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Showing posts with label risk. Show all posts
Showing posts with label risk. Show all posts

Tuesday, 20 March 2018

Evaluation of ICU Risk Models Adapted for Use as Continuous Markers of Severity of Illness Throughout the ICU Stay*


Evaluation of ICU Risk Models Adapted for Use as Continuous Markers of Severity of Illness Throughout the ICU Stay*

Badawi, Omar PharmD, MPH, FCCM1,2,3; Liu, Xinggang MD, PhD1; Hassan, Erkan PharmD, FCCM1; Amelung, Pamela J. MD, FCCP1; Swami, Sunil PhD, MPH, MBBS1
doi: 10.1097/CCM.0000000000002904

Objectives: Evaluate the accuracy of different ICU risk models repurposed as continuous markers of severity of illness.
Design: Nonintervention cohort study.
Setting: eICU Research Institute ICUs using tele-ICU software calculating continuous ICU Discharge Readiness Scores between January 2013 and March 2016.
Patients: Five hundred sixty-one thousand four hundred seventy-eight adult ICU patients with an ICU length of stay between 4 hours and 30 days.
Interventions: Not available.
Measurements and Main Results: Hourly Acute Physiology and Chronic Health Evaluation IV, Sequential Organ Failure Assessment, and Discharge Readiness Scores were calculated beginning hour 4 of the ICU stay. Primary outcome was the area under the receiver operating characteristic curve for the mean score with ICU mortality. Secondary outcomes included area under the receiver operating characteristic curves for ICU mortality with admission, median, maximum and last scores, and for death within 24 hours. The trajectories of each score were visualized by plotting the hourly averages against time in the ICU, stratified by mortality and length of stay. The area under the receiver operating characteristic curves for mean Acute Physiology and Chronic Health EvaluationSequential Organ Failure Assessment, and Discharge Readiness Scores were 0.90 (0.89–0.90), 0.86 (0.86–0.86), and 0.94 (0.94–0.94), respectively. The area under the receiver operating characteristic curves for hourly Acute Physiology and Chronic Health EvaluationSequential Organ Failure Assessment, and Discharge Readiness Scores predicting 24-hour mortality were 0.81 (0.81–0.81), 0.76 (0.76–0.76), and 0.86 (0.86–0.86). Discharge Readiness Scores had a higher area under the receiver operating characteristic curve than both Acute Physiology and Chronic Health Evaluation and Sequential Organ Failure Assessment for each metric. Acute Physiology and Chronic Health Evaluation and Sequential Organ Failure Assessment scores increased throughout the first 24 hours in both survivors and nonsurvivors; Discharge Readiness Scores continuously decreased in survivors and temporarily decreased before increasing by hour 36 in nonsurvivors with longer length of stays.
Conclusions: Acute Physiology and Chronic Health EvaluationSequential Organ Failure Assessment, and Discharge Readiness Scores all have relatively high discrimination for ICU mortality when used continuously; Discharge Readiness Scores tended to have slightly higher area under the receiver operating characteristic curves for each endpoint. These findings validate the use of these models on a population level for continuous risk adjustment in the ICU, although Acute Physiology and Chronic Health Evaluation and Sequential Organ Failure Assessment appear slower to respond to improvements in patient status than Discharge Readiness Scores, and Discharge Readiness Scores may reflect physiologic improvement from interventions, potentially underestimating risk.



Sunday, 7 January 2018

Perceptions of Risk and Safety in the ICU: A Qualitative Study of Cognitive Processes Relating to Staffing

Perceptions of Risk and Safety in the ICU: A Qualitative Study of Cognitive Processes Relating to Staffing
D’Lima, D et al

Critical Care Medicine: January 2018 - Volume 46 - Issue 1 - p 60–70

Objectives: The aims of this study were to 1) examine individual professionals’ perceptions of staffing risks and safe staffing in intensive care and 2) identify and examine the cognitive processes that underlie these perceptions. 

Design: Qualitative case study methodology with nurses, doctors, and physiotherapists. Setting: Three mixed medical and surgical adult ICUs, each on a separate hospital site within a 1,200-bed academic, tertiary London hospital group. Subjects: Forty-four ICU team members of diverse professional backgrounds and seniority. Interventions: None. Main Results: Four themes (individual, team, unit, and organizational) were identified. Individual care provision was influenced by the pragmatist versus perfectionist stance of individuals and team dynamics by the concept of an “A” team and interdisciplinary tensions. Perceptions of safety hinged around the importance of achieving a “dynamic balance” influenced by the burden of prevailing circumstances and the clinical status of patients. Organizationally, professionals’ risk perceptions affected their willingness to take personal responsibility for interactions beyond the unit. 
Conclusions: This study drew on cognitive research, specifically theories of cognitive dissonance, psychological safety, and situational awareness to explain how professionals’ cognitive processes impacted on ICU behaviors. Our results may have implications for relationships, management, and leadership in ICU. First, patient care delivery may be affected by professionals’ perfectionist or pragmatic approach. Perfectionists’ team role may be compromised and they may experience cognitive dissonance and subsequent isolation/stress. Second, psychological safety in a team may be improved within the confines of a perceived “A” team but diminished by interdisciplinary tensions. Third, counter intuitively, higher “situational” awareness for some individuals increased their stress and anxiety. Finally, our results suggest that professionals have varying concepts of where their personal responsibility to minimize risk begins and ends, which we have termed “risk horizons” and that these horizons may affect their behavior both within and beyond the unit.

