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BackgroundThe emergence of SARS-CoV-2 (ie, COVID-19) has given rise to a global pandemic affecting 215 countries and over 40 million people as of October 2020. Meanwhile, we are also experiencing an infodemic induced by the overabundance of information, some accurate and some inaccurate, spreading rapidly across social media platforms. Social media has arguably shifted the information acquisition and dissemination of a considerably large population of internet users toward higher interactivities. ObjectiveThis study aimed to investigate COVID-19-related health beliefs on one of the mainstream social media platforms, Twitter, as well as potential impacting factors associated with fluctuations in health beliefs on social media. MethodsWe used COVID-19-related posts from the mainstream social media platform Twitter to monitor health beliefs. A total of 92,687,660 tweets corresponding to 8,967,986 unique users from January 6 to June 21, 2020, were retrieved. To quantify health beliefs, we employed the health belief model (HBM) with four core constructs: perceived susceptibility, perceived severity, perceived benefits, and perceived barriers. We utilized natural language processing and machine learning techniques to automate the process of judging the conformity of each tweet with each of the four HBM constructs. A total of 5000 tweets were manually annotated for training the machine learning architectures. ResultsThe machine learning classifiers yielded areas under the receiver operating characteristic curves over 0.86 for the classification of all four HBM constructs. Our analyses revealed a basic reproduction number R0 of 7.62 for trends in the number of Twitter users posting health belief–related content over the study period. The fluctuations in the number of health belief–related tweets could reflect dynamics in case and death statistics, systematic interventions, and public events. Specifically, we observed that scientific events, such as scientific publications, and nonscientific events, such as politicians’ speeches, were comparable in their ability to influence health belief trends on social media through a Kruskal-Wallis test (P=.78 and P=.92 for perceived benefits and perceived barriers, respectively). ConclusionsAs an analogy of the classic epidemiology model where an infection is considered to be spreading in a population with an R0 greater than 1, we found that the number of users tweeting about COVID-19 health beliefs was amplifying in an epidemic manner and could partially intensify the infodemic. It is “unhealthy” that both scientific and nonscientific events constitute no disparity in impacting the health belief trends on Twitter, since nonscientific events, such as politicians’ speeches, might not be endorsed by substantial evidence and could sometimes be misleading.

BackgroundIntracerebral hemorrhage (ICH) is the deadliest form of stroke. In observational studies, lower serum magnesium has been linked to more hematoma expansion (HE) and intracranial hemorrhage, implying that supplemental magnesium sulfate is a potential acute treatment for patients with ICH and could reduce HE. FAST-MAG (Field Administration of Stroke Therapy - Magnesium) was a clinical trial of magnesium sulfate started prehospital in patients with acute stroke within 2 hours of last known well enrolled. CT was not required prior to enrollment, and several hundred patients with acute ICH were enrolled. In this ancillary analysis, we assessed the effect of magnesium sulfate treatment upon HE in patients with acute ICH.MethodsWe retrospectively analyzed data that were prospectively collected in the FAST-MAG study. Patients received intravenous magnesium sulfate or matched placebo within 2 hours of onset. We compared HE among patients allocated to intravenous magnesium sulfate or placebo with a Mann-Whitney U. We used the same method to compare neurological deficit severity (National Institutes of Health Stroke Scale) and global disability (modified Rankin Scale) at 3 months.ResultsAmong 268 patients with ICH meeting study entry criteria, mean 65.4±13/4 years, 33% were female, and 211 (79%) had a history of hypertension. Initial deficit severities were median (interquartile range) of 4 (3-5) on the Los Angeles Motor Scale in the field and National Institutes of Health Stroke Scale score of 16 (9.5-25.5) early after hospital arrival. Follow-up brain imaging was performed a median of 17.1 (11.3-22.7) hours after first scan. The magnesium and placebo groups did not statistically differ in hematoma volume on arrival, 10.1 (5.6-28.7) versus 12.4 (5.6-28.7) mL (P=0.6), or HE, 2.0 (0.1-7.4) versus 1.5 (-0.2 to 8) mL (P=0.5). There was no difference in functional outcomes (modified Rankin Scale score of 3-6), 59% versus 50% (P=0.5).ConclusionsMagnesium sulfate did not reduce HE or improve functional outcomes at 90 days. A benefit for patients with initial hypomagnesemia was not addressed.RegistrationURL: https://www.Clinicaltrialsgov; Unique identifier: NCT00059332.

