Prognostic Nutritional Index Predicts Clinical Outcome in Patients with Cerebral Venous Sinus Thrombosis

Abstract Background: Lower prognostic nutritional index (PNI) is related to poor prognosis of cardiovascular disease. However, little is known about PNI and its relationship with prognosis in cerebral venous sinus thrombosis (CVST).Methods: From January 2013 to June 2019, we retrospectively identified consecutive CVST patients. We selected patients in acute / subacute phase as subjects. Poor prognosis was defined as modified Rankin Scale (mRS) of 3-6. Multivariate logistic regression analysis was used to confirm if lower PNI was associated with poor prognosis. Results: A total of 297 subjects with 12-month follow-up data were enrolled. Thirty-three (11.1%) had poor outcome. Multivariate logistic regression analysis suggested that PNI was an important predictive factor of poor outcome in acute/subacute CVST (odds ratio, 0.903; 95% CI, 0.833-0.978; P = 0.012). The optimal cut-off value for predicting a poor prognosis of PNI was 44.2. Kaplan-Meier analysis and log-rank test suggested that the lower the PNI value, the higher the mortality rate (P<0.001). In addition, the nomogram we set up showed that lower PNI was an index of poor prognosis. The c-indexes for the cute/subacute patients with CVST was 0.872.Conclusions: Lower PNI is correlated with a higher risk of adverse clinical outcome in patients with acute/subacute CVST.

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Prognostic nutritional index predicts clinical outcomes in patients with cerebral venous sinus thrombosis

BMC Neurology ◽

10.1186/s12883-021-02436-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Jiawei Zhao ◽

Kai Liu ◽

Shen Li ◽

Yuan Gao ◽

Lu Zhao ◽

...

Keyword(s):

Regression Analysis ◽

Poor Prognosis ◽

Sinus Thrombosis ◽

Multivariate Logistic Regression Analysis ◽

Prognostic Nutritional Index ◽

Cerebral Venous Sinus Thrombosis ◽

Multivariate Logistic Regression ◽

Venous Sinus Thrombosis ◽

The Poor ◽

Nutritional Index

Abstract Background Lower prognostic nutritional index (PNI) is related to the poor prognosis of cardiovascular diseases. However, little is known about PNI and its relationship with the prognosis of cerebral venous sinus thrombosis (CVST). Methods CVST patients were retrospectively identified from January 2013 till June 2019. Patients in the acute / subacute phase were selected as subjects. Poor prognosis was defined as a modified Rankin Scale (mRS) of 3–6. Multivariate logistic regression analysis was used to confirm if lower PNI was associated with a poor prognosis. Results A total of 297 subjects with follow-up data were enrolled. Thirty-three (11.1%) had a poor outcome. Multivariate logistic regression analysis suggested that PNI was an important predictive factor of poor outcome in acute/subacute CVST (odds ratio, 0.903; 95% CI, 0.833–0.978; P = 0.012). The optimal cut-off value for predicting the poor prognosis of PNI was 44.2. Kaplan-Meier analysis and log-rank test suggested that the lower the PNI value, the higher the mortality rate (P < 0.001). In addition, the nomogram that was set up showed that lower PNI was an index of poor prognosis. The c-index for acute/subacute patients with CVST was 0.872. Conclusion Lower PNI is correlated with a higher risk of adverse clinical outcomes in patients with acute/subacute CVST.

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The Novel Biomarkers-Based HALP (Hemoglobin, Albumin, Lymphocyte And Platelet)-Prognostic Model For Acute And Subacute Patients With Cerebral Venous Sinus Thrombosis: A Retrospective Cohort Study

10.21203/rs.3.rs-91558/v1 ◽

2020 ◽

Author(s):

Shen Li ◽

Kai Liu ◽

Yuan Gao ◽

Lu Zhao ◽

Hui Fang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Functional Outcomes ◽

