scholarly journals Does Obesity Predispose Medical Intensive Care Unit Patients to Venous Thromboembolism despite Prophylaxis? A Retrospective Chart Review

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
Bradley J. Peters ◽  
Ross A. Dierkhising ◽  
Kristin C. Mara
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Venous Thromboembolism ◽  
Risk Model ◽  
Medical Intensive Care Unit ◽  
Statistical Significance ◽  
The Body ◽  
Vte Prophylaxis ◽  
Increased Risk ◽  
Medical Intensive Care

Background. Obesity is a significant issue in the critically ill population. There is little evidence directing the dosing of venous thromboembolism (VTE) prophylaxis within this population. We aimed to determine whether obesity predisposes medical intensive care unit patients to venous thromboembolism despite standard chemoprophylaxis with 5000 international units of subcutaneous heparin three times daily. Results. We found a 60% increased risk of venous thromboembolism in the body mass index (BMI) ≥ 30 kg/m2 group compared to the BMI < 30 kg/m2 group; however, this difference did not reach statistical significance. After further utilizing our risk model, neither obesity nor mechanical ventilation reached statistical significance; however, vasopressor administration was associated with a threefold risk. Conclusions. We can conclude that obesity did increase the rate of VTE, but not to a statistically significant level in this single center medical intensive care unit population.

Increased risk associated with pulmonary artery catheterization in the medical intensive care unit

2003 ◽  
Vol 18 (3) ◽  
pp. 166-171 ◽  
Author(s):  
Steve G Peters ◽  
Bekele Afessa ◽  
Paul A Decker ◽  
Darrell R Schroeder ◽  
Kenneth P Offord ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Pulmonary Artery ◽  
Medical Intensive Care Unit ◽  
Pulmonary Artery Catheterization ◽  
Increased Risk ◽  
Medical Intensive Care

scholarly journals Venous Thromboembolism in the Medical Intensive Care Unit. Is Wells Score Predictive?

CHEST Journal ◽  
2012 ◽  
Vol 142 (4) ◽  
pp. 856A
Author(s):  
Trupti Vakde ◽  
Ajit Lale ◽  
Misbahuddin Khaja ◽  
Gilda Diaz-Fuentes ◽  
Sindhaghatta Venkatram
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Venous Thromboembolism ◽  
Medical Intensive Care Unit ◽  
Wells Score ◽  
Medical Intensive Care

Obesity as a Predictor of Prolonged Mechanical Ventilation

2020 ◽  
Vol 163 (4) ◽  
pp. 750-754
Author(s):  
Diana Shao ◽  
Jeffrey Straub ◽  
Laura Matrka
Keyword(s):  
Intensive Care Unit ◽  
Mechanical Ventilation ◽  
Intensive Care ◽  
Medical Intensive Care Unit ◽  
Medical Center ◽  
Prolonged Mechanical Ventilation ◽  
Statistical Significance ◽  
Academic Medical Center ◽  
Tertiary Care ◽  
Medical Intensive Care

Objective To examine the effect of including obesity with parameters of the I-TRACH scale in predicting the need for prolonged mechanical ventilation. Study Design A retrospective cohort study. Setting Tertiary care academic medical center. Subjects and Methods Consecutive patients were identified retrospectively over a 45-month period based on need for mechanical ventilation in the medical intensive care unit. Chart review was performed to collect demographic information as well as clinical data, including duration of mechanical ventilation, body mass index (BMI), and I-TRACH parameters (heart rate >110, serum urea nitrogen >25, serum pH <7.25, serum creatinine >2, serum bicarbonate <20). Statistical analysis was performed to identify any predictors of prolonged mechanical ventilation, defined as ≥14 days and as ≥10 days. Results In total, 455 patients were identified, with an average duration of mechanical ventilation of 10.4 days (range, 0-248 days). On univariate and multivariate regression analysis, only BMI >30 reached statistical significance with respect to prolonged mechanical ventilation ( P < .05). The I-TRACH parameters—either alone or in combination—were not significantly predictive. Conclusion This study challenges previous findings regarding the I-TRACH scale and the relation of its parameters to prolonged mechanical ventilation. Furthermore, BMI >30 alone was predictive of prolonged intubation. Inclusion of BMI in predictive models could assist current decision making in determining the likelihood of prolonged mechanical ventilation in medical intensive care unit patients going forward, and obesity should be considered a predictor of prolonged mechanical ventilation.

