Early Neurological Change After Ischemic Stroke Is Associated With 90-Day Outcome
Open accessAbstract
Background and Purpose: Large-scale observational studies of acute ischemic stroke (AIS) promise to reveal mechanisms underlying cerebral ischemia. However, meaningful quantitative phenotypes attainable in large patient populations are needed. We characterize a dynamic metric of AIS instability, defined by change in National Institutes of Health Stroke Scale score (NIHSS) from baseline to 24 hours baseline to 24 hours (NIHSS baseline – NIHSS 24hours = ΔNIHSS 6-24h ), to examine its relevance to AIS mechanisms and long-term outcomes. Methods: Patients with NIHSS prospectively recorded within 6 hours after onset and then 24 hours later were enrolled in the GENISIS study (Genetics of Early Neurological Instability After Ischemic Stroke). Stepwise linear regression determined variables that independently influenced ΔNIHSS 6 –24h . In a subcohort of tPA (alteplase)-treated patients with large vessel occlusion, the influence of early sustained recanalization and hemorrhagic transformation on ΔNIHSS 6–24h was examined. Finally, the association of ΔNIHSS 6 –24h with 90-day favorable outcomes (modified Rankin Scale score 0–2) was assessed. Independent analysis was performed using data from the 2 NINDS-tPA stroke trials (National Institute of Neurological Disorders and Stroke rt-PA). Results: For 2555 patients with AIS, median baseline NIHSS was 9 (interquartile range, 4–16), and median ΔNIHSS 6 –24h was 2 (interquartile range, 0–5). In a multivariable model, baseline NIHSS, tPA-treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS 6 –24h (R 2 =0.15). In the large vessel occlusion subcohort, early sustained recanalization and hemorrhagic transformation increased the explained variance (R 2 =0.27), but much of the variance remained unexplained. ΔNIHSS 6 –24h had a significant and independent association with 90-day favorable outcome. For the subjects in the 2 NINDS-tPA trials, ΔNIHSS 3 –24h was similarly associated with 90-day outcomes. Conclusions: The dynamic phenotype, ΔNIHSS 6–24h , captures both explained and unexplained mechanisms involved in AIS and is significantly and independently associated with long-term outcomes. Thus, ΔNIHSS 6 –24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.
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Claims the paper makes
9 of 20 cited sources checked · 7 supported · 1 flagged · accuracy not yet measured
- Premisecitation
Clinically meaningful fluctuations, often defined as changes of at least 4 points, occur within the first 24 hours in more than half of acute ischemic stroke patients.
“Clinically meaningful fluctuations, frequently defined as changes of ≥ 4 points, within the first 24 hours occur in more than half of acute ischemic stroke (AIS) patients.3–5”
Quote in the paperSubstantial claim3 of 3 sources checked- cites [3] source
- cites [4] source
The Introduction discusses NIHSS changes in the first 24 hours, but defines major neurological improvement as a score of 0–1 or an improvement of at least 8 points—not a 4-point fluctuation. In Results > Baseline Characteristics (page unavailable), the overall cohort’s 24-hour NIHSS change has a median of 1 point and an interquartile range of 0–3. Those figures run contrary to the claim that changes of at least 4 points occur in more than half of patients. (LLM, conf=0.85)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured - cites [5] source
The Methods define meaningful deterioration or recovery as an NIHSS change of at least 4 points. The Results report 31 patients with recovery and 8 with deterioration among 75 studied—just over half—but the Methods specify follow-up at days 3–5, not within the first 24 hours. The paper therefore does not support the claim's timing. (LLM, conf=0.90)
Experimental — accuracy not yet measured
- Premisecitation
NIHSS measured 24 hours after stroke onset is a strong predictor of functional outcome at 90 days.
“NIH stroke scale (NIHSS) measured 24 hours after stroke onset is a strong predictor of functional outcome at 90 days.”
- Also stated in: § INTRODUCTION · boosted
“NIH stroke scale (NIHSS) measured 24 hours after stroke onset is a strong predictor of functional outcome at 90 days.1, 2”
Quote in the paperSubstantial claim1 of 2 sources checked - Also stated in: § INTRODUCTION · boosted
- Findingown data
In the GENISIS cohort, baseline NIHSS had the largest contribution of any variable to the multivariable model of ΔNIHSS6-24h.
“Of these, baseline NIHSS had the highest contribution of any variable to the model, likely due to greater variability of ΔNIHSS6–24h at higher baseline NIHSS.”
Quote in the paperNot a substantial claim - Findingown data
In the GENISIS cohort, age, site, diabetes, and African descent contributed to the final multivariable model of 90-day favorable outcome.
“Age, site, diabetes, and race (African descent) contributed to the final model.”
Quote in the paperNot a substantial claim - Findingown data
In the tPA-treated large vessel occlusion subcohort, subjects with early sustained recanalization had a higher likelihood of better outcome across groups, with an odds ratio of 6.8 (95% CI 4.0-11.5).
“Overall, subjects with ESR had a high likelihood of a better outcome (OR 6.8; 4.0, 11.5) across the groups.”
Quote in the paperSubstantial claim
- Findingown data
In the GENISIS cohort, the median change in NIHSS from baseline to 24 hours (ΔNIHSS6-24h) was 2, with an interquartile range of 0 to 5.
“median ΔNIHSS6–24h was 2 (IQR 0–5)”
Quote in the paperNot a substantial claim - Findingown data
In the tPA-treated large vessel occlusion subcohort, the Extreme Improvement group versus the other combined groups had an odds ratio of 3.8 (95% CI 1.3-11.4) for early sustained recanalization.
“The Extreme Improvement (Group 6) versus the other combined groups showed an OR of 3.8 (1.3, 11.4) for ESR.”
Quote in the paperSubstantial claim - Findingown data
In the GENISIS cohort, ΔNIHSS6-24h had a significant and independent association with 90-day favorable outcome (mRS 0-2), with an odds ratio of 1.24 (95% CI 1.21-1.27) and a partial correlation squared of 0.085.
“Stepwise logistic regression demonstrated that baseline NIHSS and ΔNIHSS6–24h had strong independent influences on outcome (Table 3). Baseline NIHSS had a partial correlation squared (PR2) of 0.140 and ΔNIHSS6–24h had a PR2 of 0.085 (with respective ORs of 0.77 (95% confidence intervals (CI) 0.75, 0.79) and 1.24 (1.21, 1.27)).”
Quote in the paperSubstantial claim - Findingown data
In the GENISIS cohort, stroke etiology explained a larger proportion of the variance in log-transformed baseline NIHSS than all other variables combined, with a partial eta-squared of 0.0752 versus 0.0499.
“This analysis (please see https://www.ahajournals.org/journal/str, Supplemental Table III) revealed that stroke etiology explained a larger proportion of the log-transformed baseline NIHSS variance than all other variables combined (partial Eta-square of 0.0752 versus 0.0499).”
Quote in the paperNot a substantial claim - Findingown data
In the GENISIS cohort, mean NIHSS differed significantly between TOAST designations except between large artery atherosclerosis and cardioembolic stroke.
“Except between LAA and CE, mean NIHSS was significantly different when compared between TOAST designations.”
Quote in the paperNot a substantial claim - Findingown data
In the GENISIS cohort, location of enrollment, age, sex, atrial fibrillation, and baseline glucose independently influenced baseline NIHSS.
“Other variables that independently influenced baseline NIHSS included location of enrollment, age, sex, atrial fibrillation and baseline glucose.”
Quote in the paperNot a substantial claim - Findingown data
In the GENISIS cohort, baseline NIHSS had a significant and independent association with 90-day favorable outcome, with an odds ratio of 0.77 (95% CI 0.75-0.79) and a partial correlation squared of 0.140.
