A Metabolomics Study of Serum in Hospitalized Patients With Chronic Schizophrenia

Purpose: Metabolomics has attracted attention as a new method for understanding the molecular mechanisms of psychiatric disorders. Current metabolomics technology allows us to measure over hundreds of metabolites at a time and is a useful indicator of the consequences of complex and continuous changes in metabolic profiles due to the execution of genomic information and external factors of biological activity. Therefore, metabolomics is imperative to the discovery of biomarkers and mechanisms associated with pathophysiological processes. In this study, we investigated metabolites changes in hospitalized patients with chronic schizophrenia compared to that in healthy controls, and examined the correlations between the metabolites and psychiatric symptoms.Patients and Methods: Thirty patients with schizophrenia and ten healthy controls participated in this study between September 2019 and June 2020. The mean duration of disease in patients with schizophrenia was 26 years. Clinical and neuropsychiatric symptoms of patients with schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS). Metabolomics was conducted using Capillary Electrophoresis Fourier Transform Mass Spectrometry (CE-FTMS), using serum samples from patients with schizophrenia and healthy controls. Metabolomics assigned a candidate compound to the 446 (cation 279, anion 167) peaks. Hierarchical cluster analysis (HCA), principal component analysis (PCA), logistic regression analysis, receiver operating characteristic (ROC) analysis, and linear regression analysis were used to analyze the metabolites changes, identifying the disease and the relationship between metabolites and psychiatric symptoms.Results: HCA showed that approximately 60% of metabolites had lower peak values in patients with schizophrenia than in healthy controls. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in patients with schizophrenia. PCA showed a clear separation between patients with schizophrenia and healthy controls in the first principal component (the contribution ratio of the first principal component was 15.9%). Logistic regression analysis suggested that the first principal component was a predictor of disease (odds = 1.36, 95%CI = 1.11–1.67, p = 0.0032). ROC analysis showed a sensitivity of 93% and a specificity of 100% for the diagnosis of schizophrenia with a cut-off value of the first principal component; −3.33 (AUC = 0.95). We extracted the high factor loading for the first principal component. Gamma-glutamyl-valine (γ-Glu-Val) was significantly negatively correlated with PANSS total scores (r = −0.45, p = 0.012) and PANSS general scores (r = −0.49, p = 0.0055). Gamma-glutamyl-phenylalanine (γ-Glu-Phe) was significantly negatively correlated with PANSS total score (r = −0.40, p = 0.031) and PANSS general score (r = −0.41, p = 0.025). Tetrahydrouridine was significantly positively correlated with PANSS negative scores (r = 0.53, p = 0.0061).Conclusion: Metabolites changes in hospitalized patients with chronic schizophrenia showed extensive and generalized declines. Glutamate metabolism and the urea cycle had the highest proportions in the metabolic pathway, which decreased in the schizophrenia group. Metabolomic analysis was useful to identify chronic schizophrenia. Some glutamate compound metabolites had a relationship with psychiatric symptoms.

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Sex-Disaggregated Data on Clinical Characteristics and Outcomes of Hospitalized Patients With COVID-19: A Retrospective Study

Frontiers in Cellular and Infection Microbiology ◽

10.3389/fcimb.2021.680422 ◽

2021 ◽

Vol 11 ◽

Author(s):

Mengdie Wang ◽

Nan Jiang ◽

Changjun Li ◽

Jing Wang ◽

Heping Yang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Clinical Characteristics ◽

Random Effect ◽

Hospitalized Patients ◽

Male And Female ◽

Female Patients ◽

Disease Outcomes ◽

Male Patients

BackgroundSex and gender are crucial variables in coronavirus disease 2019 (COVID-19). We sought to provide information on differences in clinical characteristics and outcomes between male and female patients and to explore the effect of estrogen in disease outcomes in patients with COVID-19.MethodIn this retrospective, multi-center study, we included all confirmed cases of COVID-19 admitted to four hospitals in Hubei province, China from Dec 31, 2019 to Mar 31, 2020. Cases were confirmed by real-time RT-PCR and were analyzed for demographic, clinical, laboratory and radiographic parameters. Random-effect logistic regression analysis was used to assess the association between sex and disease outcomes.ResultsA total of 2501 hospitalized patients with COVID-19 were included in the present study. The clinical manifestations of male and female patients with COVID-19 were similar, while male patients have more comorbidities than female patients. In terms of laboratory findings, compared with female patients, male patients were more likely to have lymphopenia, thrombocytopenia, inflammatory response, hypoproteinemia, and extrapulmonary organ damage. Random-effect logistic regression analysis indicated that male patients were more likely to progress into severe type, and prone to ARDS, secondary bacterial infection, and death than females. However, there was no significant difference in disease outcomes between postmenopausal and premenopausal females after propensity score matching (PSM) by age.ConclusionsMale patients, especially those age-matched with postmenopausal females, are more likely to have poor outcomes. Sex-specific differences in clinical characteristics and outcomes do exist in patients with COVID-19, but estrogen may not be the primary cause. Further studies are needed to explore the causes of the differences in disease outcomes between the sexes.

