scholarly journals External validation of a prognostic model for intensive care unit mortality: a retrospective study using the Ontario Critical Care Information System

2020 ◽  
Vol 67 (8) ◽  
pp. 981-991 ◽  
Author(s):  
Fran Priestap ◽  
Raymond Kao ◽  
Claudio M. Martin
Keyword(s):  
Intensive Care Unit ◽  
Information System ◽  
Critical Care ◽  
Intensive Care ◽  
Retrospective Study ◽  
Prognostic Model ◽  
Intensive Care Unit Mortality ◽  
External Validation ◽  
Care Information

scholarly journals Procalcitonin-guided protocol use and impact on intensive care unit and antibiotic management: a pilot study

2021 ◽  
Vol 12 (2) ◽  
pp. 563
Author(s):  
Danillo E. OLIVEIRA ◽  
Eudes G. CUNHA ◽  
Diana M. GUERRA ◽  
Valéria S. BEZERRA
Keyword(s):  
Intensive Care Unit ◽  
Critical Care ◽  
Intensive Care ◽  
Retrospective Study ◽  
Antibiotic Therapy ◽  
Hospital Costs ◽  
Protocol Adherence ◽  
Unified Health System ◽  
Antibiotic Management ◽  
Therapy Cost

Objective: To assess the procalcitonin protocol use and its impact on antibiotic therapy management of critically ill patients in the intensive care unit (ICU). Method: An observational descriptive and retrospective study conducted in an adult ICU with 28 beds from the Brazilian Unified Health System (SUS). Results: This present study observed a 78% (90/116) of PCT protocol adherence in the studied ICU. We observed a reduction in days of antibiotic treatment (DOT) going from 14 to 8,5 treatment-day duration (5.49 ± 2.2 days), impacting the overall antibiotic therapy cost for a decrease of 40.91%. Conclusion: The study revealed that PCT use was associated with substantial benefits, reducing hospital costs and days of exposure to antibiotic therapy applied to patients affected by infectious diseases in critical care settings.  

scholarly journals Impact of an Intensive Care Information System on the Length of Stay of Surgical Intensive Care Unit Patients: Observational Study (Preprint)

2019 ◽  
Author(s):  
Camille Havel ◽  
Jean Selim ◽  
Emmanuel Besnier ◽  
Philippe Gouin ◽  
Benoit Veber ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Information System ◽  
Intensive Care ◽  
Length Of Stay ◽  
Observational Study ◽  
Severity Score ◽  
University Hospital ◽  
X Rays ◽  
Icu Mortality ◽  
Care Information

BACKGROUND The implementation of computerized monitoring and prescription systems in intensive care has proven to be reliable in reducing the rate of medical error and increasing patient care time. They also showed a benefit in reducing the length of stay in the intensive care unit (ICU). However, this benefit has been poorly studied, with conflicting results. OBJECTIVE This study aimed to show the impact of computerization on the length of stay in ICUs. METHODS This was a before-after retrospective observational study. All patients admitted in the surgical ICU at the Rouen University Hospital were included, from June 1, 2015, to June 1, 2016, for the before period and from August 1, 2016, to August 1, 2017, for the after period. The data were extracted from the hospitalization report and included the following: epidemiological data (age, sex, weight, height, and body mass index), reason for ICU admission, severity score at admission, length of stay and mortality in ICU, mortality in hospital, use of life support during the stay, and ICU readmission during the same hospital stay. The consumption of antibiotics, biological analyses, and the number of chest x-rays during the stay were also analyzed. RESULTS A total of 1600 patients were included: 839 in the before period and 761 in the after period. Only the severity score Simplified Acute Physiology Score II was significantly higher in the postcomputerization period (38 [SD 20] vs 40 [SD 21]; P<.05). There was no significant difference in terms of length of stay in ICU, mortality, or readmission during the stay. There was a significant increase in the volume of prescribed biological analyses (5416 [5192-5956] biological exams prescribed in the period before Intellispace Critical Care and Anesthesia [ICCA] vs 6374 [6013-6986] biological exams prescribed in the period after ICCA; P=.002), with an increase in the total cost of biological analyses, to the detriment of hematological and biochemical blood tests. There was also a trend toward reduction in the average number of chest x-rays, but this was not significant (0.55 [SD 0.39] chest x-rays per day per patient before computerization vs 0.51 [SD 0.37] chest x-rays per day per patient after computerization; P=.05). On the other hand, there was a decrease in antibiotic prescribing in terms of cost per patient after the implementation of computerization (€149.50 [$164 USD] per patient before computerization vs €105.40 [$155 USD] per patient after computerization). CONCLUSIONS Implementation of an intensive care information system at the Rouen University Hospital in June 2016 did not have an impact on reducing the length of stay.