“Stepwise logistic regression demonstrated that baseline NIHSS and ΔNIHSS6–24h had strong independent influences on outcome (Table 3). Baseline NIHSS had a partial correlation squared (PR2) of 0.140 and ΔNIHSS6–24h had a PR2 of 0.085 (with respective ORs of 0.77 (95% confidence intervals (CI) 0.75, 0.79) and 1.24 (1.21, 1.27)).”
Quote in the paperSubstantial claim - Findingown data
In the GENISIS cohort, baseline NIHSS, tPA treatment, age, and glucose were highly significant predictors of ΔNIHSS6-24h.
“Instead, baseline NIHSS, tPA treatment, age and glucose were highly significant predictors of ΔNIHSS6–24h.”
Quote in the paperNot a substantial claim - Findingown data
In the GENISIS cohort, mean ΔNIHSS6-24h did not differ across TOAST etiologies except for a lower value in small vessel disease.
“Mean ΔNIHSS6–24h did not differ across TOAST etiologies, except for the lower ΔNIHSS6–24h in SVD (Figure 2).”
Quote in the paperNot a substantial claim - Findingown data
ΔNIHSS6-24h has a statistically significant association with 90-day outcome that is independent of baseline NIHSS and presumed stroke etiology by TOAST.
“This neurological change, captured by ΔNIHSS6–24h, has a statistically significant association with 90-day outcome; an association which is independent not only of baseline NIHSS, but also of the presumed stroke etiology (TOAST).”
Quote in the paperSubstantial claim - Findingcitation
In the NINDS tPA trials, the influence of ΔNIHSS3-24h on 90-day mRS was larger than the influence observed in the GENISIS study.
“The influence of ΔNIHSS3–24h on 90-day mRS was larger than that observed in our study.”
Quote in the paperNot a substantial claim - Findingown data
In the two NINDS tPA trials, the significant and independent contribution of ΔNIHSS3-24h and baseline NIHSS to long-term outcome was consistent when the tPA and placebo cohorts were analyzed separately.
“This significant and independent contribution of both ΔNIHSS3–24h and baseline NIHSS to long term outcome was consistent when evaluating the tPA and placebo cohorts separately as well (Table 4).”
Quote in the paperSubstantial claim - Findingown data
In the tPA-treated large vessel occlusion subcohort, the Extreme Worsening group versus the other combined groups had an odds ratio of 13.17 (95% CI 2.1-81.5) for parenchymal hematoma type 2.
“Extreme Worsening (Group 1) versus the other combined groups demonstrated an OR of 13.17 (2.1, 81.5) for PH2.”
Quote in the paperSubstantial claim - Findingown data
Neurological deficit, as measured by NIHSS, changes dynamically during the first 24 hours after acute ischemic stroke onset.
“We demonstrate that neurological deficit, as measured by NIHSS, is dynamic in the first 24 hours after ischemic stroke onset.”
Quote in the paperSubstantial claim - Findingown data
In the two NINDS tPA trials (n=606), ΔNIHSS3-24h and baseline NIHSS accounted for similar portions of the variance in favorable 90-day outcome, with PR2 values of 0.145 and 0.159, respectively.
“For favorable outcome, ΔNIHSS3–24h and baseline NIHSS accounted for similar portions of the variance (Table 4; PR2 of 0.145 and 0.159, respectively) in the overall dataset.”
Quote in the paperSubstantial claim - Findingown data
In the GENISIS cohort, the association of ΔNIHSS6-24h with long-term outcome was independent of early baseline stroke severity.
“The association of ΔNIHSS6–24h with long-term outcome in the GENISIS cohort was independent of early baseline stroke severity.”
Quote in the paperSubstantial claim - Findingown data
In the tPA-treated large vessel occlusion subcohort, adding early sustained recanalization and parenchymal hematoma type 2 to a model of ΔNIHSS6-24h increased explained variance but left most variance unexplained.
“The addition of these covariates in a model of ΔNIHSS6–24h increased the amount of explained variance within the LVO cohort, but still left a majority of variance unexplained.”
Quote in the paperNot a substantial claim - Findingown data
In the tPA-treated large vessel occlusion subcohort, subjects with parenchymal hematoma type 2 were more likely to deteriorate after initial presentation, with an odds ratio of 6.8 (95% CI 2.0-22.7).
“Subjects with a PH2 were more likely to have deterioration after the initial presentation (OR 6.8; 2.0, 22.7).”
Quote in the paperSubstantial claim - Study design and conductown data
In the GENISIS cohort, imputation of missing 90-day mRS data did not change the final multivariable model.
“Imputation of missing 90 day mRS did not impact the final multivariable model”
Quote in the paperNot a substantial claim - Interpretationreasoning
Early interventions that alter ΔNIHSS, such as reperfusion, could have a lasting impact on long-term outcomes.
“Furthermore, the independent influence of ΔNIHSS seen in both GENISIS and the NINDS studies suggests that early interventions (such as reperfusion) that alter ΔNIHSS could have a lasting impact on long-term outcomes.”
Quote in the paperSubstantial claim - Interpretationown data
Because neither early sustained recanalization nor parenchymal hematoma type 2 remained in the model for favorable outcome, they appear to act indirectly through ΔNIHSS6-24h.
“In addition, since neither ESR nor PH2 remained in the model for favorable outcome, it appears that they play an indirect role through ΔNIHSS6–24h.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The study lacked serial NIHSS measurements after tPA within the 24-hour window, preventing analysis of potential interval censoring between baseline and 24-hour NIHSS.
“lack serial NIHSS post-tPA within the 24-hour window to analyze for potential interval censoring between baseline and the 24 hour NIHSS”
Quote in the paperNot a substantial claim - Interpretationreasoning
ΔNIHSS measured between 3 hours of onset and 24 hours has a greater association with outcome than ΔNIHSS measured between 6 and 24 hours.
“Therefore, it is not surprising that ΔNIHSS values measured between 3 hours of onset and 24 hours have greater association with outcome than ΔNIHSS between 6–24 hours.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The study did not have data on potential post-discharge confounders such as rehabilitative therapies, recurrent stroke, or infections that might have influenced 90-day outcome.
“and do not have potential confounders (such as participation in rehabilitative therapies, recurrent stroke or infections) that might have occurred after discharge and influenced 90-day outcome.”
Quote in the paperNot a substantial claim - Study design and conductreasoning
The GENISIS acute ischemic stroke population is biased toward severe strokes because inclusion is limited to patients presenting within 6 hours of stroke onset.
“Another limitation is that our AIS population is biased towards severe strokes because inclusion is limited to patients that present within 6 hours of stroke onset.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The difference in ΔNIHSS distributions between GENISIS and the NINDS tPA trials was largely due to non-tPA-treated GENISIS patients, who were fundamentally different from the NINDS control group.
“The difference in distributions was largely attributed to the non-tPA treated patients in GENISIS who were fundamentally different from the NINDS control group (the non-tPA patients in GENISIS would have been excluded from the NINDS trials).”
Quote in the paperNot a substantial claim
- Classified as probably not a substantial claim. 23
- May combine two claims. 28
- The quote only partly states this claim. 4
Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing).
PremisecitationA recent publication indicated that percentile change of NIHSS has better predictive capabilities for 3-month outcomes than arithmetic change.
“While a recent publication has indicated that percentile change of NIHSS has better predictive capabilities for 3 month outcomes than arithmetic change,36”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [36] source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA recent multicenter study showed that early tPA-induced recanalization in large vessel occlusion patients significantly improved both early and long-term outcomes.
“A recent multicenter study showed that early tPA induced recanalization in LVO patients significantly improved both early and long term outcomes.33”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [33] source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe effect of endovascular treatment on 90-day mRS is in large part mediated by early changes in NIHSS.