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Dynamic evolution of osseous structure in osteonecrosis of the femoral head and dynamic collapse risks: a preliminary CT image study

Journal of Orthopaedic Surgery and Research ◽

10.1186/s13018-020-02069-8 ◽

2020 ◽

Vol 15 (1) ◽

Author(s):

Zeqing Huang ◽

Biao Tan ◽

Hengli Ye ◽

Fanyu Fu ◽

Rongtian Wang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Soft Tissue ◽

Femoral Head ◽

Roc Analysis ◽

Disease Duration ◽

Radiographic Progression ◽

Dynamic Evolution ◽

Sclerotic Bone ◽

Osseous Structure

Abstract Background Collapse risk of osteonecrosis of the femoral head (ONFH) is estimated mainly based on static indicators, including lesion size and lesion location, but bone repairing is a dynamic process that lasts for years. The present study attempted to analyze the dynamic evolution of the osseous structure and its correlation with radiographic progression. Methods This retrospective study included 50 hips with ONFH from 50 patients. Participants were divided into the non-collapse group (n = 25) and the collapse group (n = 25). Original files of the initial computed tomography (CT) images were imported into imaging processing software for morphology analysis. The volume of sclerotic bone, the volume of soft tissue, and bone mineral density (BMD) were calculated. The linear correlations between the aforementioned indicators and the disease duration were estimated. The logistic regression analysis was conducted to evaluate the correlation of these indicators with the radiographic progression. Receiver operating characteristic (ROC) analysis was used to evaluate these indicators’ prediction performance. Results The volume of sclerotic bone and the BMD grew with disease duration, but the volume of soft tissue decrease. The logistic regression analysis found that the volume of sclerotic bone and the BMD were statistically associated with radiographic progression. The ROC analysis found that the regression model, which integrated the volume of sclerotic bone and the BMD, had satisfactory performance in predicting radiographic progression. Conclusion The present study suggested a dynamic evolution of the osseous structure and a dynamic variation trend of the collapse risk in ONFH. The volume of sclerotic bone and the BMD might serve as further prognostic indicators when estimating the collapse risk.

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Association between Carotid Artery Calcification and Periodontal Disease Progression in Japanese Men and Women: A Cross-Sectional Study

Journal of Clinical Medicine ◽

10.3390/jcm9103365 ◽

2020 ◽

Vol 9 (10) ◽

pp. 3365

Author(s):

Nanae Dewake ◽

Yasuaki Ishioka ◽

Keiichi Uchida ◽

Akira Taguchi ◽

Yukihito Higashi ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Carotid Artery ◽

Logistic Regression Analysis ◽

Roc Analysis ◽

Multivariate Logistic Regression Analysis ◽

Multivariate Logistic Regression ◽

Panoramic Radiographs ◽

Carotid Artery Calcification ◽

Univariate Analyses

Objective: To evaluate the association between alveolar bone loss (ABL) detected on panoramic radiographs and carotid artery calcification (CAC) detected on computed tomography (CT). Methods: The study subjects included 295 patients (mean age ± SD: 64.6 ± 11.8 years) who visited the Matsumoto Dental University Hospital. The rate of ABL and the number of present teeth were measured on panoramic radiographs. Univariate analyses with t-tests and chi-squared tests were performed to evaluate the differences in age, gender, history of diseases, number of present teeth, and the ABL between subjects, with and without CAC. Moreover, multivariate logistic regression analysis, with forward selection and receiver operating characteristic curve (ROC) analysis, was performed. Results: The number of subjects without and with CAC was 174 and 121, respectively. Univariate analyses revealed that CAC was significantly associated with age, hypertension, osteoporosis, number of present teeth, and ABL. Multivariate logistic regression analysis adjusted for covariates revealed that the presence of CAC was significantly associated with ABL (OR = 1.233, 95% CI = 1.167–1.303). In the ROC analysis for predicting the presence of CAC, the the area under the ROC curve was the highest at 0.932 (95% CI = 0.904–0.960) for ABL, which was significant. Conclusions: Our results suggest that the measurement of ABL on panoramic radiographs may be an effective approach to identifying patients with an increased risk of CAC.

