Independent Risk Factors for Sepsis-Associated Cardiac Arrest in Patients with Septic Shock.
Won Soek YangYoun-Jung KimSeung Mok RyooWon Young KimPublished in: International journal of environmental research and public health (2021)
The clinical characteristics and laboratory values of patients with septic shock who experience in-hospital cardiac arrest (IHCA) have not been well studied. This study aimed to evaluate the prevalence of IHCA after admission into the emergency department and to identify the factors that increase the risk of IHCA in septic shock patients. This observational cohort study used a prospective registry of septic shock patients and was conducted at the emergency department of a university-affiliated hospital. The data of 887 adult (age ≥ 18 years) septic shock (defined using the Sepsis-3 criteria) patients who were treated with a protocol-driven resuscitation bundle therapy and were admitted to the intensive care unit between January 2010 and September 2018 were analyzed. The primary endpoint was the occurrence of sepsis-associated cardiac arrest. The patient mean age was 65 years, and 61.8% were men. Sepsis-associated cardiac arrest occurred in 25.3% of patients (n = 224). The 28-day survival rate after cardiac arrest was 6.7%. Multivariate logistic regression identified chronic pulmonary disease (odds ratio (OR) 2.06), hypertension (OR 0.48), unknown infection source (OR 1.82), a hepatobiliary infection source (OR 0.25), C-reactive protein (OR 1.03), and serum lactate level 6 h from shock (OR 1.34). Considering the high mortality rate of sepsis-associated cardiac arrest after cardiopulmonary resuscitation, appropriate monitoring is required in septic shock patients with major risk factors for IHCA.
Keyphrases
- septic shock
- cardiac arrest
- cardiopulmonary resuscitation
- emergency department
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- blood pressure
- peritoneal dialysis
- type diabetes
- healthcare
- stem cells
- risk factors
- acute kidney injury
- machine learning
- bone marrow
- acute care
- free survival
- replacement therapy
- patient reported outcomes