“Similar to this finding, it was recently reported that the effect of endovascular treatment on 90 day mRS is in large part mediated by early changes in NIHSS.34”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [34] source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrevious studies have consistently associated early neurologic improvement with successful reperfusion.
“Previous studies have also demonstrated that early neurologic improvement has consistently been associated with successful reperfusion.5, 31, 32”
Quote in the paperNot a substantial claim1 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationHemorrhagic transformation and lack of recanalization have been described as significant factors in neurologic worsening.
“Both HT and lack of recanalization have been described as significant factors in neurologic worsening.5, 7”
Quote in the paperNot a substantial claim1 of 2 sources checkedMay combine two claims.
Findingown dataIn the GENISIS cohort, ΔNIHSS6-24h approximated a normal distribution, ranged from −34 to +33, and had a mean of +2.78 with a standard deviation of 5.93.
“ΔNIHSS6–24h approximated a normal distribution (Figure 1C) which ranged from −34 (extreme deterioration) to +33 (extreme improvement) with a mean of +2.78 (SD 5.93).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the GENISIS cohort, TOAST was significantly associated with baseline NIHSS, with more severe strokes in the large artery atherosclerosis and cardioembolic categories and milder strokes in the small vessel disease category.
“TOAST was significantly associated with baseline NIHSS. More severe strokes fell into the LAA and CE categories; milder strokes in the SVD category, consistent with the findings of others”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the GENISIS cohort, TOAST designation accounted for 7.5% of the variance in baseline NIHSS but less than 0.5% of the variance in ΔNIHSS6-24h.
“TOAST designation had a strong influence on baseline NIHSS, accounting for 7.5% of the variance — the highest of all baseline variables – but had little influence on ΔNIHSS6–24h, accounting for less than 0.5%.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S1 (asserted), S4 (based). May combine two claims.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, early sustained recanalization and parenchymal hematoma type 2 were the only variables that remained significant in ordinal logistic regression models of early outcomes without violating the proportional odds assumption.
“Using ordinal logistic regression multivariable models to evaluate the influence of these variables on early outcomes, the only variables that remained significant and did not violate the proportional odds were ESR and PH2”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataIn the GENISIS cohort of 2,555 acute ischemic stroke patients, the median baseline NIHSS score was 9, with an interquartile range of 4 to 16.
“For 2555 AIS patients, median baseline NIHSS was 9 (IQR 4–16)”
- Also stated in: § Baseline and 24 hour Stroke Severity · plain
“Median baseline NIHSS was 9 (IQR 4–16).”
Quote in the paperNot a substantial claim- Also stated in: § Baseline and 24 hour Stroke Severity · plain
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn the GENISIS cohort, baseline NIHSS had a positively skewed distribution, with more patients having milder strokes.
“Baseline NIHSS demonstrated a positive-skewed distribution with more patients having milder strokes, typical of a cross-sectional population of AIS (Figure 1A).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn a multivariable model of GENISIS acute ischemic stroke patients, baseline NIHSS, tPA treatment, age, glucose, site, and systolic blood pressure independently predicted ΔNIHSS6-24h, and the model explained about 15% of the variance.
“In a multivariable model, baseline NIHSS, tPA treatment, age, glucose, site and systolic blood pressure independently predicted ΔNIHSS6–24h (R2=0.15).”
- Also stated in: § Change in Stroke Severity from Baseline to 24 hours (ΔNIHSS6–24h) · plain
“Overall, this model accounted for only 14.9% of the variance seen in ΔNIHSS6–24h.”
Quote in the paperNot a substantial claim- Also stated in: § Change in Stroke Severity from Baseline to 24 hours (ΔNIHSS6–24h) · plain
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown dataIn the GENISIS cohort, NIHSS at 24 hours was skewed toward lower scores, with half the subjects scoring 4 or less.
“NIHSS at 24 hours (Figure 1B) demonstrated a skew towards lower NIHSS with half the subjects scoring ≤ 4.”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, early sustained recanalization accounted for most of the explained variance in ΔNIHSS6-24h (partial eta-squared 0.2136; parameter estimate 5.952, 95% CI 4.526-7.377), and parenchymal hematoma type 2 added a smaller portion (partial eta-squared 0.061; parameter estimate −6.907, 95% CI −10.302 to −3.512).
“ESR accounted for the majority of explained variance (partial eta-square of 0.2136; parameter estimate 5.952 (4.526, 7.377)) with PH2 providing an additional portion (partial eta-square of 0.061; parameter estimate −6.907 (−10.302, −3.512)).”
Quote in the paperNot a substantial claimThe quote only partly states this claim.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, a multivariable model including recanalization and hemorrhagic transformation explained only 27% of the variance in ΔNIHSS6-24h.
“Despite inclusion of recanalization and HT, the model explained only 27% of ΔNIHSS6–24h variance.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe distribution of ΔNIHSS was compressed in the overall GENISIS population compared with the two NINDS tPA trials, but tPA-treated subjects in both studies had similar distributions with a median change of 3.
“Although there was a compression of ΔNIHSS distribution in the overall GENISIS population compared to the two NINDS tPA stroke trials (please see https://www.ahajournals.org/journal/str, Supplement Figures IVE–F), a comparison of the tPA-treated subjects in both GENISIS and NINDS revealed very similar distributions with a median change of 3.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, early sustained recanalization and severe hemorrhagic transformation (parenchymal hematoma type 2) were associated with extreme neurologic improvement and deterioration, respectively.
“In a subcohort of tPA-treated LVO patients, ESR and severe hemorrhagic transformation (PH2) were associated with extreme degrees of neurologic improvement or deterioration, respectively.”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, neither parenchymal hematoma type 2 nor early sustained recanalization had a significant influence on favorable 90-day outcome in multivariable modeling.
“In multivariable modeling of 90 day outcomes within the LVO cohort, neither PH2 nor ESR had a significant influence on favorable outcome despite meeting the univariate threshold”
Quote in the paperNot a substantial claimMay combine two claims. The quote only partly states this claim.
Findingown dataIn the tPA-treated large vessel occlusion subcohort, for favorable 90-day outcome (n=241), only baseline NIHSS and ΔNIHSS6-24h remained in the model, explaining 41.3% of the variance (baseline NIHSS PR2 0.136, OR 0.74, 95% CI 0.68-0.81; ΔNIHSS6-24h PR2 0.150, OR 1.3, 95% CI 1.2-1.4).
“For favorable outcome (n=241), only baseline NIHSS and ΔNIHSS6–24h remained in the model, explaining 41.3% of the variance (with respective PR2 and ORs of 0.136 and 0.74 (0.68, 0.81) and 0.150 and 1.3 (1.2, 1.4)).”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataHemorrhagic transformation and early sustained recanalization occur in a minority of patients, which supports the suggestion that other mechanisms determine ΔNIHSS6-24h.
“Moreover, HT and early sustained recanalization develop in a minority of patients, supporting the suggestion that other mechanisms are involved in the determination of ΔNIHSS6–24h.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
PremisecitationThe success of candidate drugs is greatly enhanced when the drug target is independently confirmed by human genetic data.
“There is accumulating evidence that the success of candidate drugs is greatly enhanced if the drug target is independently confirmed by human genetic data.16, 17”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
Study design and conductown dataIn the GENISIS study, a stepwise ordinal logistic regression for all mRS categories was attempted, but all significant models failed the proportional odds assumption, so a valid model could not be constructed.
“A stepwise ordinal logistic regression analysis was performed for all categories of the mRS scale, but all significant models failed to maintain the proportional odds assumption. Therefore, a valid model was unable to be constructed.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningΔNIHSS is both an important early metric associated with long-term outcome and a phenotype for discovering additional mechanisms that influence neurological changes during the early window.
“Thus, ΔNIHSS is not only an important early metric that is associated with long-term outcome but also a phenotype for discovering additional mechanisms to influence the neurological changes that occur during that window.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataIn the GENISIS analyses, the false discovery rate was controlled using the Benjamini-Hochberg procedure.
