A note on the “L-logistic regression models: Prior sensitivity analysis, robustness to outliers and applications”

2020 ◽  
Vol 34 (1) ◽  
pp. 183-187
Author(s):  
Saralees Nadarajah ◽  
Yuancheng Si
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Regression Models ◽  
Logistic Regression Models

In-hospital mortality after traumatic brain injury surgery: a nationwide population-based comparison of mortality predictors used in artificial neural network and logistic regression models

2013 ◽  
Vol 118 (4) ◽  
pp. 746-752 ◽  
Author(s):  
Hon-Yi Shi ◽  
Shiuh-Lin Hwang ◽  
King-Teh Lee ◽  
Chih-Lung Lin
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Hospital Mortality ◽  
Regression Models ◽  
Logistic Regression Model ◽  
Global Sensitivity Analysis ◽  
Ann Model ◽  
Logistic Regression Models ◽  
Global Sensitivity

Object Most reports compare artificial neural network (ANN) models and logistic regression models in only a single data set, and the essential issue of internal validity (reproducibility) of the models has not been adequately addressed. This study proposes to validate the use of the ANN model for predicting in-hospital mortality after traumatic brain injury (TBI) surgery and to compare the predictive accuracy of ANN with that of the logistic regression model. Methods The authors of this study retrospectively analyzed 16,956 patients with TBI nationwide who were surgically treated in Taiwan between 1998 and 2009. For every 1000 pairs of ANN and logistic regression models, the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow statistics, and accuracy rate were calculated and compared using paired t-tests. A global sensitivity analysis was also performed to assess the relative importance of input parameters in the ANN model and to rank the variables in order of importance. Results The ANN model outperformed the logistic regression model in terms of accuracy in 95.15% of cases, in terms of Hosmer-Lemeshow statistics in 43.68% of cases, and in terms of the AUC in 89.14% of cases. The global sensitivity analysis of in-hospital mortality also showed that the most influential (sensitive) parameters in the ANN model were surgeon volume followed by hospital volume, Charlson comorbidity index score, length of stay, sex, and age. Conclusions This work supports the continued use of ANNs for predictive modeling of neurosurgery outcomes. However, further studies are needed to confirm the clinical efficacy of the proposed model.

scholarly journals Early immunosuppression was associated with poor prognosis in elderly patients with sepsis: secondary analysis of the ETASS study

2020 ◽  
Author(s):  
Fei Pei ◽  
Guanrong Zhang ◽  
Lixin Zhou ◽  
Jiyun Liu ◽  
Gang Ma ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Logistic Regression ◽  
Elderly Patients ◽  
Hospital Mortality ◽  
Poor Prognosis ◽  
Regression Models ◽  
Immune Status ◽  
The Elderly ◽  
Logistic Regression Models ◽  
Definition Of

Abstract Background: Although immunosuppression has been investigated in adult septic patients, early immune status remains unclear. In this study, we aimed to assess early immune status in adult patients with sepsis stratified by age and its relevance to hospital mortality. Methods: From post hoc analysis of a multicenter, randomized controlled trial, 273 patients whose levels of monocyte human leukocyte antigen-DR (mHLA-DR) were obtained within 48 hours after onset of sepsis were enrolled. All patients were divided into elderly (≥60yrs) group and non-elderly (<60yrs) group. Early immune status was evaluated by the percentage of mHLA-DR in total monocytes within 48 hours after onset of sepsis and it was classified as immunosuppression (mHLA-DR≤30%) or non-immunosuppression (>30%). Changes in immune status were assessed by the value change in mHLA-DR on day 3 compared with the first measurement. Three logistic regression models were conducted to test the associations between early immunosuppression and hospital mortality. We also did a sensitivity analysis to find out if the definition of early immune status (24 vs. 48 hours after onset of sepsis) affects the outcomes. Results: Of the 181 elderly and 92 non-elderly septic patients, 71 (39.2%) elderly and 25 (27.2%) non-elderly died in hospital. The percentage of early immunosuppression in the elderly was twice of that of the non-elderly patients (32% vs. 16%, p=0.006). Immunosuppressed elderly had higher hospital mortality than the non-immunosuppressed elderly (53.4% vs. 32.5%, p=0.009), but there was no significant difference in mortality between immunosuppresed non-elderly patients and non-immunosuppressed non-elderly patients (33.5% vs. 26.0%, p=0.541). In all of the three logistic regression models, we found that early immunosuppression was independently associated with increased hospital mortality in elderly, but not in non-elderly patients. Sensitivity analysis further confirmed the definition of early immune status did not affect the outcomes. In addition, immune status improvement on day 3 was associated with reduced hospital mortality in both elderly and non-elderly patients. Conclusion: In adult patients with sepsis, the elderly were more susceptible to early immunosuppression after onset of sepsis. Early immunosuppression was independently associated with poor prognosis in elderly patients. Trial registration: ClinicalTrials.gov NCT00711620 , 9 July 2008, https://clinicaltrials.gov/ct2/show/NCT00711620

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

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.

scholarly journals Effect of prostatic apex shape (Lee types) and urethral sphincter length in preoperative MRI on very early continence rates after radical prostatectomy

2021 ◽  
Author(s):  
Mike Wenzel ◽  
Felix Preisser ◽  
Matthias Mueller ◽  
Lena H. Theissen ◽  
Maria N. Welte ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Radical Prostatectomy ◽  
Regression Models ◽  
Urethral Sphincter ◽  
Anatomical Characteristics ◽  
Logistic Regression Models ◽  
Pad Test ◽  
Type D ◽  
Multivariable Logistic Regression ◽  
Type C

