Development of a prediction model for 1-year poor prognosis in patients with acute ischemic stroke

The goals of this study were to develop a new prediction model to predict 1-year poor prognosis (death or modified Rankin scale score of ≥3) in patients with acute ischemic stroke (AIS) and to compare the performance of the new prediction model with other prediction scales. Baseline data of 772 patients with AIS were collected, and univariate and multivariate logistic regression analyses were performed to identify independent risk factors for 1-year poor prognosis in patients with AIS. The area under the receiver operating characteristics curve (AUC) value of the new prediction model and the THRIVE, iScore and ASTRAL scores was compared. The Hosmer-Lemeshow test was used to assess the goodness of fit of the model. We identified 196 (25.4%) patients with poor prognosis at 1-year follow-up, and of these 68 (68/196, 34.7%) had died. Multivariate logistic regression and receiver operating characteristic curve analyses showed that age ≥70 years, consciousness (lethargy or coma), history of stroke or transient ischemic attack, cancer, abnormal fasting blood glucose levels ≥7.0 mmol/L, and National Institutes of Health Stroke Scale score were independent risk factors for 1-year poor prognosis in patients with AIS. Scores were assigned for each variable by rounding off β coefficient to the integer score, and a new prediction model with a maximum total score of 9 points was developed. The AUC value of the new prediction model was higher than the THRIVE score (p<0.05). The χ2 value for the Hosmer-Lemeshow test was 7.337 (p>0.05), suggesting that the prediction model had a good fit. The new prediction model can accurately predict 1-year poor prognosis in Chinese patients with AIS.

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Perioperative Acute Ischemic Stroke in Noncardiac and Nonvascular Surgery

Anesthesiology ◽

10.1097/aln.0b013e318194b5ff ◽

2009 ◽

Vol 110 (2) ◽

pp. 231-238 ◽

Cited By ~ 56

Author(s):

Brian T. Bateman ◽

H Christian Schumacher ◽

Shuang Wang ◽

Shahzad Shaefi ◽

Mitchell F. Berman

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Logistic Regression ◽

Ischemic Stroke ◽

Renal Disease ◽

Acute Ischemic Stroke ◽

Hip Replacement ◽

Odds Ratio ◽

Lung Resection ◽

Multivariate Logistic Regression

Background Perioperative acute ischemic stroke (AIS) is a recognized complication of noncardiac, nonvascular surgery, but few data are available regarding incidence and effect on outcome. This study examines the epidemiology of perioperative AIS in three common surgeries: hemicolectomy, total hip replacement, and lobectomy/segmental lung resection. Methods Discharges for patients aged 18 yr or older who underwent any of the surgical procedures listed above were extracted from the Nationwide Inpatient Sample, an administrative database that contains 20% of all discharges from non-Federal hospitals each year, for years 2000 to 2004. Using appropriate International Classification of Diseases, 9th revision, Clinical Modification codes, patients with perioperative AIS were identified, as were comorbid conditions that may be risk factors for perioperative AIS. Multivariate logistic regression was performed to identify independent predictors of perioperative AIS and to ascertain the effect of AIS on outcome. Results A total of 0.7% of 131,067 hemicolectomy patients, 0.2% of 201,235 total hip replacement patients, and 0.6% of 39,339 lobectomy/segmental lung resection patients developed perioperative AIS. For patients older than 65 yr, AIS rose to 1.0% for hemicolectomy, 0.3% for hip replacement, and 0.8% for pulmonary resection. Multivariate logistic regression analysis revealed renal disease (odds ratio, 3.0), atrial fibrillation (odds ratio, 2.0), history of stroke (odds ratio, 1.6), and cardiac valvular disease (odds ratio, 1.5) to be the most significant risk factors for perioperative AIS. Conclusions Perioperative AIS is an important source of morbidity and mortality associated with noncardiac, nonvascular surgery, particularly in elderly patients and patients with atrial fibrillation, valvular disease, renal disease, or previous stroke.

