Machine learning-based scoring model for predicting mortality in ICU-admitted ischemic stroke patients with moderate to severe consciousness disorders

 

What possible use of predicting failure to recover helps survivors? WHY THE FUCK AREN'T YOU DOING RESEARCH THAT DELIVERS RECOVERY?

Machine learning-based scoring model for predicting mortality in ICU-admitted ischemic stroke patients with moderate to severe consciousness disorders

Zhou Zhou^1,2Bo Chen²Zhao-Jun Mei^1,2Wei Chen^1,2Wei Cao³En-Xi Xu²Jun Wang²Lei Ye^1*Hong-Wei Cheng^1*

• ¹Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China
• ²Department of Neurosurgery, Affiliated People’s Hospital of Jiangsu University, Jiangsu, China
• ³Department of Neurology, Affiliated People’s Hospital of Jiangsu University, Jiangsu, China

Background: Stroke is a leading cause of mortality and disability globally. Among ischemic stroke patients, those with moderate to severe consciousness disorders constitute a particularly high-risk subgroup. Accurate predictive models are essential for guiding clinical decisions in this population. This study aimed to develop and validate an automated scoring system using machine learning algorithms for predicting short-term (3- and 7-day) and relatively long-term (30- and 90-day) mortality in this population.

Methods: This retrospective observational study utilized data from the MIMIC-IV database, including 648 ischemic stroke patients with Glasgow Coma Scale (GCS) scores ≤12, admitted to the ICU between 2008 and 2019. Patients with GCS scores indicating speech dysfunction but clear consciousness were excluded. A total of 47 candidate variables were evaluated, and the top six predictors for each mortality model were identified using the AutoScore framework. Model performance was assessed using the area under the curve (AUC) from receiver operating characteristic (ROC) analyses.

Results: The median age of the cohort was 76.8 years (IQR, 64.97–86.34), with mortality rates of 8.02% at 3 days, 18.67% at 7 days, 33.49% at 30 days, and 38.89% at 90 days. The AUCs for the test cohort’s 3-, 7-, 30-, and 90-day mortality prediction models were 0.698, 0.678, 0.724, and 0.730, respectively.

Conclusion: We developed and validated a novel machine learning-based scoring tool that effectively predicts both short-term and relatively long-term mortality in ischemic stroke patients with moderate to severe consciousness disorders. This tool has the potential to enhance clinical decision-making and resource allocation for these patients in the ICU.(So, you can quickly triage them to the death intervention?)

Introduction

Stroke, including both ischemic and hemorrhagic types, remains one of the leading causes of mortality and long-term disability worldwide (1). Stroke mortality is projected to increase by 50% from 2020 to 2050 (2), significantly adding to the disease burden. The burden is particularly severe among patients who experience both severe ischemic stroke and consciousness disorders (3, 4), involving prolonged hospital stays, intensive rehabilitation efforts, and significant caregiver support (5). Consciousness disorders encompass a range of conditions, including coma, vegetative state, and minimally conscious state (6, 7), and are associated with significantly worse prognoses compared to ischemic stroke patients without consciousness disorders (8).

In this study, we focus on a distinct and challenging subgroup: ischemic stroke patients with moderate to severe consciousness disorders (GCS ≤ 12) at admission, excluding those with a GCS score of 4-1-6 or 4-2-6, as they are classified as having speech dysfunction with clear consciousness (9, 10). All these severe ischemic stroke patients were admitted to the ICU (11).

Patients in this category are typically incapable of independently deciding on interventions such as mechanical ventilation, artificial nutrition, surgical decompression, or even the withdrawal of life-sustaining treatment. In many severe stroke cases, however, physicians and patient surrogates must make decisions under conditions of prognostic uncertainty and ambiguous definitions of acceptable outcomes (12). Accurate prediction of outcomes in these patients is essential for guiding clinical decisions, managing resources, and providing appropriate counseling for patients’ families. Prognostic models that accurately predict outcomes for patients with severe stroke are currently insufficient. Traditional assessment tools, such as the GCS and the Modified Rankin Scale (mRS), often overlook the complexities inherent in these patients’ conditions. Moreover, these models tend to rely on static clinical evaluations and do not take advantage of the massive data available from modern healthcare databases. Recent advancements in machine learning (ML) have shown potential in developing more precise and individualized prognostic models (13, 14). ML techniques can analyze large datasets to identify patterns often missed by traditional methods, enhancing prognostic accuracy for patients (15, 16). Despite its potential, research applying machine learning to predict outcomes in severe ischemic stroke patients remains limited. This gap underscores the need for innovative approaches to improve prognostic accuracy in this high-risk population.

