scholarly journals LO10: Associations between ED crowding metrics and 72h-hour ED re-visits: Which crowding metrics are most highly associated with patient-oriented adverse outcomes?

CJEM ◽  
2019 ◽  
Vol 21 (S1) ◽  
pp. S10
Author(s):  
A. McRae ◽  
G. Innes ◽  
M. Schull ◽  
E. Lang ◽  
E. Grafstein ◽  
...  
Keyword(s):  
Patient Outcomes ◽  
Regression Models ◽  
Information Criterion ◽  
Patient Characteristics ◽  
Adverse Outcomes ◽  
Logistic Regression Models ◽  
Return Visits ◽  
Offload Delay ◽  
Ed Crowding ◽  
Meaningful Measure

Introduction: Emergency Department (ED) crowding is a pervasive problem and is associated with adverse patient outcomes. Yet, there are no widely accepted, universal ED crowding metrics. The objective of this study is to identify ED crowding metrics with the strongest association to the risk of ED revisits within 72 hours, which is a patient-oriented adverse outcome. Methods: Crowding metrics, patient characteristics and outcomes were obtained from administrative data for all ED encounters from 2011-2014 for three adult EDs in Calgary, AB. The data were randomly divided into three partitions for cross-validation, and further divided by CTAS category 1, 2/3 and 4/5. Twenty unique ED crowding metrics were calculated and assigned to each patient seen on each calendar day or shift, to standardize the exposure. Logistic regression models were fitted with 72h ED revisit as the dependent variable, and an individual crowding metric along with a common list of confounders as independent variables. Adjusted odds ratios (OR) for the 72h return visits were obtained for each crowding metric. The strength of associations between 72h revisits and crowding metrics were compared using Akaike's Information Criterion and Akaike weights. Results: This analysis is based on 1,149,939 ED encounters. Across all CTAS groups, INPUT metrics (ED census, ED occupancy, waiting time, EMS offload delay, LWBS%) were only weakly associated with the risk of 72h re-visit. Among THROUGHPUT metrics, ED Length of Stay and MD Care Time had similar adjusted ORs for 72h ED re-visit (range 0.99-1.15). Akaike weights ranging from 0.3/1.00 to 0.4/1.00 indicate that both THROUGHPUT metrics are reasonable predictors of 72h ED re-visits. All OUTPUT metrics (boarding time, # of boarded patients, % of beds occupied by boarded patients, hospital occupancy) had statistically significant ORs for 72h ED re-visits. The median boarding time had the highest adjusted OR for 72h ED re-visit (adjusted OR 1.40, 95% CI 1.33-1.47) and highest Akaike weight (0.97/1.00) compared to all other OUTPUT metrics, indicating that median boarding time had the strongest association with 72h re-visits. Conclusion: ED THROUGHPUT and OUTPUT metrics had consistent associations with 72h ED re-visits, while INPUT metrics had little to no association with 72h re-visits. Median boarding time is the strongest predictor of 72h re-visits, indicating that this may be the most meaningful measure of ED crowding.

Abstract P36: Lesional Perfusion and Permeability Are Diagnostic and Prognostic Biomarkers of Cavernous Angioma With Symptomatic Hemorrhage

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Je Yeong Sone ◽  
Nicholas Hobson ◽  
Sharbel Romanos ◽  
Abhinav Srinath ◽  
Abdallah Shkoukani ◽  
...  
Keyword(s):  
Regression Models ◽  
Prognostic Biomarker ◽  
Information Criterion ◽  
Cavernous Angioma ◽  
Prognostic Biomarkers ◽  
Diagnostic Efficacy ◽  
Logistic Regression Models ◽  
Conventional Mri ◽  
Contrast Enhanced ◽  
Univariate Analyses

