저작근 근전도에 관한 정상교합자와 ii급 부정교합자의 비교 연구

National Institute of Neurological Disorders and Stroke

Clinicians rate the patient’s prognosis for functional recovery as the most important factor when considering discharge destination from the acute setting. The prognosis and discharge destination are typically based on clinical impression, incorporating clinical and demographic factors such as stroke severity and age. However, clinicians cannot know whether the prognoses they make at the acute stage are correct if they do not routinely assess each of their patients several months later. Furthermore, this gestalt approach can produce differing opinions about prognosis and these seem to produce variation in discharge planning. Data from >31 000 stroke patients discharged from >900 acute hospitals in the United States revealed a 3-fold variation in the rates of discharge to inpatient rehabilitation and skilled nursing facilities, even when casemix and the availability of these facilities were accounted for. Together, these studies indicate that clinicians’ prognoses are an important source of variation and may contribute to inequitable access to rehabilitation services. Both studies identify the need for standardized tools to support less variable and more equitable decision-making. There are several validated scoring systems for predicting the likelihood that a patient will have a good or poor outcome based on the modified Rankin Scale (mRS), and these are compared and reviewed elsewhere. The mRS is a 7-point ordinal scale ranging from a score of 0 for no symptoms to a score of 6 for death. Outcome is typically binarized, where good means independent with a mRS score ≤2, and poor means dependent or dead with a mRS score ≥3. Scores used to predict this binary outcome are typically comprised of factors including patient age and stroke severity on admission. Some scores also include comorbidities and prestroke level of function measured with the mRS. The total number of factors is usually around 5 but can range from 4 to 13. These scales are freely available and can outperform clinicians’ predictions; however, they are not widely used in clinical practice. This might be partly because of challenges associated with implementing them in routine care. Another possibility is that a binarized good or poor outcome prediction might not be particularly useful and is therefore not sought after by clinical teams. Tools that predict outcomes for specific body functions or activities might be more useful than scales that predict a binarized good or poor outcome. The aims of this topical narrative review are to summarize factors known to predict functional outcomes and to identify and critique any available prediction scores, decision trees, and algorithms that could be used to guide stroke rehabilitation.

https://ahajournals.org/doi/pdf/10.1161/STROKEAHA.119.025696

Prediction Tools for Stroke Rehabilitation

Whether recent changes in demographic characteristics and therapeutic technologies have altered stroke outcomes remains unknown.To determine secular changes in initial neurological severity and short-term functional outcomes of patients with acute stroke by sex using a large population.This nationwide, hospital-based, multicenter, prospective registry cohort study used the Japan Stroke Data Bank and included patients who developed acute stroke from January 2000 through December 2019. Patients with stroke, including ischemic and hemorrhagic strokes, who registered within 7 days after symptom onset were studied. Modified Rankin Scale scores were assessed at hospital discharge for all patients.Time.Initial severity was assessed by the National Institutes of Health Stroke Scale for ischemic stroke and intracerebral hemorrhage and by the World Federation of Neurological Surgeons grading for subarachnoid hemorrhage. Outcomes were judged as favorable if the modified Rankin Scale score was 0 to 2 and unfavorable if 5 to 6.Of 183 080 patients, 135 266 (53 800 women [39.8%]; median [IQR] age, 74 [66-82] years) developed ischemic stroke, 36 014 (15 365 women [42.7%]; median [IQR] age, 70 [59-79] years) developed intracerebral hemorrhage, and 11 800 (7924 women [67.2%]; median [IQR] age, 64 [53-75] years) developed subarachnoid hemorrhage. In all 3 stroke types, median ages at onset increased, and the National Institutes of Health Stroke Scale and World Federation of Neurological Surgeons scores decreased throughout the 20-year period on multivariable analysis. In ischemic stroke, the proportion of favorable outcomes showed an increase over time after age adjustment (odds ratio [OR], 1.020; 95% CI, 1.015-1.024 for women vs OR, 1.015; 95% CI, 1.011-1.018 for men) but then stagnated, or even decreased in men, on multivariate adjustment including reperfusion therapy (OR, 0.997; 95% CI, 0.991-1.003 for women vs OR, 0.990; 95% CI, 0.985-0.994 for men). Unfavorable outcomes and in-hospital deaths decreased in both sexes. In intracerebral hemorrhage, favorable outcomes decreased in both sexes, and unfavorable outcomes and deaths decreased only in women. In subarachnoid hemorrhage, the proportion of favorable outcomes was unchanged, and that of unfavorable outcomes and deaths decreased in both sexes.In this study, functional outcomes improved in patients with ischemic stroke during the past 20 years in both sexes presumably partly owing to the development of acute reperfusion therapy. The outcomes of patients with hemorrhagic stroke did not clearly improve in the same period. 

