A grading scale for surgically treated patients with spontaneous supratentorial intracerebral hemorrhage: the Surgical Swedish ICH Score

2020 ◽  
Vol 133 (3) ◽  
pp. 800-807 ◽  
Author(s):  
Andreas Fahlström ◽  
Henrietta Nittby Redebrandt ◽  
Hugo Zeberg ◽  
Jiri Bartek ◽  
Andreas Bartley ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Intracerebral Hemorrhage ◽  
External Validation ◽  
Grading Scale ◽  
Ich Score ◽  
Gcs Score ◽  
Strength Of Association ◽  
Point Type ◽  
Clinical Grading

OBJECTIVEThe authors aimed to develop the first clinical grading scale for patients with surgically treated spontaneous supratentorial intracerebral hemorrhage (ICH).METHODSA nationwide multicenter study including 401 ICH patients surgically treated by craniotomy and evacuation of a spontaneous supratentorial ICH was conducted between January 1, 2011, and December 31, 2015. All neurosurgical centers in Sweden were included. All medical records and neuroimaging studies were retrospectively reviewed. Independent predictors of 30-day mortality were identified by logistic regression. A risk stratification scale (the Surgical Swedish ICH [SwICH] Score) was developed using weighting of independent predictors based on strength of association.RESULTSFactors independently associated with 30-day mortality were Glasgow Coma Scale (GCS) score (p = 0.00015), ICH volume ≥ 50 mL (p = 0.031), patient age ≥ 75 years (p = 0.0056), prior myocardial infarction (MI) (p = 0.00081), and type 2 diabetes (p = 0.0093). The Surgical SwICH Score was the sum of individual points assigned as follows: GCS score 15–13 (0 points), 12–5 (1 point), 4–3 (2 points); age ≥ 75 years (1 point); ICH volume ≥ 50 mL (1 point); type 2 diabetes (1 point); prior MI (1 point). Each increase in the Surgical SwICH Score was associated with a progressively increased 30-day mortality (p = 0.0002). No patient with a Surgical SwICH Score of 0 died, whereas the 30-day mortality rates for patients with Surgical SwICH Scores of 1, 2, 3, and 4 were 5%, 12%, 31%, and 58%, respectively.CONCLUSIONSThe Surgical SwICH Score is a predictor of 30-day mortality in patients treated surgically for spontaneous supratentorial ICH. External validation is needed to assess the predictive value as well as the generalizability of the Surgical SwICH Score.

Validation of the newly conceived Surgical Swedish ICH grading scale for surgically treated patients with intracerebral hemorrhage: patient series

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Johan A. Haga ◽  
Frantz R. Poulsen ◽  
Axel Forsse
Keyword(s):  
Intracerebral Hemorrhage ◽  
Area Under Curve ◽  
Mortality Rates ◽  
Patient Records ◽  
Patient Series ◽  
Grading Scale ◽  
One Year ◽  
Ich Score ◽  
Receiver Operator Characteristics ◽  
Clinical Grading

BACKGROUNDThe authors sought to externally validate a newly developed clinical grading scale, the Surgical Swedish ICH (SwICH) score. Patients surgically treated for spontaneous supratentorial intracerebral hemorrhage (ICH) from 2009 to 2019 in a single center in Denmark were identified. Data were retrospectively collected from patient records and neuroimaging. Surgical SwICH and ICH scores were calculated for each patient, and the validity of the Surgical SwICH was assessed and compared.OBSERVATIONSThe 126 patients included had an overall 30-day mortality rate of 23%. All patients with a Surgical SwICH score of 0 survived past one year. No patient scored the maximum Surgical SwICH score of 6. The 30-day mortality rates for Surgical SwICH scores 1, 2, 3, and 4 were 0%, 20%, 53%, and 25%, respectively (p <0.0001 for trend). Mortality rates for ICH scores 1, 2, 3, and 4 were 0%, 11%, 33%, and 76%, respectively (p <0.001 for trend). Receiver operator characteristics showed an area under curve of 0.78 for the Surgical SwICH score and 0.80 for the ICH score (p = 0.21 difference).LESSONSThe Surgical SwICH score was a good predictor of 30-day mortality in patients surgically treated for spontaneous supratentorial ICH. However, the Surgical SwICH score did not outperform the previously established ICH score in predicting 30-day mortality.

