Multivariable Prediction Models for Traumatic Spinal Cord Injury: A Systematic Review.

Background: Traumatic spinal cord injuries (TSCI) greatly affect the lives of patients and their families. Prognostication may improve treatment strategies, health care resource allocation, and counseling. Multivariable clinical prediction models (CPMs) for prognosis are tools that can estimate an absolute risk or probability that an outcome will occur. Objectives: We sought to systematically review the existing literature on CPMs for TSCI and critically examine the predictor selection methods used. Methods: We searched MEDLINE, PubMed, Embase, Scopus, and IEEE for English peer-reviewed studies and relevant references that developed multivariable CPMs to prognosticate patient-centered outcomes in adults with TSCI. Using narrative synthesis, we summarized the characteristics of the included studies and their CPMs, focusing on the predictor selection process. Results: We screened 663 titles and abstracts; of these, 21 full-text studies (2009-2020) consisting of 33 distinct CPMs were included. The data analysis domain was most commonly at a high risk of bias when assessed for methodological quality. Model presentation formats were inconsistently included with published CPMs; only two studies followed established guidelines for transparent reporting of multivariable prediction models. Authors frequently cited previous literature for their initial selection of predictors, and stepwise selection was the most frequent predictor selection method during modelling. Conclusion: Prediction modelling studies for TSCI serve clinicians who counsel patients, researchers aiming to risk-stratify participants for clinical trials, and patients coping with their injury. Poor methodological rigor in data analysis, inconsistent transparent reporting, and a lack of model presentation formats are vital areas for improvement in TSCI CPM research.

What do primary care providers want to know when caring for patients living with frailty? An analysis of eConsult communications between primary care providers and specialists.

BACKGROUND: Frailty is a complex condition that primary care providers (PCPs) are managing in increasing numbers, yet there is no clear guidance or training for frailty care. OBJECTIVES: The present study examined eConsult questions PCPs asked specialists about patients with frailty, the specialists' responses, and the impact of eConsult on the care of these patients. DESIGN: Cross-sectional observational study. SETTING: ChamplainBASE™ eConsult located in Eastern Ontario, Canada. PARTICIPANTS: Sixty one eConsult cases closed by PCPs in 2019 that use the terms "frail" or "frailty" to describe patients 65 years of age or older. MEASUREMENTS: The Taxonomy of Generic Clinical Questions (TGCQ) was used to classify PCP questions and the International Classification for Primary Care 3 (ICPC-3) was used to classify the clinical content of each eConsult. The impact of eConsult on patient care was measured by PCP responses to a mandatory survey. RESULTS: PCPs most frequently directed their questions to cardiology (n = 7; 11%), gastroenterology (n = 7; 11%), and endocrinology (n = 6; 10%). Specialist answers most often pertained to medications (n = 63, 46%), recommendations for clinical investigation (n = 24, 17%), and diagnoses (n = 22, 16%). Specialist responses resulted in PCPs avoiding referral in 57% (n = 35) of cases whereas referrals were still required in 15% (n = 9) of cases. Specialists responded to eConsults in a median 1.11 days (IQR = 0.3-4.7), and 95% (n = 58) of cases received a response within 7 days. Specialists recorded a median of 15 min to respond (IQR = 10-20), with a median cost of $50.00 CAD (IQR = 33.33 - 66.66) per eConsult. CONCLUSIONS: Through the analysis of questions and responses submitted to eConsult, this study provides novel information on PCP knowledge gaps and approaches to care for patients living with frailty. Furthermore, these analyses provide evidence that eConsult is a feasible and valuable tool for improving care for patients with frailty in primary care settings.

Use of Artificial Intelligence in the Identification and Management of Frailty: A Scoping Review Protocol.