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Predictors for Development of Oxaliplatin-induced Peripheral Neuropathy in Cancer Patients as Determined by Ordered Logistic Regression Analysis

10.21203/rs.3.rs-847675/v2 ◽

2021 ◽

Author(s):

Yuko Kanbayashi ◽

Takeshi Ishikawa ◽

Yoshiaki Kuriu ◽

Yusuke Tabuchi ◽

Eigo Otsuji ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Peripheral Neuropathy ◽

Cancer Patients ◽

Logistic Regression Analysis ◽

Roc Analysis ◽

Operating Characteristic ◽

Ordered Logistic Regression ◽

Number Of Cycles ◽

Significant Factors

Abstract Purpose This retrospective study aimed to identify predictors for the development of oxaliplatin-induced peripheral neuropathy (OXAIPN). Methods Between January 2017 and March 2021, a total 322 cancer patients at our hospital who were receiving oxaliplatin were enrolled. For the regression analysis of factors associated with oxaliplatin-induced peripheral neuropathy, variables were extracted manually from medical charts. The level of OXAIPN was evaluated using the National Cancer Institute’s Common Terminology Criteria for Adverse Events (version 5). Multivariate ordered logistic regression analysis was performed to identify predictors for the development of OXAIPN. Optimal cut-off thresholds were determined using receiver operating characteristic (ROC) analysis. Values of P <0.05 (2-tailed) were considered significant. Results Significant factors identified included body mass index (BMI) (odds ratio [OR] = 1.06, 95% confidence interval [CI] = 1.00–1.12; P = 0.046), number of cycles (OR = 1.09, 95%CI = 1.05–1.14; P <0.0001), S-1 plus oxaliplatin (SOX) regimen (OR = 0.54, 95%CI = 0.32–0.92; P = 0.023), concomitant use of proton pump inhibitors (PPIs) (OR = 1.64, 95%CI = 1.05–2.58; P = 0.031) and concomitant use of analgesic adjuvant (OR = 3.30, 95%CI = 1.09–9.97; P = 0.035). Conclusion BMI, number of cycles, SOX regimen, concomitant use of PPIs and concomitant use of analgesic drugs were identified as significant predictors for the development of OXAIPN.

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The prevalence and clinical characteristics of diabetes mellitus in Chinese inpatients with chronic schizophrenia: a multicenter cross-sectional study

PeerJ ◽

10.7717/peerj.12553 ◽

2021 ◽

Vol 9 ◽

pp. e12553

Author(s):

Yanni Wang ◽

Lingyun Zeng ◽

Lijuan Chen ◽

Xin Zhou ◽

Lijuan Huo ◽

...

Keyword(s):

Diabetes Mellitus ◽

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Clinical Characteristics ◽

Chronic Schizophrenia ◽

Cross Sectional Study ◽

World Health ◽

Sectional Study ◽

Cross Sectional

Background Diabetes mellitus (DM) is common among patients with schizophrenia. However, information on patients comorbid DM and schizophrenia is limited in China. The present study investigated the prevalence of DM and its clinical characteristics in Chinese inpatients with chronic schizophrenia. Methods A cross-sectional study was performed in Chinese inpatients with chronic schizophrenia. Diagnosis of Diabetes was established using World Health Organization diagnostic criteria for diabetes mellitus (persistent fasting glucose levels ≥ 126 mg/dl or 2-h plasma glucose ≥ 200 mg/dL after a 75-g Oral Glucose Tolerance Test). Patients were also measured height, weight, waist circumference, hip circumference, triglyceride level, and cholesterol level. Patients’ psychiatric symptoms were measured by the Positive and Negative Syndrome Scale (PANSS). Binary logistic regression analysis was performed to examine the associated demographic and clinical variables in chronic schizophrenia. Results A total of 988 inpatients (64.6% male, average age of 47.19 ± 12.55) was recruited. The prevalence of DM in Chinese patients with chronic schizophrenia was 13.8% (95% CI [11.6–15.9]%). Logistic regression analysis showed that overweight (OR = 1.90, 95% CI [1.20–3.03], p = 0.006), obesity (OR = 1.85, 95% CI [1.07–3.21], p = 0.028), comorbid hypertension (OR = 2.14, 95% CI [1.34–3.42], p = 0.002), and course of schizophrenia (OR = 1.03, 95% CI [1.01–1.06], p = 0.040) were significantly associated with the DM risk in patients with schizophrenia. Conclusion The findings indicated that diabetes mellitus was non-negligible in patients with chronic schizophrenia. Patients with schizophrenia should be regularly monitored for DM. Overweight/obesity, long duration of schizophrenia, and comorbid hypertension possibly were risk factors for diabetes.

