Introduction: Patients who present to a PSC with a large vessel occlusion are often transferred to hospitals with thrombectomy capability. Inequities in rates of hospital transfer amongst patients across various gender, racial background, and socioeconomic status are well established. A common metric used to determine quality of care in such transfers is the Door In Door Out (DIDO) time. We hypothesized that there would be no difference in the DIDO using an established systematic approach to transfers in our 14-hospital integrated healthcare system. Methods: All interhospital transfers for thrombectomy across our 14 PSCs were examined from 10/2020 - 4/2023. Age, gender, race/ethnicity, and insurance status were abstracted and used to assess if disparities in DIDO were present. ANOVA and Chi-Square were used for statistical analysis. Results: 307 patients were identified over a 3-year period across all our sites. 48.9% were female with a mean age of 69.7 (±16.2). The median NIHSS was 13 (IQR 7 - 20) and the median DIDO was 96 mins (IQR 74 - 131 mins). There was no difference in median DIDO between females 94 mins (IQR 74 - 132 mins) and males 98 mins (IQR 73 - 98 mins) (p = 0.2). When compared to White patients, there was no difference in median DIDO for Asian American/Pacific Islander (AAPI) (12.6 mins, p = 0.6), Black (-2.1 mins, p = 1.0), or Hispanic patients (7.6 mins, p = 0.7). The insurance status of our patient population was predominantly Medicare (56.4%), followed by Commercial (26.4%), Medicaid (8.1%), and Self- Pay (2.9%). The remainder were classified as Other/Missing (6.2%). When compared to the remainder of the population, we found no difference in median DIDO for patients on Medicare (-2.0 mins, p = 0.7) or Medicaid (10.8 mins, p = 0.3). Conclusions: A Southern California integrated healthcare system’s approach to thrombectomy transfers enables the removal of disparities in DIDO regardless of gender, racial background, and insurance status.
Background: IV tPA is established as an effective treatment for acute ischemic stroke. Currently it is endorsed up to 4.5 hours of last known well time by major guidelines. A randomized trial, WAKE-UP, displayed its safety and efficacy in patients who presented within 4.5 hours of waking up with their symptoms. Objective: To establish a practical tPA protocol for patients who wake up or are found with stroke symptoms at a large Comprehensive Stroke Center (CSC) and its 13 telestroke spokes (TS) based on the WAKE-UP trial. Methods: A wake up tPA protocol was created and given to all teleneurologists. Door to needle times (DTN) and reasons for no tPA were collected for 12 months post implementation and evaluated for differences between wake up (WU) and non-wake up (NW) patients. Results: 93 WU patients were identified; 23 at CSC and 70 at TS. 11 (47.8%) vs. 4 (5.7%) patients received tPA at CSC and TS, respectively. Median DTN was not significantly different for WU patients at CSC vs. TS (64 vs. 89 mins, p=0.54). Median DTN at CSC was shorter for NW vs. WU (37 vs. 64 mins; p=0.003). Similarly, median DTN at TS trended toward being shorter for NW vs. WU (44 vs. 89 mins; p=0.062). The reasons for no tPA at CSC were no mismatch found in 6 (50%), and MRI unavailability in 6 (50%); at TS were no mismatch found in 11 (16.6%), MRI unavailability in 54 (81,1%) and MRI was contraindicated in 1 (1.5%). Conclusion: Treating WU patients using a CSC Hub and TS model is feasible. DTN are longer for WU vs. NW. In the United States, MRI availability is the main barrier to WU tPA at both CSC and community hospitals. The difference between median DTN for WU between CSC and TS did not reach statistical significance, likely due to the small sample size.
Introduction: Inter-hospital transfer of stroke patients with large vessel occlusion (LVO) safely and timely from primary stroke centers to comprehensive stroke centers is needed to improve outcomes. In this study we aim at comparing use of simple 911 ambulance stat transfer with contracted ambulance pickup (CAP) used for interhospital transfer of stroke and its effect on Door In Door Out time (DIDO). Methods: Data were retrospectively abstracted for patients with an LVO from 10/2020 to 04/2024. Median DIDO times were calculated for patients who were transferred using AMR 911 vs CAP. Statistical analysis was performed using R. Results: There were total of 412 patients with acute ischemic stroke who were found to have LVO. 272 (66%) of patients were transferred using contracted ambulance pickup (CAP) while 140(34%) were transferred using 911 ambulance. There were no significant differences in baseline demographics between the CAP and 911 ambulance groups (Table1). DIDO (AMR911: median 74.50 min (IQR 57.7-96) vs CAP: 105.50 (85-133.2), p< 0.001 was significantly faster for 911 AMR cases compared to CAP cases. (graph1). Conclusions: Utilizing the widely available 911 stat ambulance process for stroke patients eligible for mechanical thrombectomy reduced DIDO time significantly, which may contribute to improved functional outcome.