INTRODUCTION: Rapid population ageing and associated health issues such as frailty are a growing public health concern. While early identification and management of frailty may limit adverse health outcomes, the complex presentations of frailty pose challenges for clinicians. Artificial intelligence (AI) has emerged as a potential solution to support the early identification and management of frailty. In order to provide a comprehensive overview of current evidence regarding the development and use of AI technologies including machine learning and deep learning for the identification and management of frailty, this protocol outlines a scoping review aiming to identify and present available information in this area. Specifically, this protocol describes a review that will focus on the clinical tools and frameworks used to assess frailty, the outcomes that have been evaluated and the involvement of knowledge users in the development, implementation and evaluation of AI methods and tools for frailty care in clinical settings. METHODS AND ANALYSIS: This scoping review protocol details a systematic search of eight major academic databases, including Medline, Embase, PsycInfo, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Ageline, Web of Science, Scopus and Institute of Electrical and Electronics Engineers (IEEE) Xplore using the framework developed by Arksey and O'Malley and enhanced by Levac et al and the Joanna Briggs Institute. The search strategy has been designed in consultation with a librarian. Two independent reviewers will screen titles and abstracts, followed by full texts, for eligibility and then chart the data using a piloted data charting form. Results will be collated and presented through a narrative summary, tables and figures. ETHICS AND DISSEMINATION: Since this study is based on publicly available information, ethics approval is not required. Findings will be communicated with healthcare providers, caregivers, patients and research and health programme funders through peer-reviewed publications, presentations and an infographic. REGISTRATION DETAILS: OSF Registries (https://doi.org/10.17605/OSF.IO/T54G8).

Enabling knowledge translation: implementation of a web-based tool for independent walking prediction after traumatic spinal cord injury.

Introduction: Several clinical prediction rules (CPRs) have been published, but few are easily accessible or convenient for clinicians to use in practice. We aimed to develop, implement, and describe the process of building a web-based CPR for predicting independent walking 1-year after a traumatic spinal cord injury (TSCI). Methods: Using the published and validated CPR, a front-end web application called "Ambulation" was built using HyperText Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. A survey was created using QualtricsXM Software to gather insights on the application's usability and user experience. Website activity was monitored using Google Analytics. Ambulation was developed with a core team of seven clinicians and researchers. To refine the app's content, website design, and utility, 20 professionals from different disciplines, including persons with lived experience, were consulted. Results: After 11 revisions, Ambulation was uploaded onto a unique web domain and launched (www.ambulation.ca) as a pilot with 30 clinicians (surgeons, physiatrists, and physiotherapists). The website consists of five web pages: Home, Calculation, Team, Contact, and Privacy Policy. Responses from the user survey (n = 6) were positive and provided insight into the usability of the tool and its clinical utility (e.g., helpful in discharge planning and rehabilitation), and the overall face validity of the CPR. Since its public release on February 7, 2022, to February 28, 2023, Ambulation had 594 total users, 565 (95.1%) new users, 26 (4.4%) returning users, 363 (61.1%) engaged sessions (i.e., the number of sessions that lasted 10 seconds/longer, had one/more conversion events e.g., performing the calculation, or two/more page or screen views), and the majority of the users originating from the United States (39.9%) and Canada (38.2%). Discussion: Ambulation is a CPR for predicting independent walking 1-year after TSCI and it can assist frontline clinicians with clinical decision-making (e.g., time to surgery or rehabilitation plan), patient education and goal setting soon after injury. This tool is an example of adapting a validated CPR for independent walking into an easily accessible and usable web-based tool for use in clinical practice. This study may help inform how other CPRs can be adopted into clinical practice.

A data-driven approach to categorize patients with traumatic spinal cord injury: cluster analysis of a multicentre database.