“The false discovery rate was controlled using the Benjamini-Hochberg procedure to evaluate the resultant p-values in the final models (and all subsequent modeling).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataBecause of site differences in baseline NIHSS, a nested model was performed and did not differ significantly in covariates or explained variance in ΔNIHSS6-24h.
“Due to site differences for baseline NIHSS, a nested model was performed and did not differ significantly in terms of the covariates and explained variance in ΔNIHSS6–24h”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataIn the GENISIS analyses, collinearity and heteroscedasticity were checked for all variables in the models using variance inflation factor and residual plots.
“Collinearity and heteroscedasticity were checked for all variables included in the models (and in all subsequent modeling) using the variance inflation factor and residual plots respectively.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationIn the GENISIS study, hemorrhagic transformation was classified according to European Cooperative Acute Stroke Study criteria with centralized adjudication.
“When follow-up imaging was available, HT was classified according to European Cooperative Acute Stroke Study criteria, with centralized adjudication.20”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [20] source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenIn the GENISIS study, covariates were collected and aligned according to a study-specific data dictionary, using NIH NINDS common data elements when available.
“All co-variates were collected and aligned according to a data dictionary generated for the study, utilizing NIH NINDS common data elements when available”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe GENISIS cohort is consistent with the real-world population amenable to acute interventions and is therefore relevant to the study.
“Thus, the GENISIS cohort is consistent with the real-world population that is amenable to acute interventions and therefore relevant to our study.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataStroke etiology has a major influence on initial stroke severity but limited influence on the processes that account for early neurological deterioration or improvement.
“These findings are consistent with previous studies,7, 29 and indicate that stroke etiology has a major influence on initial stroke severity, but limited influence on the processes that account for early neurological deterioration or improvement.”
Quote in the paperSubstantial claim0 of 2 sources checkedClassified as probably not a substantial claim. May combine two claims.
Study design and conductown dataIn the GENISIS study, NIHSS was prospectively recorded within 6 hours after onset and again 24 hours later.
“Patients with NIHSS prospectively recorded within 6h after onset and then 24h later were enrolled in the GENISIS (Genetics of Early Neurological InStability after Ischemic Stroke) study.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningBecause of the retrospective approach, the GENISIS study did not conduct an a priori power analysis on univariate predictors.
“Due to the retrospective approach, no a priori power analysis was conducted on univariate predictors.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenInstitutional Review Boards at all participating sites approved patient enrollment and data sharing for the GENISIS study.
“The Institutional Review Boards at all participating sites approved patient enrollment and data sharing.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Interpretationown dataA variety of mechanisms likely contribute to ΔNIHSS6-24h.
“A variety of mechanisms are likely to contribute to ΔNIHSS6–24h.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningΔNIHSS6-24h will be a valuable quantitative phenotype in large genetic studies of acute ischemic stroke patients for identifying novel mechanisms involved in neurological change after stroke that are relevant to human disease.
“Therefore, ΔNIHSS6–24h will be a valuable quantitative phenotype in large genetic studies of AIS patients, to identify novel mechanisms involved in neurological change after stroke that are relevant to human disease.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFailure to translate experimental models into human trials has slowed the drug development pipeline.
“Indeed, failure of translation from experimental models to human trials has slowed the drug development pipeline.14, 15”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe study had strengths including a large sample size, real-world standard-of-care patients, careful documentation of NIHSS at standardized time intervals, and replication in an independent randomized controlled trial cohort.
“This study has several strengths, including the large sample size, involving patients in real-world standard-of-care practice, careful documentation of NIHSS at standardized time intervals after stroke onset, and replication in an independent cohort of patients enrolled in a randomized controlled trial.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataIn the large vessel occlusion cohort, recanalization and hemorrhagic transformation explain a minority of the variance in ΔNIHSS6-24h, leaving most variance unexplained and suggesting that other factors captured by ΔNIHSS6-24h are involved.
“While this holds true in our analysis of the LVO cohort, recanalization and HT explain a minority of variance in ΔNIHSS6–24h, leaving the majority of variance unexplained and suggesting that there are other contributing factors that are being captured by ΔNIHSS6–24h.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningDynamic changes in early neurological function are likely time-dependent, with a higher likelihood of change earlier in the ischemic course.
“It is likely that dynamic changes in early neurological function are time-dependent, with a higher likelihood of change earlier in the ischemic course”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningΔNIHSS6-24h is likely to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of acute ischemic stroke.
“Thus, ΔNIHSS6–24h promises to be an easily obtainable and meaningful quantitative phenotype for large-scale genomic studies of AIS.”
Quote in the paperSubstantial claimMay combine two claims.
Study design and conductreasoningThe study could not estimate recruitment bias or assess intra-site and inter-site reliability for NIHSS and mRS assessment.
“As such we are unable to provide an estimation of bias in recruitment (i.e. potential selection and/or bidirectional ascertainment bias) or an assessment of intra-site and inter-site reliability for assessment of NIHSS and mRS”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThe dynamic phenotype ΔNIHSS6-24h captures both explained and unexplained mechanisms involved in acute ischemic stroke and is significantly and independently associated with long-term outcomes.
“The dynamic phenotype, ΔNIHSS6–24h, captures both explained and unexplained mechanisms involved in AIS, and is significantly and independently associated with long-term outcomes.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningΔNIHSS6-24h captures mechanisms related to early neurological change after acute ischemic stroke and thereby has a significant association with long-term outcomes.
“Thus, ΔNIHSS6–24h captures mechanisms related to early neurological change after AIS, thereby creating a significant association with long-term outcomes.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe current study excludes patients treated with thrombectomy.
“A final limitation is that the current study excludes patients treated with thrombectomy.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
A meaningful quantitative phenotype for acute ischemic stroke can be obtained in large patient populations.
“However, meaningful quantitative phenotypes attainable in large patient populations are needed.”
The paper relies on this without support.
The first 24 hours after acute ischemic stroke onset is a period in which neurological deterioration can be prevented or improvement can be enhanced.
“This critical period is a window for preventing neurological deterioration, or enhancing improvement.”