scholarly journals 30-days’ outcome of haemorrhagic stroke: correlation between intracerebral hemorrhage score and modified Rankin score

Mediscope ◽  
2018 ◽  
Vol 5 (1) ◽  
pp. 10-14
Author(s):  
AH Sarder ◽  
BK Das ◽  
KJ Mondal ◽  
MA Kabir ◽  
B Basu ◽  
...  
Keyword(s):  
Intracerebral Hemorrhage ◽  
Outcome Prediction ◽  
Prediction Models ◽  
Haemorrhagic Stroke ◽  
Tertiary Hospital ◽  
Modified Rankin Scale ◽  
Grading Scale ◽  
Ich Score ◽  
Clinical Grading

Intracerebral hemorrhage (ICH) constitutes 10% to 15% of all strokes. Within 30 days reported mortality is 35-52% and only 20% is functionally independent in 6 months. Despite several existing outcome prediction models for ICH, modified Rankin scale is found to be best predictor of outcome in early and long term period. To find out 30-day mortality in ICH and predict outcome based on modified Rankin score. In this study, 48 patients presenting with acute ICH presenting to a tertiary hospital in Khulna were enrolled. The 30-day mortality and disability were recorded, and ICH score along with modified Rankin score at presentation were calculated. In this study, the 30-day mortality rate was 27.1%; regression analysis showed the correlation between the scores (as measured by modified Rankin scale) for patient disability, intraventricular hemorrhage, the Glasgow Coma score, and volume of hematoma (>30 ml vs <30 ml) were significantly correlated with corresponding ICH scores. The ICH scale is a simple clinical grading scale which can predict mortality as well as disability in haemorrhagic stroke within 30 days that can be helpful to physicians in prioritization of their patient management and forecasting about prognosis.Mediscope Vol. 5, No. 1: Jan 2018, Page 10-14

STUDY OF&NBSP; PRONOSTIC FACTORS AFTER 30 DAYS IN PATIENTS WITH INTRACRANIAL HEMORRAGIA

2016 ◽  
pp. 68-73
Author(s):  
Thi Kieu Diem Tran ◽  
Dinh Toan Nguyen
Keyword(s):  
Ischemic Stroke ◽  
Mortality Rate ◽  
Intracerebral Hemorrhage ◽  
Prediction Models ◽  
Treatment Protocols ◽  
Pronostic Factors ◽  
Key Words Intracerebral Hemorrhage ◽  
Grading Scale ◽  
Ich Score ◽  
Clinical Grading

Background and purpose: Intracerebral hemorrhage (ICH) constitutes 10% to 15% of all strokes and remains without a treatment of proven benefit. Despite several existing outcome prediction models for ICH, there is no standard clinical grading scale for ICH analogous to those for traumatic brain injury, subarachnoid hemorrhage, or ischemic stroke. Methods: Records of all patients with acute ICH presenting to the Neurology Department, Binh Dinh General Hospital from July 2014-March 2015. Clinical outcome assessed by mRankin score and was compared with each item of ICH scale. ROC-AUC was realized to evaluated the value of ICH in prognostic the outcome of cerebral hemorrhage at day 30. Results: In the day 30: mortality rate was evaluated compared with mRS: In the group with ICH 0-1: no mortality, good outcome was 92.8% and 72.7%. ICH 2-3: mortlity rate increased 47.9% and 84.4%. ICH 4-5: mortality rate 100%. The prognostic predictor of ICH was high with Se 95%, Sp 59%. ROC-AUC 0.908, p<0.0001. Conclusions: The ICH Score is a simple clinical grading scale that allows risk stratification on presentation with ICH. The use of a scale such as the ICH Score could improve standardization of clinical treatment protocols and clinical research studies in ICH. Key words: Intracerebral hemorrhage (ICH), ischemic stroke

scholarly journals Plasma microRNA signature associated with retinopathy in patients with type 2 diabetes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Donato Santovito ◽  
Lisa Toto ◽  
Velia De Nardis ◽  
Pamela Marcantonio ◽  
Rossella D’Aloisio ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Vision Loss ◽  
External Validation ◽  
Diabetic Patients ◽  
Disease Biomarkers ◽  
Response To Stress ◽  
Severity Of The Disease ◽  
Plasma Microrna