Therefore, the primary objective of this study is to develop an automated scoring model using machine learning techniques to estimate mortality for severe ischemic stroke patients with moderate to severe consciousness disorders. By enhancing the interpretability and accuracy of the predictive model, we aim to facilitate its integration into clinical workflows and decision-making processes.

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Impact of prehospital stroke triage implementation on patients with intracerebral hemorrhage

My conclusion is that this was bad research, you didn't measure recovery at all. I think survivors would like to know how good you were at getting survivors recovered, this is a failing grade and you should be fired.

“What's measured, improves.” So said management legend and author Peter F. Drucker 

The latest here:

Impact of prehospital stroke triage implementation on patients with intracerebral hemorrhage

Tove Almqvist https://orcid.org/0000-0002-5477-391X tove.almqvist@ki.se, Anna Falk Delgado, […], and Michael V. Mazya+4View all authors and affiliations

All Articles.

https://doi.org/10.1177/17562864231168278

• 
  

• • Abstract
  • Introduction
  • Materials and methods
  • Results
  • Discussion
  • Conclusion
  • Acknowledgments
  • ORCID iD
  • Footnotes
  • References
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Abstract

Background:

Little is known about how prehospital triage using large vessel occlusion (LVO) stroke prediction scales affects patients with intracerebral hemorrhage (ICH).

Objectives:

We aimed to investigate whether the Stockholm Stroke Triage System (SSTS) implemented in 2017 has affected timing and outcomes of acute ICH neurosurgery, and to assess system triage accuracy for ICH with a neurosurgical indication or LVO thrombectomy.

Design:

Observational cohort study.

Methods:

In the Stockholm Region, we compared surgical timing, functional outcome, and death at 3 months in patients transported by code-stroke ground ambulance who had ICH neurosurgery, 2 years before versus 2 years after SSTS implementation. We also calculated triage precision metrics for treatment with either ICH neurosurgery or thrombectomy.

Results:

A total of 36 patients undergoing ICH neurosurgery were included before SSTS implementation and 30 after. No significant difference was found in timing of neurosurgery [median 7.5 (4.9–20.7) versus 9.1 (6.1–12.5) h after onset], distribution of functional outcomes (median 4 versus 4), and death at 3 months [3/29 (9%) versus 5/35 (17%)] before versus after implementation, respectively. The SSTS routed a larger proportion of patients subsequently undergoing ICH neurosurgery directly to the comprehensive stroke center: 13/36 (36%) before versus 18/30 (60%) after implementation. Overall system triage accuracy for ICH neurosurgery or thrombectomy was high at 90%, with 92% specificity and 65% sensitivity.

Conclusion:

The SSTS, initially designed for prehospital LVO stroke triage, routed more patients with neurosurgical indication for ICH directly to the comprehensive stroke center. This did not significantly affect surgical timing or outcomes.

Introduction

Recently updated intracerebral hemorrhage (ICH) guidelines from the American Heart Association/American Stroke Association recommend prehospital tools to recognize stroke and grade its severity.¹ Meanwhile, studies of prehospital severity-based algorithms on ICH are lacking. This is highlighted in the guidelines, which emphasize the need for research on the impact of regionalized large vessel occlusion (LVO) stroke pathways on ICH patients.¹ Comprehensive stroke centers (CSCs) receive a larger proportion of ICH patients after implementation of prehospital LVO protocols, owing to higher symptom severity in ICH compared with ischemic stroke and stroke mimics.^1–3 Avoiding interhospital transfers in ICH has been reported to reduce the risk of deterioration during transport and decrease costs.^4–6 It is yet unknown whether symptom-based prehospital triage of patients to a CSC leads to more rapid initiation of ICH treatments only available at CSCs, specifically acute neurosurgery.

