Antipsychotic Medication Dispensing and Associated Odds Ratios of Death In Elderly Veterans and War Widows, 2001

2006 ◽  
Vol 40 (11-12) ◽  
pp. 981-986 ◽  
Author(s):  
Jean Hollis ◽  
Stephen Touyz ◽  
David Grayson ◽  
Loelle Forrester
Keyword(s):  
Logistic Regression ◽  
Drug Toxicity ◽  
Regression Models ◽  
Reference Group ◽  
Antidepressant Medication ◽  
Mortality Rates ◽  
Elderly Subjects ◽  
Odds Ratios ◽  
Logistic Regression Models ◽  
The Difference

Objectives: To explore the odds ratios (ORs) of death associated with antipsychotic (AP) medications dispensed to elderly subjects. Method: Subjects were veterans and war widows 65 years and older dispensed an AP drug in 2001 in NSW or ACT. For all subjects, dispensing records for AP medication, benzodiazepines, lithium, carbamazepine, sodium valproate and antidepressant medication were extracted and combined with age, gender and date of death. A study date was allocated, either the date of death or a random date from 1.5.01 to 31.12.01. Subjects dispensed an AP in 2001, but not dispensed an AP or other psychotropic medication in the 120 days prior to their study date, formed a reference group. Psychotropic dispensing in the 120 days prior to the study date was analysed using nested logistic regression models to produce ORs of death associated with various AP drugs. The ORs for risperidone, olanzapine and pericyazine were compared. Haloperidol ORs were established for those dispensed the drug 0–30 days prior to study date or 31–120 days prior to the study date. Results: The ORs associated with haloperidol, olanzapine, risperidone, pericyazine, thioridazine and chlorpromazine were significant when compared with the reference group. Odds ratios for all three haloperidol periods were significant when compared with olanzapine, risperidone and pericyazine 120 day ORs. Although there was a trend favouring olanzapine when compared with risperidone, the difference in the ORs failed to reach significance (p = 0.066). Conclusions: Haloperidol is associated with significantly higher mortality rates than other AP medication but it is not clear whether this represents drug toxicity or the medical conditions for which it was dispensed. There was no evidence that the conventional AP pericyazine was associated with a higher mortality rate than olanzapine or risperidone.

scholarly journals Asymmetric Fixed Effects Models for Panel Data

2018 ◽  
Author(s):  
Paul D Allison
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Opposite Direction ◽  
Difference Method ◽  
Fixed Effects ◽  
Regression Models ◽  
Social Phenomena ◽  
Logistic Regression Models ◽  
Fixed Effects Models ◽  
The Difference

Standard fixed effects methods presume that effects of variables are symmetric: the effect of increasing a variable is the same as the effect of decreasing that variable but in the opposite direction. This is implausible for many social phenomena. York and Light (2017) showed how to estimate asymmetric models by estimating first-difference regressions in which the difference scores for the predictors are decomposed into positive and negative changes. In this paper, I show that there are several aspects of their method that need improvement. I also develop a data generating model that justifies the first-difference method but can be applied in more general settings. In particular, it can be used to construct asymmetric logistic regression models.

scholarly journals Asymmetric Fixed-effects Models for Panel Data

2019 ◽  
Vol 5 ◽  
pp. 237802311982644 ◽  
Author(s):  
Paul D. Allison
Keyword(s):  
Logistic Regression ◽  
Panel Data ◽  
Opposite Direction ◽  
Difference Method ◽  
Fixed Effects ◽  
Regression Models ◽  
Social Phenomena ◽  
Logistic Regression Models ◽  
Fixed Effects Models ◽  
The Difference

Standard fixed-effects methods presume that effects of variables are symmetric: The effect of increasing a variable is the same as the effect of decreasing that variable but in the opposite direction. This is implausible for many social phenomena. York and Light showed how to estimate asymmetric models by estimating first-difference regressions in which the difference scores for the predictors are decomposed into positive and negative changes. In this article, I show that there are several aspects of their method that need improvement. I also develop a data-generating model that justifies the first-difference method but can be applied in more general settings. In particular, it can be used to construct asymmetric logistic regression models.

Performance simulations for categorical mediation: Analyzing khb estimates of mediation in ordinal regression models

2019 ◽  
Vol 19 (4) ◽  
pp. 913-930 ◽  
Author(s):  
E. Keith Smith ◽  
Michael G. Lacy ◽  
Adam Mayer
Keyword(s):  
Logistic Regression ◽  
Nonlinear Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Experimental Conditions ◽  
Logistic Regression Models ◽  
Nonlinear Regression Models ◽  
Size Number ◽  
Confidence Interval Coverage ◽  
The Difference

Standard mediation techniques for fitting mediation models cannot readily be translated to nonlinear regression models because of scaling issues. Methods to assess mediation in regression models with categorical and limited response variables have expanded in recent years, and these techniques vary in their approach and versatility. The recently developed khb technique purports to solve the scaling problem and produce valid estimates across a range of nonlinear regression models. Prior studies demonstrate that khb performs well in binary logistic regression models, but performance in other models has yet to be investigated. In this article, we evaluate khb‘s performance in fitting ordinal logistic regression models as an exemplar of the wider set of models to which it applies. We examined performance across 38,400 experimental conditions involving sample size, number of response categories, distribution of variables, and amount of mediation. Results indicate that under all experimental conditions, khb estimates the difference (mediation) coefficient and its associated standard error with little bias and that the nominal confidence interval coverage closely matches the actual. Our results suggest that researchers using khb can assume that the routine reasonably approximates population parameters.

