In-Hospital Cardiac Arrest: Effect of the Performance of Code-Blue Team on Patient Survival

2012 ◽  
Vol 43 (5) ◽  
pp. 945
Author(s):  
H.J. Choi ◽  
G.T. Kim ◽  
S.B. Oh ◽  
H.S. Park ◽  
Y.H. Oh
2012 ◽  
Vol 42 (1) ◽  
pp. 74-78 ◽  
Author(s):  
Sultana A. Qureshi ◽  
Terence Ahern ◽  
Ryan O’Shea ◽  
Lorien Hatch ◽  
Sean O. Henderson

2020 ◽  
Vol 31 (4) ◽  
pp. 401-409
Author(s):  
Roberta Kaplow ◽  
Pam Cosper ◽  
Ray Snider ◽  
Martha Boudreau ◽  
John D. Kim ◽  
...  

Background Sudden cardiac arrest is a major cause of death worldwide. Performance of prompt, high-quality cardiopulmonary resuscitation improves patient outcomes. Objectives To evaluate the association between patient survival of in-hospital cardiac arrest and 2 independent variables: adherence to resuscitation guidelines and patient severity of illness, as indicated by the number of organ supportive therapies in use before cardiac arrest. Methods An observational study was conducted using prospectively collected data from a convenience sample. Cardiopulmonary arrest forms and medical records were evaluated at an academic medical center. Adherence to resuscitation guidelines was measured with the ZOLL R Series monitor/defibrillator using RescueNet Code Review software. The primary outcome was patient survival. Results Of 200 cases, 37% of compressions were in the recommended range for rate (100-120/min) and 63.9% were in range for depth. The average rate was above target 55.7% of the time. The average depth was above and below target 1.4% and 34.7% of the time, respectively. Of the 200 patients, 125 (62.5%) attained return of spontaneous circulation. Of those, 94 (47%) were alive 24 hours after resuscitation. Fifty patients (25%) were discharged from the intensive care unit alive and 47 (23.5%) were discharged from the hospital alive. Conclusions These exploratory data reveal overall survival rates similar to those found in previous studies. The number of pauses greater than 10 seconds during resuscitation was the one consistent factor that impacted survival. Despite availability of an audiovisual feedback system, rescuers continue to perform compressions that are not at optimal rate and depth.


Resuscitation ◽  
2020 ◽  
Vol 157 ◽  
pp. 149-155
Author(s):  
Faheem Ahmed Khan ◽  
Ting Lyu ◽  
Eng Kiang Lee ◽  
Shekhar Dhanvijay ◽  
Amit Kansal ◽  
...  

Circulation ◽  
2009 ◽  
Vol 119 (19) ◽  
pp. 2597-2605 ◽  
Author(s):  
Alex G. Garza ◽  
Matthew C. Gratton ◽  
Joseph A. Salomone ◽  
Daniel Lindholm ◽  
James McElroy ◽  
...  

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_4) ◽  
Author(s):  
Kristopher Torossian ◽  
Mina Altwail ◽  
Ryan Paternoster ◽  
Eddie Ford ◽  
Robert A Swor

Background: Bystander actions upon witnessing a cardiac arrest are crucial to improving patient survival. Bystander perceptions and actions when witnessing a cardiac arrest are complex and not well understood. Our study has three primary aims: 1) To characterize CA bystanders demographics, 2) To understand the events from patient collapse until EMS arrival, with a focus on telecommunicator or dispatcher-assisted CPR (T-CPR), and 3) Bystander knowledge/ training in CPR and their actions at the time of CA. Methods: This is a prospective observational study conducted on bystanders of out of hospital cardiac arrests (OHCA) serviced by EMS agencies in southeast Michigan. OHCA patients were identified from 3/2018- 12/2019, and bystanders of these events surveyed. Surveys were mailed to non-medical addresses with an introductory letter and paper survey. A phone interview was conducted to describe bystander demographics, events from collapse to EMS arrival, and their actions including CPR performance. We inquired regarding telecommunicator CPR instructions (T-CPR), and if CPR was not performed what were the barriers. Results: During our study period, 126 surveys were mailed, and of these 47 bystander surveys were completed. The majority of events occurred in private homes (37/47,78.7%). Few patients (10, 21.2%) survived to discharge. The bystander and patient age were (mean, range)were 62.9 (30-91 ) and 69.3 (30-100) respectively. The majority were female 27/47(57.4%), most 43/47 (91.4%) knew the patient and were family (34/47,72.3%). Bystanders knew the patient a median(range) of 32 (0-68) years. A majority of bystanders (31/47,66.0%) had CPR training and 19 performed CPR. Of the 14/47 (27.8%) that received T-CPR instructions, 9 performed CPR. CPR trained bystanders that did not perform CPR(8/31), identified panic, assessment barriers and physical reasons for not performing CPR. Conclusion: In this preliminary work, we identify that bystanders to OHCA are most often family, of similar age to the patient and knew the patient for decades. CPR educational programs should prepare trainees to know that they may well respond to loved ones. Further researcher characterizing bystanders and their actions are needed to improve cardiac arrest outcomes.


Entropy ◽  
2018 ◽  
Vol 20 (8) ◽  
pp. 591 ◽  
Author(s):  
Beatriz Chicote ◽  
Unai Irusta ◽  
Elisabete Aramendi ◽  
Raúl Alcaraz ◽  
José Rieta ◽  
...  

Optimal defibrillation timing guided by ventricular fibrillation (VF) waveform analysis would contribute to improved survival of out-of-hospital cardiac arrest (OHCA) patients by minimizing myocardial damage caused by futile defibrillation shocks and minimizing interruptions to cardiopulmonary resuscitation. Recently, fuzzy entropy (FuzzyEn) tailored to jointly measure VF amplitude and regularity has been shown to be an efficient defibrillation success predictor. In this study, 734 shocks from 296 OHCA patients (50 survivors) were analyzed, and the embedding dimension (m) and matching tolerance (r) for FuzzyEn and sample entropy (SampEn) were adjusted to predict defibrillation success and patient survival. Entropies were significantly larger in successful shocks and in survivors, and when compared to the available methods, FuzzyEn presented the best prediction results, marginally outperforming SampEn. The sensitivity and specificity of FuzzyEn were 83.3% and 76.7% when predicting defibrillation success, and 83.7% and 73.5% for patient survival. Sensitivities and specificities were two points above those of the best available methods, and the prediction accuracy was kept even for VF intervals as short as 2s. These results suggest that FuzzyEn and SampEn may be promising tools for optimizing the defibrillation time and predicting patient survival in OHCA patients presenting VF.


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