Impact of atrial fibrillation in critically ill patients admitted to a stepdown unit

Prevalence of new-onset atrial fibrillation in hospitalized patients with community-acquired pneumonia: a systematic review and meta-analysis

Community-acquired pneumonia (CAP) is a common lower respiratory tract infection, often complicated by cardiovascular events, including cardiac arrhythmias. New-onset atrial fibrillation (newAF) has been associated with increased mortality in CAP patients, especially in those critically ill; however, limited data on the prevalence of newAF in patients with CAP are available. We aim to estimate the pooled prevalence of newAF and its impact on adverse outcomes in patients with CAP, through a systematic review and meta-analysis. MEDLINE and EMBASE were systematically searched from inception to 27 January 2022. All studies reporting the prevalence of newAF in CAP patients were included and all-cause mortality was extracted when available. The pooled prevalence of newAF, 95% Confidence Intervals (CI), and 95% Prediction Intervals (PI) were computed. The inconsistency index (I2) was calculated to measure heterogeneity. Subgroup analyses were also performed. A protocol for this study was registered on PROSPERO (CRD42022307422). Among 7,655 records retrieved, 10 studies were included, with a total of 280,589 CAP patients. Pooled prevalence of newAF in CAP patients was 7.6% (95% CI 6.4-9.0%, 95% PI 4.3-13.1%, I2 = 95%). Subgroup analyses showed no significant differences according to geographical location or study design. Patients with newAF had a higher risk of mortality among the studies included in the systematic review. NewAF is a common complication, occurring in 7.6% of CAP patients, with prediction intervals suggesting an even higher burden. CAP patients who develop newAF during hospitalization may be at higher risk of mortality in both short- and long-term follow-up.

Implementation of EHMRG Risk Model in an Italian Population of Elderly Patients with Acute Heart Failure

Acute heart failure (AHF) is a cardiac emergency with an increasing incidence, especially among elderly patients. The Emergency Heart failure Mortality Risk Grade (EHMRG) has been validated to assess the 7-days AHF mortality risk, suggesting the management of patients admitted to an emergency department (ED). EHMRG has never been implemented in Italian ED nor among elderly patients. We aimed to assess EHMRG score accuracy in predicting in-hospital death in a retrospective cohort of elderly subjects admitted for AHF from the ED to an Internal Medicine Department. We enrolled, in a 24-months timeframe, all the patients admitted to an Internal Medicine Department from ED for AHF. We calculated the EHMRG score, subdividing patients into six categories, and assessing in-hospital mortality and length of stay. We evaluated EHMRG accuracy with ROC curve analysis and survival with Kaplan−Meier and Cox models. We collected 439 subjects, with 45 in-hospital deaths (10.3%), observing a significant increase of in-hospital death along with EHMRG class, from 0% (class 1) to 7.7% (class 5b; p < 0.0001). EHMRG was fairly accurate in the whole cohort (AUC: 0.75; 95%CI: 0.68−0.83; p < 0.0001), with the best cutoff observed at >103 (Se: 71.1%; Sp: 72.8%; LR+: 2.62; LR-: 0.40; PPV: 23.0%; NPV: 95.7%), but performed better considering the events in the first seven days of admission (AUC: 0.83; 95%; CI: 0.75−0.91; p < 0.0001). In light of our observations, EHMRG can be useful also for the Italian emergency system to predict the risk of short-term mortality for AHF among elderly patients. EHMRG performance was better in the first seven days but remained acceptable when considering the whole period of hospitalization.

