Initial Rhythms and Outcomes for In-Hospital Cardiac Arrest in Kenya Presented By Dr. Mohamed Hasham Varwani 1 On behalf of the authors: Dr Mzee Ngunga 1, Prof Gerald Yonga 1, Dr Benjamin Wachira 1, Dr Justin Ezekowitz 2 1 Department of Medicine, Aga Khan University Hospital Nairobi 2 Faculty of Medicine & Dentistry - University of Alberta KCS Congress: Impact through collaboration CONTACT: Tel. +254 735 833 803 Email: kcardiacs@gmail.com Web: www.kenyacardiacs.org
Disclosures Sponsored by a competitive grant from Astra Zeneca Africa. Astra Zeneca had no role in the conduct of the study or analysis of the results.
Background Cardiac arrest is a catastrophic event that commonly results in death Shockable (VF and VT) or non-shockable rhythms (PEA or asystole) Little literature on cardiac arrest patterns and resuscitation dynamics in Sub-Saharan Africa Study in Uganda: dismal survival, with ROSC occurring in only 7.4%, and 24 hour survival of only 1.6% 1 Ocen et al; Prevalence, outcomes and factors associated with adult in hospital cardiac arrests in a low-income country tertiary hospital: a prospective observational study. BMC Emergency Medicine. 2015;15(1):1-6.
Objectives Provide insight into the cardiac rhythms and outcomes associated with In hospital cardiac arrests in Kenyan hospitals PRIMARY Determine the ECG rhythms documented by the first responder during inhospital cardiac arrests and its correlation to ROSC SECONDARY Response times to the cardiac arrest Pre-arrest observations - modified early warning score (MEWS) and correlation to ROSC
Methods Prospective, multicenter study, July 2014 and April 2016 Two private hospitals in Nairobi ( total inpatient capacity of 600 beds and 60 critical care beds) Public hospitals outside Nairobi (combined inpatient capacity of 600 beds, no critical care beds) Data captured by personnel attending to the resuscitation
ELIGIBLITY Inclusion Criteria: Patients (>=18) developing cardiac arrest in hospital (only initial arrest considered) Exclusion Criteria: DNR orders Post-surgical cardiac arrests Trauma patients pregnancy or puerperium associated
OUTCOME MEASURES Patient characteristics: demographic and clinical (charts) Pre-arrest observations 4 hours: MEWS Cardiac rhythm at the time of cardiac arrest Whether ROSC achieved Survival to discharge Response time (resuscitation team)
MEWS SCORE
ETHICAL APPROVAL Approved by the Aga Khan University Ethics Committee Waiver of consent was granted
Results Patients recruited N = 353 Private Hospitals N = 250 Public Hospitals N = 103 Over 2 years
Patient Characteristics Cardiac arrest, n = 353 Age years (Mean/SD) 58.6, 19.6 Male, % 53.5% Place of arrest, % Wards/Critical care 96% ER 4% Diagnosis at time of arrest, % Myocardial Infarction 11.1% Heart Failure 14.9% Pneumonia 28.5% TB 14.4% Liver Disease 9.3% Renal Disease 14.0% Stroke 7.7% Cancer 14.5% HIV/AIDS 22.6% Sepsis 28.9% Others 67.1%
MEWS, Time to CPR and Initial Arrest Rhythms Variable All patients, n = 353 Private hospital patients, n = 250 Public hospital patients, n = 103 p-value MEWS at time of arrest, median, IQR Mean time (recognition to commencement of CPR) mins Type of cardiac arrest, % 5.0 (3-7) 6.0 (4-8) 3.0 (1-5) 0.001 0.83 (0-26) 0.47 (0-10) 1.72 (0-25) Asystole 47.6 (n = 168) 35.2 (n = 88) 77.7 (n = 80) PEA 38.2 (n =135) 52.4 (n = 131) 3.9 (n = 4) VT 3.7 (n = 13) 5.2 (n = 13) 0.0 (n = 0) VF 1.7 (n = 6) 2.4 (n = 6) 0.0 (n = 0) Unknown 8.8 (n = 31) 4.8 (n = 12) 18.4 (n = 19)
Resuscitation outcomes and drugs used Variable All patients, n = 353 Private hospital patients, n = 250 Public hospital patients, n = 103 Patients with ROSC, % 29.2 (n = 103) 40.8 (n = 102) 1.0 (n = 1) Discharged alive, % 4.3 (n = 16) 6.0 (n = 15) 1% (n = 1) Medication given during code, % of patients Adrenaline 73.1 (n = 258 92.8 (n = 232) 25.2 (n = 26) Atropine 9.9 (n = 35) 11.6 ( n = 29) 5.8 (n = 6) Bicarbonate 19.3 (n = 68) 27.2 (n = 68) 0.0 (n = 0) Others 21.8 (n = 77) 29.2 (n = 73) 3.9 (n = 4)
Results of multivariate logistic regression analysis to predict ROSC Variable Condition p-values OR (95% CI) Age 60 years 0.239 1.37 (0.81, 2.31) Sex Male 0.047** 1.70 (1.00, 2.87) Time to resuscitation (CPR) > 3 minutes 0.231 0.65 (0.23, 2.77) MEWS High 0.233 1.55 (0.76, 3.16) Intermediate 0.923 0.96 (0.40, 2.30) Rhythm PEA 0.001 3.19 (1.85, 5.49) VT/VF 0.001 5.58 (2.02, 15.45)
DISCUSSION 1 st Prospective Kenyan Cardiac Arrest Study Public and Private Sectors Pre cardiac arrest observations (MEWS) Younger mean age 58.6 years (compared to the UK national inhospital cardiac arrest 73.9 years) 1 Nolan et al. Incidence and outcome of in-hospital cardiac arrest in the United Kingdom National Cardiac Arrest Audit. Resuscitation. 2014 2016/08/04;85(8):987-92
Heart Rythms Author, Year Ngunga, 2017 Country n Asystole PEA VT/VF Unknown Kenya 353 47.6% 38.2% 5.4% 8.8% Ko, 2015 Korea 210 17% 62% 14% 5% Bergum, 2014 Nolan, 2014 Norway 258 23% 48% 27% 2% UK 22,628 72.3% 16.9% 10.9%
ROSC and Survival post cardiac arrest Author, Year Country n ROSC Survival Ngunga, 2017 Kenya 353 29.2% 4.3% (discharge) Ocen, 2015 Uganda 190 7.4% 1.6% (24 hour) Ko, 2015 Korea 210 81.9% 34.7% (discharge) Bergum, 2014 Norway 258 66% 25% (discharge)
Public vs Private 250 - private hospitals, 103 - public hospital Mean time from recognition of cardiac arrest to commencement of CPR was 0.47minutes (IQR 0-10) in private hospitals, and 1.72 mins (0-25) in public hospitals ROSC in 40.8% (private hospitals) vs 1.0% (public hospitals) Disparity may represent difference in resources between public and private hospitals presence of resuscitation teams the location of the patient
Conclusions Most cardiac arrests in this study were associated with asystole and PEA VT/VF - minority of in hospital cardiac arrests in this study - highest likelihood of ROSC The mortality for cardiac arrest is high in this cohort
Limitations Overrepresentation of patients in the private hospitals and this may have skewed the results of the findings Limited resuscitation systems in public hospitals - many patients may not have been recruited into the study
Recommendations Training healthcare personnel in recognizing early warning signs, resuscitation protocols Systems for effective resuscitation dynamics in a resource-scare environment
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