Abstract Purpose To test the effect of anatomic variants of the prostatic apex overlapping the membranous urethra (Lee type classification), as well as median urethral sphincter length (USL) in preoperative multiparametric magnetic resonance imaging (mpMRI) on the very early continence in open (ORP) and robotic-assisted radical prostatectomy (RARP) patients. Methods In 128 consecutive patients (01/2018–12/2019), USL and the prostatic apex classified according to Lee types A–D in mpMRI prior to ORP or RARP were retrospectively analyzed. Uni- and multivariable logistic regression models were used to identify anatomic characteristics for very early continence rates, defined as urine loss of ≤ 1 g in the PAD-test. Results Of 128 patients with mpMRI prior to surgery, 76 (59.4%) underwent RARP vs. 52 (40.6%) ORP. In total, median USL was 15, 15 and 10 mm in the sagittal, coronal and axial dimensions. After stratification according to very early continence in the PAD-test (≤ 1 g vs. > 1 g), continent patients had significantly more frequently Lee type D (71.4 vs. 54.4%) and C (14.3 vs. 7.6%, p = 0.03). In multivariable logistic regression models, the sagittal median USL (odds ratio [OR] 1.03) and Lee type C (OR: 7.0) and D (OR: 4.9) were independent predictors for achieving very early continence in the PAD-test. Conclusion Patients’ individual anatomical characteristics in mpMRI prior to radical prostatectomy can be used to predict very early continence. Lee type C and D suggest being the most favorable anatomical characteristics. Moreover, longer sagittal median USL in mpMRI seems to improve very early continence rates.

785 Reported Restful Sleep Predicting Emotional Distress: Does Exercise (and its modalities) moderate?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A305-A306
Author(s):  
Jesse Moore ◽  
Ellita Williams ◽  
Collin Popp ◽  
Anthony Briggs ◽  
Judite Blanc ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aerobic Exercise ◽  
Regression Models ◽  
Regression Analyses ◽  
Logistic Regression Models ◽  
The Past ◽  
Strengthening Exercise ◽  
Waking Up ◽  
The Relationship ◽  
Age And Sex

Abstract Introduction Literature shows that exercise moderates the relationship between sleep and emotional distress (ED.) However, it is unclear whether different types of exercise, such as aerobic and strengthening, affect this relationship differently. We investigated the moderating role of two types of exercise (aerobic and strengthening) regarding the relationship between ED and sleep. Methods Our analysis was based on data from 2018 National Health Interview Survey (NHIS), a nationally representative study in which 2,814 participants provided all data. Participants were asked 1) “how many days they woke up feeling rested over the past week”, 2) the Kessler 6 scale to determine ED (a score &gt;13 indicates ED), and 3) the average frequency of strengthening or aerobic exercise per week. Logistic regression analyses were performed to determine if the reported days of waking up rested predicted level of ED. We then investigated whether strengthening or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Logistic regression analyses were performed to determine if subjective reporting of restful sleep predicted level of ED. We investigated whether strengthening exercise or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Results On average, participants reported 4.41 restful nights of sleep (SD =2.41), 3.43 strengthening activities (SD = 3.19,) and 8.47 aerobic activities a week (SD=5.91.) We found a significant association between days over the past week reporting waking up feeling rested and ED outcome according to K6, Χ2(1) = -741, p= &lt;.001. The odds ratio signified a decrease of 52% in ED scores for each unit of restful sleep (OR = .48, (95% CI = .33, .65) p=&lt;.001.) In the logistic regression model with moderation, aerobic exercise had a significant moderation effect, Χ2(1) = .03, p=.04, but strengthening exercise did not. Conclusion We found that restful sleep predicted reduction in ED scores. Aerobic exercise moderated this relationship, while strengthening exercise did not. Further research should investigate the longitudinal effects of exercise type on the relationship between restful sleep and ED. Support (if any) NIH (K07AG052685, R01MD007716, K01HL135452, R01HL152453)

scholarly journals Catastrophic Household Expenditure Associated with Out-of-Pocket Healthcare Payments in Spain

2021 ◽  
Vol 18 (3) ◽  
pp. 932
Author(s):  
Samuel López-López ◽  
Raúl del Pozo-Rubio ◽  
Marta Ortega-Ortega ◽  
Francisco Escribano-Sotos
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Regression Models ◽  
Financial Risk ◽  
Household Expenditure ◽  
Financial Protection ◽  
Logistic Regression Models ◽  
Ordered Logistic Regression ◽  
Out Of Pocket Payments ◽  
The Subject

Background. The financial effect of households’ out-of-pocket payments (OOP) on access and use of health systems has been extensively studied in the literature, especially in emerging or developing countries. However, it has been the subject of little research in European countries, and is almost nonexistent after the financial crisis of 2008. The aim of the work is to analyze the incidence and intensity of financial catastrophism derived from Spanish households’ out-of-pocket payments associated with health care during the period 2008–2015. Methods. The Household Budget Survey was used and catastrophic measures were estimated, classifying the households into those above the threshold of catastrophe versus below. Three ordered logistic regression models and margins effects were estimated. Results. The results reveal that, in 2008, 4.42% of Spanish households dedicated more than 40% of their income to financing out-of-pocket payments in health, with an average annual gap of EUR 259.84 (DE: EUR 2431.55), which in overall terms amounts to EUR 3939.44 million (0.36% of GDP). Conclusion. The findings of this study reveal the existence of catastrophic households resulting from OOP payments associated with health care in Spain and the need to design financial protection policies against the financial risk derived from facing these types of costs.

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