Implementation of low-intensity thrombolysis monitoring care in routine practice: process evaluation of the Optimal Post rtPA-IV Monitoring in Acute Ischemic Stroke (OPTIMISTmain) study in the United States.

INTRODUCTION: The ongoing OPTIMISTmain study, an international, multicenter, stepped-wedge cluster randomized trial, aims to determine effectiveness and safety of low-intensity versus standard monitoring in thrombolysis-treated patients with mild-to-moderate acute ischemic stroke (AIS). An embedded process evaluation explored integration and impact of the intervention on care processes at participating US sites. METHODS: A mixed-methods approach with quantitative and qualitative data were collected between September 2021 and November 2022. Implementer surveys were undertaken at pre- and post-intervention phases to understand the perceptions of low-intensity monitoring strategy. A sample of stroke care nurses were invited to participate in semi-structured interviews at an early stage of post-intervention. Qualitative data were analyzed deductively using the normalization process theory; quantitative data were tabulated. RESULTS: Interviews with 21 nurses at 8 hospitals have shown low-intensity monitoring was well accepted, as there were less time constraints and reduced workload for each patient. There were initial safety concerns over missing deteriorating patients and difficulties in changing established routines. Proper training, education, and communication, and changing the habits and culture of care, were key elements to successfully adopting the new monitoring care into routine practice. Similar results were found in the post-intervention survey (42 nurses from 13 hospitals). Nurses reported time being freed up to provide patient education (56%), daily living care (50%), early mobilization (26%), mood/cognition assessment (44%), and other aspects (i.e. communication, family support). CONCLUSIONS: Low-intensity monitoring for patients with mild-to-moderate acute ischemic stroke, facilitated by appropriate education and organizational support, appears feasible and acceptable at US hospitals.

Successful Thrombectomy for Large Vessel Occlusion after Emergent Transoceanic Patient Transport: An International Hub and Spoke Collaboration.

Mechanical thrombectomy (MT) is the standard of care for the treatment of acute ischemic stroke due to large vessel occlusion, but the capacity to deliver this treatment can be limited in less populous areas and island territories. Here, we describe the case of a man who developed right MCA syndrome while in Bermuda who was successfully diagnosed, transported over 800 miles to the East Coast of the USA, and treated with MT within 24 h. This case underscores the benefits of having organized systems of care and demonstrates the feasibility of urgent transoceanic patient transportation for stroke requiring MT.

The main Optimal Post rTpa-Iv Monitoring in Ischemic Stroke Trial (OPTIMISTmain): protocol for a pragmatic, stepped wedge, cluster randomized controlled trial.

Introduction Careful monitoring of patients who receive intravenous thrombolysis (IVT) for acute ischemic stroke (AIS) is resource-intensive, and potentially less relevant in those with mild degrees of neurological impairment who are at low-risk of symptomatic intracerebral hemorrhage (sICH) and other complications. \ Methods OPTIMISTmain is an international, multicenter, prospective, stepped wedge, cluster randomized, blinded outcome assessed trial aims to determine whether a less-intensity monitoring protocol is at least as effective, safe and efficient as standard post-IVT monitoring in patients with mild deficits post-AIS. Clinically-stable adult patients with mild AIS (defined by a NIHSS <10) who do not require intensive care within 2 hours post-IVT are recruited at hospitals in Australia, Chile, China, Malaysia, Mexico, UK, US and Vietnam. An average of 15 patients recruited per period (overall 60 patient participants) at 120 sites for a total of 7200 IVT-treated AIS patients will provide 90% power (one-sided α 0.025). The initiation of eligible hospitals is based on a rolling process whenever ready, stratified by country. Hospitals are randomly allocated using permuted blocks into 3 sequences of implementation, stratified by country and the projected number of patients to be recruited over 12 months. These sequences have four periods that dictate the order in which they are to switch from control (usual care) to intervention (implementation of low intensity monitoring protocol) to different clusters of patients in a stepped manner. Compared to standard monitoring, the low-intensity monitoring protocol includes assessments of neurological and vital signs every 15 minutes for 2 hours, 2 hourly (versus every 30 minutes) for 8 hours, and 4 hourly (versus every 1 hour) until 24 hours, post-IVT. The primary outcome measure is functional recovery, defined by the modified Rankin scale (mRS) at 90 days, a seven-point ordinal scale (0 [no residual symptom] to 6 [death]). Secondary outcomes include death or dependency, length of hospital stay, and health-related quality of life, sICH and serious adverse events. Conclusion OPTIMISTmain will provide Level I evidence for the safety and effectiveness of a low-intensity post-IVT monitoring protocol in patients with mild severity of AIS.