Thursday, 17 November 2016

Mild Cognitive Impairment and Risk of Critical Illness

Mild Cognitive Impairment and Risk of Critical Illness

Teeters, D. A et al

Critical Care Medicine: November 2016 - Volume 44 - Issue 11 - p 2045–2051

Objectives: Approximately half of ICU admissions are comprised of patients older than 65 years old. Mild cognitive impairment is a common disorder affecting 10–20% of patients in the same age group. A need exists for exploring mild cognitive impairment and risk of critical illness. As mild cognitive impairment may be a contributor to poorer overall health or be a result of it, we sought to determine whether the presence of mild cognitive impairment independently increases the risk of critical illness admissions. 
Design: Data from the Mayo Clinic Study of Aging were analyzed. All study participants underwent prospective comprehensive cognitive testing and expert panel consensus diagnosis of both cognitive function and clinical state at baseline and subsequent visits. Comparisons were made between those with normal cognitive function and mild cognitive impairment regarding baseline health and frequency of critical illness. Setting: Single-center population-based cohort out of Olmsted County, MN. Participants: All individuals 70–89 years old were screened for prospective enrollment in the Mayo Clinic Study of Aging. Patients with preexisting dementia and ICU admission within 3 years of entry to the study were excluded from this analysis. Interventions: None. 
Measurements and Main Results: Of 2,425 patients analyzed from the Mayo Clinic Study of Aging, 1,734 patients (71%) were included in the current study. Clinical factors associated with baseline mild cognitive impairment included age, male gender, stroke, and poorer health self-rating. Using a Cox regression model adjusting for these and a priori variables of baseline health, the presence of mild cognitive impairment remained a significant predictor of ICU admission (hazard ratio, 1.50 [1.15–1.96]; p = 0.003). 
Conclusions and Relevance: The presence of mild cognitive impairment is independently associated with increased critical illness admission. Further prospective studies are needed to analyze the impact of critical illness on cognitive function.

Thursday, 18 August 2016

Real-Time Risk Prediction on the Wards: A Feasibility Study

Real-Time Risk Prediction on the Wards: A Feasibility Study
 Critical Care Medicine
Kang MA et al

Objective: Failure to detect clinical deterioration in the hospital is common and associated with poor patient outcomes and increased healthcare costs. Our objective was to evaluate the feasibility and accuracy of real-time risk stratification using the electronic Cardiac Arrest Risk Triage score, an electronic health record-based early warning score. Design: We conducted a prospective black-box validation study. Data were transmitted via HL7 feed in real time to an integration engine and database server wherein the scores were calculated and stored without visualization for clinical providers. The high-risk threshold was set a priori. Timing and sensitivity of electronic Cardiac Arrest Risk Triage score activation were compared with standard-of-care Rapid Response Team activation for patients who experienced a ward cardiac arrest or ICU transfer. Setting: Three general care wards at an academic medical center. Patients: A total of 3,889 adult inpatients. Measurements and Main Results: The system generated 5,925 segments during 5,751 admissions. The area under the receiver operating characteristic curve for electronic Cardiac Arrest Risk Triage score was 0.88 for cardiac arrest and 0.80 for ICU transfer, consistent with previously published derivation results. During the study period, eight of 10 patients with a cardiac arrest had high-risk electronic Cardiac Arrest Risk Triage scores, whereas the Rapid Response Team was activated on two of these patients (p < 0.05). Furthermore, electronic Cardiac Arrest Risk Triage score identified 52% (n = 201) of the ICU transfers compared with 34% (n = 129) by the current system (p < 0.001). Patients met the high-risk electronic Cardiac Arrest Risk Triage score threshold a median of 30 hours prior to cardiac arrest or ICU transfer versus 1.7 hours for standard Rapid Response Team activation. Conclusions: Electronic Cardiac Arrest Risk Triage score identified significantly more cardiac arrests and ICU transfers than standard Rapid Response Team activation and did so many hours in advance. 

Monday, 7 July 2008

Variation in ICU Risk - Adjusted Mortality : Impact of Methods of Assessment and Potential Confounders

Author(s): Michael W . Kuzniewicz
ISSUE: 2008 ; VOL 133 ; PART 6 (2008-June)
Journal Title: Chest ( Formerly : Diseases of the Chest ) From Free Medical Journals . com (/1995 - /Embargo: 1 year) Customer Notes: 1997 v111/1 - Print Location: Macclesfield

From Proquest NHS (01/1997 - 11/2006) Page: 1319 - 1327
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