Predictive criteria of severe cases in COVID-19 patients of early stage

Abstract Background: Patients with coronavirus disease 2019 (COVID-19) often suffer sudden deterioration of disease around 1 to 2 weeks after onset. Once the disease progressed to severe phase, clinical prognosis of patients will significantly deteriorate.Methods: This was a multicenter retrospective study on patients of all adult inpatients (≥18 years old) from Tianyou Hospital (Wuhan, China) and the Fourth Affiliated Hospital, Zhejiang University School of Medicine. All 139 patients had laboratory-confirmed COVID-19 in their early stage, which is defined as within 7 days of clinical symptoms or within 7 days of positive viral nucleic acid test for asymptomatic patients. Univariate and multivariate logistic regression models were used to determine the predictive factors in the early detection of patients who may subsequently develop into severe cases.Results: Multivariable logistic regression analysis showed that the higher level of hypersensitivity C-reactive protein (OR=4.77, 95% CI:1.92-11.87, P=0.001), elevated alanine aminotransferase (OR=6.87, 95%CI:1.56-30.21, P=0.011) and chronic comorbidities (OR=11.48, 95% CI:4.44-29.66, P<0.001) are the determining risk factors for the progression into severe pneumonia in COVID-19 patients.Conclusion: Early COVID-19 patients with chronic comorbidities, elevated hs-CRP or elevated ALT are significantly more likely to develop severe pneumonia as the disease progresses. These risk factors may facilitate the early diagnosis of critical patients in clinical practice.

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EXPRESS: A Composite Risk Model Predicts Disease Progression in Early Stages of COVID-19: a Propensity Score-matched Cohort Study

Annals of Clinical Biochemistry International Journal of Laboratory Medicine ◽

10.1177/00045632211011194 ◽

2021 ◽

pp. 000456322110111

Author(s):

Jianjun Xu ◽

Yang Gao ◽

Shaobo Hu ◽

Suzhen Li ◽

Weimin Wang ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Disease Progression ◽

Logistic Regression Analysis ◽

Risk Model ◽

Early Stage ◽

Area Under The Curve ◽

Multivariable Logistic Regression Analysis ◽

Early Stages

Background: Recently, studies on COVID-19 have focused on the epidemiology of the disease and clinical characteristics of patients, as well as on the risk factors associated with mortality during hospitalization in critical COVID-19 cases. However, few research has been performed on the prediction of disease progression in particular group of patients in the early stages of COVID-19. Methods: The study included 338 patients with COVID-19 treated at two hospitals in Wuhan, China, from December, 2019 to March, 2020. Predictors of the progression of COVID-19 from mild to severe stages were selected by the logistic regression analysis. Results: COVID-19 progression to severe and critical stages was confirmed in 78(23.1%) patients. The average value of the neutrophil-to-lymphocyte ratio (NLR) was higher in patients in the disease progression group than in the improvement group. Multivariable logistic regression analysis revealed that elevated NLR, LDH, and IL-10, were independent predictors of disease progression. The optimal cut-off value of NLR was 3.75. The values of the area under the curve, reflecting the accuracy of predicting COVID-19 progression by NLR was 0.739(95%CI: 0.605-0.804). The risk model based on NLR, LDH and IL-10 had the highest area under the ROC curve. Conclusions: The performed analysis demonstrates that high level of NLR, LDH, and IL-10 were independent risk factors for predicting disease progression in patients at the early stage of COVID-19. The risk model combined with NLR, LDH and IL-10 improved the accuracy of the prediction of disease progression in patients in the early stages of COVID-19.

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Abstract 17220: Risk Factors for Recurrent Peripartum Cardiomyopathy in 783 Women in California

Circulation ◽

10.1161/circ.138.suppl_1.17220 ◽

2018 ◽

Vol 138 (Suppl_1) ◽

Author(s):