Introduction: There has been much debate on whether transient global amnesia (TGA) increases the risk for subsequent cerebrovascular events. This study aims to assess whether certain comorbidities may increase risk for a future ischemic event. Methods: We retrospectively identified patients within the Southern California KP region using ICD 9 and ICD-10 codes who had a diagnosis of TGA from 2012-2017. Patients with prior history of stroke or TIA were excluded. We then evaluated differences in baseline demographics and characteristics in patients who were admitted to the hospital with an ischemic stroke within five years compared to those who were not. Results: There were 136 patients diagnosed with TGA between 2012-2017. Of 136, 10 (7.4%) were admitted with an acute stroke. There were no differences in age, gender, or race/ethnicity between those who had a stroke versus those that did not. In terms of vascular risk factors, those who had history of coronary artery disease (CAD) or prior MI were more likely to have a stroke compared to those who did not {6 (60%) vs. 26 (20.8%), p = 0.005}. There were no differences in other risk factors. Conclusion: After the diagnosis of TGA, those who have a history of CAD or prior MI were more likely to have an ischemic stroke within five years.div>
Background: The AHA/ASA 2021 Secondary Stroke Prevention Guideline recommends a joint decision by neurology and cardiology for patent foramen ovale (PFO) closure. The impact of a Brain Heart Team (BHT) consisting of interventional cardiologists and vascular neurologists to evaluate PFO closure is unclear. We analyzed whether a BHT implementation led to more guideline recommended PFO closures based on Risk of Paradoxical Embolism (RoPE) score and PASCAL categories across a 15-hospital system. Methods: Data were collected retrospectively between 1/2016 - 2/2023. Baseline demographics, risk factors, method of shunt identification, high-risk shunt features, post PFO atrial fibrillation and stroke rates, RoPE score and PASCAL categorization were abstracted. Non-BHT was defined as absence of vascular neurology involvement. Appropriate PFO closure was defined as RoPE score > 7 and/or PASCAL categories of possible/probable. Chi-squared and t-test were used. Results: Of 174 patients, 108 (62%) were identified as BHT and 66 (38%) as non-BHT. There were no differences in baseline risk factors between BHT and non-BHT besides hyperlipidemia (28.7% vs 53% p < .002) and smoking history (12% vs 31.8% p < .003). BHT patients were younger at age of diagnosis and PFO closure (44.8 yrs ±1.7 vs 56 yrs ±1.2 p=0.003 and 44.7 yrs ±1.9 vs. 56 yrs ±1.3 p=0.004 respectively). There were differences in race/ethnicity (Table 1). More BHT patients had possible/probable PASCAL vs non-BHT (101 [93.5%] vs 44 [66.7%], p <0.001). Patients in BHT had higher mean RoPe scores (7.34 ± 1.55 vs 6.06 ± 2.02 p <0.001). More patients in BHT had a RoPE score > 7 (77 [71.3%] vs 26 [39.4%] p <0.001). There were no differences in atrial fibrillation (5 [4.6%] vs 5 [7.6%] p = 0.635) or stroke after PFO closure (2 [1.9%] vs 2 [3%] p = 1). Conclusion: Implementing a multi-disciplinary approach with a Brain Heart Team leads to more guideline based PFO closures in cryptogenic strokes based on PASCAL and RoPE scores.
PURPOSE: The purpose of this study was to evaluate the Shieh Score's effectiveness in decreasing the rate of hospital-acquired pressure injuries when combined with an early warning notification system and standard order set of preventative measures. DESIGN: This was a prospective cohort study. SUBJECTS AND SETTING: This target population was nonpregnant, adult, hospitalized patients on inpatient and observation status at a tertiary hospital (Kaiser Permanente, Baldwin Park, California) during the 2020 year of the COVID-19 pandemic. METHODS: A new, risk assessment instrument, the Shieh Score, was developed in 2019 to predict hospitalized patients at high risk for pressure injuries. Data collection occurred between January 21, 2020, and December 31, 2020. When a hospital patient met the high-risk criteria for the Shieh Score, a provider-ordered pink-colored sheet of paper titled “Skin at Risk” was hung at the head of the bed and a standard order set of pressure injury preventative measures was implemented by nursing staff. RESULTS: Implementation of the program (Shieh Score, early warning system, and standard order set for preventive interventions) resulted in a 38% reduction in the annual hospital-acquired pressure injury rate from a mean incidence rate of 1.03 to 0.64 hospital-acquired pressure injuries per 1000 patient-days measured for the year 2020. CONCLUSION: The Shieh Score is a pressure injury risk assessment instrument, which effectively identifies patients at high risk for hospital-acquired pressure injuries and decreases the hospital-acquired pressure injury rate when combined with an early warning notification system and standard order set.
