Mobile health has been shown to improve quality, access, and efficiency of health care in select populations. We sought to evaluate the benefits of mobile health monitoring using the KidsHeart app in an infant CHD population.

We reviewed data submitted to KidsHeart from parents of infants discharged following intervention for high-risk CHD lesions including subjects status post stage 1 single ventricle palliation, ductal stent or surgical shunt, pulmonary artery band, or right ventricular outflow tract stent. We report on the benefits of a novel mobile health red flag scoring system, mobile health growth/feed tracking, and longitudinal neurodevelopmental outcomes tracking.

A total of 69 CHD subjects (63% male, 41% non-white, median age 28 days [interquartile range 20, 75 days]) were included with median mobile health follow-up of 137 days (56, 190). During the analytic window, subjects submitted 5700 mobile health red flag notifications including 245 violations (mean [standard deviation] 3 ± 3.96 per participant) with 80% (55/69) of subjects submitting at least one violation. Violations precipitated 116 interventions including hospital admission in 34 (29%) with trans-catheter evaluation in 15 (13%) of those. Growth data (n = 2543 daily weights) were submitted by 63/69 (91%) subjects and precipitated 31 feed changes in 23 participants. Sixty-eight percent of subjects with age >2 months submitted at least one complete neurodevelopment questionnaire.

In our initial experience, mobile health monitoring using the KidsHeart app enhanced interstage monitoring permitting earlier intervention, allowed for remote tracking of growth feeding, and provided a means for tracking longitudinal neurodevelopmental outcomes.

Diagnosis of acute ischemia typically relies on evidence of ischemic lesions on magnetic resonance imaging (MRI), a limited diagnostic resource. We aimed to determine associations of clinical variables and acute infarcts on MRI in patients with suspected low-risk transient ischemic attack (TIA) and minor stroke and to assess their predictive ability.

We conducted a post-hoc analysis of the Diagnosis of Uncertain-Origin Benign Transient Neurological Symptoms (DOUBT) study, a prospective, multicenter cohort study investigating the frequency of acute infarcts in patients with low-risk neurological symptoms. Primary outcome parameter was defined as diffusion-weighted imaging (DWI)-positive lesions on MRI. Logistic regression analysis was performed to evaluate associations of clinical characteristics with MRI-DWI-positivity. Model performance was evaluated by Harrel’s c-statistic.

In 1028 patients, age (Odds Ratio (OR) 1.03, 95% Confidence Interval (CI) 1.01–1.05), motor (OR 2.18, 95%CI 1.27–3.65) or speech symptoms (OR 2.53, 95%CI 1.28–4.80), and no previous identical event (OR 1.75, 95%CI 1.07–2.99) were positively associated with MRI-DWI-positivity. Female sex (OR 0.47, 95%CI 0.32–0.68), dizziness and gait instability (OR 0.34, 95%CI 0.14–0.69), normal exam (OR 0.55, 95%CI 0.35–0.85) and resolved symptoms (OR 0.49, 95%CI 0.30–0.78) were negatively associated. Symptom duration and any additional symptoms/symptom combinations were not associated. Predictive ability of the model was moderate (c-statistic 0.72, 95%CI 0.69–0.77).

Detailed clinical information is helpful in assessing the risk of ischemia in patients with low-risk neurological events, but a predictive model had only moderate discriminative ability. Patients with clinically suspected low-risk TIA or minor stroke require MRI to confirm the diagnosis of cerebral ischemia.

We investigated the impact of workflow times on the outcomes of patients treated with endovascular thrombectomy (EVT) in the late time window.

Individual patients’ data who underwent EVT in the late time window (onset to imaging >6 hours) were pooled from seven registries and randomized clinical trials. Multiple time intervals were analyzed. Mixed-effects logistic regression was used to estimate the likelihood of functional independence at 90 days (modified Rankin Scale 0–2). Mixed-effects negative binomial regression was used to evaluate the relationship between patient characteristics and workflow time intervals.