Predicting Early Seizures After Intracerebral Hemorrhage with Machine Learning.

BACKGROUND: Seizures are a harmful complication of acute intracerebral hemorrhage (ICH). "Early" seizures in the first week after ICH are a risk factor for deterioration, later seizures, and herniation. Ideally, seizure medications after ICH would only be administered to patients with a high likelihood to have seizures. We developed and validated machine learning (ML) models to predict early seizures after ICH. METHODS: We used two large datasets to train and then validate our models in an entirely independent test set. The first model ("CAV") predicted early seizures from a subset of variables of the CAVE score (a prediction rule for later seizures)-cortical hematoma location, age less than 65 years, and hematoma volume greater than 10 mL-whereas early seizure was the dependent variable. We attempted to improve on the "CAV" model by adding anticoagulant use, antiplatelet use, Glasgow Coma Scale, international normalized ratio, and systolic blood pressure ("CAV + "). For each model we used logistic regression, lasso regression, support vector machines, boosted trees (Xgboost), and random forest models. Final model performance was reported as the area under the receiver operating characteristic curve (AUC) using receiver operating characteristic models for the test data. The setting of the study was two large academic institutions: institution 1, 634 patients; institution 2, 230 patients. There were no interventions. RESULTS: Early seizures were predicted across the ML models by the CAV score in test data, (AUC 0.72, 95% confidence interval 0.62-0.82). The ML model that predicted early seizure better in the test data was Xgboost (AUC 0.79, 95% confidence interval 0.71-0.87, p = 0.04) compared with the CAV model AUC. CONCLUSIONS: Early seizures after ICH are predictable. Models using cortical hematoma location, age less than 65 years, and hematoma volume greater than 10 mL had a good accuracy rate, and performance improved with more independent variables. Additional methods to predict seizures could improve patient selection for monitoring and prophylactic seizure medications.

Practice Patterns and Attitudes Among Speech-Language Pathologists Treating Stroke Patients with Dysphagia: A Nationwide Survey.

Dysphagia management is a core component of quality stroke care. Speech-Language Pathologists (SLPs) play a key role in the management of post-stroke dysphagia. We sought to elicit perceptions, attitudes, and practice patterns regarding post-stroke dysphagia management among SLPs in the United States. We conducted a survey among SLPs registered with the American Speech-Language-Hearing Association who indicated that they care for acute stroke patients. A total of 336 participants completed the survey. Over half of the participants (58.6%) indicated that they obtain objective swallow testing in ≥ 60% of their post-stroke dysphagia patients. Almost 1 in 5 SLPs indicated that they are often unable to perform objective dysphagia testing due to limited resources (18.8% indicated resource limitations; 78.9% indicated no resources limitations; 2.4% were unsure). SLPs in hospitals without stroke center certification had higher odds of indicating limited resources compared to SLPs in certified stroke centers (OR 2.08, 95% CI 1.11-3.87). Over 75% indicated that percutaneous endoscopic gastrostomy (PEG) tubes after stroke are placed too early. SLPs who obtain objective swallow testing in ≥ 60% of patients had higher odds of indicating that PEG tubes are placed too early (OR 1.70, 95% CI 1.13-2.56). While 19.4% indicated that the optimal timing for PEG after stroke is < 7 days after admission, 25.0% indicated that the optimal timing is > 12 days. Almost 35% indicated that health care system pressures influence their recommendations, and 47.6% indicated that ≥ 25% of PEGs could be avoided if patients were given up to 7 more days for swallowing recovery.