Cites
Adams, H. P., Bendixen, B. H., Kappelle, L. J., Biller, J., Love, B. B., Gordon, D., & Marsh, E. E. (1993) · Stroke · doi:10.1161/01.str.24.1.35 · Cited by 12,350 · see citing works
Tissue Plasminogen Activator for Acute Ischemic Stroke
(1995) · New England Journal of Medicine · doi:10.1056/nejm199512143332401 · Cited by 11,654 · see citing works
Guidelines for the Early Management of Patients With Acute Ischemic Stroke
Jauch, E. C., Saver, J. L., Adams, H. P., Bruno, A., Connors, J. J. “., Demaerschalk, B. M., Khatri, P., McMullan, P. W., Qureshi, A. I., Rosenfield, K., et al. (2013) · Stroke · doi:10.1161/str.0b013e318284056a · Cited by 7,648 · see citing works
Self-citationPowers, W. J., Rabinstein, A. A., Ackerson, T., Adeoye, O. M., Bambakidis, N. C., Becker, K. J., Biller, J., Brown, M., Demaerschalk, B. M., Hoh, B. L., et al. (2018) · Stroke · doi:10.1161/str.0000000000000158 · Cited by 5,505 · see citing works
Isolated Hand Paresis: A Case Series
Alstadhaug, K. B., & Sjulstad, A. S. (2013) · Cerebrovascular Diseases Extra · doi:10.1159/000350708 · Cited by 4,090 · see citing works
Benardete, E. A., & Nair, A. K. (2015) · Cerebrovascular Diseases Extra · doi:10.1159/000370060 · Cited by 2,546 · see citing works
The support of human genetic evidence for approved drug indications
Nelson, M. R., Tipney, H., Painter, J. L., Shen, J., Nicoletti, P., Shen, Y., Floratos, A., Sham, P. C., Li, M. J., Wang, J., et al. (2015) · Nature Genetics · doi:10.1038/ng.3314 · Cited by 1,666 · see citing works
Adams, H. P., Davis, P. H., Leira, E. C., Chang, K.-C., Bendixen, B. H., Clarke, W. R., Woolson, R. F., & Hansen, M. D. (1999) · Neurology · doi:10.1212/wnl.53.1.126 · Cited by 1,456 · see citing works
Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework
Cook, D., Brown, D., Alexander, R., March, R., Morgan, P., Satterthwaite, G., & Pangalos, M. N. (2014) · Nature Reviews Drug Discovery · doi:10.1038/nrd4309 · Cited by 1,344 · see citing works
The changing landscape of ischaemic brain injury mechanisms
Lee, J.-M., Zipfel, G. J., & Choi, D. W. (1999) · Nature · doi:10.1038/399a007 · Cited by 1,102 · see citing works
Self-citationFiorelli, M., Bastianello, S., von Kummer, R., del Zoppo, G. J., Larrue, V., Lesaffre, E., Ringleb, A. P., Lorenzano, S., Manelfe, C., & Bozzao, L. (1999) · Stroke · doi:10.1161/01.str.30.11.2280 · Cited by 777 · see citing works
Impact of collateral flow on tissue fate in acute ischaemic stroke
Bang, O. Y., Saver, J. L., Buck, B. H., Alger, J. R., Starkman, S., Ovbiagele, B. I., Kim, D., Jahan, R., Duckwiler, G., Yoon, S. R., et al. (2007) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2007.132100 · Cited by 383 · see citing works
Seners, P., Turc, G., Oppenheim, C., & Baron, J.-C. (2015) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2014-308327 · Cited by 334 · see citing works
On distribution-free multiple comparisons in the one-way analysis of variance
Douglas, C. E., & Michael, F. A. (1991) · Communication in Statistics- Theory and Methods · doi:10.1080/03610929108830487 · Cited by 329 · see citing works
Future of neuroprotection for acute stroke: In the aftermath of the SAINT trials
Savitz, S. I., & Fisher, M. (2007) · Annals of Neurology · doi:10.1002/ana.21127 · Cited by 267 · see citing works
Neuroprotection for Ischaemic Stroke: Translation from the Bench to the Bedside
Sutherland, B. A., Minnerup, J., Balami, J. S., Arba, F., Buchan, A. M., & Kleinschnitz, C. (2012) · International Journal of Stroke · doi:10.1111/j.1747-4949.2012.00770.x · Cited by 259 · see citing works
Zhang, H., Prabhakar, P., Sealock, R. W., & Faber, J. E. (2010) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2010.10 · Cited by 244 · see citing works
Chalos, V., van der Ende, N. A. M., Lingsma, H. F., Mulder, M. J. H. L., Venema, E., Dijkland, S. A., Berkhemer, O. A., Yoo, A. J., Broderick, J. P., Palesch, Y. Y., et al. (2020) · Stroke · doi:10.1161/strokeaha.119.026791 · Cited by 215 · see citing works
Fonarow, G. C., Saver, J. L., Smith, E. E., et al. (2012) · Journal of the American Heart Association · doi:10.1161/jaha.111.000034 · Cited by 175 · see citing works
del Zoppo, G. J., Sharp, F. R., Heiss, W., & Albers, G. W. (2011) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2011.93 · Cited by 174 · see citing works
Wouters, A., Nysten, C., Thijs, V., & Lemmens, R. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.00308 · Cited by 162 · see citing works
Saver, J. L., & Altman, H. (2012) · Stroke · doi:10.1161/strokeaha.111.636928 · Cited by 158 · see citing works
Prehospital delay in acute stroke and TIA
Faiz, K. W., Sundseth, A., Thommessen, B., & Rønning, O. M. (2012) · Emergency Medicine Journal · doi:10.1136/emermed-2012-201543 · Cited by 141 · see citing works
Christoforidis, G. A., Karakasis, C. J., Mohammad, Y. M., et al. (2008) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1276 · Cited by 131 · see citing works
Yeo, L. L. L., Paliwal, P. R., Teoh, H. L., et al. (2012) · JAMA Neurology · doi:10.1001/2013.jamaneurol.547 · Cited by 116 · see citing works
Ischemic stroke subtypes: risk factors, functional outcome and recurrence
Sümer, M. M., & Erturk, O. (2002) · Neurological Sciences · doi:10.1007/s100720200004 · Cited by 73 · see citing works
Rangaraju, S., Frankel, M., & Jovin, T. G. (2015) · Interventional Neurology · doi:10.1159/000443801 · Cited by 69 · see citing works
Timing of Recanalization and Functional Recovery in Acute Ischemic Stroke
Tsivgoulis, G., Saqqur, M., Sharma, V. K., Brunser, A., Eggers, J., Mikulik, R., Katsanos, A. H., Sergentanis, T. N., Vadikolias, K., Perren, F., et al. (2020) · Journal of Stroke · doi:10.5853/jos.2019.01648 · Cited by 68 · see citing works
Tsivgoulis, G. K., Ribó, M., Rubiera, M., et al. (2013) · Stroke · doi:10.1161/strokeaha.112.675074 · Cited by 60 · see citing works
Self-citationAgarwal, S., Scher, E., Lord, A., Frontera, J., Ishida, K., Torres, J., Rostanski, S., Mistry, E., Mac Grory, B., Cutting, S., et al. (2020) · Stroke · doi:10.1161/strokeaha.119.027476 · Cited by 60 · see citing works
Self-citationFactors Associated with Early Hospital Arrival in Patients with Acute Ischemic Stroke
Song, D., Tanaka, E., Lee, K., Sato, S., Koga, M., Kim, Y. D., Nagatsuka, K., Toyoda, Ḱ., & Heo, J. H. (2015) · Journal of Stroke · doi:10.5853/jos.2015.17.2.159 · Cited by 46 · see citing works
Mikulik, R., Ribo, M., Hill, M. D., Grotta, J. C., Malkoff, M., Molina, C., Rubiera, M., Delgado-Mederos, R., Alvarez-Sabin, J., & Alexandrov, A. V. (2007) · Circulation · doi:10.1161/circulationaha.106.651026 · Cited by 43 · see citing works
Self-citationA User's Guide to the NINDS rt-PA Stroke Trial Database