The positive financial impact of using an Intensive Care Information System in a tertiary Intensive Care Unit

2013 ◽  
Vol 82 (3) ◽  
pp. 177-184 ◽  
Author(s):  
Eric Levesque ◽  
Emir Hoti ◽  
Sofia de La Serna ◽  
Houssam Habouchi ◽  
Philippe Ichai ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Information System ◽  
Intensive Care ◽  
Financial Impact ◽  
Care Information

scholarly journals Impact of an Intensive Care Information System on the Length of Stay of Surgical Intensive Care Unit Patients: Observational Study

10.2196/14501 ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. e14501
Author(s):  
Camille Havel ◽  
Jean Selim ◽  
Emmanuel Besnier ◽  
Philippe Gouin ◽  
Benoit Veber ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Information System ◽  
Intensive Care ◽  
Length Of Stay ◽  
Observational Study ◽  
Severity Score ◽  
University Hospital ◽  
X Rays ◽  
Icu Mortality ◽  
Care Information

Background The implementation of computerized monitoring and prescription systems in intensive care has proven to be reliable in reducing the rate of medical error and increasing patient care time. They also showed a benefit in reducing the length of stay in the intensive care unit (ICU). However, this benefit has been poorly studied, with conflicting results. Objective This study aimed to show the impact of computerization on the length of stay in ICUs. Methods This was a before-after retrospective observational study. All patients admitted in the surgical ICU at the Rouen University Hospital were included, from June 1, 2015, to June 1, 2016, for the before period and from August 1, 2016, to August 1, 2017, for the after period. The data were extracted from the hospitalization report and included the following: epidemiological data (age, sex, weight, height, and body mass index), reason for ICU admission, severity score at admission, length of stay and mortality in ICU, mortality in hospital, use of life support during the stay, and ICU readmission during the same hospital stay. The consumption of antibiotics, biological analyses, and the number of chest x-rays during the stay were also analyzed. Results A total of 1600 patients were included: 839 in the before period and 761 in the after period. Only the severity score Simplified Acute Physiology Score II was significantly higher in the postcomputerization period (38 [SD 20] vs 40 [SD 21]; P<.05). There was no significant difference in terms of length of stay in ICU, mortality, or readmission during the stay. There was a significant increase in the volume of prescribed biological analyses (5416 [5192-5956] biological exams prescribed in the period before Intellispace Critical Care and Anesthesia [ICCA] vs 6374 [6013-6986] biological exams prescribed in the period after ICCA; P=.002), with an increase in the total cost of biological analyses, to the detriment of hematological and biochemical blood tests. There was also a trend toward reduction in the average number of chest x-rays, but this was not significant (0.55 [SD 0.39] chest x-rays per day per patient before computerization vs 0.51 [SD 0.37] chest x-rays per day per patient after computerization; P=.05). On the other hand, there was a decrease in antibiotic prescribing in terms of cost per patient after the implementation of computerization (€149.50 [$164 USD] per patient before computerization vs €105.40 [$155 USD] per patient after computerization). Conclusions Implementation of an intensive care information system at the Rouen University Hospital in June 2016 did not have an impact on reducing the length of stay.

scholarly journals Diuretic strategies in patients with resistance to loop-diuretics in the intensive care unit: A retrospective study from the MIMIC-III database

2021 ◽  
Vol 65 ◽  
pp. 282-291
Author(s):  
Jean-Maxime Côté ◽  
Josée Bouchard ◽  
Patrick T. Murray ◽  
William Beaubien-Souligny
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Retrospective Study ◽  
Loop Diuretics ◽  
Mimic Iii

scholarly journals A Timely Call to Arms: COVID-19, the Circadian Clock, and Critical Care

2021 ◽  
Vol 36 (1) ◽  
pp. 55-70
Author(s):  
Jeffrey Haspel ◽  
Minjee Kim ◽  
Phyllis Zee ◽  
Tanja Schwarzmeier ◽  
Sara Montagnese ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Human Physiology ◽  
Critical Care ◽  
Intensive Care ◽  
Severe Acute Respiratory Syndrome ◽  
Circadian Clock ◽  
Clinical Course ◽  
Disease Expression ◽  
Severe Manifestation ◽  
Novel Coronavirus