Geographic and Regional Variability in Racial and Ethnic Disparities in Stroke Thrombolysis in the United States.

BACKGROUND AND PURPOSE: Intravenous thrombolysis (IVT) after ischemic stroke is underutilized in racially/ethnically minoritized groups. We aimed to determine the regional and geographic variability in racial/ethnic IVT disparities in the United States. METHODS: Acute ischemic stroke admissions between 2012 and 2018 were identified in the National Inpatient Sample. Multivariable logistic regression was used to test the association between IVT and race/ethnicity, stratified by geographic region and controlling for demographic, clinical, and hospital characteristics. RESULTS: Of the 545 509 included cases, 47 031 (8.6%) received IVT. Racially/ethnically minoritized groups had significantly lower adjusted odds of IVT compared with White people in the South Atlantic region (odds ratio [OR], 0.86 [95% CI, 0.82-0.91]), the East North Central region (OR, 0.91 [95% CI, 0.85-0.97]) and the Pacific region (OR, 0.90 [95% CI, 0.85-0.96]). In the South Atlantic region, IVT use in racial/ethnic minority groups was below the national average of all racial/ethnic minority patients (P=0.002). Compared with White patients, Black patients had lower odds of IVT in the Middle Atlantic region (OR, 0.84 [95% CI, 0.78-0.91]), the South Atlantic region (OR, 0.78 [95% CI, 0.74-0.82]), and the East North Central region (OR, 0.86 [95% CI, 0.79-0.93]). In the South Atlantic region, this difference was below the national average for Black people (P<0.001). Hispanic patients had significantly lower use of IVT only in the Pacific region (OR, 0.92 [95% CI, 0.85-0.99]), while Asian/Pacific Islander patients had lower odds of IVT in the Mountain (OR, 0.76 [95% CI, 0.59-0.98]) and Pacific region (OR, 0.89 [95% CI, 0.82-0.97]). CONCLUSIONS: Racial/ethnic disparities in IVT use in the United States vary by region. Geographic hotspots of lower IVT use in racially/ethnically minoritized groups are the South Atlantic region, driven predominantly by lower use of IVT in Black patients, and the East North Central and Pacific regions.

Exploring the Collateral Damage of the COVID-19 Pandemic on Stroke Care: A Statewide Analysis.

[Figure: see text].

Identifying Modifiable Predictors of Patient Outcomes After Intracerebral Hemorrhage with Machine Learning.

BACKGROUND/OBJECTIVE: Demonstrating a benefit of acute treatment to patients with intracerebral hemorrhage (ICH) requires identifying which patients have a potentially modifiable outcome, where treatment could favorably shift a patient's expected outcome. A decision rule for which patients have a modifiable outcome could improve the targeting of treatments. We sought to determine which patients with ICH have a modifiable outcome. METHODS: Patients with ICH were prospectively identified at two institutions. Data on hematoma volumes, medication histories, and other variables of interest were collected. ICH outcomes were evaluated using the modified Rankin Scale (mRS), assessed at 14 days and 3 months after ICH, with "good outcome" defined as 0-3 (independence or better) and "poor outcome" defined as 4-6 (dependence or worse). Supervised machine learning models identified the best predictors of good versus poor outcomes at Institution 1. Models were validated using repeated fivefold cross-validation as well as testing on the entirely independent sample at Institution 2. Model fit was assessed with area under the ROC curve (AUC). RESULTS: Model performance at Institution 1 was strong for both 14-day (AUC of 0.79 [0.77, 0.81] for decision tree, 0.85 [0.84, 0.87] for random forest) and 3 month (AUC of 0.75 [0.73, 0.77] for decision tree, 0.82 [0.80, 0.84] for random forest) outcomes. Independent predictors of functional outcome selected by the algorithms as important included hematoma volume at hospital admission, hematoma expansion, intraventricular hemorrhage, overall ICH Score, and Glasgow Coma Scale. Hematoma expansion was the only potentially modifiable independent predictor of outcome and was compatible with "good" or "poor" outcome in a subset of patients with low hematoma volumes, good Glasgow Coma scale and premorbid modified Rankin Scale scores. Models trained on harmonized data also predicted patient outcomes well at Institution 2 using decision tree (AUC 0.69 [0.63, 0.75]) and random forests (AUC 0.78 [0.72, 0.84]). CONCLUSIONS: Patient outcomes are predictable to a high level in patients with ICH, and hematoma expansion is the sole-modifiable predictor of these outcomes across two outcome types and modeling approaches. According to decision tree analyses predicting outcome at 3 months, patients with a high Glasgow Coma Scale score, less than 44.5 mL hematoma volume at admission, and relatively low premorbid modified Rankin Score in particular have a modifiable outcome and appear to be candidates for future interventions to improve outcomes after ICH.