AbstractDiabetic retinopathy (DR) is a leading cause of vision loss and disability. Effective management of DR depends on prompt treatment and would benefit from biomarkers for screening and pre-symptomatic detection of retinopathy in diabetic patients. MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression which are released in the bloodstream and may serve as biomarkers. Little is known on circulating miRNAs in patients with type 2 diabetes (T2DM) and DR. Here we show that DR is associated with higher circulating miR-25-3p (P = 0.004) and miR-320b (P = 0.011) and lower levels of miR-495-3p (P < 0.001) in a cohort of patients with T2DM with DR (n = 20), compared with diabetic subjects without DR (n = 10) and healthy individuals (n = 10). These associations persisted significant after adjustment for age, gender, and HbA1c. The circulating levels of these miRNAs correlated with severity of the disease and their concomitant evaluation showed high accuracy for identifying DR (AUROC = 0.93; P < 0.001). Gene ontology analysis of validated targets revealed enrichment in pathways such as regulation of metabolic process (P = 1.5 × 10–20), of cell response to stress (P = 1.9 × 10–14), and development of blood vessels (P = 2.7 × 10–14). Pending external validation, we anticipate that these miRNAs may serve as putative disease biomarkers and highlight novel molecular targets for improving care of patients with diabetic retinopathy.

scholarly journals Interpretable Machine Learning Algorithm Reveals Novel Gut Microbiome Features in Predicting Type 2 Diabetes

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 1559-1559
Author(s):  
Wanglong Gou ◽  
Chu-Wen Ling ◽  
Yan He ◽  
Zengliang Jiang ◽  
Yuanqing Fu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Type 2 Diabetes ◽  
Gut Microbiome ◽  
Large Scale ◽  
Validation Cohort ◽  
Learning Algorithm ◽  
External Validation ◽  
Positive Association ◽  
Interpretable Machine Learning

Abstract Objectives The gut microbiome-type 2 diabetes (T2D) relationship among human cohorts have been controversial. We hypothesized that this limitation could be addressed by integrating the cutting-edge interpretable machine learning framework and large-scale human cohort studies. Methods 3 independent cohorts with &gt;9000 participants were included in this study. We proposed a new machine learning-based analytic framework — using LightGBM to infer the relationship between incorporated features and T2D, and SHapley Additive explanation(SHAP) to identified microbiome features associated with the risk of T2D. We then generated a microbiome risk score (MRS) integrating the threshold and direction of the identified microbiome features to predict T2D risk. Results We finally identified 15 microbiome features (two of them are indicators of microbial diversity, others are taxa-related features) associated with the risk of T2D. The identified T2D-related gut microbiome features showed superior T2D prediction accuracy compared to host genetics or traditional risk factors. Furthermore, we found that the MRS (per unit change in MRS) consistently showed positive association with T2D risk in the discovery cohort (RR 1.28, 95%CI 1.23-1.33), external validation cohort 1 (RR 1.23, 95%CI 1.13-1.34) and external validation cohort 2 (GGMP, RR 1.12, 95%CI 1.06-1.18). The MRS could also predict future glucose increment. We subsequently identified dietary and lifestyle factors which could prospectively modulate the microbiome features, and found that body fat distribution may be the key factor modulating the gut microbiome-T2D relationship. Conclusions Taken together, we proposed a new analytical framework for the investigation of microbiome-disease relationship. The identified microbiome features may serve as potential drug targets for T2D in future. Funding Sources This study was funded by National Natural Science Foundation of China (81903316, 81773416), Westlake University (101396021801) and the 5010 Program for Clinical Researches (2007032) of the Sun Yat-sen University (Guangzhou, China).

scholarly journals External Validation of the UKPDS Risk Engine in Incident Type 2 Diabetes: A Need for New Type 2 Diabetes-Specific Risk Equations

Diabetes Care ◽  
2013 ◽  
Vol 37 (2) ◽  
pp. 537-545 ◽  
Author(s):  
C. A. Bannister ◽  
C. D. Poole ◽  
S. Jenkins-Jones ◽  
C. L. Morgan ◽  
G. Elwyn ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
External Validation ◽  
Incident Type ◽  
Specific Risk ◽  
Incident Type 2 Diabetes ◽  
New Type ◽  
Risk Engine

scholarly journals Prestroke Metformin Use on the 1-Year Prognosis of Intracerebral Hemorrhage Patients with Type 2 Diabetes