608 patients were included. The median age was 70 years (IQR: 58–71), 307 (50.5%) were female, and 310 (53.2%) had wake-up strokes. Successful reperfusion was achieved in 493 (81.2%) patients, and 262 (44.9%) achieved 90-day mRS 0–2. The estimated odds of functional independence decreased by 13% for every 30 minute delay from emergency department (ED) arrival to imaging time and by 7% from ED arrival to the end of EVT in the entire cohort. Also, the estimated odds of functional independence decreased by 33% for every 30 minute delay in the interval from arterial puncture to end of EVT, 16% in the interval from arrival in ED to end of EVT and 6% in the interval from stroke onset to end of EVT among patients who had a wake-up stroke.

Faster workflow from ED arrival to end of EVT is associated with improved functional independence among stroke patients treated in the late window.

To examine the association of co-morbidity with home-time after acute stroke and whether the association is influenced by age.

We conducted a province-wide study using linked administrative databases to identify all admissions for first acute ischemic stroke or intracerebral hemorrhage between 2007 and 2018 in Alberta, Canada. We used ischemic stroke-weighted Charlson Co-morbidity Index of 3 or more to identify those with severe co-morbidity. We used zero-inflated negative binomial models to determine the association of severe co-morbidity with 90-day and 1-year home-time, and logistic models for achieving ≥ 80 out of 90 days of home-time, assessing for effect modification by age and adjusting for sex, stroke type, comprehensive stroke center care, hypertension, atrial fibrillation, year of study, and separately adjusting for estimated stroke severity. We also evaluated individual co-morbidities.

Among 28,672 patients in our final cohort, severe co-morbidity was present in 27.7% and was associated with lower home-time, with a greater number of days lost at younger age (−13 days at age < 60 compared to −7 days at age 80+ years for 90-day home-time; −69 days at age < 60 compared to −51 days at age 80+ years for 1-year home-time). The reduction in probability of achieving ≥ 80 days of home-time was also greater at younger age (−22.7% at age < 60 years compared to −9.0% at age 80+ years). Results were attenuated but remained significant after adjusting for estimated stroke severity and excluding those who died. Myocardial infarction, diabetes, and cancer/metastases had a greater association with lower home-time at younger age, and those with dementia had the greatest reduction in home time.

Severe co-morbidity in acute stroke is associated with lower home-time, more strongly at younger age.

Stroke outcomes research requires risk-adjustment for stroke severity, but this measure is often unavailable. The Passive Surveillance Stroke SeVerity (PaSSV) score is an administrative data-based stroke severity measure that was developed in Ontario, Canada. We assessed the geographical and temporal external validity of PaSSV in British Columbia (BC), Nova Scotia (NS) and Ontario, Canada.

We used linked administrative data in each province to identify adult patients with ischemic stroke or intracerebral hemorrhage between 2014-2019 and calculated their PaSSV score. We used Cox proportional hazards models to evaluate the association between the PaSSV score and the hazard of death over 30 days and the cause-specific hazard of admission to long-term care over 365 days. We assessed the models’ discriminative values using Uno’s c-statistic, comparing models with versus without PaSSV.

We included 86,142 patients (n = 18,387 in BC, n = 65,082 in Ontario, n = 2,673 in NS). The mean and median PaSSV were similar across provinces. A higher PaSSV score, representing lower stroke severity, was associated with a lower hazard of death (hazard ratio and 95% confidence intervals 0.70 [0.68, 0.71] in BC, 0.69 [0.68, 0.69] in Ontario, 0.72 [0.68, 0.75] in NS) and admission to long-term care (0.77 [0.76, 0.79] in BC, 0.84 [0.83, 0.85] in Ontario, 0.86 [0.79, 0.93] in NS). Including PaSSV in the multivariable models increased the c-statistics compared to models without this variable.

PaSSV has geographical and temporal validity, making it useful for risk-adjustment in stroke outcomes research, including in multi-jurisdiction analyses.

To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a “real-world” setting.

Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a “real-world” setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY.

Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%–99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%–61.6%), but not the “real-world” setting (acceptability:32.9%–42.6%).

EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and “real-world” setting, although this was largely related to baseline patient differences favoring the “real-world” EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.

Although age-standardized stroke occurrence has been decreasing, the absolute number of stroke events globally, and in Canada, is increasing. Stroke surveillance is necessary for health services planning, informing research design, and public health messaging. We used administrative data to estimate the number of stroke events resulting in hospital or emergency department presentation across Canada in the 2017–18 fiscal year.

