The impact of pre-selected variance inflation factor thresholds on the stability and predictive power of logistic regression models in credit scoring

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

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High association of COVID-19 severity with poor gut health score in Lebanese patients

PLoS ONE ◽

10.1371/journal.pone.0258913 ◽

2021 ◽

Vol 16 (10) ◽

pp. e0258913

Author(s):

Imad Al Kassaa ◽

Sarah El Omari ◽

Nada Abbas ◽

Nicolas Papon ◽

Djamel Drider ◽

...

Keyword(s):

Logistic Regression ◽

Regression Models ◽

Equal Proportion ◽

Gut Health ◽

Kendall’S Tau ◽

High Association ◽

Kendall's Tau ◽

Health Score ◽

Logistic Regression Models ◽

The Impact

Background Coronavirus disease 2019 (COVID-19) has affected millions of lives globally. However, the disease has presented more extreme challenges for developing countries that are experiencing economic crises. Studies on COVID-19 symptoms and gut health are scarce and have not fully analyzed possible associations between gut health and disease pathophysiology. Therefore, this study aimed to demonstrate a potential association between gut health and COVID-19 severity in the Lebanese community, which has been experiencing a severe economic crisis. Methods This cross-sectional study investigated SARS-CoV-2 PCR-positive Lebanese patients. Participants were interviewed and gut health, COVID-19 symptoms, and different metrics were analyzed using simple and multiple logistic regression models. Results Analysis of the data showed that 25% of participants were asymptomatic, while an equal proportion experienced severe symptoms, including dyspnea (22.7%), oxygen need (7.5%), and hospitalization (3.1%). The mean age of the participants was 38.3 ±0.8 years, and the majority were males (63.9%), married (68.2%), and currently employed (66.7%). A negative correlation was found between gut health score and COVID-19 symptoms (Kendall’s tau-b = -0.153, P = 0.004); indicating that low gut health was associated with more severe COVID-19 cases. Additionally, participants who reported unhealthy food intake were more likely to experience severe symptoms (Kendall’s tau-b = 0.118, P = 0.049). When all items were taken into consideration, multiple ordinal logistic regression models showed a significant association between COVID-19 symptoms and each of the following variables: working status, flu-like illness episodes, and gut health score. COVID-19 severe symptoms were more common among patients having poor gut health scores (OR:1.31, 95%CI:1.07–1.61; P = 0.008), experiencing more than one episode of flu-like illness per year (OR:2.85, 95%CI:1.58–5.15; P = 0.001), and owning a job (OR:2.00, 95%CI:1.1–3.65; P = 0.023). Conclusions To our knowledge, this is the first study that showed the impact of gut health and exposure to respiratory viruses on COVID-19 severity in Lebanon. These findings can facilitate combating the pandemic in Lebanon.

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Abstract P122: The Impact of Center Certification Status on Acute Stroke Care Within a Multi-Hospital System in Western United States

Stroke ◽

10.1161/str.52.suppl_1.p122 ◽

2021 ◽

Vol 52 (Suppl_1) ◽

Author(s):

Radoslav I Raychev ◽

CrystalAnn Moreno ◽

Leslie Corless ◽

Jason W Tarpley ◽

John F Zurasky ◽

...

Keyword(s):

Logistic Regression ◽

Clinical Outcome ◽

Regression Models ◽

Process Of Care ◽

Chi Square ◽

Hospital System ◽

Logistic Regression Models ◽

Stroke Center ◽

The Impact ◽

Iv Tpa

Introduction: We aimed to investigate the impact of certification status on process of care metrics and clinical outcome in a large multi-center hospital system. Methods: We analyzed data obtained from the Providence Stroke Registry between January 2016 and December 2019. Key process of care metrics and clinical outcome were compared among patients with a discharge diagnosis of stroke and stratified based on site certification: comprehensive stroke center (CSC), thrombectomy-capable stroke center (TSC), primary stroke center (PSC) and no certification (NC). Donner’s adjusted chi-square tests were used to compare proportions for each metric grouped by certification. Generalized linear mixed effects logistic regression models were used to adjust for mode of patient arrival, age, sex, admit NIHSS, and medical history. Results: Data included 45,278 patients. Results from the analyses are summarized in the table. Donner’s adjusted chi-square analyses showed significant differences for metrics across certification groups. Results from the logistic regression models indicated significant differences in IV TPA and EVT treatment, as well as IV TPA treatment times across certification groups. There were no significant differences between TSC and CSC. Conclusions: Patients presenting with acute ischemic stroke at NC and PSC were significantly less likely to receive IV TPA or EVT with significantly less efficient IV tPA treatment times as compared to CSC. However, CSC and TSC sites performed similarly.

