Postoperative mortality in the COVID-positive hip fracture patient, a systematic review and meta-analysis.

PURPOSE: The extent to which concomitant COVID-19 infection increases short-term mortality following hip fracture is not fully understood. A systemic review and meta-analysis of COVID-19 positive hip fracture patients (CPHFPs) undergoing surgery was conducted to explore the association of COVID-19 with short-term mortality. METHODS: Review of the literature identified reports of short-term 30-day postoperative mortality in CPHFPs. For studies including a contemporary control group of COVID-19 negative patients, odds ratios of the association between COVID-19 infection and short-term mortality were calculated. Short-term mortality and the association between COVID-19 infection and short-term mortality were meta-analyzed and stratified by hospital screening type using random effects models. RESULTS: Seventeen reports were identified. The short-term mortality in CPHFPs was 34% (95% C.I., 30-39%). Short-term mortality differed slightly across studies that screened all patients, 30% (95% C.I., 22-39%), compared to studies that conditionally screened patients, 36% (95% C.I., 31-42%), (P = 0.22). The association between COVID-19 infection and short-term mortality produced an odds ratio of 7.16 (95% C.I., 4.99-10.27), and this was lower for studies that screened all patients, 4.08 (95% C.I., 2.31-7.22), compared to studies that conditionally screened patients, 8.32 (95% C.I., 5.68-12.18), (P = 0.04). CONCLUSION: CPHFPs have a short-term mortality rate of 34%. The odds ratio of short-term mortality was significantly higher in studies that screened patients conditionally than in studies that screened all hip fracture patients. This suggests mortality prognostication should consider how COVID-19 infection was identified as asymptomatic patients may fare slightly better.

The impact of COVID-19 restrictions on participant enrollment in the PREPARE trial.

Background: At the initiation of the COVID-19 pandemic, restrictions forced researchers to decide whether to continue their ongoing clinical trials. The PREPARE (Pragmatic Randomized Trial Evaluating Pre-Operative Alcohol Skin Solutions in Fractured Extremities) trial is a pragmatic cluster-randomized crossover trial in patients with open and closed fractures. PREPARE was enrolling over 200 participants per month at the initiation of the pandemic. We aim to describe how the COVID-19 research restrictions affected participant enrollment. Methods: The PREPARE protocol permitted telephone consent, however, sites were obtaining consent in-person. To continue enrollment after the initiation of the restrictions participating sites obtained ethics approval for telephone consent scripts and the waiver of a signature on the consent form. We recorded the number of sites that switched to telephone consent, paused enrollment, and the length of the pause. We used t-tests to compare the differences in monthly enrollment between July 2019 and November 2020. Results: All 19 sites quickly implement telephone consent. Fourteen out of nineteen (73.6%) sites paused enrollment due to COVID-19 restrictions. The median length of enrollment pause was 46.5 days (range, 7-121 days; interquartile range, 61 days). The months immediately following the implementation of restrictions had significantly lower enrollment. Conclusion: A pragmatic design allowed sites to quickly adapt their procedures for obtaining informed consent via telephone and allowed for minimal interruptions to enrollment during the pandemic.

Rehabilitation at the Time of Pandemic: Patient Journey Recommendations.