Punag Divanji ◽

Gregory Nah ◽

Ian Harris ◽

Anu Agarwal ◽

Nisha I Parikh

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Logistic Regression ◽

Regression Models ◽

Subsequent Pregnancy ◽

Peripartum Cardiomyopathy ◽

Lv Function ◽

Logistic Regression Models ◽

Grand Multiparity ◽

Adjusted Logistic Regression

Introduction: Characterized by significant left ventricular (LV) dysfunction and clinical heart failure (HF), peripartum cardiomyopathy (PPCM) has an incidence of approximately 1/2200 live births (0.04%). Prior studies estimate that approximately 25% of those with recovered LV function will have recurrent clinical PPCM during subsequent pregnancies, compared to 50% of those without recovered LV function. Specific predictors of recurrent PPCM have not been studied in cohorts with large numbers. Methods: From 2005-2011, we identified 1,872,227 pregnancies by International Classification of Diseases, 9th Revision (ICD-9) codes in the California Healthcare Cost and Utilization Project (HCUP) database, which captures over 95% of the California hospitalized population. Excluding 15,765 women with prior cardiovascular disease (myocardial infarction, coronary artery disease, stroke, HF, valve disease, or congenital heart disease), yielded n=1,856,462 women. Among women without prior cardiovascular disease, we identified index and subsequent pregnancies with PPCM to determine episodes of recurrent PPCM. We considered the following potential predictors of PPCM recurrence in both univariate and age-adjusted logistic regression models: age, race, hypertension, diabetes, smoking, obesity, chronic kidney disease, family history, pre-eclampsia, ectopic pregnancy, income, and insurance status. Results: In HCUP, n=783 women had pregnancies complicated by PPCM (mean age=30.8 years). Among these women, n=133 had a subsequent pregnancy (17%; mean age=28.1 years), with a mean follow-up of 4.34 years (±1.71 years). In this group of 133 subsequent pregnancies, n=14 (10.5%) were complicated by recurrent PPCM, with a mean time-to-event of 2.2 years (±1.89 years). Among the risk factors studied, the only univariate predictor of recurrent PPCM was grand multiparity, defined as ≥ 5 previous deliveries (odds ratio: 22; 95% confidence interval 4.43-118.22). The other predictors we studied were not significantly associated with recurrent PPCM in either univariate or multivariable models. Conclusion: In a large population database in California with 783 cases of PPCM over a 6-year period, 17% of women had a subsequent pregnancy, of which 10.5% had recurrent PPCM. In age-adjusted logistic regression models, grand multiparity was the only statistically significant predictor of recurrent PPCM.

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Patient characteristics of smokers undergoing lumbar spine surgery: an analysis from the Quality Outcomes Database

Journal of Neurosurgery Spine ◽

10.3171/2017.4.spine16984 ◽

2017 ◽

Vol 27 (6) ◽

pp. 661-669 ◽

Cited By ~ 3

Author(s):

Anthony L. Asher ◽

Clinton J. Devin ◽

Brandon McCutcheon ◽

Silky Chotai ◽

Kristin R. Archer ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Lumbar Spine ◽

Smoking Status ◽

Patient Characteristics ◽

Lumbar Spine Surgery ◽

Multivariable Logistic Regression Analysis ◽

Insurance Status ◽

Quality Outcomes

OBJECTIVEIn this analysis the authors compare the characteristics of smokers to nonsmokers using demographic, socioeconomic, and comorbidity variables. They also investigate which of these characteristics are most strongly associated with smoking status. Finally, the authors investigate whether the association between known patient risk factors and disability outcome is differentially modified by patient smoking status for those who have undergone surgery for lumbar degeneration.METHODSA total of 7547 patients undergoing degenerative lumbar surgery were entered into a prospective multicenter registry (Quality Outcomes Database [QOD]). A retrospective analysis of the prospectively collected data was conducted. Patients were dichotomized as smokers (current smokers) and nonsmokers. Multivariable logistic regression analysis fitted for patient smoking status and subsequent measurement of variable importance was performed to identify the strongest patient characteristics associated with smoking status. Multivariable linear regression models fitted for 12-month Oswestry Disability Index (ODI) scores in subsets of smokers and nonsmokers was performed to investigate whether differential effects of risk factors by smoking status might be present.RESULTSIn total, 18% (n = 1365) of patients were smokers and 82% (n = 6182) were nonsmokers. In a multivariable logistic regression analysis, the factors significantly associated with patients’ smoking status were sex (p < 0.0001), age (p < 0.0001), body mass index (p < 0.0001), educational status (p < 0.0001), insurance status (p < 0.001), and employment/occupation (p = 0.0024). Patients with diabetes had lowers odds of being a smoker (p = 0.0008), while patients with coronary artery disease had greater odds of being a smoker (p = 0.044). Patients’ propensity for smoking was also significantly associated with higher American Society of Anesthesiologists (ASA) class (p < 0.0001), anterior-alone surgical approach (p = 0.018), greater number of levels (p = 0.0246), decompression only (p = 0.0001), and higher baseline ODI score (p < 0.0001). In a multivariable proportional odds logistic regression model, the adjusted odds ratio of risk factors and direction of improvement in 12-month ODI scores remained similar between the subsets of smokers and nonsmokers.CONCLUSIONSUsing a large, national, multiinstitutional registry, the authors described the profile of patients who undergo lumbar spine surgery and its association with their smoking status. Compared with nonsmokers, smokers were younger, male, nondiabetic, nonobese patients presenting with leg pain more so than back pain, with higher ASA classes, higher disability, less education, more likely to be unemployed, and with Medicaid/uninsured insurance status. Smoking status did not affect the association between these risk factors and 12-month ODI outcome, suggesting that interventions for modifiable risk factors are equally efficacious between smokers and nonsmokers.