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Fibrinogen Level Combined With Platelet Count for Predicting Hemorrhagic Transformation in Acute Ischemic Stroke Patients Treated With Mechanical Thrombectomy

Frontiers in Neurology ◽

10.3389/fneur.2021.716020 ◽

2021 ◽

Vol 12 ◽

Author(s):

Changchun Lin ◽

Hui Pan ◽

Yuan Qiao ◽

Peisheng Huang ◽

Jingjing Su ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Platelet Count ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Mechanical Thrombectomy ◽

Fibrinogen Level ◽

Hemorrhagic Transformation ◽

Multivariate Logistic Regression ◽

Platelet Counts

A serious complication of acute ischemic stroke (AIS) after mechanical thrombectomy (MT) is hemorrhagic transformation (HT), which is potentially associated with clinical deterioration. This study examined predictors of HT following MT in AIS patients. Patients with AIS due to large artery occlusion in the anterior circulation, treated with MT and successfully recanalized (modified Thrombolysis in Cerebral Infarction score 2b/3), were studied retrospectively. HT was evaluated by computed tomography (CT) 24 h after MT and was diagnosed and classified into parenchymal hematoma (PH) and hemorrhagic infarction (HI). Multivariate logistic regression models were used to determine the risk factors for HT. Receiver operating characteristic (ROC) curve analysis was performed to determine the predictive utility of risk factors for HT. We enrolled 135 patients: 49 in the HT group and 86 in the non-HT group. The two groups differed significantly in baseline fibrinogen levels (p = 0.003) and platelet counts (p = 0.006). Multivariate logistic regression analyses showed that lower fibrinogen levels [odds ratio (OR), 0.41; 95% CI, 0.23–0.72; p = 0.002] and platelet counts (OR, 0.58; 95% CI, 0.33–0.99; p = 0.048) were independently associated with a higher risk of HT. Together, the binary variates fibrinogen and platelets well-predicted HT (area under the curve, 0.703; specificity, 77.9%; sensitivity, 55.1%). The combination of fibrinogen <2.165 g/L and platelets <171.5 × 109/L was the strongest predictor of HT (OR, 23.17; 95% CI, 5.75–126.80; p < 0.0001). Our study suggests that lower baseline fibrinogen levels and platelet counts may be risk factors for HT in AIS patients following MT and reperfusion. Specifically, the combination of fibrinogen level and platelet count may predict the risk of HT after MT in these patients.

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Nomogram for Predicting the Postoperative Venous Thromboembolism in Spinal Metastasis Tumor: A Multicenter Retrospective Study

Frontiers in Oncology ◽

10.3389/fonc.2021.629823 ◽

2021 ◽

Vol 11 ◽

Author(s):

Hao-ran Zhang ◽

Ming-you Xu ◽

Xiong-gang Yang ◽

Feng Wang ◽

Hao Zhang ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Venous Thromboembolism ◽

Prediction Model ◽

Regression Model ◽

Logistic Regression Model ◽

Multivariate Logistic Regression Model ◽

Multivariate Logistic Regression ◽

Independent Risk Factors

IntroductionVenous thromboembolism can be divided into deep vein thrombosis and pulmonary embolism. These diseases are a major factor affecting the clinical prognosis of patients and can lead to the death of these patients. Unfortunately, the literature on the risk factors of venous thromboembolism after surgery for spine metastatic bone lesions are rare, and no predictive model has been established.MethodsWe retrospectively analyzed 411 cancer patients who underwent metastatic spinal tumor surgery at our institution between 2009 and 2019. The outcome variable of the current study is venous thromboembolism that occurred within 90 days of surgery. In order to identify the risk factors for venous thromboembolism, a univariate logistic regression analysis was performed first, and then variables significant at the P value less than 0.2 were included in a multivariate logistic regression analysis. Finally, a nomogram model was established using the independent risk factors.ResultsIn the multivariate logistic regression model, four independent risk factors for venous thromboembolism were further screened out, including preoperative Frankel score (OR=2.68, 95% CI 1.78-4.04, P=0.001), blood transfusion (OR=3.11, 95% CI 1.61-6.02, P=0.041), Charlson comorbidity index (OR=2.01, 95% CI 1.27-3.17, P=0.013; OR=2.29, 95% CI 1.25-4.20, P=0.017), and operative time (OR=1.36, 95% CI 1.14-1.63, P=0.001). On the basis of the four independent influencing factors screened out by multivariate logistic regression model, a nomogram prediction model was established. Both training sample and validation sample showed that the predicted probability of the nomogram had a strong correlation with the actual situation.ConclusionThe prediction model for postoperative VTE developed by our team provides clinicians with a simple method that can be used to calculate the VTE risk of patients at the bedside, and can help clinicians make evidence-based judgments on when to use intervention measures. In clinical practice, the simplicity of this predictive model has great practical value.