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The impact of demographic, clinical, genetic, and imaging variables on tau PET status

European Journal of Nuclear Medicine and Molecular Imaging ◽

10.1007/s00259-020-05099-w ◽

2020 ◽

Author(s):

Rik Ossenkoppele ◽

◽

Antoine Leuzy ◽

Hanna Cho ◽

Carole H. Sudre ◽

...

Keyword(s):

Logistic Regression ◽

Cortical Thickness ◽

Regression Models ◽

Neurodegenerative Disorder ◽

Amyloid Β ◽

Binary Logistic Regression ◽

Clinical Genetic ◽

Logistic Regression Models ◽

Tau Pet ◽

The Impact

Abstract Purpose A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) are tau PET–negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET–positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

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The impact of intellectual capital on start-up expectations

Journal of Intellectual Capital ◽

10.1108/jic-04-2016-0040 ◽

2016 ◽

Vol 17 (4) ◽

pp. 654-674 ◽

Cited By ~ 20

Author(s):

Diego Matricano

Keyword(s):

Logistic Regression ◽

Intellectual Capital ◽

Regression Models ◽

Empirical Studies ◽

Binary Logistic Regression ◽

Research Trend ◽

Content Type ◽

Logistic Regression Models ◽

Start Up ◽

The Impact

Purpose According to an emerging research trend, which seeks to apply the concept of intellectual capital (IC) to the field of entrepreneurship, the purpose of this paper is to test whether IC can affect the start-up expectations of aspiring entrepreneurs. Design/methodology/approach Binary logistic regression models, based on empirical data derived from the Global Entrepreneurship Monitor website and referring to Italy over the years 2005-2010, are used to test the influence of IC (comprising human, structural and relational capital) on start-up expectations. Findings Binary logistic regression models reveal robust results. Human, structural and relational capitals affect start-up expectations in Italy. Only in 2010 did structural capital fail to do so. Research limitations/implications This study has three main limitations. The first concerns the need for further research to confirm the influence of IC on start-up expectations. The second concerns in-depth, more exhaustive analyses that cannot be carried out due to the use of second- hand data. The third deals with the reference only to Italy, over a limited time-span (2005-2010). Originality/value To the best knowledge of the author, this is one of the first empirical studies that investigate whether IC can affect start-up expectations. Results revealed by the regression models might steer other scholars’ interest toward this research path (linking IC and entrepreneurship) that has not yet been properly considered.

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Defensible inferences from a nested sequence of logistic regressions: a guide for the perplexed

Large-scale Assessments in Education ◽

10.1186/s40536-021-00111-7 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Gulsah Gurkan ◽

Yoav Benjamini ◽

Henry Braun

Keyword(s):

Logistic Regression ◽

Cognitive Skills ◽

Regression Models ◽

Large Scale ◽

Family Background ◽

National Income ◽

Logistic Models ◽

Logistic Regression Models ◽

Logistic Regressions ◽

The Impact

AbstractEmploying nested sequences of models is a common practice when exploring the extent to which one set of variables mediates the impact of another set. Such an analysis in the context of logistic regression models confronts two challenges: (i) direct comparisons of coefficients across models are generally biased due to the changes in scale that accompany the changes in the set of explanatory variables, (ii) conducting a large number of tests induces a problem of multiplicity that can lead to spurious findings of significance if not heeded. This article aims to illustrate a practical strategy for conducting analyses in the face of these challenges. The challenges—and how to address them—are illustrated using a subset of the findings reported by Braun (Large-scale Assess Educ 6(4):1–52, 2018. 10.1186/s40536-018-0058-x), drawn from the Programme for the International Assessment of Adult Competencies (PIAAC), an international, large-scale assessment of adults. For each country in the dataset, a nested pair of logistic regression models was fit in order to investigate the role of Educational Attainment and Cognitive Skills in mediating the impact of family background and demographic characteristics on the location of an individual’s annual income in the national income distribution. A modified version of the Karlson–Holm–Breen (KHB) method was employed to obtain an unbiased estimate of the true differences in the coefficients between nested logistic models. In order to address the issue of multiplicity, a recent generalization of the Benjamini–Hochberg (BH) False Discovery Rate (FDR)-controlling procedure to hierarchically structured hypotheses was employed and compared to two conventional methods. The differences between the changes in coefficients calculated conventionally and with the KHB adjustment varied from negligible to very substantial. When combined with the actual magnitudes of the coefficients, we concluded that the more proximal factors indeed act as strong mediators for the background factors, but less so for Age, and hardly at all for Gender. With respect to multiplicity, applying the FDR-controlling procedure yielded results very similar to those obtained by applying a standard per-comparison procedure, but quite a few more discoveries in comparison to the Bonferroni procedure. The KHB methodology illustrated here can be applied wherever there is interest in comparing nested logistic regressions. Modifications to account for probability sampling are practicable. The categorization of variables and the order of entry should be determined by substantive considerations. On the other hand, the BH procedure is perfectly general and can be implemented to address multiplicity issues in a broad range of settings.