Introduction: Diagnosis of cavernous angioma with symptomatic hemorrhage (CASH) requires MRI evidence of lesional bleeding associated directly with attributable symptoms. However, hemorrhagic signs of CASH may become clinically silent on conventional MRI after 3 months. As CASH is likely to rebleed for several years, accurate diagnosis of CASH that bled more than 3 months prior is needed. Hypothesis: Perfusion and permeability derivations of dynamic contrast-enhanced quantitative perfusion (DCEQP) MRI can diagnose CASH and predict bleeding/growth in CAs. Methods: CAs of 205 consecutively enrolled patients scanned with DCEQP during clinical visits were classified as CASH that bled 3 - 12 months prior (N = 55) versus non-CASH (N = 658) or CA with (N = 23) versus without (N = 721) bleeding/growth within a year after MRI. Demographics and 13 perfusion and 13 permeability derivations of DCEQP were assessed via machine learning and univariate analyses. Logistic regression models ln ( P / 1 - P ) = Σ (β i x i ) + β 0 were selected as the best diagnostic and prognostic biomarkers by minimizing the Bayesian information criterion (BIC). Results: The best diagnostic biomarker of CASH that bled 3 - 12 months prior (BIC = 321.6, Figure A) showed 80% sensitivity and 82% specificity. Permeability derivations did not add diagnostic efficacy when combined with perfusion. The best prognostic biomarker of bleeding/growth (BIC = 201.5, Figure B) showed 77% sensitivity and 72% specificity. Conclusion: Perfusion imaging may diagnose CASH even after hemorrhagic signs disappear on conventional MRI. A combination of permeability and perfusion derivations may help predict bleeding/growth in CAs.

scholarly journals Alcohol consumption and pregnancy in the Mexican national addiction survey

1997 ◽  
Vol 13 (2) ◽  
pp. 205-211 ◽  
Author(s):  
Guilherme Borges ◽  
Roberto Tapia-Conyer ◽  
Malaquías López-Cervantes ◽  
María Elena Medina-Mora ◽  
Blanca Pelcastre ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Spontaneous Abortion ◽  
Regression Models ◽  
Congenital Abnormalities ◽  
Adverse Outcomes ◽  
Multiple Logistic Regression ◽  
National Data ◽  
Logistic Regression Models ◽  
Important Relationship

In 1988, the General Directorate of Epidemiology and the Mexican Institute of Psychiatry conducted the first National Addiction Survey (ENA), providing regional and national data on alcohol, tobacco, and drug use. The ENA providing a subsample of women who have been pregnant at some time in their lives. There were 5,234 affirmative responses. Women were asked if they had suffered any of three adverse outcomes during their last pregnancy: spontaneous abortion, stillbirth, and congenital abnormalities. Prevalence of spontaneous abortion was 3.8%, stillbirth 1.2%, and congenital abnormalities 1.1 %. Multiple logistic-regression models were used to analyze the effect of alcohol consumption on these problems. Consumption during pregnancy was related only with the prevalence of congenital abnormalities, with prevalence odds of 3.4. Among habitual users during the last 12 months, oniy women in the highest use category showed an important relationship with the three problems mentioned. Follow-up studies on the Mexican population are recommended in order to obtain more conclusive findings.

scholarly journals Correlates of Adverse Outcomes in Abdominally Obese Individuals: Findings from the Five-Year Followup of the Population-Based Study of Health in Pomerania

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Nele Friedrich ◽  
Harald J. Schneider ◽  
Ulrich John ◽  
Marcus Dörr ◽  
Sebastian E. Baumeister ◽  
...  
Keyword(s):  
Abdominal Obesity ◽  
Regression Models ◽  
Kidney Diseases ◽  
Premature Death ◽  
Population Based ◽  
Serum Glucose ◽  
Adverse Outcomes ◽  
Population Based Study ◽  
Logistic Regression Models ◽  
Increased Risk