In 2017, the Stockholm Region implemented the Stockholm Stroke Triage System (SSTS), aiming to identify patients with LVO stroke and transport them directly to the CSC, bypassing more proximal primary stroke centers (PSCs). The SSTS reduced time from onset to endovascular thrombectomy (EVT) by 69 min without delaying intravenous thrombolysis (IVT), and significantly improved outcomes in EVT.^7,8 Of nearly 3000 patients annually taken to hospital by code-stroke ambulance in the Stockholm Region, 8% have previously been shown to suffer from ICH, 4% a subarachnoid or subdural hemorrhage, 44% an ischemic stroke or transient ischemic attack, and 44% a stroke mimic.⁹

First, we aimed to evaluate whether timing and outcome of acute ICH neurosurgery changed after SSTS implementation. Second, we aimed to expand previous results on SSTS accuracy for identification of patients needing EVT, by investigating the system’s accuracy for patients requiring either EVT or acute ICH neurosurgery, and assess differences between triage-positive and triage-negative ICH patients.

 

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Statewide Emergency Medical Services Protocols for Suspected Stroke and Large Vessel Occlusion

You should easily find out if your hospital has these protocols and what they are. Because YOU ARE RESPONSIBLE for having a stroke that fits these protocols so you can be treated properly and get 100% recovered. YOUR RESPONSIBILITY! Not your doctor or hospital to have exact protocols for any type of stroke coming in. 

Statewide Emergency Medical Services Protocols for Suspected Stroke and Large Vessel Occlusion

 

Carlin C. Chuck, BS¹; Thomas J. Martin, BA, NRP¹; Roshini Kalagara, BA²; et al Tracy E. Madsen, MD, PhD³; Karen L. Furie, MD⁴; Shadi Yaghi, MD⁴; Michael E. Reznik, MD⁴

Author Affiliations

JAMA Neurol. Published online September 20, 2021. doi:10.1001/jamaneurol.2021.3227

Prehospital triage is critically important in the care of patients with stroke caused by large vessel occlusion (LVO), both because of the time-sensitive nature of acute interventions and the need to appropriately use available resources.¹ However, it is unclear if standardized LVO-specific triage protocols exist among emergency medical services (EMS) nationwide.

We performed a cross-sectional analysis of publicly available statewide EMS protocols in December 2020 using online searches cross-referenced to previous literature² to characterize prehospital LVO transport algorithms across the US. We included states with mandated or recommended protocols as well as those with relevant state department of health–issued guidelines. Other states were excluded, even if they had protocols on a regional level.

Central Triage of Acute Stroke Patients Across a Distributive Stroke Network Is Safe and Reduces Transfer Denials

 'Safely',  not even measuring 100% RECOVERY. This is the reason we need survivors in charge.

Central Triage of Acute Stroke Patients Across a Distributive Stroke Network Is Safe and Reduces Transfer Denials

Derek Holder

,

Kevin Leeseberg

,

James A. Giles

,

Jin-Moo Lee

,

Sheyda Namazie

,

Andria L. Ford

Originally published22 Jun 2021https://doi.org/10.1161/STROKEAHA.120.033018Stroke. 2021;52:2671–2675

Abstract

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Background and Purpose:

Mechanical thrombectomy has dramatically increased patient volumes transferred to comprehensive stroke centers (CSCs), resulting in transfer denials for patients who need higher level of care only available at a CSC. We hypothesized that a distributive stroke network (DSN), triaging low severity acute stroke patients to a primary stroke center (PSC) upon initial telestroke consultation, would safely reduce transfer denials, thereby providing additional volume to treat severe strokes at a CSC.

Methods:

In 2017, a DSN was implemented, in which mild stroke patients were centrally triaged, via telestroke consultation, to a PSC based upon a simple clinical severity algorithm, while higher acuity/severity strokes were triaged to the CSC. In an observational cohort study, data on acute ischemic stroke patients presenting to regional community hospitals were collected pre- versus post-DSN implementation. Safety outcomes and rate of CSC transfer denials were compared pre-DSN versus post-DSN.