Purpose: The World Health Organization (WHO) declared severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a pandemic in March 2020, causing almost 3.5 million coronavirus disease (COVID-19) related deaths worldwide. The COVID-19 pandemic has imposed a significant burden on healthcare systems, economies, and social systems in many countries around the world. The access and delivery of rehabilitation care were severely disrupted, and patients have faced several challenges during the COVID-19 outbreak. These challenges include addressing new functional impairments faced by survivors of COVID-19 and infection prevention to avoid the virus spread to healthcare workers and other patients not infected with COVID-19. In this scoping review, we aim to develop rehabilitation recommendations during the COVID-19 pandemic across the continuum of rehabilitation care. Materials and Methods: Established frameworks were used to guide the scoping review methodology. Medline, Embase, Pubmed, CINAHL databases from inception to August 1, 2020, and prominent rehabilitation organizations' websites were searched. Study Selection: We included articles and reports if they were focused on rehabilitation recommendations for COVID-19 survivors or the general population at the time of the COVID-19 pandemic. Data Extraction: Two of our team members used the pre-tested data extraction form to extract data from included full-text articles. The strength and the quality of the extracted recommendations were evaluated by two reviewers using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach. Results: We retrieved 6,468 citations, of which 2,086 were eligible after removing duplicates. We excluded 1,980 citations based on the title and the abstract. Of the screened full-text articles, we included 106 studies. We present recommendations based on the patient journey at the time of the pandemic. We assessed the evidence to be of overall fair quality and strong for the recommendations. Conclusion: We have combined the latest research results and accumulated expert opinions on rehabilitation to develop acute and post-acute rehabilitation recommendations in response to the global COVID-19 pandemic. Further updates are warranted in order to incorporate the emerging evidence into rehabilitation guidelines.

Rehabilitation Care at the Time of Coronavirus Disease-19 (COVID-19) Pandemic: A Scoping Review of Health System Recommendations.

Purpose: The coronavirus disease-19 (COVID-19) was declared a pandemic by the World Health Organization in March 2020. COVID-19, caused by SARS-CoV-2 has imposed a significant burden on health care systems, economies, and social systems in many countries around the world. The provision of rehabilitation services for persons with active COVID-19 infection poses challenges to maintaining a safe environment for patients and treating providers. Materials and Methods: Established frameworks were used to guide the scoping review methodology. Medline, Embase, Pubmed, CINAHL databases from inception to August 1, 2020, and prominent rehabilitation organizations' websites were searched. Study Selection: We included articles and reports if they were focused on rehabilitation related recommendations for COVID-19 patients, treating providers, or the general population. Data Extraction: Pairs of team members used a pre-tested data abstraction form to extract data from included full-text articles. The strength and the quality of the extracted recommendations were evaluated by two reviewers using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Results: We retrieved 6,468 citations, of which 2,086 were eligible for review, after duplicates were removed. We excluded 1,980 citations based on title and abstract screening. Of the screened full-text articles, we included all 106 studies. A summary of recommendations is presented. We assessed the overall evidence to be strong and of fair quality. Conclusion: The rehabilitation setting, and processes, logistics, and patient and healthcare provider precaution recommendations identified aim to reduce the spread of SARS-CoV-2 infection and ensure adequate and safe rehabilitation services, whether face-to-face or through teleservices. The COVID-19 pandemic is rapidly changing. Further updates will be needed over time in order to incorporate emerging best evidence into rehabilitation guidelines.

Team Approach: Virtual Care in the Management of Orthopaedic Patients.

¼: Telemedicine and remote care administered through technology are among the fastest growing sectors in health care. The utilization and implementation of virtual-care technologies have further been accelerated with the recent COVID-19 pandemic. ¼: Remote, technology-based patient care is not a "one-size-fits-all" solution for all medical and surgical conditions, as each condition presents unique hurdles, and no true consensus exists regarding the efficacy of telemedicine across surgical fields. ¼: When implementing virtual care in orthopaedics, as with standard in-person care, it is important to have a well-defined team structure with a deliberate team selection process. As always, a team with a shared vision for the care they provide as well as a supportive and incentivized environment are integral for the success of the virtual-care mechanism. ¼: Future studies should assess the impact of primarily virtual, integrated, and multidisciplinary team-based approaches and systems of care on patient outcomes, health-care expenditure, and patient satisfaction in the orthopaedic population.

Usefulness of PCR Screening in the Initial Triage of Trauma Patients During COVID-19 Pandemic.