Background. Abdominal obesity is a major risk factor of cardiovascular disease (CVD), type 2 diabetes (T2DM), and premature death. However, it has not been resolved which factors predispose for the development of these adverse obesity-related outcomes in otherwise healthy individuals with abdominal obesity.Methods. We studied 1,506 abdominal obese individuals (waist-to-height ratio (WHtR) ≥ 0.5) free of CVD or T2DM from the population-based Study of Health in Pomerania and assessed the incidence of CVD or T2DM after a five-year followup. Logistic regression models were adjusted for major cardiovascular risk factors and liver, kidney diseases, and sociodemographic status.Results. During follow-up time, we observed 114 and 136 new T2DM and CVD cases, respectively. Regression models identified age, waist circumference, serum glucose, and liver disease as predictors of T2DM. Regarding CVD, only age, unemployment, and a divorced or widowed marital status were significantly associated with incident CVD. In this subgroup of obese individuals blood pressure, serum glucose, or lipids did not influence incidence of T2DM or CVD.Conclusion. We identified various factors associated with an increased risk of incident T2DM and CVD among abdominally obese individuals. These findings may improve the detection of high-risk individuals and help to advance prevention strategies in abdominal obesity.

scholarly journals The Association Between Alkaline Phosphatase and Neurological Outcome in Patients with Post-cardiac Arrest: a Secondary Analysis of Data from Belgium

2021 ◽  
Author(s):  
jiacheng he
Keyword(s):  
Alkaline Phosphatase ◽  
Logistic Regression ◽  
Cardiac Arrest ◽  
Neurological Outcome ◽  
Regression Models ◽  
Secondary Analysis ◽  
Adverse Outcomes ◽  
Blood Biomarkers ◽  
Logistic Regression Models

Abstract Background: Prognostication of the unfavourable neurological outcome(UNO) after Cardiac arrest(CA) is multimodal while blood biomarkers are an attractive option.Serum alkaline phosphatase(ALP) is shown to be associated with ischemic stroke and considered as an independent prognostic factor for long-term functional outcome after acute cerebral infarction.We aimed to study the association between ALP and UNO in 3 months in patients after CA.Methods:Review of consecutive patients admitted to the ICU at Erasme Hospital, Brussels (Belgium) following CA between January 2007 and December 2015. The outcome was the UNO in 3 months. We used multivariable logistic regression models to calculate the adjusted odd ratio (OR) with 95% confidence interval(CI). Interaction and stratified analyses were conducted according to Shock,Dobutamine.used,Hypertension,Cardiac.Etiology and Shockable.Rhythm.Results: We included 374 CA patients. The multivariate logistic regression analyses revealed that the risk of UNO in 3 months after CA was significantly associated with ALP.When ALP was Equal is divided in 3 groups, the risk of ALP>91 level and adverse outcomes was 1.7407 times of ALP<64 level (P for trend=0.19709).In the non-hypertension group, the risk of adverse outcomes increased with increased ALP by 1.018 (1.0041.01,1.032).Conclusions: ALP is an independent risk factor for the UNO in 3 months after CA, especially in non-hypertension. Elevated ALP was significantly associated with increased UNO in 3 months after CA. However, the prediction significance of ALP for long-term neurological outcome in patients after CA is needed further studied.

scholarly journals The Influence of Patient Characteristics on Anticholinergic Events in Older People

2016 ◽  
Vol 5 (3) ◽  
pp. 530-541 ◽  
Author(s):  
Mohammed Saji Salahudeen ◽  
Prasad S. Nishtala ◽  
Stephen B. Duffull
Keyword(s):  
Older People ◽  
Population Level ◽  
Information Criterion ◽  
Patient Characteristics ◽  
Model Framework ◽  
Significant Independent Predictor ◽  
Logistic Regression Models ◽  
Level Data ◽  
Hospitalised Patients ◽  
Comorbidity Index

