Dataset Information

A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

ABSTRACT: Lipids are implicated in inflammatory responses affecting acute ischaemic stroke prognosis. Therefore, we aimed to develop a predictive model that considers neutrophils and high-density lipoprotein cholesterol to predict its prognosis. This prospective study enrolled patients with acute ischaemic stroke within 24 h of onset between January 2015 and December 2017. The main outcome was a modified Rankin Scale score ≥3 at the 90th day of follow-up. Patients were divided into training and testing sets. The training set was divided into four states according to the median of neutrophils and high-density lipoprotein cholesterol levels in all patients. Through binary logistic regression analysis, the relationship between factors and prognosis was determined. A nomogram based on the results was developed; its predictive value was evaluated through internal and external validations. Altogether, 1,090 patients were enrolled with 872 (80%) and 218 (20%) in the training and testing sets, respectively. In the training set, the major outcomes occurred in 24 (10.4%), 24 (11.6%), 37 (17.2%), and 49 (22.3%) in states 1-4, respectively (P = 0.002). Validation of calibration and decision curve analyses showed that the nomogram showed better performance. The internal and external testing set receiver operating characteristics verified the predictive value [area under the curve = 0.794 (0.753-0.834), P < 0.001, and area under the curve = 0.973 (0.954-0.992), P < 0.001, respectively]. A nomogram that includes neutrophils and high-density lipoprotein cholesterol can predict the prognosis of acute ischaemic stroke, thus providing us with an effective visualization tool.

SUBMITTER: Wang N

PROVIDER: S-EPMC8914087 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

Wang Nan N Liu Hongbing H Tian Mengke M Liang Jing J Sun Wenxian W Zhang Luyang L Pei Lulu L Liu Kai K Sun Shilei S Wu Jun J Gao Yuan Y Xu Yuming Y Wang Yilong Y Song Bo B

Frontiers in neurology 20220225

Lipids are implicated in inflammatory responses affecting acute ischaemic stroke prognosis. Therefore, we aimed to develop a predictive model that considers neutrophils and high-density lipoprotein cholesterol to predict its prognosis. This prospective study enrolled patients with acute ischaemic stroke within 24 h of onset between January 2015 and December 2017. The main outcome was a modified Rankin Scale score ≥3 at the 90th day of follow-up. Patients were divided into training and testing se ...[more]

PMID: 35280284

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Project description:BackgroundIntima-media thickness (IMT) and small dense low-density lipoprotein cholesterol (sdLDL-C) have been reported to be related to atherosclerosis and stroke. This study is trying to explore the association between IMT and sdLDL-C in Chinese acute ischaemic stroke (AIS) subjects.MethodsThis study enrolled total 368 consecutive AIS patients and 165 non-AIS controls from November 2016 to February 2019. Mean IMT and carotid plaques were measured by using carotid ultrasonography method. Blood glucose and lipid parameters were measured by using an automatic biochemical instrument. SdLDL-C was detected by using the Lipoprint LDL system. IMT > 1.0 mm was defined as increased IMT. Plaque stability based on the nature of the echo was determined by ultrasound examination. Risk factors for IMT were identified by using multivariate logistic regression analysis. A logistic regression model was established to predict AIS risk. Python software (Version 3.6) was used for the statistical analysis of all data.ResultsThe carotid IMT, proportion of plaques, and the sdLDL-C, triglycerides (TG) and glucose levels were obviously higher in AIS patients than those in controls. SdLDL-C level in the IMT thickening group was higher than that in the normal IMT group. SdLDL-C and total cholesterol (TC) were risk factors for IMT, while sdLDL-C was an independent risk factor. The IMT value of the unstable plaque group was markedly higher than that of the stable plaque group. The predictive value of IMT for AIS was better than that of low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) but not as good as that of sdLDL-C. A logistic regression model was established to predict AIS risk. Additionally, carotid IMT and sdLDL-C were closely related to AIS severity and outcomes.ConclusionsSdLDL-C and TC were risk factors for increased IMT, while sdLDL-C was an independent risk factor. A prediction model based on IMT and other variables was established to screen the population with high AIS risk.