Dachs, R. J., Burton, J. H., & Joslin, J. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050113 · Cited by 32 · see citing works
Early neurological stability predicts adverse outcome after acute ischemic stroke
Irvine, H. J., Battey, T. W., Ostwaldt, A.-C., Campbell, B. C., Davis, S. M., Donnan, G. A., Sheth, K. N., & Kimberly, W. T. (2016) · International Journal of Stroke · doi:10.1177/1747493016654484 · Cited by 31 · see citing works
Predicting the Long-Term Outcome after Subacute Stroke within the Middle Cerebral Artery Territory
Bang, O. Y., Park, H., Yoon, J. H., et al. (2005) · Journal of Clinical Neurology · doi:10.3988/jcn.2005.1.2.148 · Cited by 27 · see citing works
Neuroprotective therapies: Preclinical reproducibility is only part of the problem
Tymianski, M. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aac9412 · Cited by 19 · see citing works
Vanacker, P., Lambrou, D., Eskandari, A., Ntaios, G., Cras, P., Maeder, P., Meuli, R., & Michel, P. (2015) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2015.04.002 · Cited by 18 · see citing works
TURN Score Predicts 24-Hour Cerebral Edema After IV Thrombolysis
Asuzu, D., Nyström, K. V., Sreekrishnan, A., et al. (2015) · Neurocritical Care · doi:10.1007/s12028-015-0198-6 · Cited by 17 · see citing works
Strbian, D., Sairanen, T., Rantanen, K., Piironen, K., Atula, S., Tatlisumak, T., Soinne, L., & for the Helsinki Stroke Thrombolysis Registry Group (2011) · Cerebrovascular Diseases · doi:10.1159/000320263 · Cited by 16 · see citing works
Self-citationBustamante, A., Díaz-Fernández, B., Giralt, D., et al. (2016) · International Journal of Stroke · doi:10.1177/1747493016641949 · Cited by 15 · see citing works
Self-citationWing, J. J., Baek, J., Sánchez, B. N., et al. (2014) · Cerebrovascular Diseases · doi:10.1159/000366468 · Cited by 10 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Faizy, T. D., Mlynash, M., Kabiri, R., Christensen, S., Kuraitis, G. M., Meyer, L., Bechstein, M., van Horn, N., Lansberg, M. G., Albers, G. W., et al. (2022) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-328041 · Cited by 49 · see citing works
Multi-ancestry GWAS reveals excitotoxicity associated with outcome after ischaemic stroke
Ibáñez, L., Heitsch, L., Carrera, C., Farias, F. H. G., Del‐Aguila, J. L., Dhar, R., Budde, J., Bergmann, K., Bradley, J. L., Harari, O., et al. (2022) · Brain · doi:10.1093/brain/awac080 · Cited by 51 · see citing works
Self-citationMistry, E. A., Yeatts, S. D., Khatri, P., Mistry, A. M., Detry, M. A., Viele, K., Harrell, F. E., & Lewis, R. J. (2022) · Stroke · doi:10.1161/strokeaha.121.034859 · Cited by 45 · see citing works
Self-citationLee, J., Fernández‐Cadenas, I., & Lindgren, A. G. (2021) · Stroke · doi:10.1161/strokeaha.121.032622 · Cited by 39 · see citing works
Self-citationLi, R., Liu, Y., Wu, J., Chen, X., Lu, Q., Xia, K., Liu, C., Sui, X. Y., Liu, Y., Wang, Y., et al. (2024) · Advanced Science · doi:10.1002/advs.202400426 · Cited by 44 · see citing works
Bitar, L., Uphaus, T., Thalman, C., Muthuraman, M., Gyr, L., Ji, H., Domingues, M., Endle, H., Groppa, S., Steffen, F., et al. (2022) · Science Translational Medicine · doi:10.1126/scitranslmed.abk0135 · Cited by 38 · see citing works
Self-citationYou, S., Wang, Y., Wang, X., Maeda, T., Ouyang, M., Han, Q., Li, Q., Song, L., Zhao, Y., Chen, C., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.124.036109 · Cited by 33 · see citing works
Du, J., Wang, Y., Che, B., Miao, M.-Y., Bao, A., Peng, Y., Ju, Z., Xu, T., He, J., Zhang, Y., et al. (2023) · International Journal of Stroke · doi:10.1177/17474930231180446 · Cited by 31 · see citing works
Jiang, L., Miao, Z., Chen, H., Geng, W., Yong, W., Chen, Y., Zhang, H., Duan, S., Yin, X., & Zhang, Z. (2022) · Stroke · doi:10.1161/strokeaha.122.040418 · Cited by 32 · see citing works
National Institutes of Health Stroke Scale as an Outcome Measure for Acute Stroke Trials
Yamal, J., & Grotta, J. C. (2020) · Stroke · doi:10.1161/strokeaha.120.032994 · Cited by 31 · see citing works
Lindgren, A. G., Braun, R. G., Majersik, J. J., Clatworthy, P. L., Mainali, S., Derdeyn, C. P., Maguire, J. M., Jern, C., Rosand, J. M., Cole, J. W., et al. (2021) · International Journal of Stroke · doi:10.1177/17474930211007288 · Cited by 23 · see citing works
Self-citationJin, M., Peng, Q., & Wang, Y. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e15620 · Cited by 24 · see citing works
Genome-Wide Studies in Ischaemic Stroke: Are Genetics Only Useful for Finding Genes?
Gallego-Fábrega, C., Muiño, E., Cárcel‐Márquez, J., Llucià‐Carol, L., Lledós, M., Martín-Campos, J. M., Cullell, N., & Fernández‐Cadenas, I. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23126840 · Cited by 17 · see citing works
Self-citationThe Stroke Neuro-Imaging Phenotype Repository: An Open Data Science Platform for Stroke Research
Foroushani, H. M., Dhar, R., Chen, Y., et al. (2021) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2021.597708 · Cited by 22 · see citing works
Self-citationCullell, N., Soriano‐Tárraga, C., Gallego-Fábrega, C., Cárcel‐Márquez, J., Muiño, E., Llucià‐Carol, L., Lledós, M., Esteller, M., de Moura, M. C., Montaner, J., et al. (2022) · Clinical Epigenetics · doi:10.1186/s13148-022-01340-5 · Cited by 20 · see citing works
Self-citationLai, Y., Jou, E., Mofatteh, M., et al. (2023) · Translational Neuroscience · doi:10.1515/tnsci-2022-0307 · Cited by 20 · see citing works
Du, J., Zhai, Y., Dong, W., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.030702 · Cited by 18 · see citing works
Chen, L., Zhang, L., Li, Y., Zhang, Q., Fang, Q., & Tang, X. (2024) · Brain Sciences · doi:10.3390/brainsci14030250 · Cited by 17 · see citing works
Jiang, W., & Deng, M.-L. (2022) · Clinical Neurology and Neurosurgery · doi:10.1016/j.clineuro.2022.107204 · Cited by 17 · see citing works
Evans, N. R., Sibson, L., Day, D. J., Agarwal, S., Shekhar, R., & Warburton, E. A. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-057372 · Cited by 17 · see citing works
Li, S., Ni, J., Fan, X., et al. (2022) · BMC Neurology · doi:10.1186/s12883-022-02976-9 · Cited by 16 · see citing works
Fukutomi, H., Yamamoto, T., Sibon, I., Christensen, S., Raposo, N., Marnat, G., Albucher, J., Olindo, S., Calvière, L., Sagnier, S., et al. (2022) · Radiology · doi:10.1148/radiol.220080 · Cited by 16 · see citing works
Jia, W., Jiang, Y., Jiang, Y., et al. (2023) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x231214831 · Cited by 14 · see citing works
Veerbeek, J. M., Pohl, J., Held, J. P. O., & Luft, A. R. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.797791 · Cited by 14 · see citing works
Bui, Q. V. P., Kumar, A., Chen, Y., et al. (2023) · Neurocritical Care · doi:10.1007/s12028-023-01742-0 · Cited by 12 · see citing works