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Culturally sensitive assessment of anxious-depressive distress in the Cambodian population: Avoiding category truncation

Transcultural Psychiatry ◽

10.1177/1363461519851609 ◽

2019 ◽

Vol 56 (4) ◽

pp. 643-666 ◽

Cited By ~ 6

Author(s):

Devon E. Hinton ◽

Desiree M. Seponski ◽

Sareth Khann ◽

Stephanie E. Armes ◽

Cindy J. Lahar ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

General Population ◽

Roc Analysis ◽

Sleep Paralysis ◽

Symptom Checklist ◽

Hopkins Symptom Checklist ◽

Study Results ◽

Standing Up ◽

Blurry Vision

In a large national survey in Cambodia (N = 2689), the present study investigated the prominence of certain culturally salient symptoms and syndromes in the general population and among those with anxious-depressive distress (as determined by the Hopkins Symptom Checklist-25, or HSCL). Using an abbreviated Cambodian Symptom and Syndrome Addendum (CSSA), we found that the CSSA complaints were particularly elevated among those with anxious-depressive distress. Those with anxious-depressive distress had statistically greater mean scores on all the CSSA items as well as severity of endorsement analyzed by percentage: among those with HSCL caseness, 75.3% were bothered “quite a bit” or “extremely” by “thinking a lot” (vs. 27.5% without caseness); 53.8% were bothered by “standing up and feeling dizzy” (vs. 13.8%); and 45.6% by blurry vision (vs. 16.8%). In a logistic regression analysis to predict anxious-depressive distress, 51% of the variance was accounted for by five predictors: “weak heart,” “thinking a lot,” dizziness, “ khyâl hitting up from the stomach,” and sleep paralysis. Using ROC analysis, a cut-off score of 1.81 on the CSSA was optimal as a screener to indicate anxious-depressive distress, giving a sensitivity of 0.86. The study results suggest that to avoid category truncation (i.e., the omission of key complaints that are part of an assessed distress domain) when profiling anxious-depressive distress among Cambodia population that items other than those in standard psychopathology measures should be assessed such as “thinking a lot,” “weak heart,” “blurry vision,” and “dizziness upon standing up.”

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Long Noncoding RNA GUSBP3 And SAM4 Function As Potential Diagnostic Biomarkers of Type 2 Diabetes Mellitus In Kazak Populations In The Xinjiang Region of China

10.21203/rs.3.rs-949228/v1 ◽

2021 ◽

Author(s):