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1402Thyroid stimulating hormone (TSH) is associated with general and abdominal obesity in girls during puberty

International Journal of Epidemiology ◽

10.1093/ije/dyab168.697 ◽

2021 ◽

Vol 50 (Supplement_1) ◽

Author(s):

Yingying Wang

Keyword(s):

Logistic Regression ◽

Abdominal Obesity ◽

Regression Models ◽

Population Based ◽

Thyroid Stimulating Hormone ◽

General Obesity ◽

Logistic Regression Models ◽

The Impact ◽

Serum Tsh ◽

Stimulating Hormone

Abstract Background Childhood is an important public health issue. Although both thyroid hormone and menarche are known to play a role in body metabolism and energy expenditure, no population-based study has been conducted to investigate the impact of TSH on adipogenesis among population-based girls around puberty. Methods A multi-stage cluster sampling method was used to select one junior middle school from each of 4 study areas: Minhang District in Shanghai, Haimen City in Jiangsu Province, Yuhuan City and Deqing County in Zhejiang Province. A total of 474 girls aged 11 to 14 years from 4 schools were enrolled. Information on demographic factors and puberty stage were collected, and anthropometric measurements and thyroid hormones were determined. Multivariate logistic regression models were used to assess the associations of Thyroid stimulating hormone (TSH) with the risk of obesity measured by body mess index (BMI) and waist circumference (WC). Results Of the 474 girls, the prevalences of BMI-based general obesity and WC-based abdominal obesity were 19.8% (94/474) and 21.7% (103/474), respectively. Compared with normal weight girls, the mean serum TSH concentration was significantly higher in BMI-based general overweight or obese girls (P = 0.037), but not in WC-based central overweight or obese girls (P = 0.173). In the multiple logistic regression models, for girls with highest tertile of serum TSH concentration relative to those in the lowest tertile, the odds ratios were 2.58 (95% CI 1.32 to 5.04) and 2.50 (95% CI 1.30 to 4.81) for overweight or obesity based on BMI and WC after adjustment for puberty stage and other covariates. Conclusions Serum TSH concentration was positively associated with both general and abdominal obesity in school-age girls and the association was independent of puberty. Key messages thyroid stimulating hormone; general obesity; central obesity; school-aged girls; puberty

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Severity of COVID-19 and survival in patients with rheumatic and inflammatory diseases: data from the French RMD COVID-19 cohort of 694 patients

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-218310 ◽

2020 ◽

pp. annrheumdis-2020-218310

Author(s):

Keyword(s):