Aims: To examine patient characteristics that predict adverse anticholinergic-type events in older people. Methods: This retrospective population-level study included 2,248 hospitalised patients. Individual data on medicines that are commonly associated with anticholinergic events (delirium, constipation and urinary retention) were identified. Patient characteristics examined were medicines with anticholinergic effects (ACh burden), age, sex, non-anticholinergic medicines (non-ACM), Charlson comorbidity index scores and ethnicity. The Akaike information criterion was used for model selection. The data were analysed using logistic regression models for anticholinergic events using the software NONMEM. Results: ACh burden was found to be a significant independent predictor for developing an anticholinergic event [adjusted odds ratio (aOR): 3.21, 95% CI: 1.23-5.81] for those taking an average of 5 anticholinergic medicines compared to those taking 1. Both non-ACM and age were also independent risk factors (aOR: 1.41, 95% CI: 1.31-1.51 and aOR: 1.08, 95% CI: 1.05-1.10, respectively). Conclusion: To our knowledge, this is the first study that has examined population-level data in a nonlinear model framework to predict anticholinergic-type adverse events. This study evaluated the relationship between important patient characteristics and the occurrence of anticholinergic-type events. These findings reinforce the clinical significance of reviewing anticholinergic medicines in older people.

Treatment of older patients with atrial fibrillation by morbidity burden

2020 ◽  
Author(s):  
Peter Vibe Rasmussen ◽  
Jannik Langtved Pallisgaard ◽  
Morten Lock Hansen ◽  
Gunnar Hilmar Gislason ◽  
Christian Torp-Pedersen ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Older Patients ◽  
Regression Models ◽  
Oral Anticoagulants ◽  
Rhythm Control ◽  
Adverse Outcomes ◽  
Logistic Regression Models ◽  
Morbidity Burden ◽  
Control Procedures ◽  
Multimorbid Patients

Abstract Aims  Older patients with atrial fibrillation (AF) are at risk of adverse outcomes, which is accentuated by comorbidities. We sought to examine the association between morbidity burden and the treatment of older AF patients. Methods and results  Using Danish nationwide registers we included patients ≥70 years of age between 2010 and 2017 at their first hospitalization due to AF. Using multiple logistic regression models we examined the association between morbidity burden and the odds of receiving oral anticoagulants (OACs), anti-arrhythmic drugs (AADs), and rhythm-control procedures (direct current cardioversions and catheter ablations). A total of 48 995 patients were included with a majority of women (54%), with a median age of 80 years [interquartile range (IQR) 75–85], and a median morbidity burden of 2 comorbidities (IQR 1–3). Increasing morbidity burden was associated with decreasing odds of OAC treatment with patients having &gt;5 comorbidities having the lowest odds [odds ratio (OR) 0.38, 95% confidence interval (CI) 0.35–0.42] compared to patients with low morbidity burden (0–1 comorbidities). Having &gt;5 comorbidities were associated with increased odds of AAD treatment (OR 1.90, 95% CI 1.64–2.21) and decreased odds of AF procedures (OR 0.39, 95% CI 0.31–0.48), compared to patients with a low morbidity burden (0–1 comorbidities). Examining morbidity burden continuously revealed similar results. Conclusions  In older AF patients, multimorbidity was associated with lower odds of receiving OACs and rhythm-control procedures but increased odds of AADs. This presents a clinical conundrum as multimorbid patients potentially benefit the most from treatment with OACs.

Association of Practice-Level Hospital Use With End-of-Life Outcomes, Readmission, and Weekend Hospitalization Among Medicare Beneficiaries With Cancer

2016 ◽  
Vol 12 (10) ◽  
pp. e933-e943 ◽  
Author(s):  
Jeffrey D. Clough ◽  
Larisa M. Strawbridge ◽  
Thomas W. LeBlanc ◽  
Bradley G. Hammill ◽  
Arif H. Kamal
Keyword(s):  
End Of Life ◽  
Patient Outcomes ◽  
Regression Models ◽  
Care Transitions ◽  
Medicare Beneficiaries ◽  
Life Outcomes ◽  
Logistic Regression Models ◽  
Practice Level ◽  
Level Hospital ◽  
Hospital Use

