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Distribution of individual diseases. The most prevalent comorbidities comprised by the Charlson Comorbidity Index (CCI) were coronary heart disease in 148 (21.1%) patients, diabetes in 85 (12.1%) patients and renal diseases in 73 (10.4%) patients (all left of the vertical line). Not captured by the CCI (right of the vertical line) were arterial hypertension, atrial fibrillation and dyslipidemia, present in 470 (66.9%), 338 (48.1%) and 84 (12.1%) patients. CHD Coronary Heart Disease, AIDS Acquired Immune Deficiency Syndrome
Source publication
Purpose
Comorbidities and polypharmacy are risk factors for worse outcome in stroke. However, comorbidities and polypharmacy are mostly studied separately with various approaches to assess them. We aimed to analyze the impact of comorbidity burden and polypharmacy on functional outcome in acute ischemic stroke (AIS) patients undergoing mechanical t...
Citations
... The standard information checklist includes pre-hospital heart rate, blood pressure, oxygen saturations, blood glucose, temperature and conscious level, so the trial is expected to provide additional evidence about the value of these early basic measures for predicting thrombectomy outcome when LVO is present. Future work in pre-hospital and hospital settings should also consider combining physiological factors with other nonstroke characteristics which may have a bearing on thrombectomy outcome such as frailty, pre-stroke dependency and comorbidities (Adamou et al., 2022;Tan et al., 2022;Barow et al., 2023). Although some have been included in previously published thrombectomy outcome scores (Kremers et al., 2021), especially pre-stroke dependency, it has not yet been demonstrated that they are accurate when used by non-specialist practitioners making early triage decisions towards thrombectomy providers. ...
Introduction
Mechanical thrombectomy results in more favourable functional outcomes for patients with acute large vessel occlusion (LVO) stroke. Key clinical determinants of thrombectomy outcome include symptom severity, age and time from onset to treatment, but associations have also been reported with baseline physiological observations including systolic/diastolic blood pressure (SBP/DBP), blood/serum glucose, atrial fibrillation and conscious level. As these items are routinely available during initial emergency assessment, they might help to inform early prehospital and hospital triage decisions if evidence consistently shows associations with post-thrombectomy outcome. We undertook a meta-analysis of studies reporting pre-thrombectomy physiological observations and functional outcome.
Method
PRISMA guidelines were followed to search electronic bibliographies, select articles and extract data. Medline, PubMed, Cochrane HTA, Cochrane Central and Embase were searched. Included articles were observational or interventional thrombectomy studies published between 01/08/2004-19/04/2023 reporting 3-month modified Rankin Scale, split as favourable (0–2) and unfavourable (3–6). A modified version of the Quality in Prognostic Studies (QUIPS) tool was used to assess risk of bias. RevMan 5 was used to calculate Inverse Variance with Weighted Mean Differences (WMD) and Mantel-Haenszel Odds Ratios (OR) for continuous and categorical factors respectively.
Results
Thirty seven studies were eligible from 8,687 records. Significant associations were found between unfavourable outcome and higher blood/serum glucose as a continuous (WMD = 1.34 mmol/l (95%CI 0.97 to 1.72); 19 studies; n = 3122) and categorical (OR = 2.44 (95%CI 1.9 to 3.14) variable; 6 studies; n = 5481), higher SBP (WMD = 2.98 mmHg (95%CI 0.86 to 5.11); 16 studies; n = 4,400), atrial fibrillation (OR = 1.48 (95%CI 1.08 to 2.03); 3 studies; n = 736), and lower Glasgow Coma Scale (WMD = −2.72 (95%CI −4.01 to −1.44); 2 studies; n = 99). No association was found with DBP (WMD = 0.36 mmHg (95%CI −0.76 to 1.49); 13 studies; n = 3,614).
Conclusion
Basic physiological observations might assist early triage decisions for thrombectomy and could be used in combination with other information to avoid futile treatment and ambulance transfers. It is important to acknowledge that data were only from thrombectomy treated patients in hospital settings and it cannot be assumed that the predictors identified are independent or that modification can change outcome. Further work is needed to establish the optimal combination of prognostic factors for clinical care decisions.
... Our findings also suggest that the presence of comorbidities was associated with the course of LSA after stroke-with higher LSA scores in those with fewer (0-1 vs ≥ 2) comorbidities. To the best of our knowledge, there are no previous reports on the association between comorbidities and life-space mobility in patients after stroke; however, comorbidities have repeatedly been shown to be prognostic of functional recovery, participation in life situations and survival post-stroke [4,[47][48][49][50]. The presence of comorbidities in patients after stroke may affect life-space mobility through various biopsychosocial pathways; besides potentially causing additional physical, cognitive or perceptual deficits, they may also contribute to an increased psychological distress [51] as well as physical and mental fatigue [52]. ...
Background
Life-space mobility is defined as the size of the area in which a person moves about within a specified period of time. Our study aimed to characterize life-space mobility, identify factors associated with its course, and detect typical trajectories in the first year after ischemic stroke.
Methods
MOBITEC-Stroke (ISRCTN85999967; 13/08/2020) was a cohort study with assessments performed 3, 6, 9 and 12 months after stroke onset. We applied linear mixed effects models (LMMs) with life-space mobility (Life-Space Assessment; LSA) as outcome and time point, sex, age, pre-stroke mobility limitation, stroke severity (National Institutes of Health Stroke Scale; NIHSS), modified Rankin Scale, comorbidities, neighborhood characteristics, availability of a car, Falls Efficacy Scale-International (FES-I), and lower extremity physical function (log-transformed timed up-and-go; TUG) as independent variables. We elucidated typical trajectories of LSA by latent class growth analysis (LCGA) and performed univariate tests for differences between classes.
Results
In 59 participants (mean age 71.6, SD 10.0 years; 33.9% women), mean LSA at 3 months was 69.3 (SD 27.3). LMMs revealed evidence (p ≤ 0.05) that pre-stroke mobility limitation, NIHSS, comorbidities, and FES-I were independently associated with the course of LSA; there was no evidence for a significant effect of time point. LCGA revealed three classes: “low stable”, “average stable”, and “high increasing”. Classes differed with regard to LSA starting value, pre-stroke mobility limitation, FES-I, and log-transformed TUG time.
Conclusion
Routinely assessing LSA starting value, pre-stroke mobility limitation, and FES-I may help clinicians identify patients at increased risk of failure to improve LSA.
Создание руководства поддержано Советом по терапевтическим наукам отделения клинической медицины Российской академии наук.