Project description:OBJECTIVES:To determine by how much statins reduce serum concentrations of low density lipoprotein (LDL) cholesterol and incidence of ischaemic heart disease (IHD) events and stroke, according to drug, dose, and duration of treatment. DESIGN:Three meta-analyses: 164 short term randomised placebo controlled trials of six statins and LDL cholesterol reduction; 58 randomised trials of cholesterol lowering by any means and IHD events; and nine cohort studies and the same 58 trials on stoke. MAIN OUTCOME MEASURES:Reductions in LDL cholesterol according to statin and dose; reduction in IHD events and stroke for a specified reduction in LDL cholesterol. RESULTS:Reductions in LDL cholesterol (in the 164 trials) were 2.8 mmol/l (60%) with rosuvastatin 80 mg/day, 2.6 mmol/l (55%) with atorvastatin 80 mg/day, 1.8 mmol/l (40%) with atorvastatin 10 mg/day, lovastatin 40 mg/day, simvastatin 40 mg/day, or rosuvastatin 5 mg/day, all from pretreatment concentrations of 4.8 mmol/l. Pravastatin and fluvastatin achieved smaller reductions. In the 58 trials, for an LDL cholesterol reduction of 1.0 mmol/l the risk of IHD events was reduced by 11% in the first year of treatment, 24% in the second year, 33% in years three to five, and by 36% thereafter (P < 0.001 for trend). IHD events were reduced by 20%, 31%, and 51% in trials grouped by LDL cholesterol reduction (means 0.5 mmol/l, 1.0 mmol/l, and 1.6 mmol/l) after results from first two years of treatment were excluded (P < 0.001 for trend). After several years a reduction of 1.8 mmol/l would reduce IHD events by an estimated 61%. Results from the same 58 trials, corroborated by results from the nine cohort studies, show that lowering LDL cholesterol decreases all stroke by 10% for a 1 mmol/l reduction and 17% for a 1.8 mmol/l reduction. Estimates allow for the fact that trials tended to recruit people with vascular disease, among whom the effect of LDL cholesterol reduction on stroke is greater because of their higher risk of thromboembolic stroke (rather than haemorrhagic stroke) compared with people in the general population. CONCLUSIONS:Statins can lower LDL cholesterol concentration by an average of 1.8 mmol/l which reduces the risk of IHD events by about 60% and stroke by 17%.

Project description:The purpose of this study is to investigate the non-high-density lipoprotein cholesterol (non-HDL-C) to high-density lipoprotein cholesterol (HDL-C) ratio (NHHR) as a novel compound lipid index for atherosclerosis and explore its relationship with coronary heart disease (CHD). This study also aims to establish NHHR as a sensitive indicator for early prevention of CHD and to construct a clinical prediction model to further predict the occurrence of CHD. This study selected 707 patients who visited the First People's Hospital of Mengcheng County from January 2020 to May 2024, including 466 patients with CHD and a control group. Logistic regression analysis was used to analyze the correlation between NHHR and CHD. Patients were randomly divided into a training set and validation set in a 7:3 ratio. Multivariable logistic regression was used to screen for risk factors, and a nomogram model was constructed and validated. After adjusting for confounding factors, the results showed that for each increase of 1 standard deviation in NHHR, the risk of CHD increased by 42%, with a P-value of .003. In model 3, the risk of CHD for the highest quartile increased by 144%, with a P-value of .01. The smoothed curve fitting showed a nonlinear relationship between NHHR and CHD. Multivariable logistic analysis indicated that age, body mass index, smoke, hypertension, white blood cells, fasting plasma glucose, uric acid, and NHHR were independent risk factors for predicting the occurrence of CHD (P < .05), and a risk prediction nomogram model was constructed. The receiver operating characteristic curve analysis of the training set showed an AUC of 0.922 (95% CI: 0.900-0.945), and the AUC of the validation set was 0.902 (95% CI: 0.856-0.948), indicating good model accuracy. Calibration curve analysis showed that the calibration curves of the nomogram model were very close for predicting the occurrence of CHD in the training set and validation set, and the decision curve analysis also showed a good clinical net benefit of the nomogram model. The study results indicated a strong and nonlinear correlation between NHHR and CHD. Our constructed nomogram model has a certain predictive ability for the occurrence of CHD.

