Data_Sheet_1_Association between blood viscosity and early neurological deterioration in lacunar infarction.docx

BackgroundUnderstanding the factors related to early neurologic deterioration (END) is crucial in the management of patients with lacunar infarction. Blood viscosity is a significant factor for microvascular perfusion. We investigated the association between blood viscosity and occurrence of END in lacunar infarction.MethodsWe included consecutive patients admitted for lacunar infarction within 72 h from symptoms onset. END was defined as an increase in the National Institute of Health Stroke Scale (NIHSS) score ≥2 within 24 h of admission. Viscosity was measured within 24 h of hospitalization with a scanning capillary tube viscometer. Viscosity measured at a shear rate of 300 s−1 was defined as systolic blood viscosity (SBV), whereas that measured at a shear rate of 5 s−1 as diastolic blood viscosity (DBV).ResultsOf the 178 patients included (median age, 65.5; interquartile range [IQR], 56.0, 76.0], END occurred in 33 (18.5%). DBV was significantly higher in patients with END than those without END (13.3 mPa·s [IQR 11.8, 16.0] vs. 12.3 mPa·s [IQR11.0, 13.5]; P = 0.023). In the multivariate analysis, DBV was independently associated with the occurrence of END (odds ratio 1.17; 95% confidence interval 1.01–1.36; P = 0.043). Subgroup analysis showed no heterogeneity in the effect of viscosity on the occurrence of END.ConclusionsBlood viscosity at a low shear rate (DBV) was associated with the occurrence of END in patients with lacunar infarction. Blood rheology may be important in pathophysiology of END in patients with lacunar infarction.</p

Data_Sheet_1_Early depression screening and short-term functional outcome in hospitalized patients for acute ischemic stroke.docx

BackgroundPatients with ischemic stroke are at high risk for post-stroke depression (PSD). There are limited data regarding the clinical impact of early PSD, assessed in hospitalized patients with acute ischemic stroke.MethodsThis hospital-based observational cohort study included consecutive patients with acute ischemic stroke or transient ischemic attack between July 2019 and June 2021. In the study hospital, all admitted patients were systematically screened for depression. The depression was screened using the Patient Health Questionnaire-9 (PHQ-9), and PHQ-9 positivity indicated early PSD, which was defined as a score of >4. Logistic regression analyses were used to compare the rates of poor functional outcomes at 3 months in patients with and without PHQ-9 positivity.ResultsAmong 1339 patients admitted during the study period, 775 were included, with a median age of 68.0 years, and 316 (40.8%) were women. A total of 111 (14.3%) patients were PHQ-9 positive. History of cancer and early neurological deterioration were independently associated with PHQ-9 positivity. Poor functional outcomes at 3 months were observed in 147 patients (18.8%). PHQ-9 positivity independently showed a 2.2-fold increased risk of poor functional outcome at 3 months (Odds ratio 2.23; 95% confidence interval 1.05–4.73, P = 0.037).ConclusionsPatients with history of cancer and early neurological deterioration were at risk for early PSD. Early PSD was independently associated with poor functional outcomes at 3 months. The identification of early depression could offer opportunities for further questioning and exploration of symptoms, as well as interventions.</p

Data_Sheet_1_Impact of Sarcopenia on Functional Outcomes Among Patients With Mild Acute Ischemic Stroke and Transient Ischemic Attack: A Retrospective Study.docx

IntroductionSarcopenia, a age-related disease characterized by loss of muscle mass accompanied by loss of function, is associated with nutrition imbalance, physical inactivity, insulin resistance, inflammation, metabolic syndrome, and atherosclerosis which are risk factors for cardiovascular disease. However, its association with outcomes after ischemic stroke has not been well-established. This study investigated whether functional outcomes of patients with acute ischemic stroke is associated with sarcopenia.MethodsData were collected from 568 consecutive patients with acute ischemic stroke with National Institute of Health Stroke Scale 0–5 or transient ischemic attack who underwent bioelectrical impedance analysis between March 2018 and March 2021. Sarcopenia was defined, as low muscle mass, as measured by bioelectrical impedance analysis, and low muscle strength, as indicated by the Medical Research Council score. Unfavorable functional outcome was defined as mRS score of 2–6 at 90 days after discharge. The relationship between functional outcomes and the presence of sarcopenia or its components was determined.ResultsOf the 568 patients included (mean age 65.5 ± 12.6 years, 64.6% male), sarcopenia was detected in 48 (8.5%). After adjusting for potential confounders, sarcopenia was independently and significantly associated with unfavorable functional outcome (odds ratio 2.37, 95% confidence interval 1.15–4.73 for unfavorable functional outcome, odds ratio 2.10, 95% confidence interval 1.18–3.71 for an increase in the mRS score). Each component of sarcopenia was also independently associated with unfavorable functional outcome (odds ratio 1.76, 95% confidence interval 1.05–2.95 with low muscle mass, odds ratio 2.64, 95% confidence interval 1.64–4.23 with low muscle strength). The impact of low muscle mass was larger in men than in women, and in patients with lower muscle mass of the lower extremities than in those with lower muscle mass of the upper extremities.ConclusionsIn this study, the prevalence of sarcopenia in patients with stroke was lower than most of previous studies and patients with sarcopenia showed higher likelihood for unfavorable functional outcomes at 90 days after acute ischemic stroke or TIA. Further investigation of the interventions for treating sarcopenia and its impact on the outcome of ischemic stroke patients is needed.</p