Variability in Palliative Care Use after Intracerebral Hemorrhage at US Hospitals: A Multilevel Analysis.

BACKGROUND: Palliative care (PC) is an essential component of comprehensive care of patients with intracerebral hemorrhage (ICH). In the present study, we sought to characterize the variability of PC use after ICH among US hospitals. METHODS: ICH admissions from hospitals with at least 12 annual ICH cases were identified in the Nationwide Inpatient Sample between 2008 and 2011. We used multilevel logistic regression modeling to estimate between-hospital variance in PC use. We calculated the intraclass correlation coefficient (ICC), proportional variance change, and median OR after accounting for individual-level and hospital-level covariates. RESULTS: Among 26,791 ICH admissions, 12.5% received PC (95% CI 11.5-13.5). Among the 629 included hospitals, the median rate of PC use was 9.1 (interquartile range 1.5-19.3) per 100 ICH admissions, and 150 (23.9%) hospitals had no recorded PC use. The ICC of the random intercept (null) model was 0.274, suggesting that 27.4% of the overall variability in PC use was due to between-hospital variability. Adding hospital-level covariates to the model accounted for 25.8% of the between-hospital variance observed in the null model, with 74.2% of between-hospital variance remaining unexplained. The median OR of the fully adjusted model was 2.62 (95% CI 2.41-2.89), indicating that a patient moving from 1 hospital to another with a higher intrinsic propensity of PC use had a 2.63-fold median increase in the odds of receiving PC, independent of patient and hospital factors. CONCLUSIONS: Substantial variation in PC use after ICH exists among US hospitals. A substantial proportion of this between-hospital variability remains unexplained even after accounting for patient and hospital characteristics.

Comorbid Psychiatric Disease Is Associated With Lower Rates of Thrombolysis in Ischemic Stroke.

BACKGROUND AND PURPOSE: Intravenous thrombolysis (IVT) improves outcomes after acute ischemic stroke but is underused in certain patient populations. Mental illness is pervasive in the United States, and patients with comorbid psychiatric disease experience inequities in treatment for a range of conditions. We aimed to determine whether comorbid psychiatric disease is associated with differences in IVT use in acute ischemic stroke. METHODS: Acute ischemic stroke admissions between 2007 and 2011 were identified in the Nationwide Inpatient Sample. Psychiatric disease was defined by International Classification of Diseases, Ninth Revision, Clinical Modification codes for secondary diagnoses of schizophrenia or other psychoses, bipolar disorder, depression, or anxiety. Using logistic regression, we tested the association between IVT and psychiatric disease, controlling for demographic, clinical, and hospital factors. RESULTS: Of the 325 009 ischemic stroke cases meeting inclusion criteria, 12.8% had any of the specified psychiatric comorbidities. IVT was used in 3.6% of those with, and 4.4% of those without, psychiatric disease (P<0.001). Presence of any psychiatric disease was associated with lower odds of receiving IVT (adjusted odds ratio, 0.80; 95% confidence interval, 0.76-0.85). When psychiatric diagnoses were analyzed separately individuals with schizophrenia or other psychoses, anxiety, or depression each had significantly lower odds of IVT compared to individuals without psychiatric disease. CONCLUSIONS: Acute ischemic stroke patients with comorbid psychiatric disease have significantly lower odds of IVT. Understanding barriers to IVT use in such patients may help in developing interventions to increase access to evidence-based stroke care.