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Towards stronger antenatal care: Understanding predictors of late presentation to antenatal services and implications for obstetric risk management in Rwanda

PLoS ONE ◽

10.1371/journal.pone.0256415 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0256415

Author(s):

Christina N. Schmidt ◽

Elizabeth Butrick ◽

Sabine Musange ◽

Nathalie Mulindahabi ◽

Dilys Walker

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Antenatal Care ◽

Low Birthweight ◽

Secondary Data ◽

Neonatal Morbidity ◽

Late Presentation ◽

Health Centers ◽

Logistic Regression Models ◽

Pregnancy Testing

Background Early antenatal care (ANC) reduces maternal and neonatal morbidity and mortality through identification of pregnancy-related complications, yet 44% of Rwandan women present to ANC after 16 weeks gestational age (GA). The objective of this study was to identify factors associated with delayed initiation of ANC and describe differences in the obstetric risks identified at the first ANC visit (ANC-1) between women presenting early and late to care. Methods This secondary data analysis included 10,231 women presenting for ANC-1 across 18 health centers in Rwanda (May 2017-December 2018). Multivariable logistic regression models were constructed using backwards elimination to identify predictors of presentation to ANC at ≥16 and ≥24 weeks GA. Logistic regression was used to examine differences in obstetric risk factors identified at ANC-1 between women presenting before and after 16- and 24-weeks GA. Results Sixty-one percent of women presented to ANC at ≥16 weeks and 24.7% at ≥24 weeks GA, with a mean (SD) GA at presentation of 18.9 (6.9) weeks. Younger age (16 weeks: OR = 1.36, 95% CI: 1.06, 1.75; 24 weeks: OR = 1.33, 95% CI: 0.95, 1.85), higher parity (16 weeks: 1–4 births, OR = 1.55, 95% CI: 1.39, 1.72; five or more births, OR = 2.57, 95% CI: 2.17, 3.04; 24 weeks: 1–4 births, OR = 1.93, 95% CI: 1.78, 2.09; five or more births, OR = 3.20, 95% CI: 2.66, 3.85), lower educational attainment (16 weeks: primary, OR = 0.75, 95% CI: 0.65, 0.86; secondary, OR = 0.60, 95% CI: 0.47,0.76; university, OR = 0.48, 95% CI: 0.33, 0.70; 24 weeks: primary, OR = 0.64, 95% CI: 0.53, 0.77; secondary, OR = 0.43, 95% CI: 0.29, 0.63; university, OR = 0.12, 95% CI: 0.04, 0.32) and contributing to household income (16 weeks: OR = 1.78, 95% CI: 1.40, 2.25; 24 weeks: OR = 1.91, 95% CI: 1.42, 2.55) were associated with delayed ANC-1 (≥16 and ≥24 weeks GA). History of a spontaneous abortion (16 weeks: OR = 0.74, 95% CI: 0.66, 0.84; 24 weeks: OR = 0.70, 95% CI: 0.58, 0.84), pregnancy testing (16 weeks: OR = 0.48, 95% CI: 0.33, 0.71; 24 weeks: OR = 0.41, 95% CI: 0.27, 0.61; 24 weeks) and residing in the same district (16 weeks: OR = 1.55, 95% CI: 1.08, 2.22; 24 weeks: OR = 1.73, 95% CI: 1.04, 2.87) or catchment area (16 weeks: OR = 1.53, 95% CI: 1.05, 2.23; 24 weeks: OR = 1.84, 95% CI: 1.28, 2.66; 24 weeks) as the health facility were protective against delayed ANC-1. Women with a prior preterm (OR, 0.71, 95% CI, 0.53, 0.95) or low birthweight delivery (OR, 0.72, 95% CI, 0.55, 0.95) were less likely to initiate ANC after 16 weeks. Women with no obstetric history were more likely to present after 16 weeks GA (OR, 1.18, 95% CI, 1.06, 1.32). Conclusion This study identified multiple predictors of delayed ANC-1. Focusing existing Community Health Worker outreach efforts on the populations at greatest risk of delaying care and expanding access to home pregnancy testing may improve early care attendance. While women presenting late to care were less likely to present without an identified obstetric risk factor, lower than expected rates were identified in the study population overall. Health centers may benefit from provider training and standardized screening protocols to improve identification of obstetric risk factors at ANC-1.