scholarly journals Influence of year-on-year performance on final degree classification in a chiropractic master's degree program

2016 ◽  
Vol 30 (1) ◽  
pp. 14-19 ◽  
Author(s):  
Philip Dewhurst ◽  
Jacqueline Rix ◽  
David Newell
Keyword(s):  
Logistic Regression ◽  
Problem Solving ◽  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Logistic Regression Models ◽  
The Difference ◽  
Degree Classification ◽  
Grade Performance ◽  
Final Degree

Objective: We explored if any predictors of success could be identified from end-of-year grades in a chiropractic master's program and whether these grades could predict final-year grade performance and year-on-year performance. Methods: End-of-year average grades and module grades for a single cohort of students covering all academic results for years 1–4 of the 2013 graduating class were used for this analysis. Analysis consisted of within-year correlations of module grades with end-of-year average grades, linear regression models for continuous data, and logistic regression models for predicting final degree classifications. Results: In year 1, 140 students were enrolled; 85.7% of students completed the program 4 years later. End-of-year average grades for years 1–3 were correlated (Pearson r values ranging from .75 to .87), but the end-of-year grades for years 1–3 were poorly correlated with clinic internship performance. In linear regression, several modules were predictive of end-of-year average grades for each year. For year 1, logistic regression showed that the modules Physiology and Pharmacology and Investigative Imaging were predictive of year 1 performance (odds ratio [OR] = 1.15 and 0.9, respectively). In year 3, the modules Anatomy and Histopathology 3 and Problem Solving were predictors of the difference between a pass/merit or distinction final degree classification (OR = 1.06 and 1.12, respectively). Conclusion: Early academic performance is weakly correlated with final-year clinic internship performance. The modules of Anatomy and Histopathology year 3 and Problem Solving year 3 emerged more consistently than other modules as being associated with final-year classifications.

Care Practices and Bronchopulmonary Dysplasia Debate

PEDIATRICS ◽  
1987 ◽  
Vol 80 (6) ◽  
pp. 969-970
Author(s):  
JACOB KELLER ◽  
MARY ELLEN AVERY
Keyword(s):  
Logistic Regression ◽  
Birth Weight ◽  
Null Hypothesis ◽  
Regression Models ◽  
Multiple Logistic Regression ◽  
Dummy Variables ◽  
Logistic Regression Models ◽  
Independent Variables ◽  
Care Practices ◽  
The Difference

In Reply.— We appreciate the opportunity to clarify the issues raised by Barry et al. We tested the significance of the differences among centers in the incidence of chronic lung disease, adjusted for sex, race, and birth weight, by computing two multiple logistic regression models. The first model included only sex, race, and birth weight as independent variables. The second model additionally included seven dummy variables representing the eight centers. Twice the difference in the log likelihoods in the two models has a χ2 distribution with 7 df under the null hypothesis of no center differences.

Association of Body Composition and Intradialytic Hypotension in Hemodialysis Patients

2020 ◽  
Vol 49 (3) ◽  
pp. 334-340
Author(s):  
Maolu Tian ◽  
Yan Zha ◽  
Shuwen Qie ◽  
Xin Lin ◽  
Jing Yuan
Keyword(s):  
Body Composition ◽  
Logistic Regression ◽  
Regression Models ◽  
Density Lipoprotein ◽  
Intradialytic Hypotension ◽  
Logistic Regression Models ◽  
Multifrequency Bioimpedance ◽  
Dialysis Vintage ◽  
The Difference ◽  
Adjusted Logistic Regression

Background/Aim: The relationship between body mass index (BMI) and intradialytic hypotension (IDH) has been inconsistently reported, but no further research has investigated the correlation between body composition and IDH so far. This study aimed to determine whether the lean tissue index (LTI), fat tissue index (FTI), or both derived from body composition monitoring (BCM) is associated with IDH defined as a nadir intradialytic systolic blood pressure of <90 mm Hg and ≥3 episodes hypotension per 10 hemodialysis (HD) treatments in patients undergoing prevalent HD. Methods: The observational cohort study comprised 1,463 patients receiving thrice-weekly HD from 13 dialysis centers. LTI and FTI were assessed using a BCM machine, a multifrequency bioimpedance spectroscopy device. Unadjusted and multivariable adjusted logistic regression models were fit to estimate the association of body composition with the odds of developing IDH. Results: One hundred and seven patients (7.3%) were diagnosed as IDH. The difference in dialysis vintage, BMI, FTI, LTI, high-density lipoprotein cholesterol, and C-reactive protein between IDH and non-IDH groups was statistically significant (all p < 0.05). The prevalence of diabetes among IDH patients was slightly higher than among non-IDH patients. In logistic regression models, low LTI and high FTI, but not high BMI were associated with greater odds of IDH (“high” as above median and “low” as below median). When patients were further stratified into 4 distinct body composition groups based on both the LTI and FTI, only the low LTI/high FTI group was connected with a significantly higher odds of IDH (OR 2.686, 95% CI 1.072–6.734; reference: low LTI/low FTI group). Conclusions: The LTI and FTI can provide better correlation of IDH occurrence than the BMI alone in prevalent HD patients. The low LTI/high FTI appears to be most associated with IDH. An optimal body composition for preventing the occurrence of IDH needs to be determined.

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)

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