Race Differences in Gastrostomy Tube Placement After Stroke in Majority-White, Minority-Serving, and Racially Integrated US Hospitals.

We sought to determine individual and system contributions to race disparities in percutaneous endoscopic gastrostomy (PEG) tube placement after stroke. Ischemic stroke admissions were identified from the Nationwide Inpatient Sample between 2007 and 2011. Hospitals were categorized based on the percentage of ethnic/racial minority stroke patients (< 25% ethnic/racial minorities ["majority-white hospitals"], 25-50% ethnic/racial minorities ["racially integrated hospitals"], or > 50% ethnic/racial minorities ["minority-serving hospitals"]). Logistic regression was used to evaluate the association between ethnicity/race and PEG utilization within and between the different hospital strata. Among 246,825 stroke admissions, patients receiving care in minority-serving hospitals had higher odds of PEG compared to patients in majority-white hospitals, regardless of individual patient race (adjusted odds ratio [OR] 1.24, 95% CI 1.12-1.38). Ethnic/racial minorities had higher odds of PEG than whites in any hospital strata; however, this discrepancy was largest in majority-white hospitals (OR 1.62, 95% CI 1.48-1.76), and smallest in minority-serving hospitals (OR 1.22, 95% CI 1.11-1.33; p for interaction < 0.001). Ethnic/racial minority patients had similar odds of PEG in any hospital strata, while white patients had increasing odds of PEG in racially integrated and minority-serving compared to majority-white hospitals (OR 1.28, 95% CI 1.15-1.43 in racially integrated, and OR 1.39, 95% CI 1.23-1.57 in minority-serving, compared to majority-white hospitals, p for trend < 0.001). The likelihood of PEG after ischemic stroke was increased in minority-serving compared to majority-white hospitals. White patients had higher odds of PEG in minority-serving compared to majority-white hospitals, indicating a systemic difference in PEG placement across hospitals.

Improving the Accuracy of Scores to Predict Gastrostomy after Intracerebral Hemorrhage with Machine Learning.

BACKGROUND: Gastrostomy placement after intracerebral hemorrhage indicates the need for continued medical care and predicts patient dependence. Our objective was to determine the optimal machine learning technique to predict gastrostomy. METHODS: We included 531 patients in a derivation cohort and 189 patients from another institution for testing. We derived and tested predictions of the likelihood of gastrostomy placement with logistic regression using the GRAVo score (composed of Glasgow Coma Scale ≤12, age >50 years, black race, and hematoma volume >30 mL), compared to other machine learning techniques (kth nearest neighbor, support vector machines, random forests, extreme gradient boosting, gradient boosting machine, stacking). Receiver Operating Curves (Area Under the Curve, [AUC]) between logistic regression (the technique used in GRAVo score development) and other machine learning techniques were compared. Another institution provided an external test data set. RESULTS: In the external test data set, logistic regression using the GRAVo score components predicted gastrostomy (P < 0.001), however, with a lower AUC (0.66) than kth nearest neighbors (AUC 0.73), random forests (AUC 0.74), Gradient boosting machine (AUC 0.77), extreme gradient boosting (AUC 0.77), (P < 0.01 for all compared to logistic regression). Results from the internal test set were similar. CONCLUSIONS: Machine learning techniques other than logistic regression (eg, random forests, extreme gradient boost, and kth nearest neighbors) were significantly more accurate for predicting gastrostomy using the same independent variables. Machine learning techniques may assist clinicians in identifying patients likely to need interventions.