Diagnostic performance of disseminated intravascular coagulation (DIC) diagnostic classifiers in this study.

Diagnostic performance of disseminated intravascular coagulation (DIC) diagnostic classifiers in this study.</p

Laboratory results for full DIC profile parameters.

Laboratory results for full DIC profile parameters.</p

Machine learning-based diagnosis for disseminated intravascular coagulation (DIC): Development, external validation, and comparison to scoring systems

<div><p>The major challenge in the diagnosis of disseminated intravascular coagulation (DIC) comes from the lack of specific biomarkers, leading to developing composite scoring systems. DIC scores are simple and rapidly applicable. However, optimal fibrin-related markers and their cut-off values remain to be defined, requiring optimization for use. The aim of this study is to optimize the use of DIC-related parameters through machine learning (ML)-approach. Further, we evaluated whether this approach could provide a diagnostic value in DIC diagnosis. For this, 46 DIC-related parameters were investigated for both clinical findings and laboratory results. We retrospectively reviewed 656 DIC-suspected cases at an initial order for full DIC profile and labeled their evaluation results (Set 1; DIC, n = 228; non-DIC, n = 428). Several ML algorithms were tested, and an artificial neural network (ANN) model was established via independent training and testing using 32 selected parameters. This model was externally validated from a different hospital with 217 DIC-suspected cases (Set 2; DIC, n = 80; non-DIC, n = 137). The ANN model represented higher AUC values than the three scoring systems in both set 1 (ANN 0.981; ISTH 0.945; JMHW 0.943; and JAAM 0.928) and set 2 (AUC ANN 0.968; ISTH 0.946). Additionally, the relative importance of the 32 parameters was evaluated. Most parameters had contextual importance, however, their importance in ML-approach was different from the traditional scoring system. Our study demonstrates that ML could optimize the use of clinical parameters with robustness for DIC diagnosis. We believe that this approach could play a supportive role in physicians’ medical decision by integrated into electrical health record system. Further prospective validation is required to assess the clinical consequence of ML-approach and their clinical benefit.</p></div

Relative importance of clinical and laboratory variables in the ANN model.

In the developed ANN model, 32 variables are used and their relative importance is calculated based on the weight value, reflecting connectivity of neurons, using ‘Connection Weight’ approach to provide explanatory insights for each variable. (Total sum: 100%, average importance: 3.13%).</p

Heat map presentation of the datasets used in this study.

<p>The x-axis denotes individual cases and the y-axis corresponds to the clinical variables. Each cell shows values of variables for each case. All cases are sorted horizontally by the labeled DIC status and predicted ANN model values. Rows 2–5 (ANN model, ISTH, JMHW, and JAAM criteria) show predictions of different DIC diagnostic classifiers based on the cut-off values (0.501 for ANN) or points (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0195861#pone.0195861.t001" target="_blank">Table 1</a>).</p

Diagnostic performance of ANN model and scoring systems with receiver operating characteristic curve analysis and density plot.

<p>(A) Training (Set 1): ANN model shows the best performance among the four diagnostic classifiers. The area under curve (AUC) values: ANN (0.981), ISTH (0.945), JMHW (0.943), and JAAM (0.928). (B) External validation (Set 2): four variables were unavailable owing to the different hematologic analyzers, therefore the AUC value was compromised compared to the development set in the ANN model; ANN (0.968), ISTH (0.946). (C, D) Density plots of two represented diagnostic classifiers (ANN model, ISTH criteria) shows that the ANN model far obviously differentiates two groups (DIC and non-DIC). The cut-off value for the ANN model is determined at 0.501.</p

Diagnostic scoring systems for disseminated intravascular coagulation (DIC) used in this study.

<p>Diagnostic scoring systems for disseminated intravascular coagulation (DIC) used in this study.</p