Background: Conducting clinical trials for traumatic spinal cord injury (tSCI) presents challenges due to patient heterogeneity. Identifying clinically similar subgroups using patient demographics and baseline injury characteristics could lead to better patient-centered care and integrated care delivery. Purpose: We sought to (1) apply an unsupervised machine learning approach of cluster analysis to identify subgroups of tSCI patients using patient demographics and injury characteristics at baseline, (2) to find clinical similarity within subgroups using etiological variables and outcome variables, and (3) to create multi-dimensional labels for categorizing patients. Study design: Retrospective analysis using prospectively collected data from a large national multicenter SCI registry. Methods: A method of spectral clustering was used to identify patient subgroups based on the following baseline variables collected since admission until rehabilitation: location of the injury, severity of the injury, Functional Independence Measure (FIM) motor, and demographic data (age, and body mass index). The FIM motor score, the FIM motor score change, and the total length of stay were assessed on the subgroups as outcome variables at discharge to establish the clinical similarity of the patients within derived subgroups. Furthermore, we discussed the relevance of the identified subgroups based on the etiological variables (energy and mechanism of injury) and compared them with the literature. Our study also employed a qualitative approach to systematically describe the identified subgroups, crafting multi-dimensional labels to highlight distinguishing factors and patient-focused insights. Results: Data on 334 tSCI patients from the Rick Hansen Spinal Cord Injury Registry was analyzed. Five significantly different subgroups were identified (p-value ≤0.05) based on baseline variables. Outcome variables at discharge superimposed on these subgroups had statistically different values between them (p-value ≤0.05) and supported the notion of clinical similarity of patients within each subgroup. Conclusion: Utilizing cluster analysis, we identified five clinically similar subgroups of tSCI patients at baseline, yielding statistically significant inter-group differences in clinical outcomes. These subgroups offer a novel, data-driven categorization of tSCI patients which aligns with their demographics and injury characteristics. As it also correlates with traditional tSCI classifications, this categorization could lead to improved personalized patient-centered care.

Prognostic Value of Coronary Computed Tomography Angiography in Coronary Artery Bypass Graft Patients Systematic Review and Meta-Analysis.

We sought to assess the prognostic value of coronary computed tomographic angiography (CCTA) in patients with coronary artery bypass graft (CABG) by meta-analysis. MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched for relevant original articles published up to July 2021. CCTA prognostic studies enrolling patients with CABG were screened and included if outcomes included all-cause mortality or major adverse cardiac events. Maximally adjusted hazard ratios (HRs) were extracted for CCTA-derived prognostic factors. HRs were log-transformed and pooled across studies using the DerSimonian-Laird random-effects model and statistical heterogeneity was assessed using the I2 statistic. Of 1,576 screened articles, 4 retrospective studies fulfilled all inclusion criteria. Collectively, a total of 1,809 patients with CABG underwent CCTA (mean [SD] age 67.0 [8.5] years across 3 studies, 81.5% male across 4 studies). Coronary artery disease severity and revascularization were categorized using 2 models: unprotected coronary territories and coronary artery protection score. The pooled HRs from the random-effects models using the most highly adjusted study estimate were 3.64 (95% confidence interval 2.48 to 5.34, I2 = 57.8%, p <0.001; 4 studies) and 4.85 (95% confidence interval 3.17 to 7.43, I2 = 39.9%, p <0.001; 2 studies) for unprotected coronary territories and coronary artery protection score, respectively. In conclusion, in a limited number of studies, CCTA is an independent predictor of adverse events in patients with CABG. Larger studies using uniform models and endpoints are needed.

Using electronic consultation (eConsult) to identify frailty in provider-to-provider communication: a feasibility and validation study.

BACKGROUND: Frailty is a complex age-related clinical condition that increases vulnerability to stressors. Early recognition of frailty is challenging. While primary care providers (PCPs) serve as the first point of contact for most older adults, convenient tools for identifying frailty in primary care are lacking. Electronic consultation (eConsult), a platform connecting PCPs to specialists, is a rich source of provider-to-provider communication data. Text-based patient descriptions on eConsult may provide opportunities for earlier identification of frailty. We sought to explore the feasibility and validity of identifying frailty status using eConsult data. METHODS: eConsult cases closed in 2019 and submitted on behalf of long-term care (LTC) residents or community-dwelling older adults were sampled. A list of frailty-related terms was compiled through a review of the literature and consultation with experts. To identify frailty, eConsult text was parsed to measure the frequency of frailty-related terms. Feasibility of this approach was assessed by examining the availability of frailty-related terms in eConsult communication logs, and by asking clinicians to indicate whether they can assess likelihood of frailty by reviewing the cases. Construct validity was assessed by comparing the number of frailty-related terms in cases about LTC residents with those about community-dwelling older adults. Criterion validity was assessed by comparing clinicians' ratings of frailty to the frequency of frailty-related terms. RESULTS: One hundred thirteen LTC and 112 community cases were included. Frailty-related terms identified per case averaged 4.55 ± 3.95 in LTC and 1.96 ± 2.68 in the community (p < .001). Clinicians consistently rated cases with ≥ 5 frailty-related terms as highly likely of living with frailty. CONCLUSIONS: The availability of frailty-related terms establishes the feasibility of using provider-to-provider communication on eConsult to identify patients with high likelihood of living with this condition. The higher average of frailty-related terms in LTC (versus community) cases, and agreement between clinician-provided frailty ratings and the frequency of frailty-related terms, support the validity of an eConsult-based approach to identifying frailty. There is potential for eConsult to be used as a case-finding tool in primary care for early recognition and proactive initiation of care processes for older patients living with frailty.