Prognostic Model ◽

Sinus Thrombosis ◽

Cerebral Venous Sinus Thrombosis ◽

Venous Sinus ◽

Clinical Prognosis ◽

Venous Sinus Thrombosis

Abstract Background: To evaluate the prognosis values of HALP in acute or subacute cerebral venous sinus thrombosis (CVST), to explore the new prognostic model for CVST.Methods: Consecutive patients who were diagnosed as having acute and subacute CVST were retrospectively investigated. We determined the patients' functional outcomes by modified Rankin Scale (mRS). Multivariate logistic regression analysis was used to assess the relationship between factors and poor functional outcomes. The area under the ROC curve (AUC) was estimated to evaluate the ability of markers and models in predicting clinical prognosis. The prognostic model was presented as nomogram. In addition, the decision curve analysis (DCA) was used to analyze the benefit of this model. Furthermore, survival curves were described by the Kaplan‑Meier analysis. Results: A total of 270 patients were included of which 31 had poor outcome. Multivariable logistic regression analysis demonstrated HALP (OR=0.978, 95%CI: 0.958-0.999, P=0.039) was a protective predictor of outcome. The AUC of HALP was 0.749 (95% CI: 0.633-0.865, P=0.044). DCA demonstrated that this model significantly improved risk prediction at threshold probabilities of CVST at 0 to 85%. Patients with higher HALP (P=0.006) presented higher overall survival rates. Conclusions: HALP may be a potential protective marker in acute and subacute CVST patients. The new prognostic model with HALP had potentially better value for Chinese CVST patients.

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The Novel Biomarkers-Based HALP (Hemoglobin, Albumin, Lymphocyte and Platelet)-Prognostic Model for Acute and Subacute Patients with Cerebral Venous Sinus Thrombosis: A Retrospective Cohort Study

10.21203/rs.3.rs-78715/v1 ◽

2020 ◽

Author(s):

Shen Li ◽

Kai Liu ◽

Yuan Gao ◽

Lu Zhao ◽

Hui Fang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Functional Outcomes ◽

Prognostic Model ◽

Sinus Thrombosis ◽

Cerebral Venous Sinus Thrombosis ◽

Venous Sinus ◽

Clinical Prognosis ◽

Venous Sinus Thrombosis

Abstract Background and purpose: To evaluate the prognosis values of HALP in acute or subacute cerebral venous sinus thrombosis (CVST), to explore the new prognostic model for CVST.Methods: Consecutive patients who were diagnosed as having acute and subacute CVST were retrospectively investigated. We determined the patients' functional outcomes by modified Rankin Scale (mRS). Multivariate logistic regression analysis was used to assess the relationship between factors and poor functional outcomes. The area under the ROC curve (AUC) was estimated to evaluate the ability of markers and models in predicting clinical prognosis. The prognostic model was presented as nomogram. In addition, the decision curve analysis (DCA) was used to analyze the benefit of this model. Furthermore, survival curves were described by the Kaplan‑Meier analysis. Results: A total of 270 patients were included of which 31 had poor outcome. Multivariable logistic regression analysis demonstrated HALP (OR=0.978, 95%CI: 0.958-0.999, P=0.039) was a protective predictor of outcome. The AUC of HALP was 0.749 (95% CI: 0.633-0.865, P=0.044). DCA demonstrated that this model significantly improved risk prediction at threshold probabilities of CVST at 0 to 85%. Patients with higher HALP (P=0.006) presented higher overall survival rates. Conclusions: HALP may be a potential protective marker in acute and subacute CVST patients. The new prognostic model with HALP had potentially better value for Chinese CVST patients.

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Scoring Model to Predict Functional Outcome in Poor-Grade Aneurysmal Subarachnoid Hemorrhage

Frontiers in Neurology ◽

10.3389/fneur.2021.601996 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jie Shen ◽

Jianbo Yu ◽

Sicong Huang ◽

Rajneesh Mungur ◽

Kaiyuan Huang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Subarachnoid Hemorrhage ◽

Poor Prognosis ◽

Aneurysmal Subarachnoid Hemorrhage ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Scoring Model ◽

Poor Grade ◽

New Scoring

Background: Patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH), defined as World Federation of Neurosurgical Societies (WFNS) grades IV–V have high rates of disability and mortality. The objective of this study was to accurately prognosticate the outcomes of patients with poor-grade aSAH by developing a new scoring model.Methods: A total of 147 poor-grade aSAH patients in our center were enrolled. Risk variables identified by multivariate logistic regression analysis were used to devise a scoring model (total score, 0–9 points). The scores were estimated on the basis of β coefficients. A cohort of 68 patients from another institute was used to validate the model.Results: Multivariate logistic regression analysis revealed that modified Fisher grade >2 [odds ratio [OR], 2.972; P = 0.034], age ≥65 years (OR, 3.534; P = 0.006), conservative treatment (OR, 5.078; P = 0.019), WFNS grade V (OR, 2.638; P = 0.029), delayed cerebral ischemia (OR, 3.170; P = 0.016), shunt-dependent hydrocephalus (OR, 3.202; P = 0.032), and cerebral herniation (OR, 7.337; P < 0.001) were significant predictors for poor prognosis [modified Rankin Scale [mRS] ≥3]. A scoring system was constructed by the integration of these factors and divided the poor-grade aSAH patients into three categories: low risk (0–1 points), intermediate risk (2–3 points), and high risk (4–9 points), with predicted risks of poor prognosis of 11, 52, and 87%, respectively (P < 0.001). The area under the curve in the derivation cohort was 0.844 (95% CI, 0.778–0.909). The AUC in the validation cohort was 0.831 (95% CI, 0.732–0.929).Conclusions: The new scoring model can improve prognostication and help decision-making for subsequent complementary treatment in patients with aSAH.