Twenty-Year Change in Severity and Outcome of Ischemic and Hemorrhagic Strokes

OBJECTIVE Stroke-associated immunosuppression and inflammation are increasingly recognized as factors triggering infections and thus potentially influencing outcome after stroke. Several studies have demonstrated that elevated neutrophil-to-lymphocyte ratio (NLR) is a significant predictor of adverse outcomes for patients with ischemic stroke or intracerebral hemorrhage. Thus far, in patients with subarachnoid hemorrhage the association between NLR and outcome is insufficiently established. The authors sought to investigate the association between NLR on admission and functional outcome in aneurysmal subarachnoid hemorrhage (aSAH). METHODS This observational study included all consecutive aSAH patients admitted to a German tertiary center over a 5-year period (2008-2012). Data regarding patient demographics and clinical, laboratory, and in-hospital measures, as well as neuroradiological data, were retrieved from institutional databases. Functional outcome was assessed at 3 and 12 months using the modified Rankin Scale (mRS) score and categorized into favorable (mRS score 0-2) and unfavorable (mRS score 3-6). Patients' radiological and laboratory characteristics were compared between aSAH patients with favorable and those with unfavorable outcome at 3 months. In addition, multivariate analysis was conducted to investigate parameters independently associated with favorable outcome. Receiver operating characteristic (ROC) curve analysis was undertaken to identify the best cutoff for NLR to discriminate between favorable and unfavorable outcome in these patients. To account for imbalances in baseline characteristics, propensity score matching was carried out to assess the influence of NLR on outcome measures. RESULTS Overall, 319 patients with aSAH were included. Patients with unfavorable outcome at 3 months were older, had worse clinical status on admission (Glasgow Coma Scale score and Hunt and Hess grade), greater amount of subarachnoidal and intraventricular hemorrhage (modified Fisher Scale grade and Graeb score), and higher rates of infectious complications (pneumonia and sepsis). A significantly higher NLR on admission was observed in patients with unfavorable outcome according to mRS score (median [IQR] NLR 5.8 [3.0-10.0] for mRS score 0-2 vs NLR 8.3 [4.5-12.6] for mRS score 3-6; p < 0.001). After adjustments, NLR on admission remained a significant predictor for unfavorable outcome in SAH patients (OR [95% CI] 1.014 [1.001-1.027]; p = 0.028). In ROC analysis, an NLR of 7.05 was identified as the best cutoff value to discriminate between favorable and unfavorable outcome (area under the curve = 0.614, p < 0.001, Youden's index = 0.211; mRS score 3-6: 94/153 [61.4%] for NLR ≥ 7.05 vs 67/166 [40.4%] for NLR < 7.05; p < 0.001). Subanalysis of patients with NLR levels ≥ 7.05 vs < 7.05, performed using 2 propensity score-matched cohorts (n = 133 patients in each group), revealed an increased proportion of patients with unfavorable functional outcome at 3 months in patients with NLR ≥ 7.05 (mRS score 3-6 at 3 months: NLR ≥ 7.05 82/133 [61.7%] vs NLR < 7.05 62/133 [46.6%]; p = 0.014), yet without differences in mortality at 3 months (NLR ≥ 7.05 37/133 [27.8%] vs NLR < 7.05 27/133 [20.3%]; p = 0.131). CONCLUSIONS Among aSAH patients, NLR represents an independent parameter associated with unfavorable functional outcome. Whether the impact of NLR on functional outcome is related to preexisting comorbidities or represents independent causal relationships in the context of stroke-associated immunosuppression should be investigated in future studies.