Individual and System Contributions to Race and Sex Disparities in Thrombolysis Use for Stroke Patients in the United States.

BACKGROUND AND PURPOSE: Intravenous thrombolysis (IVT) is underutilized in ethnic minorities and women. To disentangle individual and system-based factors determining disparities in IVT use, we investigated race/sex differences in IVT utilization among hospitals serving varying proportions of minority patients. METHODS: Ischemic stroke admissions were identified from the Nationwide Inpatient Sample between 2007 and 2011. Hospitals were categorized based on the percentage of minority patients admitted with stroke (<25% minority patients [white hospitals], 25% to 50% minority patients [mixed hospitals], or >50% minority patients [minority hospitals]). Logistic regression was used to evaluate the association between race/sex and IVT use within and between the different hospital strata. RESULTS: Among 337 201 stroke admissions, white men had the highest odds of IVT among all race/sex groups in any hospital strata, and the odds of IVT for white men did not differ by hospital strata. For white women and minority men, the odds of IVT were significantly lower in minority hospitals compared with white hospitals (odds ratio, 0.83; 95% confidence interval, 0.71-0.97, for white women; and odds ratio, 0.82; 95% confidence interval, 0.69-0.99, for minority men). Race disparities in IVT use among women were observed in white hospitals (odds ratio, 0.88; 95% confidence interval, 0.78-0.99, in minority compared with white women), but not in minority hospitals (odds ratio, 0.94, 95% confidence interval, 0.82-1.09). Sex disparities in IVT use were observed among whites but not among minorities. CONCLUSIONS: Minority men and white women have significantly lower odds of IVT in minority hospitals compared with white hospitals. IVT use in white men does not differ by hospital strata.

Racial Differences in Palliative Care Use After Stroke in Majority-White, Minority-Serving, and Racially Integrated U.S. Hospitals.

OBJECTIVES: Racial/ethnic differences in palliative care resource use after stroke have been recognized, but it is unclear whether patient or hospital characteristics drive this disparity. We sought to determine whether palliative care use after intracerebral hemorrhage and ischemic stroke differs between hospitals serving varying proportions of minority patients. DESIGN: Population-based cross-sectional study. SETTING: Inpatient hospital admissions from the Nationwide Inpatient Sample between 2007 and 2011. PATIENTS: A total of 46,735 intracerebral hemorrhage and 331,521 ischemic stroke cases. INTERVENTIONS: Palliative care use. MEASUREMENTS AND MAIN RESULTS: Intracerebral hemorrhage and ischemic stroke admissions were identified from the Nationwide Inpatient Sample between 2007 and 2011. Hospitals were categorized based on the percentage of ethnic minority stroke patients (< 25% minorities ["white hospitals"], 25-50% minorities ["mixed hospitals"], or > 50% minorities ["minority hospitals"]). Logistic regression was used to evaluate the association between race/ethnicity and palliative care use within and between the different hospital strata. Stroke patients receiving care in minority hospitals had lower odds of palliative care compared with those treated in white hospitals, regardless of individual patient race/ethnicity (adjusted odds ratio, 0.65; 95% CI, 0.50-0.84 for intracerebral hemorrhage and odds ratio, 0.62; 95% CI, 0.50-0.77 for ischemic stroke). Ethnic minorities had a lower likelihood of receiving palliative care compared with whites in any hospital stratum, but the odds of palliative care for both white and minority intracerebral hemorrhage patients was lower in minority compared with white hospitals (odds ratio, 0.66; 95% CI, 0.50-0.87 for white and odds ratio, 0.64; 95% CI, 0.46-0.88 for minority patients). Similar results were observed in ischemic stroke. CONCLUSIONS: The odds of receiving palliative care for both white and minority stroke patients is lower in minority compared with white hospitals, suggesting system-level factors as a major contributor to explain race disparities in palliative care use after stroke.

Racial and Socioeconomic Disparities in Gastrostomy Tube Placement After Intracerebral Hemorrhage in the United States.