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Factors associated with 90-day acute ischemic stroke in patients ≥70 years old with total hip arthroplasty for hip fracture

BMC Geriatrics ◽

10.1186/s12877-021-02728-3 ◽

2022 ◽

Vol 22 (1) ◽

Author(s):

Rui He ◽

Guoyou Wang ◽

Ting Li ◽

Huarui Shen ◽

LijuanZhang

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Logistic Regression ◽

Ischemic Stroke ◽

Hip Fracture ◽

Total Hip Arthroplasty ◽

Older Age ◽

Factors Associated ◽

Independent Risk Factors ◽

D Dimer

Abstract Background Postoperative ischemic stroke is a devastating complication following total hip arthroplasty (THA). The purpose of the current study was to investigate the incidence of postoperative acute ischemic stroke (AIS) in patients ≥70 years old with THA for hip fracture after 90 days and independent risk factors associated with 90-day AIS. Methods A multicenter retrospective study was conducted, patients ≥70 years old with THA for hip fracture under general anesthesia were included from February 2017 to March 2020. Patients with AIS within 90 days after THA were identified as AIS group; patients with no AIS were identified as no AIS group. The baseline characteristics and risk factors were collected, multivariable logistic regression was used to identify independent risk factors of 90-dayAIS. Results: 2517 patients (mean age 76.18 ± 6.01) were eligible for inclusion in the study. 2.50% (63/2517) of patients had 90-day AIS. Compared with no AIS, older age, diabetes, hyperlipidemia, atrial fibrillation (AF) and higher D-dimer value were more likely in patients with AIS (P < 0.05), and anticoagulant use was fewer in patients with AIS. ROC curve analysis showed that the optimal cut point of D-dimer for AIS was D-dimer≥4.12 μg/ml. Multivariate logistic regression analysis showed that D-dimer≥4.12 μg/ml [adjusted odds ratio (aOR), 4.44; confidence interval (CI), 2.50–7.72; P < 0.001], older age (aOR, 1.08; 95%CI, 1.03–1.12; P < 0.001), hyperlipidemia (aOR, 2.28; 95%CI, 1.25–4.16; P = 0.007), atrial fibrillation (aOR, 5.84; 95% CI, 1.08–15.68; P = 0.001), and diabetes (aOR, 2.60; 95% CI, 1.56–4.39; P < 0.001) were associated with increased risk of 90-day AIS after THA. Conclusions In conclusion, we found that the incidence of 90-day AIS in patients≥70 years old with THA for hip fracture was 2.5%. Older age, diabetes, hyperlipidemia, AF and higher D-dimer value were independent risk factors for 90-day AIS in patients≥70 years old with THA for hip fracture.

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Risk factors affecting the 1-year outcomes of minor ischemic stroke: results from Xi’an stroke registry study of China[1]

10.21203/rs.3.rs-38303/v2 ◽

2020 ◽

Author(s):

Zhongzhong Liu ◽

Wenjuan Lin ◽

Qingli Lu ◽

Jing Wang ◽

Pei Liu ◽

...

Keyword(s):