We currently find ourselves in the midst of a global coronavirus disease 2019 (COVID-19) pandemic, caused by the highly infectious novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we discuss aspects of SARS-CoV-2 biology and pathology and how these might interact with the circadian clock of the host. We further focus on the severe manifestation of the illness, leading to hospitalization in an intensive care unit. The most common severe complications of COVID-19 relate to clock-regulated human physiology. We speculate on how the pandemic might be used to gain insights on the circadian clock but, more importantly, on how knowledge of the circadian clock might be used to mitigate the disease expression and the clinical course of COVID-19.

scholarly journals Development of a machine learning model for predicting pediatric mortality in the early stages of intensive care unit admission

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bongjin Lee ◽  
Kyunghoon Kim ◽  
Hyejin Hwang ◽  
You Sun Kim ◽  
Eun Hee Chung ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Intensive Care ◽  
Validation Cohort ◽  
External Validation ◽  
Learning Model ◽  
Derivation Cohort ◽  
Icu Admission ◽  
Early Stages ◽  
Machine Learning Model

AbstractThe aim of this study was to develop a predictive model of pediatric mortality in the early stages of intensive care unit (ICU) admission using machine learning. Patients less than 18 years old who were admitted to ICUs at four tertiary referral hospitals were enrolled. Three hospitals were designated as the derivation cohort for machine learning model development and internal validation, and the other hospital was designated as the validation cohort for external validation. We developed a random forest (RF) model that predicts pediatric mortality within 72 h of ICU admission, evaluated its performance, and compared it with the Pediatric Index of Mortality 3 (PIM 3). The area under the receiver operating characteristic curve (AUROC) of RF model was 0.942 (95% confidence interval [CI] = 0.912–0.972) in the derivation cohort and 0.906 (95% CI = 0.900–0.912) in the validation cohort. In contrast, the AUROC of PIM 3 was 0.892 (95% CI = 0.878–0.906) in the derivation cohort and 0.845 (95% CI = 0.817–0.873) in the validation cohort. The RF model in our study showed improved predictive performance in terms of both internal and external validation and was superior even when compared to PIM 3.

Diagnosis of Auditory Neuropathy Spectrum Disorder in the Neonatal Intensive Care Unit Population

2021 ◽  
pp. 019459982110298
Author(s):  
Chengetai Mahomva ◽  
Yi-Chun Carol Liu ◽  
Nikhila Raol ◽  
Samantha Anne
Keyword(s):  
Intensive Care Unit ◽  
Information System ◽  
Intensive Care ◽  
Neonatal Intensive Care Unit ◽  
Health Information ◽  
Neonatal Intensive Care ◽  
Health Information System ◽  
Auditory Neuropathy ◽  
Spectrum Disorder ◽  
Nicu Admission

Objective To determine the incidence of auditory neuropathy spectrum disorder (ANSD) and its risk factors among the neonatal intensive care unit (NICU) population from 2009 to 2018 in the Pediatric Health Information System database. Study Design Retrospective national database review. Setting Population-based study. Methods The Pediatric Health Information System database was queried to identify patients ≤18 years old with NICU admission and ANSD diagnosis. Patient demographics, jaundice diagnosis, use of mechanical ventilation, extracorporeal membrane oxygenation, furosemide, and/or aminoglycosides were extracted. Multivariable linear regression was used to assess trends in incidence. Chi-square analysis was used to assess differences between patients with and without ANSD. Logistic regression was used to assess factors associated with ANSD. Results From 2009 to 2018, there was an increase in (1) NICU admissions from 14,079 to 24,851 ( P < .001), (2) total ANSD diagnoses from 92 to 1847 ( P = .001), and (3) annual total number of patients with ANSD and NICU admission increased from 4 to 16 ( P = .005). There was strong correlation between the increases in total number of NICU admissions and total ANSD diagnoses over time ( R = 0.76). The average ANSD incidence was 0.052% with no statistically significant change over 10 years. When compared with all NICU admissions, children with ANSD had a higher association with use of furosemide ( P < .001) and ventilator ( P < .001). Conclusion Despite a statistically significant increase in NICU admissions and total ANSD diagnosis, the incidence of ANSD in the NICU population has not increased from 2009 to 2018. Furosemide and mechanical ventilator use were associated with increased likelihood of ANSD.

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