Results:

The pre-DSN cohort (n=150), triaged to the CSC, had a similar rate of symptomatic intracerebral hemorrhage and discharge location compared with the post-DSN cohort (n=150), triaged to the PSC. Time to stroke unit admission was faster post-DSN (2 hours 40 minutes) versus pre-DSN (3 hours 29 minutes; P<0.001). Transfer denials were reduced post-DSN (3.8%) versus pre-DSN (1.8%; P=0.02), despite an increase in telestroke consultation volume over the same period (median, 3 calls per day pre-DSN versus 5 calls per day post-DSN; P=0.001). No patients who were triaged to the PSC required subsequent transfer to the CSC.

Conclusions:

A DSN, triaging mild ischemic stroke patients from community hospitals to a PSC, safely reduced transfer denials to the CSC, allowing greater capacity at the CSC to treat higher acuity stroke patients.

Footnotes

*D. Holder, K. Leeseberg, and J.A. Giles contributed equally as cofirst authors.

†S. Namazie and A.L. Ford contributed equally as cosenior authors.

The Data Supplement is available with this article at https://www.ahajournals.org/doi/suppl/10.1161/STROKEAHA.120.033018.

For Sources of Funding and Disclosures, see page 2674.

Correspondence to: Andria L. Ford, MD, MSCI, Department of Neurology, Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO 63110, Email forda@wustl.edu

Sheyda Namazie, MD, MBA, BJC Healthcare, Center for Clinical Excellence, 8300 Eager Rd, Suite 400, St. Louis, MO 63144, Email sheyda.namazie-kummer@bjc.org

 

Utility of Severity-Based Prehospital Triage for Endovascular Thrombectomy

For all the backslapping this still did not measure 100% recovery. Please talk to survivors sometime, your ideas on what survivors want and the research you do does not help us get to 100% recovery. 

“What's measured, improves.” So said management legend and author Peter F. Drucker 

The latest here:

Utility of Severity-Based Prehospital Triage for Endovascular Thrombectomy

ACT-FAST Validation Study

Henry Zhao

,

Karen Smith

,

Stephen Bernard

,

Michael Stephenson

,

Henry Ma

,

Ronil V. Chandra

,

Thanh Phan

,

Christopher F. Bladin

,

Leonid Churilov

,

Douglas Crompton

, … See all authors

Originally published22 Dec 2020https://doi.org/10.1161/STROKEAHA.120.031467Stroke. 2021;52:70–79

Abstract

Background and Purpose:

Severity-based assessment tools may assist in prehospital triage of patients to comprehensive stroke centers (CSCs) for endovascular thrombectomy (EVT), but criticisms regarding diagnostic inaccuracy have not been adequately addressed. This study aimed to quantify the benefits and disadvantages of severity-based triage in a large real-world paramedic validation of the Ambulance Clinical Triage for Acute Stroke Treatment (ACT-FAST) algorithm.

Methods:

Ambulance Victoria paramedics assessed the prehospital ACT-FAST algorithm in patients with suspected stroke from November 2017 to July 2019 following an 8-minute training video. All patients were transported to the nearest stroke center as per current guidelines. ACT-FAST diagnostic accuracy was compared with hospital imaging for the presence of large vessel occlusion (LVO) and need for CSC-level care (LVO, intracranial hemorrhage, and tumor). Patient-level time saving to EVT was modeled using a validated Google Maps algorithm. Disadvantages of CSC bypass examined potential thrombolysis delays in non-LVO infarcts, proportion of patients with false-negative EVT, and CSC overburdening.

Results:

Of 517 prehospital assessments, 168/517 (32.5%) were ACT-FAST positive and 132/517 (25.5%) had LVO. ACT-FAST sensitivity and specificity for LVO was 75.8% and 81.8%, respectively. Positive predictive value was 58.8% for LVO and 80.0% when intracranial hemorrhage and tumor (CSC-level care) were included. Within the metropolitan region, 29/55 (52.7%) of ACT-FAST-positive patients requiring EVT underwent a secondary interhospital transfer. Prehospital bypass with avoidance of secondary transfers was modeled to save 52 minutes (95% CI, 40.0–61.5) to EVT commencement. ACT-FAST was false-positive in 8 patients receiving thrombolysis (8.1% of 99 non-LVO infarcts) and false-negative in 4 patients with EVT requiring secondary transfer (5.4% of 74 EVT cases). CSC bypass was estimated to over-triage 1.1 patients-per-CSC-per-week in our region.