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Preoperative Lymphocyte-to-monocyte Ratio and CA125 Level as Risk Factors for Advanced Ovarian Cancer

10.21203/rs.3.rs-77009/v1 ◽

2020 ◽

Author(s):

Ying Tang ◽

Huiquan Hu ◽

Yalan Tang ◽

Fangxiang Tang ◽

Dan Lin ◽

...

Keyword(s):

Risk Factors ◽

Ovarian Cancer ◽

Logistic Regression ◽

Early Stage ◽

Advanced Ovarian Cancer ◽

High Specificity ◽

Advanced Stage ◽

Binary Logistic Regression Model ◽

Lymphocyte To Monocyte Ratio ◽

The Relationship

Abstract Background: Detailed descriptions of the relationship between lymphocyte-to-monocyte ratio alone and combined with CA125 (COLC) and advanced stage of ovarian cancer (OC) have been lacking to date. This study is to analyze the relationship between LMR, CA125 and COLC and advanced stage of OC.Methods: A retrospective clinicopathologic review was performed. The receiver-operating characteristic (ROC) curves of LMR, CA125, and COLC staging OC were constructed. Furthermore, a binary logistic regression model was used to assay the independent risk factors.Results: A total of 225 patients with OC were identified in this cohort. Eighty-five patients with OC were diagnosed at an early stage, and 140 OC patients were diagnosed at an advanced stage. The median of LMR at the early stage was higher than the advanced stage (4.39 vs. 2.78), and the median of CA125 was lower than the advanced stage (80 U/mL vs. 251.25 U/mL). Multivariate logistic regression indicated that LMR (OR=0.314, 95% confidence interval [CI]: 0.143–0.687, P=0.004) and CA125 (OR=4.045, 95%CI: 1.883–8.692, P<0.001) were associated with OC staging. Furthermore, the area under the curve of COLC was higher than that of LMR (0.779 vs. 0.732) or CA125 (0.779 vs. 0.708) in staging OC. The specificity of COLC was higher than that of LMR (87.11% vs. 70.61%) or CA125 (87.11% vs. 61.21%) in staging OC.Conclusions: LMR alone or in combination with CA125 might be associated with OC staging. Besides, as a predictive factor, COLC may have high specificity in staging OC.

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A model-based concordance-type index for evaluating the added predictive ability of novel risk factors and markers in the logistic regression models

Journal of Applied Statistics ◽

10.1080/02664763.2019.1580253 ◽

2019 ◽

Vol 46 (12) ◽

pp. 2145-2163 ◽

Cited By ~ 1

Author(s):

M. Shafiqur Rahman ◽

Afrin Sadia Rumana

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Models ◽

Predictive Ability ◽

Logistic Regression Models ◽

Model Based ◽

Novel Risk Factors

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Association between Neutrophil-Lymphocyte and Platelet-Lymphocyte Ratios and Coronary Artery Calcification Score among Asymptomatic Patients: Data from a Cross-Sectional Study

Mediators of Inflammation ◽

10.1155/2019/6513847 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8 ◽

Cited By ~ 9

Author(s):

Carlos V. Serrano ◽

Fernando R. de Mattos ◽

Fábio G. Pitta ◽

Cesar H. Nomura ◽

James de Lemos ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Coronary Artery ◽