Randomized Controlled Trials (RCTs) are considered the gold standard for measuring the efficacy of medical interventions. However, RCTs are expensive, and use a limited population. Techniques to estimate the effects of stroke interventions from observational data that minimize confounding would be useful. We used regression discontinuity design (RDD), a technique well-established in economics, on the Get With The Guidelines-Stroke (GWTG-Stroke) data set. RDD, based on regression, measures the occurrence of a discontinuity in an outcome (e.g., odds of home discharge) as a function of an intervention (e.g., alteplase) that becomes significantly more likely when crossing the threshold of a continuous variable that determines that intervention (e.g., time from symptom onset, since alteplase is only given if symptom onset is less than e.g., 3 h). The technique assumes that patients near either side of a threshold (e.g., 2.99 and 3.01 h from symptom onset) are indistinguishable other than the use of the treatment. We compared outcomes of patients whose estimated onset to treatment time fell on either side of the treatment threshold for three cohorts of patients in the GWTG-Stroke data set. This data set spanned three different treatment thresholds for alteplase (3 h, 2003-2007, N = 1,869; 3 h, 2009-2016, N = 13,086, and 4.5 h, 2009-2016, N = 6,550). Patient demographic characteristics were overall similar across the treatment thresholds. We did not find evidence of a discontinuity in clinical outcome at any treatment threshold attributable to alteplase. Potential reasons for failing to find an effect include violation of some RDD assumptions in clinical care, large sample sizes required, or already-well-chosen treatment threshold.

ObjectiveTo compare the clinical characteristics and outcomes of primary intracerebral hemorrhage (ICH) with and without methamphetamine exposure.MethodsWe performed a retrospective analysis of patients diagnosed with spontaneous, nontraumatic ICH over a 3-year period between January 2013 and December 2016. Demographics, clinical measures, and outcomes were compared between ICH patients with positive methamphetamine toxicology tests vs those with negative methamphetamine toxicology tests.ResultsMethamphetamine-positive ICH patients were younger than methamphetamine-negative ICH patients (52 vs 67 years, p < 0.001). Patients with methamphetamine-positive ICH had higher diastolic blood pressure (115 vs 101, p = 0.003), higher mean arterial pressure (144 vs 129, p = 0.01), longer lengths of hospital (18 vs 8 days, p < 0.001) and intensive care unit (ICU) stay (10 vs 5 days, p < 0.001), required more days of IV antihypertensive medications (5 vs 3 days, p = 0.02), and had more subcortical hemorrhages (63% vs 46%, p = 0.05). The methamphetamine-positive group had better premorbid modified Rankin Scale (mRS) scores (p < 0.001) and a greater change in functional ability as measured by mRS at the time of hospital discharge (p = 0.001). In multivariate analyses, methamphetamine use predicted both hospital length of stay (risk ratio [RR] 1.54, confidence interval [CI] 1.39-1.70, p < 0.001) and ICU length of stay (RR 1.36, CI 1.18-1.56, p < 0.001), but did not predict poor outcome (mRS 4-6).ConclusionsMethamphetamine use is associated with earlier age at onset of ICH, longer hospital stays, and greater change in functional ability, but did not predict outcome.

Objective: Hematoma expansion (HE) predicts disability and death after acute intracerebral hemorrhage (ICH). Aspirin and anticoagulants have been associated with HE. We tested the hypothesis that P2Y12 inhibitors predict subsequent HE in patients. We explored laboratory measures of P2Y12 inhibition and dual antiplatelet therapy with aspirin (DAPT). Methods: We prospectively identified patients with ICH. Platelet activity was measured with the VerifyNow‐P2Y12 assay. Hematoma volumes for initial and follow‐up CTs were calculated using a validated semi‐automated technique. HE was defined as the difference between hematoma volumes on the initial and follow‐up CT scans. Nonparametric statistics were performed with Kruskal–Wallis H, and correction for multiple comparisons performed with Dunn's test. Results: In 194 patients, 15 (7.7%) were known to take a P2Y12 inhibitor (clopidogrel in all but one). Patients taking a P2Y12 inhibitor had more HE compared to patients not taking a P2Y12 inhibitor (3.5 [1.2–11.9] vs. 0.1 [−0.8–1.4] mL, p = 0.004). Patients taking DAPT experienced the most HE (7.2 [2.6–13.8] vs. 0.0 [−1.0–1.1] mL, p = 0.04). The use of P2Y12 inhibitors was associated with less P2Y12 activity (178 [149–203] vs. 288 [246–319] P2Y12 reaction units, p = 0.005). Interpretation: Patients taking a P2Y12 inhibitor had more HE and less P2Y12 activity. The effect was most pronounced in patients on DAPT, suggesting a synergistic effect of P2Y12 inhibitors and aspirin with respect to HE. Acute reversal of P2Y12 inhibitors in acute ICH requires further study. [ABSTRACT FROM AUTHOR]