Hospitalization data were obtained from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database and the Ministry of Health and Social Services in Quebec. Emergency department data were obtained from the CIHI National Ambulatory Care Reporting System (Alberta and Ontario). Stroke events were identified using ICD-10 coding. Data were linked into episodes of care to account for readmissions and interfacility transfers. Projections for emergency department visits for provinces/territories outside of Alberta and Ontario were generated based upon age and sex-standardized estimates from Alberta and Ontario.

In the 2017–18 fiscal year, there were 108,707 stroke events resulting in hospital or emergency department presentation across the country. This was made up of 54,357 events resulting in hospital admission and 54,350 events resulting in only emergency department presentation. The events resulting in only emergency department presentation consisted of 25,941 events observed in Alberta and Ontario and a projection of 28,409 events across the rest of the country.

We estimate a stroke event resulting in hospital or emergency department presentation occurs every 5 minutes in Canada.

Neurocognitive testing may advance the goal of predicting near-term suicide risk. The current study examined whether performance on a Go/No-go (GNG) task, and computational modeling to extract latent cognitive variables, could enhance prediction of suicide attempts within next 90 days, among individuals at high-risk for suicide.

136 Veterans at high-risk for suicide previously completed a computer-based GNG task requiring rapid responding (Go) to target stimuli, while withholding responses (No-go) to infrequent foil stimuli; behavioral variables included false alarms to foils (failure to inhibit) and missed responses to targets. We conducted a secondary analysis of these data, with outcomes defined as actual suicide attempt (ASA), other suicide-related event (OtherSE) such as interrupted/aborted attempt or preparatory behavior, or neither (noSE), within 90-days after GNG testing, to examine whether GNG variables could improve ASA prediction over standard clinical variables. A computational model (linear ballistic accumulator, LBA) was also applied, to elucidate cognitive mechanisms underlying group differences.

On GNG, increased miss rate selectively predicted ASA, while increased false alarm rate predicted OtherSE (without ASA) within the 90-day follow-up window. In LBA modeling, ASA (but not OtherSE) was associated with decreases in decisional efficiency to targets, suggesting differences in the evidence accumulation process were specifically associated with upcoming ASA.

These findings suggest that GNG may improve prediction of near-term suicide risk, with distinct behavioral patterns in those who will attempt suicide within the next 90 days. Computational modeling suggests qualitative differences in cognition in individuals at near-term risk of suicide attempt.

The Passive Surveillance Stroke Severity (PaSSV) Indicator was derived to estimate stroke severity from variables in administrative datasets but has not been externally validated.

We used linked administrative datasets to identify patients with first hospitalization for acute stroke between 2007-2018 in Alberta, Canada. We used the PaSSV indicator to estimate stroke severity. We used Cox proportional hazard models and evaluated the change in hazard ratios and model discrimination for 30-day and 1-year case fatality with and without PaSSV. Similar comparisons were made for 90-day home time thresholds using logistic regression. We also linked with a clinical registry to obtain National Institutes of Health Stroke Scale (NIHSS) and compared estimates from models without stroke severity, with PaSSV, and with NIHSS.

There were 28,672 patients with acute stroke in the full sample. In comparison to no stroke severity, addition of PaSSV to the 30-day case fatality models resulted in improvement in model discrimination (C-statistic 0.72 [95%CI 0.71–0.73] to 0.80 [0.79–0.80]). After adjustment for PaSSV, admission to a comprehensive stroke center was associated with lower 30-day case fatality (adjusted hazard ratio changed from 1.03 [0.96–1.10] to 0.72 [0.67–0.77]). In the registry sample (N = 1328), model discrimination for 30-day case fatality improved with the inclusion of stroke severity. Results were similar for 1-year case fatality and home time outcomes.

Addition of PaSSV improved model discrimination for case fatality and home time outcomes. The validity of PASSV in two Canadian provinces suggests that it is a useful tool for baseline risk adjustment in acute stroke.

Collateral status is an indicator of a favorable outcome in stroke. Leptomeningeal collaterals provide alternative routes for brain perfusion following an arterial occlusion or flow-limiting stenosis. Using a large cohort of ischemic stroke patients, we examined the relative contribution of various demographic, laboratory, and clinical variables in explaining variability in collateral status.

