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A nomogram to predict cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients: A retrospective cohort study.

ABSTRACT: To establish a nomogram model to predict early cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients.A retrospective cohort study was held between January 2016 and October 2018. One hundred twenty seven out of 170 consecutive patients with supratentorial spontaneous intracranial hematoma were enrolled in this study. They were divided into development (n?=?92) and validation (n?=?35) dataset according to their admission time. Mini-mental State Examination (MMSE) was conducted between the third and the sixth month after the onset of stroke. MMSE ? 24 was considered as cognitive impairment. Univariate and multivariate logistic regression was used to screen for independent risk factors which correlate with cognitive impairment on the development dataset. A nomogram was built based on Akaike Information Criterion (AIC). Receiver operating characteristic (ROC) curve and calibration curve on development and validation dataset was drawn with each area under the curves (AUC) calculated. The decision curve analysis was also conducted with the development dataset.The bleeding volume, Glasgow Coma Scale (GCS), and intraventricular hemorrhage (IVH) are the most significant risk factors which may cause cognitive impairment both in the univariate and multivariate analysis. The finial model performed good discrimination ability on both development and validation dataset with AUC 0.911 and 0.919. Most patients would benefit from the model according to the decision curve analysis.A nomogram, constructed based on bleeding volume, GCS, and IVH can provide a feasible tool to evaluate cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients.

SUBMITTER: Gong K

PROVIDER: S-EPMC6824656 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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A nomogram to predict cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients: A retrospective cohort study.

Gong Kai K Zhao Lizheng L Guo Jianfeng J Wang Zhanxiang Z

Medicine 20191001 42

To establish a nomogram model to predict early cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients.A retrospective cohort study was held between January 2016 and October 2018. One hundred twenty seven out of 170 consecutive patients with supratentorial spontaneous intracranial hematoma were enrolled in this study. They were divided into development (n = 92) and validation (n = 35) dataset according to their admission time. Mini-mental State Examination ( ...[more]

PMID: 31626144

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Project description:INTRODUCTION:Trials in Alzheimer's disease are increasingly focusing on prevention in asymptomatic individuals. We hypothesized that indicators of mild cognitive impairment (MCI) may be present in the content of spoken language in older adults and be useful in distinguishing those with MCI from those who are cognitively intact. To test this hypothesis, we performed linguistic analyses of spoken words in participants with MCI and those with intact cognition participating in a clinical trial. METHODS:Data came from a randomized controlled behavioral clinical trial to examine the effect of unstructured conversation on cognitive function among older adults with either normal cognition or MCI (ClinicalTrials.gov: NCT01571427). Unstructured conversations (but with standardized preselected topics across subjects) were recorded between interviewers and interviewees during the intervention sessions of the trial from 14 MCI and 27 cognitively intact participants. From the transcription of interviewees recordings, we grouped spoken words using Linguistic Inquiry and Word Count (LIWC), a structured table of words, which categorizes 2500 words into 68 different word subcategories such as positive and negative words, fillers, and physical states. The number of words in each LIWC word subcategory constructed a vector of 68 dimensions representing the linguistic features of each subject. We used support vector machine and random forest classifiers to distinguish MCI from cognitively intact participants. RESULTS:MCI participants were distinguished from those with intact cognition using linguistic features obtained by LIWC with 84% classification accuracy which is well above chance 60%. DISCUSSION:Linguistic analyses of spoken language may be a powerful tool in distinguishing MCI subjects from those with intact cognition. Further studies to assess whether spoken language derived measures could detect changes in cognitive functions in clinical trials are warrented.

Project description:BackgroundIntraventricular hemorrhage (IVH) after intracerebral hemorrhage (ICH) is a strong independent predictor of poor outcomes. Although the location and volume of ICH are associated with IVH, our knowledge concerning the mechanism of IVH after ICH is still limited. This study aimed to investigate the relationship between hematoma morphology and IVH in patients with supratentorial deep ICH.MethodsWe retrospectively analyzed adult patients (aged ≥18 years) with spontaneous supratentorial deep ICH who underwent computed tomography (CT) within 48 h after ICH symptom onset in Peking University First Hospital between January 2017 and August 2022. We collected the clinical and imaging data of the patients and assessed hematoma morphology using several quantitative radiological parameters including hematoma volume, sphericity index, A/B ratio (A: the largest area of hematoma; B: the largest diameter 90° to A on the same slice), and our newly proposed largest diameter-midline angle (LMA). Multivariable logistic regression analysis was used to analyze the relationship between these parameters and the presence of IVH on the initial CT scan.ResultsAmong 114 patients with spontaneous supratentorial deep ICH, 41 (36.0%) had IVH. In patients with IVH, the sphericity index was lower than that in individuals without IVH, while the LMA was larger. Multivariate logistic regression analysis showed that sphericity index [0.1-unit odds ratio (OR) =0.252; 95% CI: 0.089-0.709; P=0.009] and the LMA (10-unit OR =1.281; 95% CI: 1.007-1.630; P=0.04) were independently associated with the presence of IVH in patients with supratentorial deep ICH. Univariate analyses showed that hematoma volume, A/B ratio, sphericity index, and the LMA were significantly associated with poor outcomes at discharge.ConclusionsTwo quantitative parameters of hematoma morphology, sphericity index and the LMA, were significantly associated with the presence of IVH in patients with supratentorial deep ICH. Further prospective studies with larger sample sizes are needed to validate our results.

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A nomogram to predict cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients: A retrospective cohort study.

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A nomogram to predict cognitive impairment after supratentorial spontaneous intracranial hematoma in adult patients: A retrospective cohort study.

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