Project description:BackgroundAnimal studies suggest that high-density lipoprotein cholesterol (HDL-C) attenuates reperfusion injury. We aimed to assess whether higher serum HDL-C levels modulate the risk of intracranial haemorrhage (ICH) after thrombectomy in human stroke survivors.MethodsWe included consecutive patients from our prospective anterior circulation large vessel occlusion (acLVO) registry who underwent thrombectomy between 01/2017 and 01/2023 at the tertiary stroke centre of the University Hospital Carl Gustav Carus in Dresden, Germany in a propensity score-matched analysis. We assessed the association between serum HDL-C levels and post-interventional ICH as well as 90-day functional outcome quantified by the modified Rankin Scale (mRS). For sensitivity analysis, we used multivariable lasso logistic regression. Analyses were adjusted for demographics, cardiovascular risk profiles, stroke characteristics, and procedural times.ResultsOf 1702 patients screened, 807 (420 women, median age 77 years [66-84, IQR]) were included. Post-interventional ICH reduced the probability of a favourable functional outcome (90-day mRS 0-2) by 14.8% (ß = 0.15; 95% CI [0.06;0.24]; p = 0.001. An HDL-C level above the median (1.15 mmol/L) decreased the probability of ICH by 13.6% (ß = - 0.14; 95CI% [- 0.22; - 0.05]; p = 0.002) and increased the probability of favourable functional outcome by 13.2% (ß = - 0.13; 95CI% [- 0.22; - 0.05]; p = 0.003). In sensitivity analyses, higher HDL-C levels were independently associated with lower odds of ICH (adjusted OR 0.62; 95% CI [0.43;0.88]; p = 0.008) and higher odds of favourable functional outcome (adjusted OR 0.60; 95% CI [0.40; 0.90]; p = 0.015).ConclusionsIn patients undergoing thrombectomy for acLVO, higher HDL-C levels were associated with a reduced probability of post-interventional ICH and a favourable functional outcome. These observations could not be explained by conventional vascular risk profiles.

Project description:ObjectiveThis study aimed to develop and validate a nomogram for predicting the risk of 3 months adverse outcomes among young adults with acute ischemic stroke (AIS).MethodsPatients aged between 18 and 50 with acute ischemic stroke (AIS) at the Shenyang First's People Hospital, between January 1st 2017 to May 30th 2023 were included in this retrospective study. The primary outcome was a three-month unfavorable outcome, evaluated with modified Rankin Scale (mRS > 2). Univariate logistic regression was used to select the independent factors of prognosis and multivariate logistic regression to establish a new nomogram model. We used the area under the receiver-operating characteristic curve (ROC) to evaluate the discriminative performance and used the calibration curve with Hosmer-Lemeshow goodness of fit test to assess the calibration performance of the risk prediction model. Decision curve analysis (DCA) was applied to assess the clinical utility of the nomogram.ResultsA total of 1,015 patients were enrolled. Gender (male vs. female; Odds ratio[OR], 0.5562[95% Confidence Interval (CI), 0.3104-1.0478]; p = 0.053), family history of stroke (OR, 3.5698[95%CI 1.5632-8.0329], p < 0.001), prior stroke (OR, 2.1509[95%CI 1.2610-3.6577], p < 0.001), previous heart disease (OR, 3.4047[95%CI, 1.7838-6.6976], p < 0.01) toast type (cardio-embolism stroke vs. large-artery atherosclerosis (LAA), OR, 0.0847[0.0043-0.5284], p < 0.01), toast type (stroke of undetermined etiology vs. LAA, OR, 0.0847[0.0439-0.5284], p < 0.01), mRS at admission (OR, 15.2446 [9.1447-26.3156], p < 0.0001), adherence to medication (OR, 2.1197[95%CI, 1.1924-3.7464], p < 0.001), systolic blood pressure (SBP; OR, 1.0145[1.0041-1.0250], p < 0.001), and lactate dehydrogenase (LDH; OR, 1.0060[1.0010-1.0111], p < 0.01) were related to 3 months adverse outcomes among young adults with AIS. The nomogram displayed excellent calibration and discrimination. DCA confirmed the clinical applicability of the model.ConclusionThe nomogram comprised of gender, family history of stroke, prior stroke, previous heart disease, toast type, mRS score at admission, adherence to medication, SBP and LDH may predict 3 months adverse outcomes among young adults with AIS.

Dataset Information

A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

Publications

A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

Similar Datasets

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