Neutrophil-to-lymphocyte ratio as an independent predictor for unfavorable functional outcome in aneurysmal subarachnoid hemorrhage.

Objective: To compare the prognostic accuracy of various acute stroke prognostic scales using a large, independent, clinical trials dataset.

Methods: We directly compared 8 stroke prognostic scales, chosen based on focused literature review (Acute Stroke Registry and Analysis of Lausanne [ASTRAL]; iSCORE; iSCORE-revised; preadmission comorbidities, level of consciousness, age, and neurologic deficit [PLAN]; stroke subtype, Oxfordshire Community Stroke Project, age, and prestroke modified Rankin Scale [mRS] [SOAR]; modified SOAR; Stroke Prognosis Instrument 2 [SPI2]; and Totaled Health Risks in Vascular Events [THRIVE]) using individual patient-level data from a clinical trials archive (Virtual International Stroke Trials Archive [VISTA]). We calculated area under receiver operating characteristic curves (AUROC) for each scale against 90-day outcomes of mRS (dichotomized atmRS.2), Barthel Index (.85), and mortality. We performed 2 complementary analyses: the first limited to patients with complete data for all components of all scales (simultaneous) and the second using as many patients as possible for each individual scale (separate). We compared AUROCs and performed sensitivity analyses substituting extreme outcome values for missing data.

Results: In total, 10,777 patients contributed to the analyses. Our simultaneous analyses suggested that ASTRAL had greatest prognostic accuracy for mRS, AUROC 0.78 (95% confidence interval [CI] 0.75–0.82), and SPI2 had poorest AUROC, 0.61 (95%CI 0.57–0.66). Our separate analyses confirmed these results: ASTRAL AUROC 0.79 (95% CI 0.78–0.80 and SPI2 AUROC 0.60 (95% CI 0.59–0.61). On formal comparative testing, there was a significant difference in modified Rankin Scale AUROC between ASTRAL and all other scales. Sensitivity analysis identified no evidence of systematic bias from missing data.

Conclusions: Our comparative analyses confirm differences in the prognostic accuracy of stroke scales. However, even the best performing scale had prognostic accuracy that may not be sufficient as a basis for clinical decision-making.

/pdf/validating-and-comparing-stroke-prognosis-scales-h0hbmnpft9.pdf

Validating and comparing stroke prognosis scales.

Background: There are many prognostic scales that aim to predict functional outcome following acute stroke. Despite considerable research interest, these scales have had limited impact in routine clinical practice. This may be due to perceived problems with internal validity (quality of research), as well as external validity (generalizability of results). We set out to collate information on exemplar stroke prognosis scales, giving particular attention to the scale content, derivation, and validation. Methods: We performed a focused literature search, designed to return high profile scales that use baseline clinical data to predict mortality or disability. We described prognostic utility and collated information on the content, development and validation of the tools. We critically appraised chosen scales based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies (CHARMS). Results: We chose 10 primary scales that met our inclusion criteria, six of which had revised/modified versions. Most primary scales used 5 input variables (range: 4-13), with substantial overlap in the variables included. All scales included age, eight included a measure of stroke severity, while five scales incorporated pre-stroke level of function (often using modified Rankin Scale), comorbidities and classification of stroke type. Through our critical appraisal, we found issues relating to excluding patients with missing data from derivation studies, and basing the selection of model variable on significance in univariable analysis (in both cases noted for six studies). We identified separate external validation studies for all primary scales but one, with a total of 60 validation studies. Conclusions: Most acute stroke prognosis scales use similar variables to predict long-term outcomes and most have reasonable prognostic accuracy. While not all published scales followed best practice in development, most have been subsequently validated. Lack of clinical uptake may relate more to practical application of scales rather than validity. Impact studies are now necessary to investigate clinical usefulness of existing scales.

/pdf/thinking-about-the-future-a-review-of-prognostic-scales-used-a9wl8h1fgm.pdf

Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke.

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Validating and comparing stroke prognosis scales.

Thinking About the Future: A Review of Prognostic Scales Used in Acute Stroke.