Conclusions:

The overall benefits of an ACT-FAST algorithm bypass strategy in expediting EVT and avoiding secondary transfers are estimated to substantially outweigh the disadvantages of potentially delayed thrombolysis and over-triage, with only a small proportion of EVT patients missed.

 

Pre-hospital Triage of Acute Ischemic Stroke Patients—Importance of Considering More Than Two Transport Options

Once again you have to have the proper stroke with the correct presentations to be treated properly.   This leaves vast numbers of strokes left behind. NOT ACCEPTABLE. Do you think you can accomplish that? No consequences to the doctors for not having prepared for all eventualities. But severe consequences to the stroke survivors, if they survive.

Pre-hospital Triage of Acute Ischemic Stroke Patients—Importance of Considering More Than Two Transport Options

Ludwig Schlemm^1,2,3*, Eckhard Schlemm^4,5, Christian H. Nolte^1,2,3,6,7 and Matthias Endres^1,2,3,6,7

• ¹Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH), Berlin, Germany
• ²Center for Stroke Research Berlin (CSB), Charité – Universitätsmedizin, Berlin, Germany
• ³Berlin Institute of Health (BIH), Berlin, Germany
• ⁴Medizinische Fakultät, Universität Hamburg, Hamburg, Germany
• ⁵Klinik und Poliklinik für Neurologie, Kopf- und Neurozentrum, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
• ⁶DZHK (German Center for Cardiovascular Research), Partner Site, Berlin, Germany
• ⁷DZNE (German Center for Neurodegenerative Diseases), Partner Site, Berlin, Germany

Background: Patients with acute ischemic stroke (AIS) and large vessel occlusion benefit from rapid access to mechanical thrombectomy in addition to intravenous thrombolysis. Prehospital triage algorithms to determine the optimal transport destination for AIS patients with unknown vessel status have so far only considered two alternatives: the nearest comprehensive (CSC) and the nearest primary stroke center (PSC).

Objective: This study explores the importance of considering a larger number of PSCs during pre-hospital triage of AIS patients.

Methods: Analysis was performed in random two-dimensional abstract geographic stroke care infrastructure environments and two models based on real-world geographic scenarios. Transport times to CSCs and PSCs were calculated to define sub-regions with specific triage properties. Possible transport destinations included the nearest CSC, the nearest PSC, and any of the remaining PSCs that are not closest to the scene, but transport to which would imply a shorter total time-to-CSC-via-PSC.

Results: In abstract geographic environments, the median relative size of the sub-region where a triage decision is required ranged from 34 to 92%. The median relative size of the sub-region where more than two triage options need to be considered ranged from 0 to 56%. The achievable reduction in time-to-thrombectomy (“benefit”) exceeded the increase in time-to-thrombolysis (“harm”) by a factor of 2 in 30.5–37.0% of the sub-region where more than two triage options need to be considered. Results were confirmed in geographic environments based on real-world urban and rural stroke care infrastructures.

Conclusion: Pre-hospital triage algorithms for AIS patients that only take into account the nearest CSC and the nearest PSC as transport destinations may be unable to identify the optimal transport destination for a significant proportion of patients.

Introduction

Background

International guidelines recommend early administration of intravenous thrombolysis for eligible patients with acute ischemic stroke (AIS); in addition, patients with proximal large vessel occlusion (LVO) should receive mechanical thrombectomy (MT) as quickly as possible (1). As the clinical benefit of both thrombolysis (2–4) and MT (5–7) diminishes over time, research efforts in recent years have focused on improving clinical outcome by reducing pre-hospital (8–10) and intra-hospital delays (11, 12). With regard to pre-hospital delays, directly transporting AIS patients to an MT-capable comprehensive stroke center (CSC) instead of a nearer non-MT-capable primary stroke center (PSC) has been suggested as one strategy to reduce time to MT for patients with LVO (13). Given that information about the vessel status of patients is typically not available to emergency medical personnel in the field, patients that are likely to benefit from direct transportation to a CSC need to be selected based on clinical and demographic variables. Several clinical pre-hospital stroke severity scales with similar accuracies to estimate the likelihood of LVO exist (14); however, the optimal instruments as well as the most appropriate cutoff values to inform pre-hospital triage decisions and to select patients for direct transportation to a CSC are not currently known (1). Previous studies that explored the impact of triage algorithms to determine the most adequate transport destination for AIS patients only allowed for a decision between two alternatives, namely transport to the nearest CSC, bypassing all PSCs; and transport to the nearest PSC (15–17). However, clinical experience as well as fundamental geographic observations suggest that oftentimes a PSC that is not nearest to the scene, but from which a patient could be transferred quickly to a CSC if necessary, might be a better primary transport destination option than the nearest PSC.