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Efficacy of flurbiprofen axetil for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries

JA Clinical Reports ◽

10.1186/s40981-020-00403-x ◽

2020 ◽

Vol 6 (1) ◽

Author(s):

Atsushi Kotera

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Postoperative Pain ◽

Logistic Regression Analysis ◽

Pain Control ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Postoperative Pain Control ◽

Flurbiprofen Axetil ◽

Postanesthetic Shivering

Abstract Background Postanesthetic shivering is an unpleasant adverse event in surgical patients. A nonsteroidal anti-inflammatory drug has been reported to be useful in preventing postanesthetic shivering in several previous studies. The aim of this study was to evaluate the efficacy of flurbiprofen axetil being a prodrug of a nonsteroidal anti-inflammatory drug for preventing postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries. Method This study is a retrospective observational study. I collected data from patients undergoing gynecologic laparotomy surgeries performed between October 1, 2019, and September 30, 2020, at Kumamoto City Hospital. All the patients were managed with general anesthesia with or without epidural analgesia. The administration of intravenous 50 mg flurbiprofen axetil for postoperative pain control at the end of the surgery was left to the individual anesthesiologist. The patients were divided into two groups: those who had received intravenous flurbiprofen axetil (flurbiprofen group) and those who had not received intravenous flurbiprofen axetil (non-flurbiprofen group), and I compared the frequency of postanesthetic shivering between the two groups. Additionally, the factors presumably associated with postanesthetic shivering were collected from the medical charts. Intergroup differences were assessed with the χ2 test with Yates’ correlation for continuity category variables. The Student’s t test was used to test for differences in continuous variables. Furthermore, a multivariate logistic regression analysis was performed to elucidate the relationship between the administration of flurbiprofen axetil and the incidence of PAS. Results I retrospectively examined the cases of 141 patients aged 49 ± 13 (range 21-84) years old. The overall postanesthetic shivering rate was 21.3% (30 of the 141 patients). The frequency of postanesthetic shivering in the flurbiprofen group (n = 31) was 6.5%, which was significantly lower than that in the non-flurbiprofen group (n = 110), 25.5% (p value = 0.022). A multivariate logistic regression analysis showed that administration of flurbiprofen axetil was independently associated with a reduced incidence of postanesthetic shivering (odds ratio 0.12; 95% confidence interval, 0.02-0.66, p value = 0.015). Conclusions My result suggests that intraoperative 50 mg flurbiprofen axetil administration for postoperative pain control is useful to prevent postanesthetic shivering in patients undergoing gynecologic laparotomy surgeries.

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The association between hypoglycemia and glycemic variability in elderly patients with type 2 diabetes: a prospective observational study

Diabetology & Metabolic Syndrome ◽

10.1186/s13098-021-00656-1 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Takahisa Handa ◽

Akinobu Nakamura ◽

Aika Miya ◽

Hiroshi Nomoto ◽

Hiraku Kameda ◽

...

Keyword(s):

Type 2 Diabetes ◽

Logistic Regression ◽

Regression Analysis ◽

Observational Study ◽

Elderly Patients ◽

Prospective Observational Study ◽

Multivariate Logistic Regression Analysis ◽

Glycemic Variability ◽

Multivariate Logistic Regression

Abstract Background This study aimed to explore predictive factors of time below target glucose range (TBR) ≥ 1% among patients’ characteristics and glycemic variability (GV) indices using continuous glucose monitoring data in elderly patients with type 2 diabetes. Methods We conducted a prospective observational study on 179 (71 female) Japanese outpatients with type 2 diabetes aged ≥ 65 years. The characteristics of the participants with TBR ≥ 1% were evaluated by multivariate logistic regression analysis. Receiver-operating characteristic (ROC) curve analyses of GV indices, comprising coefficient of variation (CV), standard deviation, and mean amplitude of glycemic excursions, were performed to identify the optimal index for the identification of patients with TBR ≥ 1%. Results In the multivariate logistic regression analysis, none of the clinical characteristics, including HbA1c and C-peptide index, were independent markers for TBR ≥ 1%, while all three GV indices showed significant associations with TBR ≥ 1%. Among the three GV indices, CV showed the best performance based on the area under the curve in the ROC curve analyses. Conclusions Among elderly patients with type 2 diabetes, CV reflected TBR ≥ 1% most appropriately among the GV indices examined. Trial registration UMIN-CTR: UMIN000029993. Registered 16 November 2017