Logistic Regression ◽

Regression Models ◽

Musculoskeletal Diseases ◽

Severe Disease ◽

Forward Selection ◽

Logistic Regression Models ◽

Risk Of Death ◽

Hospitalised Patients ◽

Epidemiological Characteristics ◽

The Impact

ObjectivesThere is little known about the impact of SARS-CoV-2 on patients with inflammatory rheumatic and musculoskeletal diseases (iRMD). We examined epidemiological characteristics associated with severe disease, then with death. We also compared mortality between patients hospitalised for COVID-19 with and without iRMD.MethodsIndividuals with suspected iRMD-COVID-19 were included in this French cohort. Logistic regression models adjusted for age and sex were used to estimate adjusted ORs and 95% CIs of severe COVID-19. The most significant clinically relevant factors were analysed by multivariable penalised logistic regression models, using a forward selection method. The death rate of hospitalised patients with iRMD-COVID-19 (moderate–severe) was compared with a subset of patients with non-iRMD-COVID-19 from a French hospital matched for age, sex, and comorbidities.ResultsOf 694 adults, 438 (63%) developed mild (not hospitalised), 169 (24%) moderate (hospitalised out of the intensive care unit (ICU) and 87 (13%) severe (patients in ICU/deceased) disease. In multivariable imputed analyses, the variables associated with severe infection were age (OR=1.08, 95% CI: 1.05–1.10), female gender (OR=0.45, 95% CI: 0.25–0.80), body mass index (OR=1.07, 95% CI: 1.02–1.12), hypertension (OR=1.86, 95% CI: 1.01–3.42), and use of corticosteroids (OR=1.97, 95% CI: 1.09–3.54), mycophenolate mofetil (OR=6.6, 95% CI: 1.47–29.62) and rituximab (OR=4.21, 95% CI: 1.61–10.98). Fifty-eight patients died (8% (total) and 23% (hospitalised)). Compared with 175 matched hospitalised patients with non-iRMD-COVID-19, the OR of mortality associated with hospitalised patients with iRMD-COVID-19 was 1.45 (95% CI: 0.87–2.42) (n=175 each group).ConclusionsIn the French RMD COVID-19 cohort, as already identified in the general population, older age, male gender, obesity, and hypertension were found to be associated with severe COVID-19. Patients with iRMD on corticosteroids, but not methotrexate, or tumour necrosis factor alpha and interleukin-6 inhibitors, should be considered as more likely to develop severe COVID-19. Unlike common comorbidities such as obesity, and cardiovascular or lung diseases, the risk of death is not significantly increased in patients with iRMD.Trial registration numberClinicalTrials.gov Registry (NCT04353609).

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Finding a Method for Optimizing Risk Adjustment When Comparing Surgical-Site Infection Rates

Infection Control and Hospital Epidemiology ◽

10.1086/502398 ◽

2004 ◽

Vol 25 (4) ◽

pp. 313-318 ◽

Cited By ~ 53

Author(s):

Christian Brandt ◽

Sonja Hansen ◽

Dorit Sohr ◽

Franz Daschner ◽

Henning Rüden ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Surgical Site Infection ◽

Regression Models ◽

Predictive Power ◽

Risk Index ◽

Significant Risk ◽

Site Infection ◽

Logistic Regression Models ◽

System Risk

AbstractObjective:To investigate whether stratification of the risk of developing a surgical-site infection (SSI) is improved when a logistic regression model is used to weight the risk factors for each procedure category individually instead of the modified NNIS System risk index.Design and Setting:The German Nosocomial Infection Surveillance System, based on NNIS System methodology, has 273 acute care surgical departments participating voluntarily. Data on 9 procedure categories were included (214,271 operations).Methods:For each of the procedure categories, the significant risk factors from the available data (NNIS System risk index variables of ASA score, wound class, duration of operation, and endoscope use, as well as gender and age) were identified by multiple logistic regression analyses with stepwise variable selection. The area under the receiver operating characteristic (ROC) curve resulting from these analyses was used to evaluate the predictive power of logistic regression models.Results:For most procedures, at least two of the three variables contributing to the NNIS System risk index were shown to be independent risk factors (appendectomy, knee arthroscopy, cholecystectomy, colon surgery, herniorrhaphy, hip prosthesis, knee prosthesis, and vascular surgery). The predictive power of logistic regression models (including age and gender, when appropriate) was low (between 0.55 and 0.71) and for most procedures only slightly better than that of the NNIS System risk index.Conclusion:Without the inclusion of additional procedure-specific variables, logistic regression models do not improve the comparison of SSI rates from various hospitals.

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Releases From a Local Jail: The Impact of Visitation on Recidivism

Criminal Justice Policy Review ◽

10.1177/0887403420919480 ◽

2020 ◽

pp. 088740342091948 ◽

Cited By ~ 1

Author(s):

William M. Casey ◽

Jennifer E. Copp ◽

William D. Bales

Keyword(s):

Logistic Regression ◽

Regression Models ◽

Large Body ◽

Current Investigation ◽

Research Attention ◽

Logistic Regression Models ◽

Local Jail ◽

Number Of Visits ◽

Using Data ◽

The Impact

There is a large body of research that examines the impact of visitation on the likelihood of recidivism among released state prisoners. That research reveals that receiving any visits, and a greater number of visits, reduces the likelihood of recidivism. However, whether the recidivism-reducing effect of visitation operates within the jail setting remains unclear. Using data from a Florida jail, the current investigation examines the association between visitation and recidivism among a cohort of releases ( N = 6,565). Analyses also consider the extent to which the frequency of visits impacts the likelihood of recidivism. Findings from a series of logistic regression models reveal that inmates who received visits were no less likely to recidivate than their counterparts. Yet, among inmates who were visited, those receiving more frequent visits were less likely to recidivate. This departs from existing visitation research and underscores the importance of directing research attention to local jails.

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