Decision Analysis Model for Prehospital Triage of Patients With Acute Stroke

Based on this, research is needed to get every stroke survivor 100% recovered.  The endpoint of every triage scenario is 100% recovery. I don't care how fucking hard that is going to be. Leaders step up to these challenges. Are you a leader or a CHICKENSHIT?

Decision Analysis Model for Prehospital Triage of Patients With Acute Stroke

Yaqian Xu

,

Neal S. Parikh

,

Boshen Jiao

,

Joshua Z. Willey

,

Amelia K. Boehme

,

Mitchell S.V. Elkind

Originally published14 Mar 2019https://doi.org/10.1161/STROKEAHA.118.023272Stroke. 2019;0

Abstract

Background and Purpose—

We used a decision analysis approach to analyze triage strategies for patients with acute stroke symptoms while accounting for prehospital large vessel occlusion (LVO) screening methods and key time metrics.

Methods—

Our decision analysis compared anticipated functional outcomes for patients within the IV-tPA (intravenous tissue-type plasminogen activator) treatment window in the mothership and drip-and-ship frameworks. Key branches of the model included IV-tPA eligibility, presence of an LVO, and endovascular therapy eligibility. Our decision analysis evaluated 2 prehospital LVO screening approaches: (1) no formal screening and (2) the use of clinical LVO screening scales. An excellent outcome was defined as modified Rankin Scale scores 0–1. Probabilities and workflow times were guideline-based or imputed from published studies. In sensitivity analyses, we individually and jointly varied transport time to the nearest primary stroke center, additional time required to transport directly to a comprehensive stroke center, and LVO screening scale predictive probabilities. We evaluated 2 separate scenarios: one in which ideal time metrics were achieved and one under current real-world metrics.

Results—

In the ideal metrics scenario, the drip-and-ship strategy was almost always favored in the absence of formal LVO screening. For patients screened positive for an LVO, mothership was favored if the additional transport time to the comprehensive stroke center was <3 to 23 minutes. Under real-world conditions, in which primary stroke center workflow is slower than ideal, the mothership strategy was favored in more scenarios, regardless of formal LVO screening. For example, mothership was favored with an additional transport time to the comprehensive stroke center of <32 to 99 minutes for patients screened positive for an LVO and <28 to 39 minutes in the absence of screening.

Conclusions—

Joint consideration of LVO probability, screening, workflow times, and transport times may improve prehospital stroke triage. Drip-and-ship was more favorable when more ideal primary stroke center workflow times were modeled.

Footnotes

Presented in part at the International Stroke Conference, Los Angeles, CA, January 24–26, 2018.
The online-only Data Supplement is available with this article at https://www.ahajournals.org/doi/suppl/10.1161/STROKEAHA.118.023272.

Correspondence to Mitchell S. V. Elkind, MD, MS, Division of Neurology Clinical Outcomes Research and Population Sciences (NeuroCORPS), Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, 710 W 168th St, New York, NY 10032. Email mse13@columbia.edu

Time, Flow, and Location Key to Lytic Sufficiency for Stroke

By using the word triage this means that we still don't have protocols on how stroke should be treated in the first hours. You better hope like hell you have a stroke that matches the clinical trials so your doctors know exactly what to do.  Otherwise you get to be a guinea pig in 'winging it'.  We still have no clue how fast tPA needs to be delivered to get full recovery from it.

