Association between case signalment and disease diagnosis in urinary bladder disease in Australian cats and dogs

2021 ◽  
pp. 104063872110040
Author(s):  
Emily Jones ◽  
John Alawneh ◽  
Mary Thompson ◽  
Rachel Allavena
Keyword(s):  
Logistic Regression ◽  
Urinary Bladder ◽  
Disease Diagnosis ◽  
Bladder Tissue ◽  
Laboratory Service ◽  
Bladder Disease ◽  
Increased Risk ◽  
Bladder Diseases ◽  
Urinary Bladder Diseases ◽  
The University

Urinary bladder diseases are common in dogs and cats; however, there is little published work on urinary bladder disease in Australian pets. We identified pathology records of Australian dogs and cats with urinary bladder tissue submitted to the University of Queensland Veterinary Laboratory Service during 1994–2016 ( n = 320). We described the proportion of bladder diseases in dogs and cats, and applied the less-commonly used logistic regression procedure to quantify associations between signalment variables and disease diagnosis that were evident using descriptive statistics alone. After preliminary analysis, both species were combined because of similar results. Spayed/castrated animals were 74% less likely to be diagnosed with cystitis compared with intact animals. Animals 4–11 y old were also at lower risk of being diagnosed with cystitis compared with younger or older animals. Male animals were at increased risk of neoplasia compared to females, which contrasts with reports from North America and Europe. There was increased risk for developing neoplasia with progressive age, with up to 20 times higher odds in the > 11-y age group. Logistic regression modeling provided unique insight into proportionate morbidity of urinary bladder diseases in Australian dogs and cats.

scholarly journals Predicting Diagnosis of Australian Canine and Feline Urinary Bladder Disease Based on Histologic Features

2020 ◽  
Vol 7 (4) ◽  
pp. 190
Author(s):  
Emily Jones ◽  
John Alawneh ◽  
Mary Thompson ◽  
Chiara Palmieri ◽  
Karen Jackson ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Urinary Bladder ◽  
Cognitive Biases ◽  
Disease Modeling ◽  
Disease Model ◽  
Statistical Technique ◽  
Regression Modeling ◽  
Bladder Disease ◽  
Logistic Regression Modeling ◽  
Bladder Diseases

Anatomic pathology is a vital component of veterinary medicine but as a primarily subjective qualitative or semiquantitative discipline, it is at risk of cognitive biases. Logistic regression is a statistical technique used to explain relationships between data categories and outcomes and is increasingly being applied in medicine for predicting disease probability based on medical and patient variables. Our aims were to evaluate histologic features of canine and feline bladder diseases and explore the utility of logistic regression modeling in identifying associations in veterinary histopathology, then formulate a predictive disease model using urinary bladder as a pilot tissue. The histologic features of 267 canine and 71 feline bladder samples were evaluated, and a logistic regression model was developed to identify associations between the bladder disease diagnosed, and both patient and histologic variables. There were 102 cases of cystitis, 84 neoplasia, 42 urolithiasis and 63 normal bladders. Logistic regression modeling identified six variables that were significantly associated with disease outcome: species, urothelial ulceration, urothelial inflammation, submucosal lymphoid aggregates, neutrophilic submucosal inflammation, and moderate submucosal hemorrhage. This study demonstrated that logistic regression modeling could provide a more objective approach to veterinary histopathology and has opened the door toward predictive disease modeling based on histologic variables.

scholarly journals Intravesical drug delivery approaches for improved therapy of urinary bladder diseases

2021 ◽  
pp. 100100
Author(s):  
Luca Palugan ◽  
Matteo Cerea ◽  
Micol Cirilli ◽  
Saliha Moutaharrik ◽  
Alessandra Maroni ◽  
...  
Keyword(s):  
Drug Delivery ◽  
Urinary Bladder ◽  
Bladder Diseases ◽  
Urinary Bladder Diseases

Urinary Bladder Diseases

2010 ◽  
pp. 199-199
Author(s):  
Suresh Bakle ◽  
Bipin Daga
Keyword(s):  
Urinary Bladder ◽  
Bladder Diseases ◽  
Urinary Bladder Diseases

scholarly journals Diagnosis of urinary bladder diseases in dogs by using two-dimensional and three-dimensional ultrasonography

2015 ◽  
Vol 8 (7) ◽  
pp. 819-822 ◽  
Author(s):  
Dinesh Dehmiwal ◽  
S.M. Behl ◽  
Prem Singh ◽  
Rishi Tayal ◽  
Madan Pal ◽  
...  
Keyword(s):  
Urinary Bladder ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Bladder Diseases ◽  
Urinary Bladder Diseases

scholarly journals Impact of a goal-directed factor-based coagulation management on thromboembolic events following major trauma

2019 ◽  
Vol 27 (1) ◽  
Author(s):  
Anais L. Stein ◽  
Julian Rössler ◽  
Julia Braun ◽  
Kai Sprengel ◽  
Patrick E. Beeler ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Major Trauma ◽  
University Hospital ◽  
Allogeneic Blood ◽  
Thromboembolic Events ◽  
Blood Products ◽  
Coagulation Management ◽  
Period 2 ◽  
Increased Risk ◽  
The University