BACKGROUND AND PURPOSE: Percutaneous endoscopic gastrostomy (PEG) tubes are widely used for enteral feeding of patients after intracerebral hemorrhage (ICH). We sought to determine whether PEG placement after ICH differs by race and socioeconomic status. METHODS: Patient discharges with ICH as the primary diagnosis from 2007 to 2011 were queried from the Nationwide Inpatient Sample. Logistic regression was used to evaluate the association between race, insurance status, and household income with PEG placement. RESULTS: Of 49 946 included ICH admissions, a PEG was placed in 4464 (8.94%). Among PEG recipients, 47.2% were minorities and 15.6% were Medicaid enrollees, whereas 33.7% and 8.2% of patients without a PEG were of a race other than white and enrolled in Medicaid, respectively (P<0.001). Compared with whites, the odds of PEG were highest among Asians/Pacific Islanders (odds ratio [OR] 1.62, 95% confidence interval [CI] 1.32-1.99) and blacks (OR 1.42, 95% CI 1.28-1.59). Low household income (OR 1.25, 95% CI 1.09-1.44 in lowest compared with highest quartile) and enrollment in Medicaid (OR 1.36, 95% CI 1.17-1.59 compared with private insurance) were associated with PEG placement. Racial disparities (minorities versus whites) were most pronounced in small/medium-sized hospitals (OR 1.77, 95% CI 1.43-2.20 versus OR 1.31, 95% CI 1.17-1.47 in large hospitals; P value for interaction 0.011) and in hospitals with low ICH case volume (OR 1.58, 95% CI 1.38-1.81 versus OR 1.29, 95% CI 1.12-1.50 in hospitals with high ICH case volume; P value for interaction 0.007). CONCLUSIONS: Minority race, Medicaid enrollment, and low household income are associated with PEG placement after ICH.

ICAT: a simple score predicting critical care needs after thrombolysis in stroke patients.

BACKGROUND: Patients receiving intravenous thrombolysis (IVT) for acute ischemic stroke are at risk of developing complications, commonly necessitating admission to an intensive care unit (ICU). At present, most IVT is administered in the Emergency Department or in dedicated stroke units, but no evidence-based criteria exist that allow for early identification of patients at increased risk of developing ICU needs. The present study describes a novel prediction score aiming to identify a subpopulation of post-IVT patients at high risk for critical care interventions. METHODS: We retrospectively analyzed data from 301 patients undergoing IVT at our institutions during a 5-year period. Two hundred and ninety patients met inclusion criteria. The sample was randomly divided into a development and a validation cohort. Logistic regression was used to develop a risk score by weighting predictors of critical care needs based on strength of association. RESULTS: Seventy-two patients (24.8%) required critical care interventions. Black race (odds ratio [OR] 3.81, p=0.006), male sex (OR 3.79, p=0.008), systolic blood pressure (SBP; OR 1.45 per 10 mm Hg increase in SBP, p<0.001), and NIH stroke scale (NIHSS; OR 1.09 per 1 point increase in NIHSS, p=0.071) were independent predictors of critical care needs. The optimal model for score development, predicting critical care needs, achieved an AUC of 0.782 in the validation group. The score was named the ICAT (Intensive Care After Thrombolysis) score, assigning the following points: black race (1 point), male sex (1 point), SBP (2 points if 160-200 mm Hg; 4 points if >200 mm Hg), and NIHSS (1 point if 7-12; 2 points if >12). Each 1-point increase in the score was associated with 2.22-fold increased odds for critical care needs (95% CI 1.78-2.76, p<0.001). A score ≥ 2 was associated with over 13 times higher odds of critical care needs compared to a score <2 (OR 13.60, 95% CI 3.23-57.19), predicting critical care with 97.2% sensitivity and 28.0% specificity. CONCLUSION: The ICAT score, combining information about race, sex, SBP, and NIHSS, predicts critical care needs in post-IVT patients and may be helpful when triaging post-IVT patients to the appropriate monitoring environment.