A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data

BACKGROUND

Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically significant hypoglycemia within one week.

METHODS

We developed a machine learning model to estimate the probability that a patient will experience a clinically significant hypoglycemic event, defined as CGM readings below 54 mg/dL for at least 15 consecutive minutes, within one week. The model takes as input the patient's CGM time series over a given week, and outputs the predicted probability of a clinically significant hypoglycemic event the following week. We used 10-fold cross-validation and external validation (testing on cohorts different from the training cohort) to evaluate performance. We used CGM data from three different cohorts of patients with T1D: REPLACE-BG (226 patients), Juvenile Diabetes Research Foundation (JDRF; 355 patients) and Tidepool (120 patients).

RESULTS

In 10-fold cross-validation, the average area under the receiver operating characteristic curve (ROC-AUC) was 0.77 (standard deviation [SD]: 0.0233) on the REPLACE-BG cohort, 0.74 (SD: 0.0188) on the JDRF cohort, and 0.76 (SD: 0.02) on the Tidepool cohort. In external validation, the average ROC-AUC across the three cohorts was 0.74 (SD: 0.0262).

CONCLUSIONS

We developed a machine learning algorithm to estimate the probability of a clinically significant hypoglycemic event within one week. Predictive algorithms may provide diabetes care providers using RPM with additional context when prioritizing T1D patients for review.

Surgical Preparedness Index in Orthopaedics During the Coronavirus Disease 2019 (COVID-19) Pandemic

The coronavirus disease 2019 (COVID-19) pandemic has increased the vulnerability of routine surgical procedures and elective surgery preparedness all over the world, with the suspension of most elective surgeries during the pandemic and the backlog of patients currently on waiting lists, especially in publicly funded healthcare systems. On average, at the beginning of the year 2022, about 200 million patients awaited surgery all over the world. By enhancing the strength of surgical preparedness, there is a better chance of strengthening elective surgical systems against shocks such as future pandemics or climate emergencies. We explore the implications, challenges, and strategies of the concept of surgical preparedness to maintain sustainability in the global healthcare system, especially in low- and middle-income countries (LMICs), with the experiences gained during the COVID-19 pandemic.

Patient prioritization and management during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic affected the healthcare system in a major way generally. Healthcare re-organization of resources and manpower, establishing management protocols and specific patients’ pathways are all evolving with the continuously changing situation. Neuro-vascular management and its re-organization are part of these global measures to cope with this pandemic in a way to establish less risky patients’ pathways, help in patients’ triage, protecting the staff by introducing training and applying safety measures and to manage neuro-vascular emergencies and elective activity. We here describe the situation of the pandemic affecting neuro-vascular interventions and propose our recommendations for patients’ triage, resources management and organization, remote solutions and preparations for any future waves.

Directives of general surgical practice during the COVID-19 pandemic: A systematic review

The coronavirus disease 2019 (COVID-19) is a serious global pandemic that has extremely affected health-care systems. This article aimed to review the perspectives of general surgical practice during the COVID-19 pandemic. A systematic review of the literature addressing modification to general surgical practice during the COVID-19 pandemic indexed in PubMed, Scopus, Google, and Google scholar was carried out on June 19-20, 2020. The literature review yielded 577 articles. The exclusion of duplication, articles not in English, and specialized ones in various surgical disciplines precluded 398 articles. Finally, following checking for relevance and publication status, 114 papers were included. Recommendations for surgical practice during the COVID-19 pandemic revolved around mitigation of the risk of virus transmission to patients and health-care workers. The emerging themes of safety precautions were related to patient prioritization and testing, mindful consideration of the operative strategy, optimum use of personal protective equipment, operative room setup, and departmental organization. However, those recommendations were often diverging and bore on a dearth of evidence and personal opinions. Multidisciplinary work and cooperation among surgical specialties are required to establish and validate the protocols for safe surgical practice during the pandemic and perhaps similar crises in future. The COVID-19 pandemic has brought several challenges to the field of medicine, including the surgical specialty. The centrality of safety precautions emerging in this crisis requires surgeons to adopt the new roles and work standards and translate them into practice during the pandemic and perhaps longer.

Coupling Wearable Devices and Decision Theory in the United States Emergency Department Triage Process: A Narrative Review

This research was motivated by the nurses' decision-making process in the current emergency department (ED) triage process in the United States. It explores how continuous vital signs monitoring can be integrated into the ED. The article presents four shortcomings on current ED triage systems and proposes a new conceptual clinical decision support model that exploits the benefits of combining wireless wearable devices with Multi-Attribute Utility Theory to address those shortcomings. A literature review was conducted using various engineering and medical research databases, analyzing current practices and identifying potential improvement opportunities. The results from the literature review show that advancements in wireless wearable devices provide opportunities to enhance current ED processes by monitoring patients while they wait after triage and, therefore, reduce the risk of an adverse event. A dynamic mathematical decision support model to prioritize patients is presented, creating a feedback loop in the ED. The coupling of wearable devices (to collect data) with decision theory (to synthesize and organize the information) can assist in reducing sources of uncertainty inherent to ED systems. The authors also address the feasibility of the proposed conceptual model.