Self-citationArrival time at a referral hospital and functional disability of people with stroke: a cohort study
Moraes, M. D. A., de Jesus, P. A. P., Muniz, L. S., Baccin, C. A., Barreto, A. B. M., Sales, R. S., Pires, C. G. D. S., Teles, C. A. D. S., & Mussi, F. C. (2023) · Sao Paulo Medical Journal · doi:10.1590/1516-3180.2022.0510.r1.27022023 · Cited by 10 · see citing works
Dong, A., Maïer, B., Guillon, B., et al. (2023) · Revue Neurologique · doi:10.1016/j.neurol.2022.10.003 · Cited by 10 · see citing works
Lu, S., Zhang, J., Wu, R., et al. (2022) · Journal of Computer Assisted Tomography · doi:10.1097/rct.0000000000001341 · Cited by 10 · see citing works
Zhao, Y., Zhu, H., Dai, C., et al. (2025) · Brain and Behavior · doi:10.1002/brb3.70577 · Cited by 9 · see citing works
Lu, Q., Zhang, H., Cao, X., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.980135 · Cited by 8 · see citing works
Stroke recovery phenotyping through network trajectory approaches and graph neural networks
Krishnagopal, S., Lohse, K. R., & Braun, R. G. (2022) · Brain Informatics · doi:10.1186/s40708-022-00160-w · Cited by 7 · see citing works
Cheng, S., Wei, Y., Zheng, H., Zhang, Q., Yang, X., Lü, Z., Huang, Z., Wan, Z., Shi, Y., Zhang, J., et al. (2025) · EClinicalMedicine · doi:10.1016/j.eclinm.2025.103684 · Cited by 6 · see citing works
Self-citationLai, Y., Mofatteh, M., Baizabal‐Carvallo, J. F., He, J., Wu, W., Wang, D., Yan, W., Ma, J., Zhou, S., Sun, Y., et al. (2025) · Frontiers in Neurology · doi:10.3389/fneur.2025.1492013 · Cited by 6 · see citing works
Faizy, T. D., Yedavalli, V. S., Salim, H. A., et al. (2025) · Journal of NeuroInterventional Surgery · doi:10.1136/jnis-2024-022642 · Cited by 6 · see citing works
Avula, A., Bui, Q. V. P., Kumar, A., et al. (2024) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2024.107913 · Cited by 6 · see citing works
Self-citationGenomics of stroke recovery and outcome
Lindgren, A. G. (2025) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x251332528 · Cited by 5 · see citing works
Multi-Omics Approaches to Discovering Acute Stroke Injury and Recovery Mechanisms
Giles, J. A., Lee, J., & Dhar, R. (2024) · Springer eBooks · doi:10.1007/978-3-031-41777-1_19 · Cited by 5 · see citing works
Self-citationMinchell, E., Rumbach, A. F., & Finch, E. (2022) · International Journal of Speech-Language Pathology · doi:10.1080/17549507.2022.2140830 · Cited by 5 · see citing works
Association between nocturnal oxygen desaturation and ischaemic stroke outcomes
Wojtasz, I., Tomski, A., & Kaźmierski, R. (2022) · Neurologia i Neurochirurgia Polska · doi:10.5603/pjnns.a2022.0033 · Cited by 5 · see citing works
Gouta, N., Daoussi, N., Dhia, R. B., et al. (2025) · The Neurohospitalist · doi:10.1177/19418744251341922 · Cited by 4 · see citing works
A failure of forward translation? The case of neuroprotection
Lee, J., Rosand, J. M., & Cruchaga, C. (2021) · Vessel Plus · doi:10.20517/2574-1209.2020.72 · Cited by 4 · see citing works
Self-citationZheng, X., Zhao, M., Yang, Z., Kang, L., Li, R., Gao, Y., Zhang, G., & Lai, X. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2026.1737871 · Cited by 3 · see citing works
Bu, F., Cai, R., Zhang, W., Tang, X., Cui, G., & Yang, X. (2025) · Frontiers in Neurology · doi:10.3389/fneur.2025.1668816 · Cited by 5 · see citing works
Xiaoni, Z., Xu, Y., & Ma, R. (2024) · Journal of Medical Biochemistry · doi:10.5937/jomb0-51371 · Cited by 3 · see citing works
Cárcel‐Márquez, J., Muiño, E., Gallego-Fábrega, C., Cullell, N., Lledós, M., Llucià‐Carol, L., Martín-Campos, J. M., Sobrino, T., Campos, F., Castillo, J., et al. (2024) · Stroke · doi:10.1161/strokeaha.124.047833 · Cited by 3 · see citing works
Self-citationZhu, L. N., Qin, Y., Kang, T., Ying, Y., Cao, Y. M., & Shi, J. (2025) · Annals of Medicine · doi:10.1080/07853890.2025.2610555 · Cited by 2 · see citing works
Using human genomics to validate drug targets for acute ischemic stroke
Heitsch, L., & Lee, J. (2025) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x251383948 · Cited by 1 · see citing works
Self-citationBergh, E., Askim, T., Rønning, O. M., et al. (2025) · BMC Health Services Research · doi:10.1186/s12913-025-12979-0 · Cited by 1 · see citing works
Yan, Z., Mofatteh, M., Nguyen, T. N., et al. (2025) · Medicine · doi:10.1097/md.0000000000042055 · Cited by 1 · see citing works
Deng, Y., Song, L., Chen, H. Y., Yin, Y., Wang, A., Zhang, X., Zhang, Y., Jia, B., Huo, X., Luo, G., et al. (2025) · Therapeutic Advances in Neurological Disorders · doi:10.1177/17562864251376818 · Cited by 1 · see citing works
Lian, I., Chiu, P., Hsieh, Y., et al. (2023) · Therapeutic Advances in Chronic Disease · doi:10.1177/20406223231153564 · Cited by 1 · see citing works
Yang, X., Yang, J., Sun, D., et al. (2022) · Interventional Neuroradiology · doi:10.1177/15910199221133164 · Cited by 1 · see citing works
Advances in Stroke: Genetics, Genomics, Precision Medicine
Dichgans, M., & Meschia, J. F. (2022) · Stroke · doi:10.1161/strokeaha.122.039305 · Cited by 1 · see citing works
Huang, H., Zhang, C., Kong, X., Min, Z., Peng, M., Xu, H., Yin, X., Zhang, Z., & Jiang, L. (2026) · European Journal of Radiology · doi:10.1016/j.ejrad.2026.113064
Fang, L., Zhou, Y., Yang, J., et al. (2026) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2026.109220
Plasma choline and betaine and neurological function trajectory after acute ischemic stroke
Zong, Z., Zhou, C., Guo, H., et al. (2026) · BMC Neurology · doi:10.1186/s12883-026-05132-9
Glial fibrillary acidic protein: a potential blood biomarker for acute ischemic stroke
Taha, Y., Soliman, R., ElAziz, A. A., Ahmed, A., & ElMonem, N. A. A. (2026) · The Egyptian Journal of Neurology Psychiatry and Neurosurgery · doi:10.1186/s41983-026-01176-3
Lin, C.-W., Wang, W., Huang, J.-L., Wu, S.-H., Lin, C.-Y., Lin, C.-Y., & Wang, C. C. N. (2026) · Cerebrovascular Diseases Extra · doi:10.1159/000552048
Zheng, X., Yang, Z., Wu, H., Zhao, M., Que, C., Xiong, X., Mu, Y., Zhang, G., Kang, L., Gao, Y., et al. (2026) · Frontiers in Medicine · doi:10.3389/fmed.2026.1754648
Eddy, R., Marcel, G., Jakir, J. H., et al. (2026) · Brain Network Disorders · doi:10.1016/j.bnd.2025.12.005
Yuan, Y., Cai, W., Feng, Y., et al. (2026) · Frontiers in Neurology · doi:10.3389/fneur.2026.1686413
Croese, R., Santing, J. A. L., Jellema, K., et al. (2026) · Acta Neurologica Belgica · doi:10.1007/s13760-025-02942-5
Lee, J., Ohn, S. H., Jang, Y. W., Chang, W. H., Park, K. D., & Kim, D. Y. (2026) · Yonsei Medical Journal · doi:10.3349/ymj.2025.0603
Self-citationRare Variant Association Analysis Uncovers Involvement of VNN2 in Stroke Outcome