Purpose: To determine the relationships between hospital use of treating oncology practices and patient outcomes. Patients and Methods: Retrospective analysis of 397,646 Medicare beneficiaries who received anticancer therapy in 2012. Each beneficiary was associated with a practice; practices were ranked on the basis of risk-adjusted hospital use, that is, inpatient intensity. Outcomes included 30-day readmission, weekend admissions, intensive care unit stays in the last month of life, and hospice stay of ≥ 7 days. Outcomes were measured for each quartile of practice-level inpatient intensity. We fit multivariable logistic regression models to calculate adjusted odds ratios (ORs) for each outcome for each quartile of inpatient intensity. Results: Total 30-day readmissions were 22.8% and 31.9% (OR, 1.45; 95% CI, 1.39 to 1.50) for patients in practices with the lowest versus highest quartiles of inpatient intensity, respectively; unplanned readmissions were 19.8% and 27.1% (OR, 1.36; 95% CI, 1.31 to 1.41), respectively. The proportion of admissions that occurred on weekends was similar across quartiles. Patients of practices in the highest quartiles of inpatient intensity had higher rates of death in an ICU stay in the last month of life (25.5% versus 18.0%; OR, 1.33; 95% CI, 1.19 to 1.49) and a lower rate of hospice stay of at least 7 days (50.9% to 42.5%; OR, 0.79; 95% CI, 0.74 to 0.86). Conclusion: Medical oncology practices that seek to reduce hospitalizations should consider focusing initially on processes related to end-of-life care and care transitions.

Surgical oncology outcomes: The role of nurse practice environments

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6105-6105
Author(s):  
C. R. Friese ◽  
L. H. Aiken
Keyword(s):  
Logistic Regression ◽  
Patient Outcomes ◽  
Regression Models ◽  
Surgical Oncology ◽  
Cancer Center ◽  
Practice Environment ◽  
Failure To Rescue ◽  
Oncology Patient ◽  
Logistic Regression Models

6105 Background: Increased attention has focused on the role of hospital characteristics on cancer patient outcomes. We examined two cancer-specific credentials, as well registered nurse practice environments, on outcomes of care. Methods: Through secondary analysis of existing data from hospital claims, the tumor registry, and a statewide of survey of nurses (RNs), we studied 30-day mortality (D) and failure to rescue (death given a complication) (FTR) for surgical oncology patients treated in 164 Pennsylvania hospitals from 1998–1999 (N=24,618). We compared D and FTR rates by a hospital’s NCI cancer center designation, American College of Surgeon’s (ACoS) cancer program approval and categorized scores on the Practice Environment Scale of the Nursing Work Index (PES-NWI). The PES-NWI scales measure RN participation in hospital affairs, RN foundations for quality of care, nurse manager leadership/support, staffing/resource adequacy, and RN-physician relations. Multivariate logistic regression models examined predictors of D and FTR, controlling for 25 patient variables. Standard errors were corrected for patient clustering in hospitals. Results: NCI centers had lower D and FTR rates (p < .01). ACoS hospitals had lower D and FTR rates (ns). Hospitals with low scores on PES-NWI scales had the poorest outcomes (p < .01). In logistic regression models, significant predictors included unfavorable PES-NWI Scores for D (OR=1.32, 95% CI: 1.06–1.65) and FTR (OR=1.39, 95% CI:1.03–1.88), and NCI centers for D (OR=0.64, 95% CI: 0.50–0.83) and FTR (OR=0.67, 95% CI: 0.47–0.96). The NCI effect lost significance when environment was included. ACoS program effects were small (OR= 0.99, p = .90) for both outcomes. Conclusions: Favorable outcomes in NCI centers may be partly explained by practice environments. The practice environment of RNs significantly predicts surgical oncology patient outcomes, and should be a focus of quality improvement activities. No significant financial relationships to disclose.

scholarly journals How Important Is Income in Explaining Avoidance of Care Due to Cost-Sharing Payments? Results From a Mixed Methods Sequential Explanatory Study.

