scholarly journals Random Survival Forests for Predicting the Bed Occupancy in the Intensive Care Unit

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Joeri Ruyssinck ◽  
Joachim van der Herten ◽  
Rein Houthooft ◽  
Femke Ongenae ◽  
Ivo Couckuyt ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
University Hospital ◽  
Bed Occupancy ◽  
Time Period ◽  
Daunting Task ◽  
Failure Assessment ◽  
Random Survival Forests ◽  
Occupancy Prediction ◽  
Survival Forests

Predicting the bed occupancy of an intensive care unit (ICU) is a daunting task. The uncertainty associated with the prognosis of critically ill patients and the random arrival of new patients can lead to capacity problems and the need for reactive measures. In this paper, we work towards a predictive model based on Random Survival Forests which can assist physicians in estimating the bed occupancy. As input data, we make use of the Sequential Organ Failure Assessment (SOFA) score collected and calculated from 4098 patients at two ICU units of Ghent University Hospital over a time period of four years. We compare the performance of our system with a baseline performance and a standard Random Forest regression approach. Our results indicate that Random Survival Forests can effectively be used to assist in the occupancy prediction problem. Furthermore, we show that a group based approach, such as Random Survival Forests, performs better compared to a setting in which the length of stay of a patient is individually assessed.

scholarly journals Sequential Organ Failure Assessment score trends and sepsis survival in a Brazilian university hospital intensive care unit

Critical Care ◽  
2007 ◽  
Vol 11 (Suppl 2) ◽  
pp. P465
Author(s):  
D Moreira Lima ◽  
B Ferreira de Almeida ◽  
R Cordioli ◽  
E Tadeu Moura ◽  
I Schimdtbauer ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Sequential Organ Failure Assessment ◽  
Organ Failure ◽  
University Hospital ◽  
Assessment Score ◽  
Hospital Intensive Care Unit ◽  
Failure Assessment ◽  
Sepsis Survival

Parameters of bed occupancy of intensive care units in Hungary

2011 ◽  
Vol 152 (24) ◽  
pp. 946-950 ◽  
Author(s):  
Miklós Gresz
Keyword(s):  
Health Care ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Health Insurance ◽  
Intensive Care Units ◽  
Emergency Care ◽  
Present Author ◽  
Bed Occupancy ◽  
National Network ◽  
Bed Capacity

According to the Semmelweis Plan for Saving Health Care, ”the capacity of the national network of intensive care units in Hungary is one but not the only bottleneck of emergency care at present”. Author shows on the basis of data reported to the health insurance that not on a single calendar day more than 75% of beds in intensive care units were occupied. There were about 15 to 20 thousand sick days which could be considered unnecessary because patients occupying these beds were discharged to their homes directly from the intensive care unit. The data indicate that on the whole bed capacity is not low, only in some institutions insufficient. Thus, in order to improve emergency care in Hungary, the rearrangement of existing beds, rather than an increase of bed capacity is needed. Orv. Hetil., 2011, 152, 946–950.

scholarly journals Establishment of a prognostic model based on the Sequential Organ Failure Assessment score for patients with first-time acute myocardial infarction

2021 ◽  
Vol 49 (5) ◽  
pp. 030006052110119
Author(s):  
Shuai Zheng ◽  
Jun Lyu ◽  
Didi Han ◽  
Fengshuo Xu ◽  
Chengzhuo Li ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Sequential Organ Failure Assessment ◽  
Organ Failure ◽  
Sofa Score ◽  
Cardiovascular Events ◽  
Failure Assessment ◽  
First Time

Objective This study aimed to identify the prognostic factors of patients with first-time acute myocardial infarction (AMI) and to establish a nomogram for prognostic modeling. Methods We studied 985 patients with first-time AMI using data from the Multi-parameter Intelligent Monitoring for Intensive Care database and extracted their demographic data. Cox proportional hazards regression was used to examine outcome-related variables. We also tested a new predictive model that includes the Sequential Organ Failure Assessment (SOFA) score and compared it with the SOFA-only model. Results An older age, higher SOFA score, and higher Acute Physiology III score were risk factors for the prognosis of AMI. The risk of further cardiovascular events was 1.54-fold higher in women than in men. Patients in the cardiac surgery intensive care unit had a better prognosis than those in the coronary heart disease intensive care unit. Pressurized drug use was a protective factor and the risk of further cardiovascular events was 1.36-fold higher in nonusers. Conclusion The prognosis of AMI is affected by age, the SOFA score, the Acute Physiology III score, sex, admission location, type of care unit, and vasopressin use. Our new predictive model for AMI has better performance than the SOFA model alone.

scholarly journals Prevalence of multidrug-resistant Acinetobacter baumannii in a critical care setting: A tertiary teaching hospital experience

2021 ◽  
Vol 9 ◽  
pp. 205031212110011
Author(s):  
Thabit Alotaibi ◽  
Abdulrhman Abuhaimed ◽  
Mohammed Alshahrani ◽  
Ahmed Albdelhady ◽  
Yousef Almubarak ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Mortality Rate ◽  
Acinetobacter Baumannii ◽  
Care Setting ◽  
Multidrug Resistant ◽  
University Hospital ◽  
Published Data ◽  
Tertiary Teaching ◽  
The Mean

Background: The management of Acinetobacter baumannii infection is considered a challenge especially in an intensive care setting. The resistance rate makes it difficult to manage and is believed to lead to higher mortality. We aim to investigate the prevalence of Acinetobacter baumannii and explore how different antibiotic regimens could impact patient outcomes as there are no available published data to reflect our population in our region. Methods: We conducted a retrospective review of all infected adult patients admitted to the intensive care unit at King Fahad University Hospital with a confirmed laboratory diagnosis of Acinetobacter baumannii from 1 January 2013 until 31 December 2017. Positive cultures were obtained from the microbiology department and those meeting the inclusive criteria were selected. Variables were analyzed using descriptive analysis and cross-tabulation. Results were further reviewed and audited by blinded co-authors. Results: A comprehensive review of data identified 198 patients with Acinetobacter baumannii. The prevalence of Acinetobacter baumannii is 3.37%, and the overall mortality rate is 40.81%. Our sample consisted mainly of male patients, that is, 68.7%, with a mean age of 49 years, and the mean age of female patients was 56 years. The mean age of survivors was less than that of non-survivors, that is, 44.95 years of age. We observed that prior antibiotic use was higher in non-survivors compared to survivors. From the review of treatment provided for patients infected with Acinetobacter baumannii, 65 were treated with colistin alone, 18 were treated with carbapenems, and 22 were treated with a combination of both carbapenems and colistin. The mean length of stay of Acinetobacter baumannii–infected patients was 20.25 days. We found that the survival rates among patients who received carbapenems were higher compared to those who received colistin. Conclusion: We believe that multidrug-resistant Acinetobacter baumannii is prevalent and associated with a higher mortality rate and represents a challenging case for every intensive care unit physician. Further prospective studies are needed.

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