Tao Ba ◽

Tianshui Ma ◽

Yuan Sun ◽

YuRong Zhu ◽

Xiaoli Wang ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Real Time ◽

Microarray Analysis ◽

Logistic Regression Analysis ◽

Differentially Expressed ◽

Healthy Controls ◽

Chain Reaction ◽

Diagnostic Biomarkers ◽

Kazakh Population

Abstract Background: The pathogenesis of T2DM is influenced by a combination of genetic and environmental factors, among which LncRNAs have a huge impact on diabetes.In this study, we investigated the diagnostic value of lncRNA GUSBP3 and lncRNA SAM4 for T2DM in Kazakhs in Xinjiang. Methods: In this study, differentially expressed lncRNAs and mRNAs were screened by microarray analysis microarray in a Kazakh population in Xinjiang, and the expression of two candidate lncRNAs (lnc-GUSBP-3 and lnc-SAM-4) was further validated by quantitative real-time polymerization chain reaction (qRT-PCR).Meanwhile, GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Spearman’s correlation analysis was used to elucidate the correlation between lnc-GUSBP-3 and lnc-SAM-4 expression and metabolic characteristics. We found that the expression of lnc-GUSBP-3 and lnc-SAM-4 was up-regulated in the T2DM group compared to healthy controls. Multivariate logistic regression analysis showed that DBP, FIns and lnc-GUSBP3 were associated with T2DM susceptibility.In addition, ROC curves were used to evaluate the diagnostic potential of lnc-GUSBP3 and lnc-SAM4. Results: We conducted a microarray analysis of PBMC collected from patients with T2DM and healthy controls, all of Kazakh origin. In the microanalysis, we identified 89 differentially expressed lncRNAs, and 147 differentially expressed mRNAs. real-time quantitative reverse transcription polymerase chain reaction analysis of peripheral blood mononuclear cell (PBMC) samples from T2DM patients and healthy controls from the Xinjiang Kazakh population revealed significantly increased levels of lncRNAs GUSBP3 and SAM4 in T2DM patients. Logistic regression analysis revealed that lncRNA GUSBP3 expression correlated negatively with FIns, but positively with creatinine and uric acid (UA). Furthermore, lncRNA SAM4 expression correlated negatively with low-density lipoprotein cholesterol levels, but positively with UA. The area under the receiver operating characteristic curve values for lnc-GUSBP3 and lnc-SAM4 were 0.789 (95% CI = 0.672–0.906) and 0.741 (95% CI = 0.616–0.866), respectively. Conclusion: There were significant changes in lncRNA and mRNA in Kazakh T2DM patients. LncRNA-GUSBP3 and lncRNA-SAM4 may serve as potential diagnostic biomarkers for T2DM in Kazakhs in Xinjiang.

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Association Between Serum Insulin-Like Growth Factor 1 Levels and the Clinical Symptoms of Chronic Schizophrenia: Preliminary Findings

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.653802 ◽

2021 ◽

Vol 12 ◽

Author(s):

Naomichi Okamoto ◽

Koji Yoshino ◽

Shogo Kitagawa ◽

Rintaro Fujii ◽

Shinsuke Hamada ◽

...

Keyword(s):

Growth Factor ◽

Environmental Health ◽

Clinical Symptoms ◽

Psychiatric Symptoms ◽

Serum Insulin ◽

Chronic Schizophrenia ◽

Healthy Controls ◽

Insulin Like Growth Factor ◽

Significant Difference ◽

The University

Purpose: Insulin-like growth factor 1 (IGF-1) is a trophic mediator that is regulated by growth hormone and associated with the proliferation, development, and growth of neural cells. IGF-1 may be associated with the pathophysiology of schizophrenia, but this association remains controversial. This study aimed to investigate the relationship between serum IGF-1 levels and psychiatric symptoms in patients with chronic schizophrenia.Patients and Methods: A total of 65 patients were recruited from the University of Occupational and Environmental Health, Komine Eto Hospital, Moji Matsugae Hospital, Shin-Moji Hospital, and Tsutsumi Hospital in Kitakyushu between September 2019 and June 2020. Further, 20 healthy age- and sex-matched control participants were recruited from the Komine Eto Hospital and the University of Occupational and Environmental Health. Patients with schizophrenia were assessed using the Positive and Negative Syndrome Scale (PANSS) and the Drug-Induced Extrapyramidal Symptoms Scale. Serum levels of free plus albumin-bound IGF-1 (IGF-1) were measured by immunoradiometric assay. The measurements were performed using antibody beads for bound/free separation. Associations between serum IGF-1 levels and the PANSS scores were determined. We also examined the associations between serum IGF-1 levels and diabetes, antipsychotic drug use, and disease duration.Results: No significant difference was found in the serum IGF-1 level between patients with schizophrenia and healthy controls. Serum IGF-1 levels were significantly negatively correlated with the PANSS total score (R2 = 0.06, p = 0.015) and PANSS general score (R2 = 0.088, p = 0.008), but not with the PANSS positive scores and PANSS negative scores. Serum IGF-1 levels were not related to the prevalence of diabetes (p = 0.64). However, a significant correlation was observed between serum IGF-1 levels and age (B = −1.88, p < 0.0001). Serum IGF-1 levels could not distinguish patients with schizophrenia and healthy controls.Conclusion: The association between serum IGF-1 levels and psychiatric symptoms may be complicated in patients with chronic schizophrenia.

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LDL-C/HDL-C is associated with ischaemic stroke in patients with non-valvular atrial fibrillation: a case-control study

10.21203/rs.3.rs-60899/v2 ◽

2020 ◽

Author(s):

Xiao-Xue Zhang ◽

Meng Wei ◽

Lu-Xiang Shang ◽

Yan-Mei Lu ◽

Ling Zhang ◽

...

