scholarly journals Body Mass Index and Pressure Ulcers: Improved Predictability of Pressure Ulcers in Intensive Care Patients

2014 ◽  
Vol 23 (6) ◽  
pp. 494-501 ◽  
Author(s):  
S. Hyun ◽  
X. Li ◽  
B. Vermillion ◽  
C. Newton ◽  
M. Fall ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Intensive Care ◽  
Body Mass ◽  
Pressure Ulcers ◽  
Intensive Care Patients

Hospital-acquired pressure ulcers and risk of hospital mortality in intensive care patients on mechanical ventilation

2014 ◽  
Vol 20 (4) ◽  
pp. 362-368 ◽  
Author(s):  
Francisco Manzano ◽  
Ana M. Pérez-Pérez ◽  
Susana Martínez-Ruiz ◽  
Cristina Garrido-Colmenero ◽  
Delphine Roldan ◽  
...  
Keyword(s):  
Mechanical Ventilation ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Pressure Ulcers ◽  
Intensive Care Patients ◽  
Hospital Acquired

OR62: Association of Body Mass Index and Outcome in Chronic Hemodialysis Patients Requiring Intensive Care Therapy

2017 ◽  
Vol 36 ◽  
pp. S25
Author(s):  
W. Druml ◽  
W. Winnicki ◽  
P. Metnitz ◽  
P. Zajic ◽  
T. Fellinger ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Intensive Care ◽  
Body Mass ◽  
Hemodialysis Patients ◽  
Chronic Hemodialysis ◽  
Intensive Care Therapy

scholarly journals Body Mass Index and Mortality in Korean Intensive Care Units: A Prospective Multicenter Cohort Study

PLoS ONE ◽  
2014 ◽  
Vol 9 (4) ◽  
pp. e90039 ◽  
Author(s):  
So Yeon Lim ◽  
Won-Il Choi ◽  
Kyeongman Jeon ◽  
Eliseo Guallar ◽  
Younsuck Koh ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Cohort Study ◽  
Intensive Care ◽  
Intensive Care Units ◽  
Body Mass ◽  
Multicenter Cohort Study ◽  
Multicenter Cohort

Predictive value of abdominal obesity vs. body mass index for determining risk of intensive care unit mortality

2010 ◽  
Vol 38 (5) ◽  
pp. 1308-1314 ◽  
Author(s):  
Jean-Baptiste M. Paolini ◽  
Julien Mancini ◽  
Michèle Genestal ◽  
Hélène Gonzalez ◽  
Rachel Eshima McKay ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Body Mass ◽  
Abdominal Obesity ◽  
Predictive Value ◽  
Intensive Care Unit Mortality

scholarly journals Effect of maternal underweight on fetal outcome

Biomedicine ◽  
2020 ◽  
Vol 39 (3) ◽  
pp. 480-483
Author(s):  
Monteiro Geraldin ◽  
N Anupama ◽  
Rekha D. Kini ◽  
Nayanatara A. K. ◽  
Sneha Shetty ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Weight Gain ◽  
Body Mass ◽  
Neonatal Intensive Care ◽  
Fetal Outcome ◽  
Chi Square ◽  
Chi Square Test ◽  
Nicu Admission

Introduction and Aim: Nutritional state of the mother before and during pregnancy is one of the important determinants along with factors like pre-pregnancy BMI, weight gain during pregnancy and gestational age which determines pregnancy outcome. Adequate gestational weight gain contributes for better pregnancy outcomes in both mother and infants for short- and long-term health. Materials and Methods: This is an observational study conducted retrospectively over a year comprised 300 pregnant subjects in their second trimester. Incidence of anemia, preterm labour, intrauterine growth retardation (IUGR) and neonatal intensive care unit (NICU) admission were compared in women with various Body Mass index (BMI). Analysis of the data was done using SPSS version 13 using chi square test and p ? 0.05 was considered statistically significant. Results: Out of 300 subjects, 79 developed anemia, among these 64(81%) were in the underweight category. 49 cases had a preterm delivery, out of these 49 cases, about 37(75.5%) belonged to the underweight BMI category. 39 cases delivered an intra-uterine growth retarded baby. Out of these 39 cases, about 25 (64.1%) belonged to the underweight BMI category. 56 neonates required intensive care unit (NICU) admission, of which 41 (73.2%) neonates born for underweight BMI mothers. Conclusion: The high proportions of underweight pregnancies in this study reflects the poor nutritional status. Adverse effects of maternal low body mass index target the fetus. Adequate weight gain of pregnant woman is an extremely important factor for the fetal outcome.  

scholarly journals Predictors for extubation failure in COVID-19 patients using a machine learning approach

Critical Care ◽  
2021 ◽  
Vol 25 (1) ◽  
Author(s):  
Lucas M. Fleuren ◽  
Tariq A. Dam ◽  
Michele Tonutti ◽  
Daan P. de Bruin ◽  
Robbert C. A. Lalisang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Body Mass Index ◽  
Intensive Care ◽  
Critically Ill ◽  
Body Mass ◽  
Life Support ◽  
Extubation Failure ◽  
Machine Learning Algorithms ◽  
Optimal Timing ◽  
Predictor Importance

Abstract Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. Conclusion The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

Anxiety, Insomnia and Body Mass Index scores in Italian nurses engaged in the care of COVID-19 patients

2020 ◽  
Vol 20 ◽  
Author(s):  
Elsa Vitale ◽  
Rocco Mea ◽  
Francesca Di Dio ◽  
Anna Canonico ◽  
Vito Galatola
Keyword(s):  
Body Mass Index ◽  
Intensive Care ◽  
Weight Gain ◽  
Severe Acute Respiratory Syndrome ◽  
Sleep Quality ◽  
Body Mass ◽  
Male Nurses ◽  
Female Nurses ◽  
Development Of Anxiety ◽  
Very High

Background: A new Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) (COVID-19) infection was reported in Wuhan, China, and quickly spread, becoming a global health emergency. Literature shows how nursing work is particularly stressful and how this condition is closely connected to the development of anxiety disorders, sleep quality and can also influence eating behavior with consequent variations in BMI values. Objective: The study aims to investigate and correlate the levels of anxiety, insomnia and Body Mass Index among nurses directly involved in the care of patients in the intensive care units with the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) infection. Method: An observatory study was conducted assessing and correlating the anxiety and insomnia levels and BMI values of each nurse before (until December 2019) and during (until May 2020) the pandemic. Results: In total, 291 Italian nurses joined the study. There are no statistically significant differences between female nurses and male nurses for both groups of participants with or without anxiety (p=0.655). Female nurses with mild, moderate and severe insomnia levels were statistically more numerous than male nurses (p=0.025). For the same BMI differences, the levels of anxiety and insomnia were statistically significant between them (p<0.001). Conclusion: Nurses engaged in the treatment of the most serious patients with Covid-19 are subjected to very high levels of stress due to the nature of the nursing job, shifting, poor rest, anxiety due to health emergency period and weight gain.

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