Abstract Background A factor-based coagulation management following major trauma is recommended as standard of care by the European Trauma Treatment Guidelines. However, concerns about the thromboembolic risk of this approach are still prevalent. Our study therefore aims to assess if such a haemostatic management is associated with an increased risk for thromboembolic events. Methods In this retrospective observational study carried out at the University Hospital Zurich we compared two three-year periods before (period 1: 2005–2007) and after (period 2: 2012–2014) implementation of a factor-based coagulation algorithm. We included all adult patients following major trauma primarily admitted to the University Hospital Zurich. Thromboembolic events were defined as a new in-hospital appearance of any peripheral thrombosis, arterial embolism, pulmonary embolism, stroke or myocardial infarction. A logistic regression was performed to investigate the association of thromboembolic events with possible confounders such as age, sex, specific Abbreviated Injury Scale (AIS) subgroups, allogeneic blood products, and the coagulation management. Results Out of 1138 patients, 772 met the inclusion criteria: 344 patients in period 1 and 428 patients in period 2. Thromboembolic events were present in 25 patients (7.3%) of period 1 and in 42 patients (9.8%) of period 2 (raw OR 1.39, 95% CI 0.83 to 2.33, p = 0.21). Only AIS extremities (adjusted OR 1.26, 95% CI 1.05 to 1.52, p = 0.015) and exposure to allogeneic blood products (adjusted OR 2.39, 95% CI 1.33 to 4.30, p = 0.004) were independently associated with thromboembolic events in the logistic regression, but the factor-based coagulation management was not (adjusted OR 1.60, 95% CI 0.90–2.86, p = 0.11). Conclusion There is no evidence that a goal-directed, factor-based coagulation management is associated with an increased risk for thromboembolic events following major trauma.

A novel excitation-emission wavelength model to facilitate the diagnosis of urinary bladder diseases

2015 ◽  
Author(s):  
Ilya Rafailov ◽  
Scott Palmer ◽  
Karina Litvinova ◽  
Victor Dremin ◽  
Andrey Dunaev ◽  
...  
Keyword(s):  
Urinary Bladder ◽  
Emission Wavelength ◽  
Bladder Diseases ◽  
Urinary Bladder Diseases

scholarly journals Elevated glycohemoglobin is linked to critical illness in CoVID-19: a retrospective analysis

2021 ◽  
Vol 8 ◽  
pp. 204993612110273
Author(s):  
Samuel Windham ◽  
Melissa P. Wilson ◽  
Connor Fling ◽  
David Sheneman ◽  
Taylor Wand ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Characteristic Curve ◽  
P Value ◽  
University Of Colorado ◽  
Increased Risk ◽  
Unit Increase ◽  
Chart Abstraction ◽  
Control Of Diabetes ◽  
Novel Coronavirus ◽  
The University

Background: Several studies have explored hospitalization risk factors with the novel coronavirus disease 2019 (COVID-19) infection. Our goal was to identify clinical characteristics outside of laboratory or radiologic data associated with intubation or death within 7 days of admission. Methods: The first 436 patients admitted to the University of Colorado Hospital (Denver metropolitan area) with confirmed COVID-19 were included. Demographics, comorbidities, and select medications were collected by chart abstraction. Missing height for calculating body mass index (BMI) was imputed using the median height for patients’ sex and race/ethnicity. Adjusted odds ratios (aOR) were estimated using multivariable logistic regression and a minimax concave penalty (MCP) regularized logistic regression explored prediction. Results: Participants had a mean [standard deviation (SD)] age 55 (17), BMI 30.9 (8.2), 55% were male and 80% were ethnic/racial minorities. Increasing age [aOR: 1.24 (1.07, 1.45) per 10 years], higher BMI (aOR 1.03 (1.00, 1.06), and poorly controlled diabetes [hemoglobin A1C (HbA1c) ⩾ 8] (aOR 2.26 (1.24, 4.12) were significantly ( p < 0.05) associated with greater odds of intubation or death. Female sex [aOR: 0.63, 95% CI (0.40, 0.98); p value = 0.043] was associated with lesser odds of intubation or death. The odds of death and/or intubation increased 19% for every 1 unit increase in HbA1c value [OR: 1.19 (1.01, 1.43); p = 0.04]. Our final MCP model included indicators of A1C ⩾ 8, age > 65, sex, and minority status, but predicted intubation/death only slightly better than random chance [area under the receiver operating characteristic curve (AUC) = 0.61 (0.56, 0.67)]. Conclusion: In a hospitalized patient cohort with COVID-19, worsening control of diabetes as evidenced by higher HbA1c was associated with increased risk of intubation or death within 7 days of admission. These results complement and help clarify previous associations found between diabetes and acute disease in COVID-19. Importantly, our analysis is missing some known predictors of severity in COVID-19. Our predictive model had limited success, suggesting unmeasured factors contribute to disease severity differences.

scholarly journals 22. Description of Hospitalized Patients with Influenza Vaccine Failure