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Risk factors for tissue expander infection in scar reconstruction: a retrospective cohort study of 2374 consecutive cases

Burns & Trauma ◽

10.1093/burnst/tkaa037 ◽

2020 ◽

Vol 8 ◽

Author(s):

Chen Dong ◽

Minhui Zhu ◽

Luguang Huang ◽

Wei Liu ◽

Hengxin Liu ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Treatment Failure ◽

Logistic Regression Analysis ◽

Disease Duration ◽

Multivariate Logistic Regression Analysis ◽

Tissue Expansion ◽

Multivariate Logistic Regression ◽

Hematoma Evacuation

Abstract Background Tissue expansion is used for scar reconstruction owing to its excellent clinical outcomes; however, the complications that emerge from tissue expansion hinder repair. Infection is considered a major complication of tissue expansion. This study aimed to analyze the perioperative risk factors for expander infection. Methods A large, retrospective, single-institution observational study was carried out over a 10-year period. The study enrolled consecutive patients who had undergone tissue expansion for scar reconstruction. Demographics, etiological data, expander-related characteristics and postoperative infection were assessed. Univariate and multivariate logistic regression analysis were performed to identify risk factors for expander infection. In addition, we conducted a sensitivity analysis for treatment failure caused by infection as an outcome. Results A total of 2374 expanders and 148 cases of expander infection were assessed. Treatment failure caused by infection occurred in 14 expanders. Multivariate logistic regression analysis identified that disease duration of ≤1 year (odds ratio (OR), 2.07; p < 0.001), larger volume of expander (200–400 ml vs <200 ml; OR, 1.74; p = 0.032; >400 ml vs <200 ml; OR, 1.76; p = 0.049), limb location (OR, 2.22; p = 0.023) and hematoma evacuation (OR, 2.17; p = 0.049) were associated with a high likelihood of expander infection. Disease duration of ≤1 year (OR, 3.88; p = 0.015) and hematoma evacuation (OR, 10.35; p = 0.001) were so related to high risk of treatment failure. Conclusions The rate of expander infection in patients undergoing scar reconstruction was 6.2%. Disease duration of <1 year, expander volume of >200 ml, limb location and postoperative hematoma evacuation were independent risk factors for expander infection.

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Donepezil Combined with DL-3-n-Butylphthalide Delays Cognitive Decline in Patients with Mild to Moderate Alzheimer’s Disease: A Multicenter, Prospective Cohort Study

Journal of Alzheimer s Disease ◽

10.3233/jad-201381 ◽

2021 ◽

Vol 80 (2) ◽

pp. 673-681

Author(s):

Jin Wang ◽

Xiaojuan Guo ◽

Wenhui Lu ◽

Jie Liu ◽

Hong Zhang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Logistic Regression ◽

Regression Analysis ◽

Cohort Study ◽

Prospective Cohort ◽

Daily Living ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Significant Difference

Background: Vascular factors and mitochondria dysfunction contribute to the pathogenesis of Alzheimer’s disease (AD). DL-3-n-butylphthalide (NBP) has an effect in protecting mitochondria and improving microcirculation. Objective: The aim was to investigate the effect of donepezil combined NBP therapy in patients with mild-moderate AD. Methods: It was a prospective cohort study. 92 mild-moderate AD patients were classified into the donepezil alone group (n = 43) or the donepezil combined NBP group (n = 49) for 48 weeks. All patients were evaluated with Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog), Clinician’s Interview-Based Impression of Change plus caregiver input (CIBIC-plus), Alzheimer’s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), and Neuropsychiatric Inventory (NPI) every 12 weeks. All patients were monitored for adverse events (AEs). The efficacy was analyzed using multivariate logistic regression analysis. Results: The multivariate logistic regression analysis showed that the changes of ADAS-cog score (OR = 2.778, 95% CI: [1.087, 7. 100], p = 0.033) and ADCS-ADL score (OR = 2.733, 95% CI: [1.002, 7.459], p = 0.049) had significant difference between donepezil alone group and donepezil combined NBP group, while the changes of NPI (OR = 1.145, 95% CI: [0.463, 2.829], p = 0.769), MMSE (OR = 1.563, 95% CI: [0.615, 3.971], p = 0.348) and CIBIC-plus (OR = 2.593, 95% CI: [0.696, 9.685], p = 0.156) had no significant difference. The occurrence of AEs was similar in the two groups. Conclusion: Over the 48-week treatment period, donepezil combined NBP group had slower cognitive decline and better activities of daily living in patients with mild to moderate AD. These indicated that the multi-target therapeutic effect of NBP may be a new choice for AD treatment.

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