May 10, 2019April 9, 2019Free AccessIn-Hospital Stroke Treated with IV-tPA within a Tertiary Hospital with Neurology Residents versus Hospitals without Neurology Residents (S57.005)Manya Khrlobyan, Jiaxiao Shi, Zahra Ajani, Duy Le, Howard Rho, An Ly, Denise Gaffney, and Navdeep SanghaAuthors Info & AffiliationsApril 9, 2019 issue92 (15_supplement)https://doi.org/10.1212/WNL.92.15_supplement.S57.005 Letters to the Editor
Introduction: In-hospital strokes (IHS) often have delayed recognition time and a delay in physician assessment, playing a role in unfavorable outcomes. Telestroke (TS) participation is linked to lower odds of hospital mortality and is safe and effective in treating acute ischemic stroke. We implemented a TS program for IHS patients at primary stroke centers (PSC) and assessed tPA time metrics, complications and 90-day functional outcomes as compared to a robust in hospital stroke system of care at a comprehensive stroke center (CSC). Methods: Using a network database, data for all in-hospital code strokes were retrospectively abstracted between 2010-2020 at a CSC and 11 PSC’s. The CSC was compared to PSC’s pre and post implementation of a TS program. Data were analyzed using Wilcoxon rank-sum test, chi-square and exact tests. Results: We identified 193 patients, 77 at the CSC, 71 at pre-tele PSC’s, and 45 at post-tele PSC’s. Symptom-recognition-time (SRT) to neurology evaluation (median 15min {IQR 10-27} vs 75min {IQR 45-126, p=<0.0001) and SRT to IV t-PA (median 65min {IQR 46-91} vs 94min {IQR 73-112}, p=<0.001) were all faster at the CSC vs pre-tele PSC’s. There was no difference in rate of complications (p=0.05). When stroke mimics were excluded, CSC patients had a favorable 90-day mRS of 0-1 (24 patients, 35% vs 11 patients, 19%, p=0.04). After implementation of TS at PSC’s, there was no difference in tPA time metrics, except SRT to neurology evaluation remained faster at CSC (median 15min {IQR 10-27} vs 31min {IQR 18.5-52.5}, p=0.0002). There was no difference in rate of complications (p=0.21) and mRS at 90 days (p=0.82). Conclusions: Implementation of a TS program for IHS at PSC’s may improve tPA time metrics and 90 functional outcomes to the standards of CSC’s without increasing complication rates. Our study was limited by retrospective design and small sample size.
Background: Stroke in women of childbearing age is not only disabling but also has lifelong consequences for family planning. There are no large studies on maternal and fetal outcomes in patients with a history of stroke. Methods: We retrospectively collected data from January 2004 to December 2021 on women aged 18-50 years, who had a pregnancy following their cerebrovascular event (CVE) using ICD-10 codes to identify the eligible subjects. Demographic data including maternal age, race, gestational age, mode of delivery, associated medical conditions were collected. Results: 219 patients were included in this cohort with a mean age of 29.1±6.2 at the time of CVE, and a median time between CVE and delivery of 34 months (IQR:13-65). 17 (7.8%) had history of factor V Leiden, Protein C deficiency or lupus associated hypercoagulable state. The initial CVE was identified as acute ischemic stroke in 77 (35.2%), transient ischemic attack (TIA) in 64 (29.2%), subarachnoid hemorrhage in 46 (21%), intracerebral hemorrhage in 23 (10.5%), and cerebral venous thrombosis in 9 (4.2%). The maternal adverse events were seen in 38 (17.3%) patients: 29 (13.2%) with HELLP Syndrome/eclampsia/pre-eclampsia, and 9 (4.1%) with recurrent TIA/stroke within 1 year after pregnancy. The rate of maternal adverse events decreased 5 years after the index stroke (Figure 1A). Patients with a history of stroke were at higher risk of having preterm delivery 38 (17.4%) than the general population. 27 (12.3%) of newborn infants had 1min Apgar<7 while 6 (2.7%) had 5 min Apgar<7. The rate of neonatal poor outcomes (preterm birth or Apgar<7) decreased over time (Figure 1B). Conclusion: The rate of maternal and neonatal adverse events are high in the first 5 years after the CVE and begin to decline thereafter.
Modeling gas flow through fractures of subsurface rock is a particularly challenging problem because of the heterogeneous nature of the material. High-fidelity simulations using discrete fracture network (DFN) models are one methodology for predicting gas particle breakthrough times at the surface but are computationally demanding. We propose a Bayesian machine learning method that serves as an efficient surrogate model, or emulator, for these three-dimensional DFN simulations. Our model trains on a small quantity of simulation data with given statistical properties and, using a graph/path-based decomposition of the fracture network, rapidly predicts quantiles of the breakthrough time distribution on DFNs with those statistical properties. The approach, based on Gaussian Process Regression (GPR), outputs predictions that are within 20%–30% of high-fidelity DFN simulation results. Unlike previously proposed methods, it also provides uncertainty quantification, outputting confidence intervals that are essential given the uncertainty inherent in subsurface modeling. Our trained model runs within a fraction of a second, considerably faster than reduced-order models yielding comparable accuracy (Hyman et al., 2017; Karra et al., 2018) and multiple orders of magnitude faster than high-fidelity simulations.
