scholarly journals Copeptin levels are associated with organ dysfunction and death in the intensive care unit after out-of-hospital cardiac arrest

Critical Care ◽  
2015 ◽  
Vol 19 (1) ◽  
Author(s):  
Giuseppe Ristagno ◽  
◽  
Roberto Latini ◽  
Mario Plebani ◽  
Martina Zaninotto ◽  
...  
2019 ◽  
Vol 27 (3) ◽  
pp. 155-161 ◽  
Author(s):  
Veerapong Vattanavanit ◽  
Supattra Uppanisakorn ◽  
Thanapon Nilmoje

Background: Out-of-hospital cardiac arrest results in a high mortality rate. The 2015 American Heart Association guideline for post-cardiac arrest was launched and adopted into our institutional policy. Objectives: We aimed to evaluate post-cardiac arrest care and compare the results with the 2015 American Heart Association guideline and clinical outcomes of out-of-hospital cardiac arrest patients. Methods Included in this study were all adult patients who survived out-of-hospital cardiac arrest and were admitted to the Medical Intensive Care Unit of Songklanagarind Hospital, Thailand. The retrospective review was from 1 January 2016 to 31 December 2017. Results: From a total of 161 post-cardiac arrest patients admitted to the medical intensive care unit, 69 out-of-hospital cardiac arrest patients were identified. The most common cause of arrest was presumed cardiac in origin (45.0%) in which the majority was acute myocardial infarction (67.8%). Coronary intervention and targeted temperature management were performed in 27.5% and 13% of all out-of-hospital cardiac arrest patients, respectively. Survival to hospital discharge was 42%. Independent factors associated with survival to discharge were shockable rhythms, lower adrenaline doses, and the absence of hypotension at medical intensive care unit admission. Conclusion: Compliance with the 2015 American Heart Association post-cardiac arrest care guideline was low in our institution, especially in coronary intervention and targeted temperature management.


2019 ◽  
Vol 9 (7) ◽  
pp. 779-787 ◽  
Author(s):  
Laust Obling ◽  
Christian Hassager ◽  
Charlotte Illum ◽  
Johannes Grand ◽  
Sebastian Wiberg ◽  
...  

Background: Patients admitted to a cardiac intensive care unit are often unconscious with uncertain prognosis. Automated infrared pupillometry for neurological assessment in the intensive care unit may provide early prognostic information. This study aimed to determine the prognostic value of automated pupillometry in different subgroups of patients in a cardiac intensive care unit with 30-day mortality as the primary endpoint and neurological outcome as the secondary endpoint. Methods: A total of 221 comatose patients were divided into three groups: out-of-hospital cardiac arrest, in-hospital cardiac arrest and others (i.e. patients with cardiac diagnoses other than cardiac arrest). Automated pupillometry was serially performed until discharge or death and pupil measurements were analysed using the neurological pupil index algorithm. We applied receiver operating characteristic curves in univariable and multivariable logistic regression models and a calculated Youden index identified neurological pupil index cut-off values at different specificities. Results: In out-of-hospital cardiac arrest patients higher neurological pupil index values were independently associated with lower 30-day mortality. The univariable model for 30-day mortality had an area under the curve of 0.87 and the multivariable model achieved an area under the curve of 0.94. The Youden index identified a neurological pupil index cut-off in out-of-hospital cardiac arrest patients of 2.40 for a specificity of 100%. For patients with in-hospital cardiac arrest and other cardiac diagnoses, we found no association between neurological pupil index values and 30-day mortality, and the univariable models showed poor predictive values. Conclusion: Automated infrared pupillometry has promising predictive value after out-of-hospital cardiac arrest, but poor predictive value in patients with in-hospital cardiac arrest or cardiac diagnoses unrelated to cardiac arrest. Our data suggest a possible neurological pupil index cut-off of 2.40 for poor outcome in out-of-hospital cardiac arrest patients.


Resuscitation ◽  
2010 ◽  
Vol 81 (2) ◽  
pp. S67
Author(s):  
A. Schober ◽  
A. Bojic ◽  
D. Hörburger ◽  
M. Stöckl ◽  
P. Stratil ◽  
...  

2022 ◽  
Author(s):  
Nilesh Anand Devanand ◽  
Mohammed Ishaq Ruknuddeen ◽  
Natalie Soar ◽  
Suzanne Edwards

Abstract Objective: To determine factors associated with withdrawal of life-sustaining therapy (WLST) in intensive care unit (ICU) patients following out-of-hospital cardiac arrest (OHCA).Methods: A retrospective review of ICU data from patient clinical records following OHCA was conducted from January 2010 to December 2015. Demographic features, cardiac arrest characteristics, clinical attributes and targeted temperature management were compared between patients with and without WLST. We dichotomised WLST into early (ICU length of stay <72 hours) and late (ICU length of stay ≥72 hours). Factors independently associated with WLST were determined by multivariable binary logistic regression using a backward elimination method, and results were depicted as odds ratios (OR) with 95% confidence intervals (CI).Results: The study selection criteria resulted in a cohort of 260 ICU patients post-OHCA, with a mean age of 58 years and the majority were males (178, 68%); 151 patients (58%) died, of which 145 (96%) underwent WLST, with the majority undergoing early WLST (89, 61%). Status myoclonus was the strongest independent factor associated with early WLST (OR 38.90, 95% CI 4.55–332.57; p < 0.001). Glasgow Coma Scale (GCS) motor response of <4 on day 3 post-OHCA was the strongest factor associated with delayed WLST (OR 91.59, 95% CI 11.66–719.18; p < 0.0001).Conclusion: The majority of deaths in ICU patients post-OHCA occurred following early WLST. Status myoclonus and a GCS motor response of <4 on day 3 post-OHCA are independently associated with WLST.


2021 ◽  
Vol 50 (1) ◽  
pp. 683-683
Author(s):  
Karthik Kailasam ◽  
Abhishek Bhardwaj ◽  
Justin Hanks ◽  
Tarik Hanane ◽  
Deborah Rathz ◽  
...  

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