What is the level of information technology maturity in Ontario's long-term care homes? A cross-sectional survey study protocol.

INTRODUCTION: The number of Canadians 75 years and older is expected to double over the next 20 years, putting continuing care systems such as long-term care (LTC) homes under increasing pressure. Health information technology (IT) has been found to improve the quality, safety and efficiency of care in numerous clinical settings and could help optimise LTC for residents. However, the level of health IT adoption in Ontario's LTC homes is unknown and, as a result, requires an accurate assessment to provide a baseline understanding for future planning. METHODS AND ANALYSIS: We will use a cross-sectional design to investigate the level of IT maturity in Ontario's LTC homes. IT maturity will be assessed with the LTC IT Maturity Instrument, a validated survey examining IT capabilities, the extent of IT use and degree of internal/external IT integration across the domains of resident care, clinical support and administrative activities. All LTC homes in Ontario will be invited to participate. The Director of Care for each home will be directly contacted for recruitment. The survey will be distributed online (or by paper, if preferred) to LTC homes and completed by a staff member designated by the LTC to be knowledgeable about its IT systems. Analyses will consist of descriptive statistics characterising IT maturity across LTC homes and inferential statistics to examine the association between key facility-level characteristics (size, ownership, rurality) and IT maturity. ETHICS AND DISSEMINATION: This study was reviewed by the Ottawa Health Science Network Research Ethics Board and was exempt from full ethics review. Findings will be disseminated through peer-reviewed publication and presentations to the scientific community and stakeholders. Dissemination of our findings will not only inform provincial planning for harnessing the potential of technology in LTC but may also enable quality improvement initiatives in individual LTC homes.

Electronic consultation use by advanced practice nurses in older adult care-A descriptive study of service utilization data.

AIMS AND OBJECTIVES: To describe characteristics of service utilization by advanced practice nurses (APNs) employing an electronic consultation (eConsult) service in their care for older adults. BACKGROUND: Canada's aging population is projected to place unprecedented demands on the healthcare system. APNs, which include clinical nurse specialists (CNSs) and nurse practitioners (NPs), are nurses with advanced knowledge who can independently provide age-appropriate care. eConsult is a secure web-based platform enabling asynchronous, provider-to-provider communication. APNs can send and receive eConsults to address patient-specific concerns. METHODS: This is a retrospective analysis of eConsult utilization and user survey data for cases completed in 2019, reported in line with the STROBE guidelines. Eligible eConsults included those that had APN involvement (as a referrer or responder) and were concerning an older patient (≥65 years). Descriptive statistics were used to analyse service utilization and survey response data. RESULTS: Of 430 eligible eConsults, 421 (97.9%) were initiated by NPs and the rest by physicians. 23 (5.3%) were received by a CNS, of which 14 (3.3%) involved an NP-to-CNS exchange. Median specialist response interval was 0.9 days. 53% of eConsults was for dermatology, haematology, cardiology, gastroenterology and endocrinology. 73% of eConsults avoided a face-to-face referral after the consultation. In 90% of eConsults, APNs rated the service as helpful and/or educational. CONCLUSIONS: Through eConsult, APNs can collaborate with each other and physicians to access and provide a breadth of advice facilitating timely specialist-informed care for older patients, thus helping to alleviate some of the demands placed on the healthcare system. RELEVANCE TO CLINICAL PRACTICE: There is an opportunity for APNs to further adopt eConsult into their clinical practice, and this can, in turn, support the integration of the APN role in the health workforce. PATIENT OR PUBLIC CONTRIBUTION: Current APN eConsult users were involved in the study design and interpretation of results.