Alcaide-Consuegra, E., Mola-Caminal, M., Escaramís, G., et al. (2025) · Stroke · doi:10.1161/strokeaha.124.049365
Self-citationEffect of COMT Val158Met Polymorphism on Stroke Functional Outcome and Recovery
Liang, J., Xu, M., Wang, X., Li, H., Luo, X., Christoforou, A., & Wang, Q. M. (2025) · Neurorehabilitation and neural repair · doi:10.1177/15459683251340926
Cheng, S., Wei, Y., Zheng, H., Zhang, Q., Yang, X., Lü, Z., Shi, Y., Zhang, J., Guo, C., Liao, X., et al. (2025) · medRxiv · doi:10.1101/2025.05.11.25326629
Predicting language outcome after stroke using machine learning: in search of the big data benefit
Saranti, M., Neville, D., White, A., Rotshtein, P., Hope, T. M. H., Price, C. J., & Bowman, H. (2025) · NeuroImage Clinical · doi:10.1016/j.nicl.2025.103858
Rare Variant Association Analysis Uncovers Involvement of VNN2 in Stroke OutcomePreprint
Alcaide-Consuegra, E., Mola-Caminal, M., Escaramís, G., et al. (2024) · medRxiv · doi:10.1101/2024.09.18.24313937
Self-citationNada, M. M., Kasem, S. M., Fahim, M., et al. (2022) · Benha Journal of Applied Sciences · doi:10.21608/bjas.2022.292769
Cullell, N., Soriano‐Tárraga, C., Gallego-Fábrega, C., Cárcel‐Márquez, J., Muiño, E., Llucià‐Carol, L., Lledós, M., Esteller, M., de Moura, M. C., Montaner, J., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1677106/v1
Self-citationStroke recovery phenotyping through network trajectory approaches and graph neural networksPreprint
Krishnagopal, S., Lohse, K. R., & Braun, R. G. (2021) · medRxiv · doi:10.1101/2021.09.29.21264313
- Authors
- Heitsch, L., Ibanez, L., Carrera, C., Binkley, M. M., Strbian, D., Tatlisumak, T., Bustamante, A., Ribó, M., Molina, C., Dávalos, A., López-Cancio, E., Muñoz-Narbona, L., Soriano-Tárraga, C., Giralt-Steinhauer, E., Obach, V., Slowik, A., Pera, J., Lapicka-Bodzioch, K., Derbisz, J., Sobrino, T., Castillo, J., Campos, F., Rodríguez-Castro, E., Arias-Rivas, S., Segura, T., Serrano-Heras, G., Vives-Bauza, C., Díaz-Navarro, R., Tur, S., Jimenez, C., Martí-Fàbregas, J., Delgado-Mederos, R., Arenillas, J., Krupinski, J., Cullell, N., Torres-Aguila, N. P., Muiño, E., Cárcel-Márquez, J., Moniche, F., Cabezas, J. A., Ford, A. L., Dhar, R., Roquer, J., Khatri, P., Jiménez-Conde, J., Fernandez-Cadenas, I., Montaner, J., Rosand, J., Cruchaga, C., Lee, J.-M., & on behalf of the International Stroke Genetics Consortium
- Affiliations
- Washington University in St. Louis (US)
- Department of Psychiatry (L.I., C. Cruchaga), Washington University School of Medicine, St Louis, MO.
- Universitat Autònoma de Barcelona (ES)
- Helsinki University Hospital (FI)
- Hospital Universitari Germans Trias i Pujol (ES)
- Department of Neurology, Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain (E.L.-C.).
- Institut Hospital del Mar d’Investigacions Mediques (IMIM), Barcelona, Spain (L.M.-N., C.S.-T., E.G.-S., J.R., J.J.-C.).
- Department of Neuroscience, Hospital Clinic, University of Barcelona and August Pi I Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain (V.O.).
- Department of Neurology (A.S., J.P., J.D.), Jagiellonian University Medical College, Krakow, Poland.
- Jagiellonian University (PL)
- Universidade de Santiago de Compostela (ES)
- Clinical Neurosciences Research Laboratory, Health Research Institute of Santiago de Compostela, Hospital Clinico Universitario, Universidade de Santiago de Compostela, Spain (T.S., J.C., F.C., E.R.-C., S.A.-R.).
- Department of Neurology, Hospital Universitario de Albacete, Spain (T.S., G.S.-H.).
- Department of Neurology, Son Espases University Hospital, IdISBa, Palma de Mallorca, Spain (C.V.-B., R.D.-N., S.T., C.J.).
- Health Research Institute of the Balearic Islands (ES)
- Department of Neurology, Hospital de la Santa Creu I Sant Pau, Barcelona, Spain (J.M.-F., R.D.-M.).
- Hospital Clínico Universitario de Valladolid (ES)
- Department of Neurology, Hospital Mutua de Terrassa, Spain (J.K., I.F.-C.).
- Stroke Pharmacogenomics and Genetics, Fundacio Docencia I Recerca Mutua de Terrassa, Spain (N.C., E.M., J.C.-M., I.F.-C.).
- Stroke Pharmacogenomics and Genetics, Sant Pau Institute of Research, Sant Pau Hospital, Barcelona, Spain (N.C., N.P.T.-A., E.M., J.C.-M.).
- Hospital de Sant Pau (ES)
- Hospital Universitario Virgen del Rocío (ES)
- Harvard University (US)
- University of Cincinnati (US)
- Hospital Del Mar (ES)
- Neurovascular Research Laboratory and Neurovascular Unit, Vall d’Hebron Institute of Research (VHIR) (C. Carrera, A.B., I.F.-C., J.M.), Universitat Autonoma de Barcelona, Spain.
- Corresponding author
- Cruchaga, Carlos
- ORCID
- Heitsch, Laura
- Carrera, Caty
- Binkley, Michael M.
- Strbian, Daniel
- Tatlisumak, Turgut
- Bustamante, Alejandro
- Ribó, Marc
- Molina, Carlos
- Dávalos, Antoni
- López-Cancio, Elena
- Muñoz-Narbona, Lucia
- Pera, Joanna
- Sobrino, Tomás
- Castillo, José
- Campos, Francisco
- Arias-Rivas, Susana
- Segura, Tomas
- Serrano-Heras, Gemma
- Martí-Fàbregas, Joan
- Arenillas, Juan
- Torres-Aguila, Nuria P.
- Muiño, Elena
- Moniche, Francisco
- Cabezas, Juan A.
- Ford, Andria L.
- Dhar, Rajat
- Roquer, Jaume
- Khatri, Pooja
- Jiménez-Conde, Jordi
- Fernandez-Cadenas, Israel
- Montaner, Joan
- Rosand, Jonathan
- Cruchaga, Carlos
- Lee, Jin-Moo
- Venue
- Stroke
- Published
- 2021-01
- Volume
- 52
- Issue
- 1
- Pages
- 132-141
- ISSN
- 0039-2499 (ISSN-L)
- 1524-4628
- PMC
- PMC7769959
- OpenAlex
- W3112147170
- Cited by
- 70
- References
- 41
- Citations by year
- 2026: 11 · 2025: 16 · 2024: 8 · 2023: 8 · 2022: 22 · 2021: 4 · 2020: 1
- FWCI
- 6.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Stroke (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RISalud Institutional Health Repository of Andalucía (submittedVersion, other-oa)
- Jagiellonian University Repository (Jagiellonian University) (submittedVersion, other-oa)
- Funders
- National Institute on Aging (P50AG005681, P30AG066444)
- National Heart, Lung, and Blood Institute (R01HL129241)
- National Institute of Neurological Disorders and Stroke (R01NS085419, K23NS099487, K23NS099440, U24NS107230)
- Topics
- Health Sciences › Medicine › Epidemiology › Acute Ischemic Stroke Management
- Health Sciences › Medicine › Neurology › Intracerebral and Subarachnoid Hemorrhage Research
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cerebrovascular and Carotid Artery Diseases
- Keywords
- acute ischemic stroke, functional outcome, large vessel occlusion, alteplase, tissue plasminogen activator, recanalization, hemorrhagic transformation, stroke prognosis, modified Rankin Scale, glucose, systolic blood pressure, age, stroke phenotypes
- MeSH terms
- Ischemic Stroke, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Severity of Illness Index, Recovery of Function
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