the performance of intraoperative neurophysiology. Guidelines are formulated based on exhaustive literature review, recruitment of expert opinion, and broad consensus among ASNM membership. Input is likewise sought from sister societies and related constituencies. Adherence to a literature-based, formalized process characterizes the construction of all ASNM guidelines. The guidelines covering the Professional Practice of intraoperative neurophysiological monitoring were initially published January 24th, 2013, and subsequently that document has undergone review and revision to accommodate broad inter- and intra-societal feedback. This current version of the ASNM Professional Practice Guideline was fully approved for publication according to ASNM bylaws on February 22nd, 2018, and thus overwrites and supersedes the initial guideline.

Effect of polyethylene glycol (PEG) molecular weight and nanofillers on the properties of banana pseudostem nanocellulose films.

The aims of this study were to investigate the effects of polyethylene glycol (PEG) molecular weight (MW) and PEG interaction with nanofillers (nanoclay and graphene oxide) on the properties of banana pseudostem nanocellulose films. PEG MW significantly affected the properties of the films. Low MW PEGs (400 and 1000 g/mol) had better interaction with nanocellulose than the PEG with higher MW and improved the flexibility of the films by about 100%. Interaction between PEG1000 and nanofillers significantly modified the properties of the composite films. PEG1000 had a good interaction with nanoclay, which was reflected by the formation of intercalated nanoclay in the cellulose matrix. The presence of nanoclay and graphene oxide in the PEG plasticised films improved the tensile strength and contact angle of the films compared to the film that only contained PEG. These findings suggest that the properties of banana pseudostem nanocellulose film can be improved by combining PEG with nanofillers.

Advances in the computational and molecular understanding of the prostate cancer cell nucleus.

Nuclear alterations are a hallmark of many types of cancers, including prostate cancer (PCa). Recent evidence shows that subvisual changes, ones that may not be visually perceptible to a pathologist, to the nucleus and its ultrastructural components can precede visual histopathological recognition of cancer. Alterations to nuclear features, such as nuclear size and shape, texture, and spatial architecture, reflect the complex molecular-level changes that occur during oncogenesis. Quantitative nuclear morphometry, a field that uses computational approaches to identify and quantify malignancy-induced nuclear changes, can enable a detailed and objective analysis of the PCa cell nucleus. Recent advances in machine learning-based approaches can now automatically mine data related to these changes to aid in the diagnosis, decision making, and prediction of PCa prognoses. In this review, we use PCa as a case study to connect the molecular-level mechanisms that underlie these nuclear changes to the machine learning computational approaches, bridging the gap between the clinical and computational understanding of PCa. First, we will discuss recent developments to our understanding of the molecular events that drive nuclear alterations in the context of PCa: the role of the nuclear matrix and lamina in size and shape changes, the role of 3-dimensional chromatin organization and epigenetic modifications in textural changes, and the role of the tumor microenvironment in altering nuclear spatial topology. We will then discuss the advances in the applications of machine learning algorithms to automatically segment nuclei in prostate histopathological images, extract nuclear features to aid in diagnostic decision making, and predict potential outcomes, such as biochemical recurrence and survival. Finally, we will discuss the challenges and opportunities associated with translation of the quantitative nuclear morphometry methodology into the clinical space. Ultimately, accurate identification and quantification of nuclear alterations can contribute to the field of nucleomics and has applications for computationally driven precision oncologic patient care.