Ventricular Rupture at the Site of a Septic Myocardial Abscess After Acute Myocardial Infarction.

Mechanical complications after acute myocardial infarction are well-described yet catastrophic complications of acute coronary syndromes. Uniquely, we describe a rare case of left ventricular free wall rupture at the site of a septic myocardial abscess after an anterior wall myocardial infarction. (Level of Difficulty: Advanced.).

Correction: Natural Language Processing to Identify Digital Learning Tools in Postgraduate Family Medicine: Protocol for a Scoping Review.

[This corrects the article DOI: 10.2196/34575.].

Natural Language Processing to Identify Digital Learning Tools in Postgraduate Family Medicine: Protocol for a Scoping Review.

BACKGROUND: The COVID-19 pandemic has highlighted the growing need for digital learning tools in postgraduate family medicine training. Family medicine departments must understand and recognize the use and effectiveness of digital tools in order to integrate them into curricula and develop effective learning tools that fill gaps and meet the learning needs of trainees. OBJECTIVE: This scoping review will aim to explore and organize the breadth of knowledge regarding digital learning tools in family medicine training. METHODS: This scoping review follows the 6 stages of the methodological framework outlined first by Arksey and O'Malley, then refined by Levac et al, including a search of published academic literature in 6 databases (MEDLINE, ERIC, Education Source, Embase, Scopus, and Web of Science) and gray literature. Following title and abstract and full text screening, characteristics and main findings of the included studies and resources will be tabulated and summarized. Thematic analysis and natural language processing (NLP) will be conducted in parallel using a 9-step approach to identify common themes and synthesize the literature. Additionally, NLP will be employed for bibliometric and scientometric analysis of the identified literature. RESULTS: The search strategy has been developed and launched. As of October 2021, we have completed stages 1, 2, and 3 of the scoping review. We identified 132 studies for inclusion through the academic literature search and 127 relevant studies in the gray literature search. Further refinement of the eligibility criteria and data extraction has been ongoing since September 2021. CONCLUSIONS: In this scoping review, we will identify and consolidate information and evidence related to the use and effectiveness of existing digital learning tools in postgraduate family medicine training. Our findings will improve the understanding of the current landscape of digital learning tools, which will be of great value to educators and trainees interested in using existing tools, innovators looking to design digital learning tools that meet current needs, and researchers involved in the study of digital tools. TRIAL REGISTRATION: OSF Registries osf.io/wju4k; https://osf.io/wju4k INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34575.

Electronic Consultation by Advanced Practice Nurses to Improve Access to Specialist Care for Older Adults.

Older adults face several challenges when accessing specialist care. Advanced practice nurses (APNs) can perform an important role in primary care for older adults, particularly when bolstered with digital tools. In the current study, we conducted a multiple case study of electronic consultations (eConsults) involving APNs to assess how these practitioners use the service to improve access to care. All eConsults submitted by or to an APN in 2019 on behalf of patients aged ≥65 years were reviewed to identify examples from six settings representative of the range of advanced nursing practices. For each setting, a final case was chosen using an iterative process and stratified by specialty and type of advice. Included cases were assessed using a conceptual framework for health care access. Selected cases illustrate how APNs can be effective users of eConsults in a diversity of health care settings. The framework allowed for an in-depth study of access over the range of interactions that take place among patients, caregivers, providers, and the health care system. [Journal of Gerontological Nursing, 48(4), 33-40.].

Abnormal Social Interactions in a Drosophila Mutant of an Autism Candidate Gene: Neuroligin 3.

Social interactions are typically impaired in neuropsychiatric disorders such as autism, for which the genetic underpinnings are very complex. Social interactions can be modeled by analysis of behaviors, including social spacing, sociability, and aggression, in simpler organisms such as Drosophila melanogaster. Here, we examined the effects of mutants of the autism-related gene neuroligin 3 (nlg3) on fly social and non-social behaviors. Startled-induced negative geotaxis is affected by a loss of function nlg3 mutation. Social space and aggression are also altered in a sex- and social-experience-specific manner in nlg3 mutant flies. In light of the conserved roles that neuroligins play in social behavior, our results offer insight into the regulation of social behavior in other organisms, including humans.