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Logistic Regression ◽

Regression Analysis ◽

Roc Curve ◽

Principal Component Regression ◽

Principal Component ◽

Multivariate Logistic Regression ◽

Principal Component Regression Analysis ◽

Independent Risk Factors

Abstract Background: This study explored the relationships between the low-/high-density lipoprotein cholesterol ratio (LDL-C/HDL-C) and other clinical indicators and ischaemic stroke (IS) in patients with non-valvular atrial fibrillation (NVAF) in Xinjiang. The findings could provide a theoretical and therapeutic basis for NVAF patients.Methods: NVAF patients who were admitted to 10 medical centres across Xinjiang were divided into stroke (798 patients) and control (2671 patients) groups according to the occurrence of first acute IS occurred. Univariate and multivariate logistic regression analysis were used to examine the independent risk factors for IS in NVAF patients. Factor analysis and principal component regression analysis were used to analyse the main factors influencing IS. Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminatory ability of LDL-C/HDL-C for predicting the occurrence of IS.Results: The stroke group had an average age of 71.64 ± 9.96 years and included 305 females (38.22%). The control group had a mean age of 67.30 ± 12.01 years and included 825 females (30.89%). Multivariate logistic regression showed that the risk of IS in the highest LDL-C/HDL-C quartile ( ≥2.73) was 16.23-fold that of the lowest quartile ( < 1.22); IS risk was 2.27-fold higher in obese patients than in normal-weight subjects; IS risk was 3.15-fold higher in smoking patients than in non-smoking patients. The area under the ROC curve of LDL-C/HDL-C was 0.76, the optimal critical value was 2.33, the sensitivity was 63.53%, and the specificity was 76.34%. Principal component regression analysis showed that LDL-C/HDL-C, age, smoking, drinking, LDL-C and hypertension were risk factors for IS in NVAF patients.Conclusions: LDL-C/HDL-C >1.22, smoking, BMI ≥24 kg/m2 and CHA2DS2-VASc score were independent risk factors for IS in NVAF patients; LDL-C/HDL-C was the main risk factor.

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LDL-C/HDL-C is associated with ischaemic stroke in patients with non-valvular atrial fibrillation: a case-control study

10.21203/rs.3.rs-60899/v3 ◽

2020 ◽

Author(s):

Xiao-Xue Zhang ◽

Meng Wei ◽

Lu-Xiang Shang ◽

Yan-Mei Lu ◽

Ling Zhang ◽

...

Keyword(s):

Risk Factors ◽

Atrial Fibrillation ◽

Logistic Regression ◽

Regression Analysis ◽

Roc Curve ◽

Principal Component Regression ◽

Principal Component ◽

Multivariate Logistic Regression ◽

Principal Component Regression Analysis ◽

Independent Risk Factors

Abstract Background: This study explored the relationships between the low-/high-density lipoprotein cholesterol ratio (LDL-C/HDL-C) and other clinical indicators and ischaemic stroke (IS) in patients with non-valvular atrial fibrillation (NVAF) in Xinjiang. The findings could provide a theoretical and therapeutic basis for NVAF patients.Methods: NVAF patients who were admitted to 10 medical centres across Xinjiang were divided into stroke (798 patients) and control (2671 patients) groups according to the occurrence of first acute IS. Univariate and multivariate logistic regression analysis were used to examine the independent risk factors for IS in NVAF patients. Factor analysis and principal component regression analysis were used to analyse the main factors influencing IS. Receiver operating characteristic (ROC) curve analysis was used to evaluate the discriminatory ability of LDL-C/HDL-C for predicting the occurrence of IS.Results: The stroke group had an average age of 71.64 ± 9.96 years and included 305 females (38.22%). The control group had a mean age of 67.30 ± 12.01 years and included 825 females (30.89%). Multivariate logistic regression showed that the risk of IS in the highest LDL-C/HDL-C quartile ( ≥2.73) was 16.23-fold that of the lowest quartile ( < 1.22); IS risk was 2.27-fold higher in obese patients than in normal-weight subjects; IS risk was 3.15-fold higher in smoking patients than in non-smoking patients. The area under the ROC curve of LDL-C/HDL-C was 0.76, the optimal critical value was 2.33, the sensitivity was 63.53%, and the specificity was 76.34%. Principal component regression analysis showed that LDL-C/HDL-C, age, smoking, drinking, LDL-C and hypertension were risk factors for IS in NVAF patients.Conclusions: LDL-C/HDL-C >1.22, smoking, BMI ≥24 kg/m2 and CHA2DS2-VASc score were independent risk factors for IS in NVAF patients; LDL-C/HDL-C was the main risk factor.

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