Patients with acute ischemic stroke in the anterior circulation were enrolled in a multi-center hospital-based observational study. Intracranial occlusions and collateral status were identified and graded using multiphase computed tomography angiography. Based on the percentage of affected territory filled by collateral supply, collaterals were graded as either poor (0–49%), good (50–99%), or optimal (100%). Between-group differences in demographic, laboratory, and clinical factors were explored using ordinal regression models. Further, we explored the contribution of measured variables in explaining variance in collateral status.

386 patients with collateral status classified as poor (n = 64), good (n = 125), and optimal (n = 197) were included. Median time from symptom onset to CT was 120 (IQR: 78–246) minutes. In final multivariable model, male sex (OR 1.9, 95% CIs [1.2, 2.9], p = 0.005) and leukocytosis (OR 1.1, 95% CIs [1.1, 1.2], p = 0.001) were associated with poor collaterals. Measured variables only explained 44.8–53.0% of the observed between-patient variance in collaterals.

Male sex and leukocytosis are associated with poorer collaterals. Nearly half of the variance in collateral flow remains unexplained and could be in part due to genetic differences.

Increased risk donors in paediatric heart transplantation have characteristics that may increase the risk of infectious disease transmission despite negative serologic testing. However, the risk of disease transmission is low, and refusing an IRD offer may increase waitlist mortality. We sought to determine the risks of declining an initial IRD organ offer.

We performed a retrospective analysis of candidates waitlisted for isolated PHT using 20072017 United Network of Organ Sharing datasets. Match runs identified candidates receiving IRD offers. Competing risks analysis was used to determine mortality risk for those that declined an initial IRD offer with stratified Cox regression to estimate the survival benefit associated with accepting initial IRD offers. Overall, 238/1067 (22.3%) initial IRD offers were accepted. Candidates accepting an IRD offer were younger (7.2 versus 9.8 years, p < 0.001), more often female (50 versus 41%, p = 0.021), more often listed status 1A (75.6 versus 61.9%, p < 0.001), and less likely to require mechanical bridge to PHT (16% versus 23%, p = 0.036). At 1- and 5-year follow-up, cumulative mortality was significantly lower for candidates who accepted compared to those that declined (6% versus 13% 1-year mortality and 15% versus 25% 5-year mortality, p = 0.0033). Decline of an IRD offer was associated with an adjusted hazard ratio for mortality of 1.87 (95% CI 1.24, 2.81, p < 0.003).

IRD organ acceptance is associated with a substantial survival benefit. Increasing acceptance of IRD organs may provide a targetable opportunity to decrease waitlist mortality in PHT.

We examined the return on investment (ROI) from the Endovascular Reperfusion Alberta (ERA) project, a provincially funded population-wide strategy to improve access to endovascular therapy (EVT), to inform policy regarding sustainability.

We calculated net benefit (NB) as benefit minus cost and ROI as benefit divided by cost. Patients treated with EVT and their controls were identified from the ESCAPE trial. Using the provincial administrative databases, their health services utilization (HSU), including inpatient, outpatient, physician, long-term care services, and prescription drugs, were compared. This benefit was then extrapolated to the number of patients receiving EVT increased in 2018 and 2019 by the ERA implementation. We used three time horizons, including short (90 days), medium (1 year), and long-term (5 years).

EVT was associated with a reduced gross HSU cost for all the three time horizons. Given the total costs of ERA were $2.04 million in 2018 ($11,860/patient) and $3.73 million in 2019 ($17,070/patient), NB per patient in 2018 (2019) was estimated at −$7,313 (−$12,524), $54,592 ($49,381), and $47,070 ($41,859) for short, medium, and long-term time horizons, respectively. Total NB for the province in 2018 (2019) were −$1.26 (−$2.74), $9.40 ($10.78), and $8.11 ($9.14) million; ROI ratios were 0.4 (0.3), 5.6 (3.9) and 5.0 (3.5). Probabilities of ERA being cost saving were 39% (31%), 97% (96%), and 94% (91%), for short, medium, and long-term time horizons, respectively.

The ERA program was cost saving in the medium and long-term time horizons. Results emphasized the importance of considering a broad range of HSU and long-term impact to capture the full ROI.