Risk Factors ◽

Regression Analysis ◽

Ischemic Stroke ◽

Multivariate Logistic Regression Analysis ◽

Stroke Recurrence ◽

Multivariate Logistic Regression ◽

Factors Affecting ◽

Nihss Score ◽

Minor Ischemic Stroke ◽

Independent Risk Factors

Abstract Background: The incidences of stroke recurrence, disability, and all-cause death of patients with minor ischemic stroke (MIS) remain problematic. The aim of the present was to identify risk factors associated with adverse outcomes at 1-year after MIS in the Xi’an region of China. Methods: The cohort of this prospective cohort study included MIS patients aged 18–97 years with a National Institutes of Health Stroke Scale (NIHSS) score of ≤ 3 who were treated in any of four hospitals in Xi’an region of China between January and December 2015. The 1-year percentage of stroke recurrence, disability, and all-cause death were evaluated. Multivariate logistic regression analysis was performed to assess the association between the identified risk factors and clinical outcomes. Results: Among the 1,121 patients included for analysis, the percentage of stroke recurrence, disability, and all-cause death at 1 year after MIS were 3.4% (38/1121), 9.3% (104/1121), and 3.3% (37/1121), respectively. Multivariate logistic regression analysis identified age, current smoking, and pneumonia as independent risk factors for stroke recurrence. Age, pneumonia, and alkaline phosphatase were independent risk factors for all-cause death. Independent risk factors for disability were age, pneumonia, NIHSS score on admission, and leukocyte count. Conclusions: The 1-year outcomes of MIS is not optimistic in the Xi’an region of China, especially high percentage of disability. In this study, we found the risk factors affecting 1-year stroke recurrence, disability and, all-cause death which need further verification in the subsequent studies.

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Risk Factors and Neurologic Outcomes in Patients With Traumatic Brain Injury and Coagulopathy Within 72 Hours Post-operatively

10.21203/rs.3.rs-145018/v1 ◽

2021 ◽

Author(s):

Tao Chang ◽

Xigang Yan ◽

Chao Zhao ◽

Yufu Zhang ◽

Bao Wang ◽

...

Keyword(s):

Risk Factors ◽

Traumatic Brain Injury ◽

Logistic Regression ◽

Brain Injury ◽

Multivariate Logistic Regression ◽

Neurologic Outcomes ◽

Post Operative Period ◽

Duration Of Surgery ◽

Independent Risk Factors ◽

Time Of Admission

Abstract Background There are few studies on the development and effect of coagulopathy in patients with a traumatic brain injury (TBI) during the early post-operative period. We determined the risk factors and neurologic outcomes of in patients with a TBI and coagulopathy diagnosed by routine laboratory tests within 72 hours post-operatively. Methods The baseline characteristics, intra-operative management, and follow-up results of 462 patients with TBIs were obtained and retrospectively analyzed by multivariate logistic regression from January 2015 to June 2019. Coagulopathy was defined as an activated partial thromboplastin time > 40 seconds, international normalized ratio >1.4, or a platelet count < 100×109 /L.Results Multivariate logistic regression analysis revealed that the Glasgow Coma Scale (GCS) at the time of admission, Injury Severity Score (ISS) at the time of admission, pupil mydriasis, duration of surgery, intra-operative blood loss, and intra-operative crystalloid resuscitation were independent risk factors for patients who developed a coagulopathy post-operatively. There were statistical differences in mortality (p = 0.049), the Glasgow Outcome Scale-Extended (GCS-E; p = 0.024), and the modified Rankin Scale (p = 0.043) between patients with and without coagulopathy 1 week after surgery. Coagulopathy within 72 h after surgery revealed a trend for higher mortality at 1 week (66.7%), 3 months (71.4%), and 6 months (76.2%). Furthermore, coagulopathy and contusion expansion in the early post-operative period were independent risk factors for TBI mortality after surgery. Intra-operative crystalloid resuscitation had a substantial diagnostic accuracy in predicting coagulopathy within 72 h post-operatively (area under the curve [AUC] = 0.972).Conclusion Coagulopathy within 72 h post-operatively in patients with a TBI predicted worse disease progression and unfavorable neurologic outcomes. Hence, we should take practical and reasonable measures to manage these risk factors, which may protect patients with a TBI from post-operative coagulopathy.