Smoking Status ◽

Statistical Tests ◽

Low Grade ◽

Neutrophil Lymphocyte Ratio ◽

Lymphocyte Ratio ◽

Markers Of Inflammation ◽

Asymptomatic Patients

Introduction. Atherosclerosis is a low-grade inflammatory disease. Among markers of inflammation, importance has been given to the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR). The objective of this study was to examine the association between these hematological indices of inflammation and coronary atherosclerotic calcification in clinically asymptomatic patients. Methods. This study had clinical and laboratorial data collected from consecutive asymptomatic patients that underwent computed tomography coronary artery calcium (CAC) scoring. Risk factors, NLR, and PLR were evaluated at different categories of CAC scoring. Statistical tests included chi-square, linear regression, and logistic regression. Patients (N=247; age 60.4±8.0 years and 60.7% men) were allocated into four categories according to the CAC score. Results. Respective age, sex (male), NLR, and PLR distribution within groups were as follows: CAC=0 (n=98; 52.5±13.6 years, 55%, 2.0±1.0, and 121.5±41.5), CAC 1-100 (N=64; 61.3±11.0 years, 60%, 2.2±1.2, and 125.6 ± 45.6), CAC 101-400 (N=37; 64.2±11.6 years, 67%,2.6±1.3, and 125.4±55.9), and CAC>400 (N=48; 69.3±11.1 years, 66%, 3.3±2.0, and 430.1±1787.4). The association between risk factors and CAC score was assessed. Hypertension status and smoking status were similar within groups, while the presence of diabetes (P=0.02) and older age (P≤0.001) was more prevalent in the CAC>400 group. LDL cholesterol was greater in the higher CAC score groups (P=0.002). Multivariate logistic regression of the quartile analysis showed that age and NLR were independently associated with CAC>100 (OR (CI), P value): 2.06 (1.55-2.73, P=0.00001) and 1.82 (1.33-2.49, P=0.0002), respectively. Conclusion. Within asymptomatic patients, NLR provides additional risk stratification, as an independent association between NLR extent and CAD extent was identified. Moreover, PLR was not an inflammation marker for CAD severity.

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Forced Sexual Victimization Among Youth in Custody: Do Risk Factors Vary by Gender and Perpetrator?

The Prison Journal ◽

10.1177/0032885519894561 ◽

2019 ◽

Vol 100 (2) ◽

pp. 151-172

Author(s):

Eileen M. Ahlin

Keyword(s):

Risk Factors ◽

Gender Differences ◽

Logistic Regression ◽

National Survey ◽

Regression Models ◽

Sexual Victimization ◽

Multivariate Logistic Regression ◽

Logistic Regression Models ◽

Factors Associated ◽

Using Data

There is relatively little literature examining risk factors associated with sexual victimization among youth in custody. The current study explored whether risk of forced sexual victimization among youth in custody differs by gender or perpetrator. Using data from a sample of 8,659 youth who participated in the National Survey of Youth in Custody, multivariate logistic regression models were employed to investigate gender differences in risk factors associated with overall forced sexual victimization and staff-on-inmate and inmate-on-inmate forced sexual victimization. Findings suggest that gender differences are more pronounced when perpetrator type is considered.

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Maternal age as a risk factor for cerebral palsy

Anthropological Review ◽

10.2478/anre-2021-0009 ◽

2021 ◽

Vol 84 (2) ◽

pp. 117-131

Author(s):

Marta Sternal ◽

Barbara Kwiatkowska ◽

Krzysztof Borysławski ◽

Agnieszka Tomaszewska

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Cerebral Palsy ◽

Regression Model ◽

Maternal Age ◽

Logistic Regression Model ◽

Significant Risk ◽

Control Group ◽

Logistic Regression Models ◽

Pregnancy And Childbirth

Abstract The relationship between maternal age and the occurrence of cerebral palsy is still highly controversial. The aim of the study was to examine the effect of maternal age on the risk of CP development, taking into account all significant risk factors and the division into single, twin, full-term, and pre-term pregnancies. The survey covered 278 children with CP attending selected educational institutions in Poland. The control group consisted of data collected from the medical records of 435 children born at Limanowa county hospital, Poland. The analyses included socio-economic factors, factors related to pregnancy and childbirth, and factors related to the presence of comorbidities and diseases in the child. Constructed logistic regression models were used for statistical analyses. For all age categories included in the estimated models (assessing the effect of demographic factors on the development of CP), only the category of ≤24 years of age (in the group of all children) was significant. It was estimated that in this mother’s age category, the risk of CP is lower (OR 0.6, 95% CI: 0.3–1.0) in comparison to mothers aged 25-29 (p = 0.03). However, estimation with the use of a complex logistic regression model did not show any significant effect of maternal age on the incidence of CP in groups from different pregnancies types. It became apparent that maternal age is a weak predictor of CP, insignificant in the final logistic regression model. It seems correct to assume that the studies conducted so far, showing a significant effect of maternal age in this respect, may be associated with bias in the estimators used to assess the risk of CP due to the fact that other important risk factors for CP development were not included in the research.

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