Individuals with common diseases but with a low polygenic risk score could be prioritized for rare variant screening

PURPOSE

Identifying rare genetic causes of common diseases can improve diagnostic and treatment strategies, but incurs high costs. We tested whether individuals with common disease and low polygenic risk score (PRS) for that disease generated from less expensive genome-wide genotyping data are more likely to carry rare pathogenic variants.

METHODS

We identified patients with one of five common complex diseases among 44,550 individuals who underwent exome sequencing in the UK Biobank. We derived PRS for these five diseases, and identified pathogenic rare variant heterozygotes. We tested whether individuals with disease and low PRS were more likely to carry rare pathogenic variants.

RESULTS

While rare pathogenic variants conferred, at most, 5.18-fold (95% confidence interval [CI]: 2.32-10.13) increased odds of disease, a standard deviation increase in PRS, at most, increased the odds of disease by 5.25-fold (95% CI: 5.06-5.45). Among diseased patients, a standard deviation decrease in the PRS was associated with, at most, 2.82-fold (95% CI: 1.14-7.46) increased odds of identifying rare variant heterozygotes.

CONCLUSION

Rare pathogenic variants were more prevalent among affected patients with a low PRS. Therefore, prioritizing individuals for sequencing who have disease but low PRS may increase the yield of sequencing studies to identify rare variant heterozygotes.

Prioritization of Proton Patients in the COVID-19 Pandemic: Recommendations from The New York Proton Center

It has been well documented from the early days of the 2019 novel coronavirus (COVID-19) pandemic that patients with a diagnosis of cancer are not only at higher risks of contracting a COVID-19 infection but also at higher risks of suffering severe, and possibly fatal, outcomes from the infection. Given that the United States has the greatest number of positive coronavirus cases, it is likely that many, if not all, radiation oncology clinics will be faced with the challenge of safely balancing a patient's risk of contracting COVID-19, while under active radiation treatment, against their risk of cancer progression if treatment is delayed. To address this challenge, the New York Proton Center established an internal algorithm that considers treatment-related, tumor-related, and patient-related characteristics. Despite having suffered staff shortages due to illness, this algorithm has allowed the center to maintain patient treatment volumes while keeping the rate of COVID-19 infection low.

Population Health and Cost-Effectiveness Implications of a "Treat All" Recommendation for HCV: A Review of the Model-Based Evidence

The World Health Organization HCV Guideline Development Group is considering a "treat all" recommendation for persons infected with hepatitis C virus (HCV). We reviewed the model-based evidence of cost-effectiveness and population health impacts comparing expanded treatment policies to more limited treatment access policies, focusing primarily on evaluations of all-oral directly acting antivirals published after 2012. Searching PubMed, we identified 2,917 unique titles. Sequentially reviewing titles and abstracts identified 226 potentially relevant articles for full-text review. Sixty-nine articles met all inclusion criteria-42 cost-effectiveness analyses and 30 models of population-health impacts, with 3 articles presenting both types of analysis. Cost-effectiveness studies for many countries concluded that expanding treatment to people with mild liver fibrosis, who inject drugs (PWID), or who are incarcerated is generally cost-effective compared to more restrictive treatment access policies at country-specific prices. For certain patient subpopulations in some countries-for example, elderly individuals without fibrosis-treatment is only cost-effective at lower prices. A frequent limitation is the omission of benefits and consequences of HCV transmission (i.e., treatment as prevention; risks of reinfection), which may underestimate or overestimate the cost-effectiveness of a "treat all" policy. Epidemiologic modeling studies project that through a combination of prevention, aggressive screening and diagnosis, and prompt treatment for all fibrosis stages, it may be possible to virtually eliminate HCV in many countries. Studies show that if resources are not available to diagnose and treat all HCV-infected individuals, treatment prioritization may be needed, with alternative prioritization strategies resulting in tradeoffs between reducing mortality or reducing incidence. Notably, because most new HCV infections are among PWID in many settings, HCV elimination requires unrestricted treatment access combined with injection transmission disruption strategies. The model-based evidence suggests that a properly constructed strategy that substantially expands HCV treatment could achieve cost-effective improvements in population health in many countries.

Ethical Considerations of Triage Following Natural Disasters: The IDF Experience in Haiti as a Case Study

Natural disasters in populated areas may result in massive casualties and extensive destruction of infrastructure. Humanitarian aid delegations may have to cope with the complicated issue of patient prioritization under conditions of severe resource scarcity. A triage model, consisting of five principles, is proposed for the prioritization of patients, and it is argued that rational and reasonable agents would agree upon them. The Israel Defense Force's humanitarian mission to Haiti following the 2010 earthquake serves as a case study for the various considerations taken into account when designing the ethical-clinical policy of field hospitals. The discussion focuses on three applications: the decision to include an intensive care unit, the decision to include obstetrics and neonatal units, and the treatment policy for compound fractures.