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Middle Cerebral Artery-to-Uterine Artery Pulsatility Index Ratio Independently Predicts Adverse Perinatal Outcome in Pregnancies at Term

10.21203/rs.3.rs-51822/v1 ◽

2020 ◽

Author(s):

Sufen Zhou ◽

Hongyan Guo ◽

Heng Liu ◽

Mingqun Li

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Middle Cerebral Artery ◽

Perinatal Outcome ◽

Pulsatility Index ◽

Uterine Artery ◽

Regression Analyses ◽

Multivariate Logistic Regression ◽

Adverse Perinatal Outcome ◽

Independent Risk Factors

Abstract Background: This study aimed to investigate potential predictors, including cerebroplacental ratio (CPR), middle cerebral artery (MCA)/uterine artery pulsatility index (PI) ratio, for adverse perinatal outcome in pregnancies at term.Methods: This was an observational, prospective study of recruited pregnancies at term. An adverse perinatal outcome was set as the primary observational endpoint. The receiver operating characteristic (ROC) curve was plotted to investigate the predictive and cut-off values of risk factors for adverse perinatal outcome. Independent risk factors (maternal, neonatal, prenatal ultrasound and Doppler variables) for adverse perinatal outcome were evaluated by the univariate and multivariate logistic regression analyses.Results: A total of 392 pregnancies at term were included and 19.4% of them had suffered adverse perinatal outcome. CPR (OR: 0.42, 95%CI: 0.20-0.93, P=0.032) and MCA/uterine artery PI ratio (OR: 0.25, 95%CI: 0.16-0.42, P=0.032) were two independent risk factors for adverse perinatal outcome by univariate and multivariate logistic regression analyses.Conclusions: MCA/uterine artery PI ratio is a good predictor of adverse perinatal outcome in pregnancies at term.

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A COACHS Nomogram to Predict the Probability of Three-Month Unfavorable Outcome after Acute Ischemic Stroke in Chinese Patients

Cerebrovascular Diseases ◽

10.1159/000497243 ◽

2019 ◽

Vol 47 (1-2) ◽

pp. 80-87 ◽

Cited By ~ 2

Author(s):

BaiLi Song ◽

YuKai Liu ◽

Linda Nyame ◽

XiangLiang Chen ◽

Teng Jiang ◽

...

Keyword(s):

Logistic Regression ◽

Heart Disease ◽

Ischemic Stroke ◽

Blood Glucose ◽

Acute Ischemic Stroke ◽

Valvular Heart Disease ◽

Cerebral Hemorrhage ◽

Unfavorable Outcome ◽

Stroke Patients ◽

Lemeshow Test

Background: Accurate prognostication of unfavorable outcome made at the early onset of stroke is important to both the clinician and the patient management. This study was aimed to develop a nomogram based on the integration of parameters to predict the probability of 3-month unfavorable functional outcome in Chinese acute ischemic stroke patients. Methods: We retrospectively collected patients who underwent acute ischemic stroke at Stroke Center of the Nanjing First Hospital (China) between May 2013 and May 2018. After exclusion, the study population includes 1,025 patients for nomogram development. The main outcome measure was 3-month unfavorable outcome (modified Rankin Scale > 2). Multivariable logistic regression analysis was used to develop the predicting model, and stepwise logistic regression with the Akaike information criterion was utilized to find best-fit nomogram model. We incorporated the creatinine, fast blood glucose, age, previous cerebral hemorrhage, previous valvular heart disease, and NHISS score (COACHS), and these factors were presented with a nomogram. We assessed the discriminative performance by using the area under curve (AUC) of receiver-operating characteristic (ROC) and calibration of risk prediction model by using the Hosmer-Lemeshow test. Results: Multivariate analysis of the 1,025 patients for logistic regression helped identify the independent factors as National Institutes of Health Stroke Scale score on admission, age, previous valvular heart disease, fasting blood glucose, creatinine, and previous cerebral hemorrhage, which were included in the COACHS nomogram. The AUC-ROC of nomogram was 0.799. Calibration was good (p = 0.1376 for the Hosmer-Lemeshow test). Conclusions: The COACHS nomogram may be used to predict unfavorable outcome at 3 months after acute ischemic stroke in Chinese population. It may be also a reliable tool that is effective in its clinical utilization to risk-stratify acute stroke patients.