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S35-S35
Author(s):  
Joanna Kimball ◽  
Yuwei Zhu ◽  
Dayna Wyatt ◽  
Helen Talbot
Keyword(s):  
Logistic Regression ◽  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Older Patients ◽  
Influenza A ◽  
Influenza Season ◽  
Hospitalized Patients ◽  
Vaccine Failure ◽  
Increased Risk ◽  
Immunosuppressed Patients

Abstract Background Despite influenza vaccination, some patients develop illness and require hospitalization. Many factors contribute to vaccine failure, including mismatch of the vaccine and circulating strains, waning immunity, timing of influenza season, age and patient comorbidities such as immune function. This study compared vaccinated, hospitalized patients with and without influenza. Methods This study used 2015–2019 Tennessee data from the US Hospitalized Adult Influenza Vaccine Effectiveness Network database. Enrolled patients were ≥ 18 years vaccinated for the current influenza season and admitted with an acute respiratory illness. Patient or surrogate interviews and medical chart abstractions were performed, and influenza vaccinations were confirmed by vaccine providers. Influenza PCR testing was performed in a research lab. Statistical analyses were performed with STATA and R using Pearson’s chi-squared, Kruskal-Wallis and Wilcoxon rank-sum tests and multivariate logistic regression. Results 1236 patients met study criteria, and 235 (19%) tested positive for influenza. Demographics, vaccines and comorbidities were similar between the two groups (Table 1) except for morbid obesity, which was more common in influenza negative patients (13% vs 8%, p = 0.04), and immunosuppression, which was more common in the influenza positive (63% vs 54%, p = 0.01). Logistic regression analysis demonstrated older patients (OR 1.47, 95% CI 1.03–2.10) and immunosuppressed patients (OR 1.56, 1.15–2.12) were at increased risk for influenza (Table 2 and Figure 1). Immunosuppression also increased the risk for influenza A/H3N2 (OR 1.86, 95% CI 1.25–2.75). A sensitivity analysis was performed on patients who self-reported influenza vaccination for the current season without vaccine verification and demonstrated increased risk of influenza in older adults (OR 1.66, 95% CI 1.16–2.39). Table 1: Demographics of influenza positive versus influenza negative patients in influenza vaccinated, hospitalized patients. Table 2: Logistic regression analyses of vaccinated, hospitalized influenza positive patients; vaccinated, hospitalized patients with influenza A subtypes and self-reported vaccinated, hospitalized influenza positive patients. Figure 1: Predicted Probability of Hospitalization with Influenza, Influenza A/H1N1 and Influenza A/H3N2 in Vaccinated Patients by Age. Conclusion Our study demonstrated an increased risk of influenza vaccine failure in older patients and immunosuppressed patients. These groups are also at increased risk for influenza complications. To improve protection of these patients against future influenza illnesses, more effective vaccines are needed, and more research on ring vaccination should be pursued. Disclosures All Authors: No reported disclosures

scholarly journals Prior Admissions as a Risk Factor for Readmission in Patients Surgically Treated for Femur Fractures: Implications for a Potential Hip Fracture Bundle

2021 ◽  
Vol 12 ◽  
pp. 215145932199616
Author(s):  
Robert Erlichman ◽  
Nicholas Kolodychuk ◽  
Joseph N. Gabra ◽  
Harshitha Dudipala ◽  
Brook Maxhimer ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Hip Fracture ◽  
Logistic Regression Analysis ◽  
Hip Fractures ◽  
Surgical Procedure ◽  
Hospital Admissions ◽  
Fracture Care ◽  
Increased Risk ◽  
Payment Models

Introduction: Hip fractures are a significant economic burden to our healthcare system. As there have been efforts made to create an alternative payment model for hip fracture care, it will be imperative to risk-stratify reimbursement for these medically comorbid patients. We hypothesized that patients readmitted to the hospital within 90 days would be more likely to have a recent previous hospital admission, prior to their injury. Patients with a recent prior admission could therefore be considered higher risk for readmission and increased cost. Methods: A retrospective chart review identified 598 patients who underwent surgical fixation of a hip or femur fracture. Data on readmissions within 90 days of surgical procedure and previous admissions in the year prior to injury resulting in surgical procedure were collected. Logistic regression analysis was used to determine if recent prior admission had increased risk of 90-day readmission. A subgroup analysis of geriatric hip fractures and of readmitted patients were also performed. Results: Having a prior admission within one year was significantly associated (p < 0.0001) for 90-day readmission. Specifically, logistic regression analysis revealed that a prior admission was significantly associated with 90-day readmission with an odds ratio of 7.2 (95% CI: 4.8-10.9). Discussion: This patient population has a high rate of prior hospital admissions, and these prior admissions were predictive of 90-day readmission. Alternative payment models that include penalties for readmissions or fail to apply robust risk stratification may unjustly penalize hospital systems which care for more medically complex patients. Conclusions: Hip fracture patients with a recent prior admission to the hospital are at an increased risk for 90-day readmission. This information should be considered as alternative payment models are developed for hip fracture care.

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