scholarly journals A Retrospective Analysis and Comparison of Prisoners and Community-Based Patients with COVID-19 Requiring Intensive Care During the First Phase of the Pandemic in West Texas

2020 ◽  
Vol 11 ◽  
pp. 215013272095468
Author(s):  
Kiran Ali ◽  
Sanjana Rao ◽  
Gilbert Berdine ◽  
Victor Test ◽  
Kenneth Nugent
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Length Of Stay ◽  
Medical Intensive Care Unit ◽  
Prison Population ◽  
Community Based ◽  
Increased Risk ◽  
Gi Symptoms ◽  
Medical Intensive Care ◽  
The Mean

Background: COVID-19 is a highly infectious disease which usually presents with respiratory symptoms. This virus is disseminated through respiratory droplets, and, therefore, individuals residing in close quarters are at a higher risk for the acquisition of infection. The prison population is at a significantly increased risk for infection. Methods: Prisoners from the Montford Correctional facility in Lubbock, Texas, hospitalized in the medical intensive care unit at University Medical Center between March 1, 2020 and May 15, 2020 were compared to community-based patients hospitalized in the same medical intensive care unit. Clinical information, laboratory results, radiographic results, management requirements, and outcomes were compared. Results: A total of 15 community-based patients with a mean age of 67.4 ± 15.5 years were compared to 5 prisoners with a mean age of 56.0 ± 9.0 years. All prisoners were men; 10 community-based patients were men. Prisoners presented with fever, dyspnea, and GI symptoms. The mean number of comorbidities in prisoners was 2.4 compared to 1.8 in community-based patients. Prisoners had significantly lower heart rates and respiratory rates at presentation than community-based patients. The mean length of stay in prisoners was 12.6 ± 8.9 days; the mean length of stay in community-based patients was 8.6 ± 6.5. The case fatality rate was 60% in both groups. Conclusions: Prisoners were younger than community-based patients but required longer lengths of stay and had the same mortality rate. This study provides a basis for comparisons with future studies which could involve new treatment options currently under study.

scholarly journals Glycemic Control in the Medical Intensive Care Unit

2009 ◽  
Vol 3 (6) ◽  
pp. 1330-1341 ◽  
Author(s):  
Michelle A. Kovalaske ◽  
Gunjan Y. Gandhi
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Glycemic Control ◽  
Critically Ill ◽  
Glucose Control ◽  
Medical Intensive Care Unit ◽  
Adverse Outcomes ◽  
Acute Hyperglycemia ◽  
Increased Risk ◽  
Medical Intensive Care

Hyperglycemia in the critically ill is a well-known phenomenon, even in those without known diabetes. The stress response is due to a complex interplay between counter-regulatory hormones, cytokines, and changes in insulin sensitivity. Illness/infection, overfeeding, medications (e.g., corticosteroids), insufficient insulin, and/or volume depletion can be additional contributors. Acute hyperglycemia can adversely affect fluid balance (through glycosuria and dehydration), immune and endothelial function, inflammation, and outcome. While there are several insulin infusion protocols that are able to safely and effectively treat hyperglycemia, the bulk of accumulated evidence does not support a causal relationship between acute hyperglycemia and adverse outcomes in the medical intensive care unit. Meta-analysis of randomized controlled trials suggests there is no benefit to tightening glucose control to normal levels compared to a reasonable and achievable goal of 140 to 180 mg/dl. There is a significantly increased risk of hypoglycemia. Although there is some evidence that patients without known diabetes have worse outcomes than those with known diabetes, more recent evidence is conflicting. Glycemic control in critically ill patients should not be neglected, as studies have not tested tight versus no/poor control, but tight versus good control. A moderate approach to managing critical illness hyperglycemia seems most prudent at this juncture. Future research should ascertain whether there are certain subgroups of patients that would benefit from tighter glycemic goals. It also remains to be seen if tight glucose control is beneficial once hypoglycemia is minimized with technological advances such as continuous glucose monitoring systems.

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