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Wen-Jun Tu ◽  
Qingjia Zeng ◽  
Kai Wang ◽  
Yu Wang ◽  
Bao-Liang Sun ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Ischemic Stroke ◽  
Intracerebral Hemorrhage ◽  
Absolute Difference ◽  
Inhospital Mortality ◽  
Hematoma Volume ◽  
Recurrence Rates ◽  
Discharged Patients

Background. Although recent studies have focused on the use of metformin in treating ischemic stroke, there is little literature to support whether it can treat intracerebral hemorrhage (ICH). Therefore, this study is aimed at evaluating the possible effects of prestroke metformin (MET) on ICH patients with type 2 diabetes. Methods. From January 2010 to December 2019, all first-ever ICH patients with type 2 diabetes from our hospitals were included. All discharged patients would receive a one-time follow-up at 1 year after admission. Death, disability, and recurrence events were recorded. Results. We included 730 patients for analysis (the median age: 65 [IQR, 56-72] years and 57.7% was men). Of those patients, 281 (38.5%) had received MET before ICH (MET+), whereas 449 (61.5%) had not (MET−). MET (+) patients had a lower median baseline hematoma volume than did MET (-) patients (9.6 ml [IQR, 5.3-22.4 ml] vs. 14.7 ml [IQR, 7.9-28.6 ml]; P < 0.001 ). The inhospital mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (6.4% vs 8.9%, respectively; absolute difference, −2.5% [95% CI, −3.9% to −0.7%]; OR, 0.70 [95% CI, 0.39 to 1.27]; P = 0.22 ). The 1-year mortality events were not significantly reduced in the MET (+) group compared with the MET (-) group (14.1% vs 17.4%, respectively; absolute difference, −3.3% [95% CI, −5.1% to −1.8%]; OR, 0.73 [95% CI, 0.47 to 1.14]; P = 0.16 ). The 1-year disability events were not significantly reduced in the MET (+) group compared with the MET (-) group (28.4% vs 34.1%, respectively; absolute difference, −5.7% [95% CI, −8.2% to −3.3%]; OR, 0.77 [95% CI, 0.52 to 1.13]; P = 0.18 ). Finally, the recurrence rates in those two groups were not significantly different (MET [+] vs. MET [-]: 6.4% vs. 5.9%; absolute difference, 0.5% [95% CI, 0.2% to 1.3%]; OR, 1.08 [95% CI, 0.51 to 2.28]; P = 0.84 ). Conclusions. Pre-ICH metformin use was not associated with inhospital mortality and 1-year prognosis in diabetic ICH patients.

scholarly journals Study to assess predictive value of waist to height ratio and body mass index as a risk factor of hypertension and type 2 diabetes mellitus

2017 ◽  
Vol 4 (4) ◽  
pp. 1099
Author(s):  
Sampat Raj Nagar ◽  
Manish Jain
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Risk Factor ◽  
Predictive Value ◽  
Odds Ratio ◽  
Health Workers ◽  
Training Centre ◽  
Strength Of Association

Background: Hypertension and diabetes have become important world-wide public-health challenges. Assessment of risk for Hypertension and Diabetes requires identifying an easy tool that can be used by health workers in screening programmes. To compare predictive value of WHtR against BMI in assessing risk of Hypertension and Diabetes. Methods: A case-control study was carried out at MB Hospital and Urban Health Training Centre (UHTC) attached to RNT Medical College, Udaipur, Rajasthan. Selected individuals were examined and interviewed using semi-structured questionnaire. Anthropometric measurements were carried out. Odds ratios were derived for quantitative analysis. Results: Observed proportion of BMI ≥ 25 kg /m2 was 60.4% in type 2 diabetes cases, whereas 39.6% in controls. Odds ratio was 2.383. Observed proportion of BMI ≥ 25 kg/ m2 was 66.7% in HTN cases, whereas 33.3% in controls with a Odds ratio of 3.484. An Odds ratio of 3.151, showed existence of strong association of WHtR above 0.5 with hypertension. Observed proportion of WHtR above 0.5 was 56.3% in type 2 diabetes cases, whereas 43.7% in controls and Odds ratio was 4.292. Conclusions: The OR of WHtR in diabetes (4.292) in compared to OR of BMI (2.303), shows the strength of association of WHtR as an alarming risk factor for diabetes than BMI; whereas an equivalent strength of association was observed for hypertension. Study favours the use of anthropometric measures especially WHtR for predicting type 2 diabetes mellitus and hypertension. 

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