Predictors of acute hospital mortality and length of stay in patients with new-onset atrial fibrillation: a first-hand experience from a medical emergency team response provider.

BACKGROUND: Atrial fibrillation (AF) occurs frequently following cardiothoracic surgery and treatment decisions are informed by evidence-based clinical guidelines. Outside this setting there are few data to guide clinical management. AIM: To describe the characteristics, management and outcomes of hospitalised adult patients with new-onset AF. METHODS: The medical emergency team (MET) database was utilised to identify patients who had a 'MET call' activated for tachycardia between 2015 and 2016. Patients with sinus tachycardia, pre-existing AF/atrial flutter or other known tachyarrhythmia were excluded. Primary outcomes were length of hospital stay and in-hospital mortality. RESULTS: New-onset AF was identified in 137 patients: 68 medically managed; 38 non-cardiothoracic post-operative; and 31 cardiothoracic post-operative. Mean age was 74 ± 11.6 years and 72 (53%) were male. Of 79 patients who underwent echocardiography, 80% had left atrial dilatation and 14% had reduced left ventricular ejection fraction (LVEF). Mean length of stay (LOS) was 12 days and in-hospital mortality rate was 11%. On multivariable analysis, the odds of death during acute hospitalisation was 7.4 times higher in patients with heart failure with reduced LVEF (odds ratio 7.4, 95% confidence interval (CI) 1.23-44.8, P = 0.028). Length of acute hospital stay increased by 36% if the duration of AF was longer than 48 h (beta coefficient 0.36, 95% CI -0.015 to 0.74, P = 0.059). CONCLUSION: Left ventricular systolic dysfunction in hospitalised patients with new-onset AF is associated with increased all-cause mortality whereas lower serum potassium levels are associated with an increased LOS. A prospective study is planned to compare outcomes based on in-hospital treatment strategies.

Development and internal validation of the multivariable CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) clinical risk prediction model.

BACKGROUND: Intensive care unit (ICU) outcome prediction models, such as Acute Physiology And Chronic Health Evaluation (APACHE), were designed in general critical care populations and their use in obstetric populations is contentious. The aim of the CIPHER (Collaborative Integrated Pregnancy High-dependency Estimate of Risk) study was to develop and internally validate a multivariable prognostic model calibrated specifically for pregnant or recently delivered women admitted for critical care. METHODS: A retrospective observational cohort was created for this study from 13 tertiary facilities across five high-income and six low- or middle-income countries. Women admitted to an ICU for more than 24 h during pregnancy or less than 6 weeks post-partum from 2000 to 2012 were included in the cohort. A composite primary outcome was defined as maternal death or need for organ support for more than 7 days or acute life-saving intervention. Model development involved selection of candidate predictor variables based on prior evidence of effect, availability across study sites, and use of LASSO (Least Absolute Shrinkage and Selection Operator) model building after multiple imputation using chained equations to address missing data for variable selection. The final model was estimated using multivariable logistic regression. Internal validation was completed using bootstrapping to correct for optimism in model performance measures of discrimination and calibration. RESULTS: Overall, 127 out of 769 (16.5%) women experienced an adverse outcome. Predictors included in the final CIPHER model were maternal age, surgery in the preceding 24 h, systolic blood pressure, Glasgow Coma Scale score, serum sodium, serum potassium, activated partial thromboplastin time, arterial blood gas (ABG) pH, serum creatinine, and serum bilirubin. After internal validation, the model maintained excellent discrimination (area under the curve of the receiver operating characteristic (AUROC) 0.82, 95% confidence interval (CI) 0.81 to 0.84) and good calibration (slope of 0.92, 95% CI 0.91 to 0.92 and intercept of -0.11, 95% CI -0.13 to -0.08). CONCLUSIONS: The CIPHER model has the potential to be a pragmatic risk prediction tool. CIPHER can identify critically ill pregnant women at highest risk for adverse outcomes, inform counseling of patients about risk, and facilitate bench-marking of outcomes between centers by adjusting for baseline risk.

Inappropriate continuation of stress ulcer prophylaxis beyond the intensive care setting.

OBJECTIVE: To determine how frequently stress ulcer prophylaxis (SUP) medications prescribed in the intensive care unit are inappropriately continued on the ward and on hospital discharge. DESIGN: Retrospective cohort study; chart review. SETTING: Two Australian ICUs: one tertiary centre and one metropolitan centre. PARTICIPANTS: We included 387 adult, non-pregnant patients who were admitted to the ICU between 1 February 2011 and 31 March 2011 and who survived to hospital discharge. MAIN OUTCOME MEASURES: Rate of unnecessary continuation of ICU-prescribed SUP medications on the ward and on discharge from hospital. RESULTS: While in the ICU, 329 of the 387 patients (85%) were prescribed SUP medications. Of the 233 patients who had not been taking acid-suppressive medications before admission to the ICU, 190 were prescribed SUP medications in the ICU. Of these 190 patients, most (63%) had their SUP continued in the ward without any obvious indication, and many (39%) had their SUP medications inappropriately continued on discharge from hospital. CONCLUSIONS: SUP medications commenced in ICU are frequently continued unnecessarily, both in the wards and hospital discharge.