BACKGROUND: Hospitals worldwide have postponed all nonessential surgery during the COVID-19 pandemic, but non-COVID-19 patients are still in urgent need of care. Uncertainty about a patient's COVID-19 status risks infecting health care workers and non-COVID-19 inpatients. We evaluated the use of quantitative reverse transcription polymerase chain reaction (RT-qPCR) screening for COVID-19 on admission for all patients with fractures. METHODS: We conducted a retrospective cohort study of patients older than 18 years admitted with low-energy fractures who were tested by RT-qPCR for SARS-CoV-2 at any time during hospitalization. Two periods based on the applied testing protocol were defined. During the first period, patients were only tested because of epidemiological criteria or clinical suspicion based on fever, respiratory symptoms, or radiological findings. In the second period, all patients admitted for fracture treatment were screened by RT-qPCR. RESULTS: We identified 15 patients in the first period and 42 in the second. In total, 9 (15.8%) patients without clinical or radiological findings tested positive at any moment. Five (33.3%) patients tested positive postoperatively in the first period and 3 (7.1%) in the second period (P = 0.02). For clinically unsuspected patients, postoperative positive detection went from 3 of 15 (20%) during the first period to 2 of 42 (4.8%) in the second (P = 0.11). Clinical symptoms demonstrated high specificity (92.1%) but poor sensitivity (52.6%) for infection detection. CONCLUSIONS: Symptom-based screening for COVID-19 has shown to be specific but not sensitive. Negative clinical symptoms do not rule out infection. Protocols and separated areas are necessary to treat infected patients. RT-qPCR testing on admission helps minimize the risk of nosocomial and occupational infection. LEVEL OF EVIDENCE: Diagnostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

The First Modified Delphi Consensus Statement for Resuming Bariatric and Metabolic Surgery in the COVID-19 Times.

The purpose of this study was to achieve consensus amongst a global panel of expert bariatric surgeons on various aspects of resuming Bariatric and Metabolic Surgery (BMS) during the Coronavirus Disease-2019 (COVID-19) pandemic. A modified Delphi consensus-building protocol was used to build consensus amongst 44 globally recognised bariatric surgeons. The experts were asked to either agree or disagree with 111 statements they collectively proposed over two separate rounds. An agreement amongst ≥ 70.0% of experts was construed as consensus as per the predetermined methodology. We present here 38 of our key recommendations. This first global consensus statement on the resumption of BMS can provide a framework for multidisciplinary BMS teams planning to resume local services as well as guide future research in this area.

Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.

PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level approach to monitor the second wave of covid-19 in the USA. METHOD: We use an artificial intelligence framework based on timeline of policy interventions that triangulated results based on the three approaches-Bayesian susceptible-infected-recovered (SIR), Kalman filter, and machine learning. RESULTS: Our findings suggest three important insights. First, the effective growth rate of covid-19 infections dropped in response to the approximate dates of key policy interventions. We find that the change points for spreading rates approximately coincide with the timelines of policy interventions across respective countries. Second, forecasted trend until mid-June in the USA was downward trending, stable, and linear. Sweden is likely to be heading in the other direction. That is, Sweden's forecasted trend until mid-June appears to be non-linear and upward trending. Canada appears to fall somewhere in the middle-the trend for the same period is flat. Third, a Kalman filter based robustness check indicates that by mid-June the USA will likely have close to two million virus cases, while Sweden will likely have over 44,000 covid-19 cases. CONCLUSION: We show that drop in effective growth rate of covid-19 infections was sharper in the case of stringent policies (USA and Canada) but was more gradual in the case of relaxed policy (Sweden). Our study exhorts policy makers to take these results into account as they consider the implications of relaxing lockdown measures.

Trials and tribulations: so many potential treatments, so few answers.