2021 ◽  
Author(s):  
Benjamin H. Salampessy ◽  
France R.M. Portrait ◽  
Marianne Donker ◽  
Ismail Ismail ◽  
Eric J.E. Hijden
Keyword(s):  
Demand Response ◽  
Cost Sharing ◽  
Regression Models ◽  
Personal Characteristics ◽  
Patient Characteristics ◽  
Relative Importance ◽  
Structured Interviews ◽  
Logistic Regression Models ◽  
Complex Design ◽  
Negative Connotation

Abstract Background The avoidance of healthcare by patients because of the costs involved has become more prevalent in recent years. Certain patient characteristics, such as income, are known to be associated with a stronger demand-response to cost-sharing. In this study, we first assess the relative importance of patient characteristics with regard to the avoidance of healthcare due to cost-sharing payments, and then employ qualitative methods in order to understand these findings better. Methods Survey data was collected from a Dutch panel of frequent users of healthcare. Logistic regression models and dominance analyses were performed to assess the relative importance of patient characteristics with regard to the avoidance, i.e., personal characteristics, health, skills and financial situation. Semi-structured interviews (n = 5) were conducted with those who had avoided healthcare. The verbatim transcribed interviews were thematically analyzed. Results Of the 7,339 respondents who completed the questionnaire, 1,048 respondents (14.3%) had avoided healthcare because of the deductible requirement. Dominance analyses revealed that an individual’s financial leeway contributed the most (34.8%) to the model’s overall McFadden’s pseudo-R2 (i.e., 0.12), followed by income (25.6%), age (19.6%) and sense of mastery (8.9%). Similar results were observed in stratified models and in population weighted models. Qualitative analyses distinguished four main themes: (1) the financial reasons and (2) personal considerations that affected the decision whether to use healthcare, (3) the perceived uncertainty in payments due to the complex design of cost-sharing programs, and (4) whether the use of healthcare was perceived as compulsory. Furthermore, ‘avoidance of healthcare’ seemed to have a negative connotation. Conclusion Our findings show that avoidance of healthcare depends on various factors including income, and imply that focusing solely on lowering cost-sharing payments for certain individuals will only partly reduce this avoidance. Our study underlines the need for a broader perspective in the design of cost-sharing programs.

scholarly journals Association of Fatigue With Sarcopenia and its Elements: A Secondary Analysis of SABE-Bogotá

2017 ◽  
Vol 3 ◽  
pp. 233372141770373 ◽  
Author(s):  
Daniela Patino-Hernandez ◽  
David Gabriel David-Pardo ◽  
Miguel Germán Borda ◽  
Mario Ulises Pérez-Zepeda ◽  
Carlos Cano-Gutiérrez
Keyword(s):  
Regression Models ◽  
Handgrip Strength ◽  
Secondary Analysis ◽  
Adverse Outcomes ◽  
Multiple Logistic Regression ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Independent Variables ◽  
Confounding Variables ◽  
Aging Adults

Objective: Sarcopenia, fatigue, and depression are associated with higher mortality rates and adverse outcomes in the aging population. Understanding the association among clinical variables, mainly symptoms, is important for screening and appropriately managing these conditions. The aim of this article is to evaluate the association among sarcopenia and its elements with depression and fatigue. Method: We used cross-sectional data from 2012 SABE ( Salud, Bienestar y Envejecimiento)-Bogotá study, which included 2,000 participants of ages ≥60 years. Sarcopenia and its elements were taken as the dependent variable, while fatigue and depression were the main independent variables. We tested the association among these through multiple logistic regression models, which were fitted for each dependent variable and adjusted for confounding variables. Results: Our findings showed that gait speed was associated with fatigue (adjusted odds ratio [OR] = 1.41, 95% confidence interval [CI] = [1.05, 1.90], p = .02) as well as abnormal handgrip strength (adjusted OR = 1.40, 95% CI = [1.02, 1.93], p = .04). No other associations were significant. Conclusion: While sarcopenia and fatigue are not associated, two of the sarcopenia-defining variables are associated with fatigue; this suggests that lack of sarcopenia does not exclude undesirable outcomes related to fatigue in aging adults. Also, the lack of association between sarcopenia-defining elements and depression demonstrates that depression and fatigue are different concepts.

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