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Decreased eGFR Is Associated With Ischemic Stroke in Patients With Dilated Cardiomyopathy

Clinical and Applied Thrombosis/Hemostasis ◽

10.1177/1076029619866909 ◽

2019 ◽

Vol 25 ◽

pp. 107602961986690 ◽

Cited By ~ 1

Author(s):

Yuqing Deng ◽

Zhiqing Chen ◽

Lili Hu ◽

Zhenyan Xu ◽

Jinzhu Hu ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Ischemic Stroke ◽

Dilated Cardiomyopathy ◽

Logistic Regression Analysis ◽

Multivariate Logistic Regression Analysis ◽

Analysis Model ◽

Multivariate Logistic Regression ◽

Increased Risk

Dilated cardiomyopathy (DCM) is increasingly indicated as a cause of cardioembolic syndrome, in particular, cardioembolic ischemia stroke. However, the potential risk factors for stroke among DCM patients remain under investigated. DCM patients hospitalized from June 2011 to June 2016 were included. The cases were defined as the group of DCM patients with stroke compared with those without stroke. Clinical characteristic data were collected and compared between the two groups including demographic data, complicated diseases, echocardiography index, and laboratory parameters and estimated glomerular filtration rate (eGFR). A multivariate logistic regression analysis model adjusted by sex and age was used to explore the related risk factors for stroke in DCM patients. A total of 779 hospitalized patients with DCM were included. Of these, 55 (7.1%) had experienced a stroke. Significantly lower eGFR levels (68.03 ± 26.22 vs 79.88 ± 24.25 mL/min/1.73 m2, P = .001) and larger left atrial diameters (45.32 ± 7.79 vs 43.25 ± 7.11 mm, P = .04) were found in the group of patients having DCM with stroke compared to those without stroke. When the eGFR was categorized as eGFR >60, 30<eGFR≤ 60 and eGFR ≤ 30, there were more patients with 30<eGFR≤ 60 (30.9% vs 17.7%) and eGFR≤ 30 (9.1% vs 3.3%) in the ischemic stroke group ( P = 0.003). A multivariate logistic regression analysis model adjusted by sex and age showed that 30 <eGFR≤60 (odds ratio [OR]: 2.07, 95% confidence interval [CI]: [1.05-4.07], P = .035) and eGFR≤30 (OR: 4.04, 95% CI: [1.41-11.62], P = .009) were statistically associated with ischemic stroke in patients with DCM. It is concluded that decreased eGFR is significantly associated with an increased risk of ischemic stroke in patients with DCM.

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Neutrophil-to-lymphocyte Ratio as a Risk Determinant of Hemorrhage Transformation in Acute Ischemic Stroke

Journal of Modern Neurology ◽

10.36922/jmn.v5i1.900 ◽

2020 ◽

pp. 8-16

Author(s):

Shuang Ma ◽

Bilal Muhammad ◽

Shu Kan ◽

Zhen-Ying Shang ◽

Li Wang ◽

...

Keyword(s):

Risk Factors ◽

Ischemic Stroke ◽

Acute Ischemic Stroke ◽

Multivariate Logistic Regression Analysis ◽

Hemorrhagic Transformation ◽

Neutrophil To Lymphocyte Ratio ◽

Optimal Cutoff ◽

Ischemic Lesion ◽

Lymphocyte Ratio ◽

Independent Risk Factors

Objective: The purpose of this study was to investigate the clinical significance between neutrophil-to-lymphocyte ratio (NLR) and classification of non-thrombolytic hemorrhagic transformation (HT) in acute ischemic stroke (AIS), to unravel new diagnostic approach. Methods: We recruited and selected 636 patients who did not undergo thrombolytic therapy between May 2018 and April 2019 at the Affiliated Hospital of Xuzhou Medical University. The laboratory and clinical data were collected within 24 h after the onset of AIS. Based on the status of HT development during hospitalization, all participants were divided into three groups, namely, the non-HT (NHT) group, hemorrhagic infarction (HI) group, and parenchymal hematoma (PH) group. Results: Multivariate logistic regression analysis showed that NLR and the ischemic lesion diameter are independent risk factors of HI and PH, while the score of National Institutes of Health Stroke Scale (NIHSS) and cardioembolism are considered to be independent risk factors for PH only. Receiver operating characteristic (ROC) analysis determined that the optimal cutoff values of NLR in HI group and PH group were 3.75 and 3.97, respectively. The optimal cutoff value can be used as the critical value for the unfavorable outcome. Conclusion: NLR values were significantly increased and correlated with both HI and PH groups and NLR could be used as a predictor of both HI and PH.

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