PURPOSE: The purpose of this review is to quantify the landscape of current clinical trials ongoing for therapies in the treatment of COVID-19. A secondary purpose is to examine the relationship between public and scientific interests in potential therapies for COVID-19. METHODS: A systematic search of clinicaltrials.gov was undertaken on April 22, 2020, to identify all currently registered clinical trials investigating potential therapies for patients with COVID-19. Public interest in the various therapies was quantified utilizing Google Trends. Public interest in hydroxychloroquine and chloroquine was plotted against the cumulative number of active clinical trials evaluating antimalarials as potential COVID-19 therapies over time. RESULTS: There were 341 interventional studies and 208 different therapies actively registered on clinicaltrials.gov whose primary aim is the treatment of COVID-19. The median sample size was 120 patients (range 4-6000) with 154 (45%) trials reporting a planned sample size of 100 patients or less. There was a strong positive correlation (r = 0.76, p = 0.01) between the number of registered clinical trials and the public interest in the top ten proposed therapies. Following the spike in public interest, the average number of new trials increased tenfold with respect to antimalarial therapies. CONCLUSIONS: The relatively small sample sizes and the number of independent trials investigating similar therapies are concerning. Resources may not be being allocated based on scientific merit and may be driven by public consciousness and speculation. Moving forward, a concerted effort focused on implementing large, well-coordinated and carefully designed multi-armed clinical trials will help to ensure that the most promising therapeutic options are rigorously studied and clinically meaningful results produced.

Maximizing virtual meetings and conferences: a review of best practices.

PURPOSE: In the current COVID-19 pandemic, it is more important than ever to maximize communication in the scientific and medical community. In the context of academic meetings and conferences, there is the growing need for a set of guidelines secondary to the COVID-19 pandemic, and the growing environmental and economic challenges that large academic and medical conferences face. These Virtual Meetings Best Practices were established in response to the scant evidence and guidance on the topic. METHODS: These best practice guidelines were developed from a scoping review of peer-reviewed literature, grey literature and lay literature. MEDLINE and Embase databases were scoped for relevant, non-duplicate articles. For lay articles, Google searches were utilized. The recommendations that comprise this document are a compilation of nonexperimental descriptive studies (e.g. case studies) and expert committee reports, opinions and/or experience of respected authorities, and lay articles. RESULTS: We identified four phases of the meeting cycle: Pre-planning considerations, Planning, Accomplishing conference goals through execution, gauging Response and Engaging the target audience for future cycles (PrePARE). Akin to the Plan, Do, Study, Act Cycle of quality improvement interventions, this document is meant to drive meaningful initial and subsequent interventions in the meetings of the medical and academic community. This covers actions and preparation for registration, scheduling, speakers, attendees, event type, technology, monetization/marketing, dealing with disruptions, post-event deliverables, response and engagement strategies. Enhanced access to integrated, high-quality and efficient virtual meetings will establish a new norm as an effective alternative for innovative health research, education and information dissemination in orthopaedics and beyond. CONCLUSIONS: Given the uncertainty of whether large in-person gatherings will be permitted, advisable or responsible later into the summer of 2020 and beyond, these guidelines will aid events being converted and scheduled as virtual-only meetings. As we move forward in the era of increased utility and utilization of virtual conferencing, these guidelines will serve as a benchmark and standard for surgeons in the field.

Deep learning COVID-19 detection bias: accuracy through artificial intelligence.

BACKGROUND: Detection of COVID-19 cases' accuracy is posing a conundrum for scientists, physicians, and policy-makers. As of April 23, 2020, 2.7 million cases have been confirmed, over 190,000 people are dead, and about 750,000 people are reported recovered. Yet, there is no publicly available data on tests that could be missing infections. Complicating matters and furthering anxiety are specific instances of false-negative tests. METHODS: We developed a deep learning model to improve accuracy of reported cases and to precisely predict the disease from chest X-ray scans. Our model relied on convolutional neural networks (CNNs) to detect structural abnormalities and disease categorization that were keys to uncovering hidden patterns. To do so, a transfer learning approach was deployed to perform detections from the chest anterior-posterior radiographs of patients. We used publicly available datasets to achieve this. RESULTS: Our results offer very high accuracy (96.3%) and loss (0.151 binary cross-entropy) using the public dataset consisting of patients from different countries worldwide. As the confusion matrix indicates, our model is able to accurately identify true negatives (74) and true positives (32); this deep learning model identified three cases of false-positive and one false-negative finding from the healthy patient scans. CONCLUSIONS: Our COVID-19 detection model minimizes manual interaction dependent on radiologists as it automates identification of structural abnormalities in patient's CXRs, and our deep learning model is likely to detect true positives and true negatives and weed out false positive and false negatives with > 96.3% accuracy.

Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America.

BACKGROUND: The detection of coronavirus disease 2019 (COVID-19) cases remains a huge challenge. As of April 22, 2020, the COVID-19 pandemic continues to take its toll, with >2.6 million confirmed infections and >183,000 deaths. Dire projections are surfacing almost every day, and policymakers worldwide are using projections for critical decisions. Given this background, we modeled unobserved infections to examine the extent to which we might be grossly underestimating COVID-19 infections in North America. METHODS: We developed a machine-learning model to uncover hidden patterns based on reported cases and to predict potential infections. First, our model relied on dimensionality reduction to identify parameters that were key to uncovering hidden patterns. Next, our predictive analysis used an unbiased hierarchical Bayesian estimator approach to infer past infections from current fatalities. RESULTS: Our analysis indicates that, when we assumed a 13-day lag time from infection to death, the United States, as of April 22, 2020, likely had at least 1.3 million undetected infections. With a longer lag time-for example, 23 days-there could have been at least 1.7 million undetected infections. Given these assumptions, the number of undetected infections in Canada could have ranged from 60,000 to 80,000. Duarte's elegant unbiased estimator approach suggested that, as of April 22, 2020, the United States had up to >1.6 million undetected infections and Canada had at least 60,000 to 86,000 undetected infections. However, the Johns Hopkins University Center for Systems Science and Engineering data feed on April 22, 2020, reported only 840,476 and 41,650 confirmed cases for the United States and Canada, respectively. CONCLUSIONS: We have identified 2 key findings: (1) as of April 22, 2020, the United States may have had 1.5 to 2.029 times the number of reported infections and Canada may have had 1.44 to 2.06 times the number of reported infections and (2) even if we assume that the fatality and growth rates in the unobservable population (undetected infections) are similar to those in the observable population (confirmed infections), the number of undetected infections may be within ranges similar to those described above. In summary, 2 different approaches indicated similar ranges of undetected infections in North America. LEVEL OF EVIDENCE: Prognostic Level V. See Instructions for Authors for a complete description of levels of evidence.

Impact of COVID-19 on orthopaedic care: a call for nonoperative management.

BACKGROUND: Surgical specialties face unique challenges caused by SARS-COV-2 (COVID-19). These disruptions will call on clinicians to have greater consideration for non-operative treatment options to help manage patient symptoms and provide therapeutic care in lieu of the traditional surgical management course of action. This study aimed to summarize the current guidance on elective surgery during the COVID-19 pandemic, assess how this guidance may impact orthopaedic care, and review any recommendations for non-operative management in light of elective surgery disruptions. METHODS: A systematic search was conducted, and included guidance were categorized as either "Selective Postponement" or "Complete Postponement" of elective surgery. Selective postponement was considered as guidance that suggested elective cases should be evaluated on a case-by-case basis, whereas complete postponement suggested that all elective procedures be postponed until after the pandemic, with no case-by-case consideration. In addition, any statements regarding conservative/non-operative management were summarized when provided by included reports. RESULTS: A total of 11 reports from nine different health organizations were included in this review. There were seven (63.6%) guidance reports that suggested a complete postponement of non-elective surgical procedures, whereas four (36.4%) reports suggested the use of selective postponement of these procedures. The guidance trends shifted from selective to complete elective surgery postponement occurred throughout the month of March. The general guidance provided by these reports was to have an increased consideration for non-operative treatment options whenever possible and safe. As elective surgery begins to re-open, non-operative management will play a key role in managing the surgical backlog caused by the elective surgery shutdown. CONCLUSION: Global guidance from major medical associations are in agreement that elective surgical procedures require postponement in order to minimize the risk of COVID-19 spread, as well as increase available hospital resources for managing the influx of COVID-19 patients. It is imperative that clinicians and patients consider non-operative, conservative treatment options in order to manage conditions and symptoms until surgical management options become available again, and to manage the increased surgical waitlists caused by the elective surgery shutdowns.