Time, Flow, and Location Key to Lytic Sufficiency for Stroke

Recanalization factors pinned down in prospective analysis

• by Nicole Lou, Reporter, MedPage Today/CRTonline.org September 11, 2018

How responsive an intracranial thrombus is to alteplase (Activase) depends on certain factors that could help inform how patients with acute ischemic stroke should be triaged, according to a global prospective cohort study.
IV alteplase was associated with higher odds of successful recanalization, at 30.4% versus 13.3% for non-recipients (difference 17.1%, 95% CI 10.2%-25.8%) among the 575 stroke patients with intracranial occlusions observed on CT angiography in the INTERRSeCT study, reported online in JAMA by Andrew Demchuk, MD, of University of Calgary in Alberta, and collaborators.
Among those getting alteplase, the factors associated with recanalization of the arterial occlusion were:

• Time from treatment start to recanalization assessment: OR 1.28 for every 30-minute interval (95% CI 1.18-1.38)
• More distal thrombus location: OR 5.61 (95% CI 2.38-13.26)
• Greater residual flow: OR 7.03 (95% CI 3.32-14.87)

In contrast, the sole predictor of recanalization without IV alteplase was male sex.
"Patients with factors associated with thrombus responsiveness to alteplase (e.g., thrombus permeability) may not require transfer because they will recanalize with IV alteplase," Demchuk's group suggested.
The stroke patients in the study -- from 12 centers across North America, Europe, and East Asia -- had a median 114 minutes elapse from the last time they were known to be well to baseline CT angiography, 19 minutes between baseline CT angiography to the start of alteplase administration, and then another 132.5 minutes to recanalization assessment.
"The results of this study suggest that recanalization with IV alteplase is a continuous process over time," the authors said. "With a plasma half-life of 6 to 7 minutes, alteplase is not likely to be biologically active at 6 hours following administration. However, it is possible that the early thrombus debulking effects of alteplase translate to less overall thrombus, allowing endogenous tissue plasminogen activator [tPA] to complete the remaining lysis required."
The INTERRSeCT findings may be relevant in deciding where to send stroke patients who are potential candidates for endovascular therapy, the investigators suggested.
"When transport times are several hours longer to a comprehensive stroke center compared with a primary stroke center, evaluation at a primary stroke center for initial treatment with IV alteplase is likely the better option based on reasonable recanalization rates with alteplase over several hours," they said.
This is the most important message of this study, according to Brian Silver, MD, of UMass Memorial Health Care in Worcester, Massachusetts.
"What the actual distance or time duration should be is not clear at this time, but anything over 60 minutes probably does not warrant diversion to a comprehensive stroke center because of potential negative implications for the patient," he said in an interview.
On the other hand, Tudor Jovin, MD, of the University of Pittsburgh Medical Center, wasn't completely on board.
"This is another piece in the puzzle but it doesn't solve the puzzle [of how to triage patients]," he told MedPage Today. "By the time patients get to CT angiography to determine the level and characteristics of the occlusion, the patient is already at the primary stroke center."
The "holy grail" would be to have this information in the field, before hospital arrival, Jovin said. This may be possible with mobile stroke units (which have yet to prove their cost-effectiveness, he noted) or the use of transcranial ultrasound in ambulances.
Another issue is the need for more refined predictive capabilities: "Even if you identify some patients who have, say, a 70% chance of opening up with IV tPA, is that enough to send them to a non-thrombectomy place? None of these methods detect the chance of recanalization with tPA to a level where we are actually comfortable taking a patient to a non-thrombectomy center," cautioned Jovin.
Nevertheless, he called Demchuk's study "very important," because it confirms with prospective data what other retrospective studies had previously suggested about recanalization rates. "We can now put more reliable numbers when we plan trials and things like that -- the recanalization rate of tPA in someone with internal carotid artery occlusion [for example] ... We now have better numbers to quote."
One caveat to the study, Demchuk and colleagues acknowledged, was that patients were enrolled in 2010-2016, during a period of significant evolution in stroke care. Additionally, the sample was relatively small and precluded subset analyses by occlusion site.
Study participants were a median 72 years old and 51.5% men. Treatments provided were alteplase only (47.8%), alteplase plus endovascular thrombectomy (33.9%), thrombectomy alone (8.3%), and conservative treatment (9.9%).

Demchuk reported receiving honoraria for CME events from Medtronic.
Jovin and Silver disclosed no conflicts of interest.

• Primary Source

  JAMA

  Source Reference: Menon BK, et al “Association of clinical, imaging, and thrombus characteristics with recanalization of visible intracranial occlusion in patients with acute ischemic stroke” JAMA 2018; DOI: 10.1001/jama.2018.12498.