Improving the EHMRG Prognostic Evaluation of Acute Heart Failure with TAPSE/PASp: A Sequential Approach

The Emergency Heart Failure Mortality Risk Grade (EHMRG) can predict short-term mortality in patients admitted for acute heart failure (AHF) in the emergency department (ED). This paper aimed to evaluate if TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can improve in-hospital death prediction in patients at moderate-to-high risk, according to EHMRG score classification. From 1 January 2018 to 30 December 2019, we retrospectively enrolled all the consecutive subjects admitted to our Internal Medicine Department for AHF from the ED. We performed bedside echocardiography within the first 24 h of admission. We evaluated EHMRG and NYHA in the ED, days of admission in Internal Medicine, and in-hospital mortality. We assessed cutoffs with ROC curve analysis and survival with Kaplan–Meier and Cox regression. We obtained a cohort of 439 subjects; 10.3% underwent in-hospital death. Patients with normal TAPSE/PASp in EHMRG Classes 4, 5a, and 5b had higher survival rates (100%, 100%, and 94.3%, respectively), while subjects with pathologic TAPSE/PASp had lower survival rates (81.8%, 78.3%, and 43.4%, respectively) (p < 0.0001, log-rank test). TAPSE/PASp, an echocardiographic marker of ventricular desynchronization, can further stratify the risk of in-hospital death evaluated by EHMRG.

Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation

Critically ill patients affected by atrial fibrillation are at high risk of adverse events: however, the actual risk stratification models for haemorrhagic and thrombotic events are not validated in a critical care setting. With this paper we aimed to identify, adopting topological data analysis, the risk factors for therapeutic failure (in-hospital death or intensive care unit transfer), the in-hospital occurrence of stroke/TIA and major bleeding in a cohort of critically ill patients with pre-existing atrial fibrillation admitted to a stepdown unit; to engineer newer prediction models based on machine learning in the same cohort. We selected all medical patients admitted for critical illness and a history of pre-existing atrial fibrillation in the timeframe 01/01/2002–03/08/2007. All data regarding patients’ medical history, comorbidities, drugs adopted, vital parameters and outcomes (therapeutic failure, stroke/TIA and major bleeding) were acquired from electronic medical records. Risk factors for each outcome were analyzed adopting topological data analysis. Machine learning was used to generate three different predictive models. We were able to identify specific risk factors and to engineer dedicated clinical prediction models for therapeutic failure (AUC: 0.974, 95%CI: 0.934–0.975), stroke/TIA (AUC: 0.931, 95%CI: 0.896–0.940; Brier score: 0.13) and major bleeding (AUC: 0.930:0.911–0.939; Brier score: 0.09) in critically-ill patients, which were able to predict accurately their respective clinical outcomes. Topological data analysis and machine learning techniques represent a concrete viewpoint for the physician to predict the risk at the patients’ level, aiding the selection of the best therapeutic strategy in critically ill patients affected by pre-existing atrial fibrillation.

The value of admission Troponin I to predict outcomes in suspected infections in elderly patients admitted in Internal Medicine: results from the SOFA-T collaboration, a multi-center study

Elderly patients affected by suspected infection and declining clinical conditions can be admitted to stepdown units (SDU), but a risk stratification is necessary to optimize their management. Admission troponin I (aTnI) has a prognostic role, however, one of the most commonly used stratification tools, the Sequential Organ Failure Assessment score (SOFA), does not consider myocardial injury. With this paper, we aimed to evaluate the prognostic accuracy of a new score, named SOFA-T, considering both SOFA score and aTnI in a cohort of elderly patients admitted to the stepdown beds of two Internal Medicine departments. Patients aged > 65 years admitted in SDU of two different hospitals of the same region in a 12-months timeframe were retrospectively assessed obtaining age, sex, days of admission, in-hospital death, SOFA, aTnI and comorbidities. The best aTnI cutoff for in-hospital death was calculated with ROC curve analysis; dichotomous variables were compared with chi-squared test; continuous variables were compared with t test or Mann-Whitney test. We obtained a cohort of 390 patients. The best aTnI cutoff was 0.31 ng/ml: patients with increased aTnI had higher risk of in-hospital death (OR: 1.834; 95% CI 1.160-2.900; p = 0.009), and higher SOFA (6.81 ± 2.71 versus 5.97 ± 3.10; p = 0.010). Adding aTnI to SOFA increased significantly the area under the curve (AUC_SOFA = 0.68; 95% CI 0.64-0.73; AUC_SOFA-T = 0.71; 95% CI 0.65-0.76; p = 0.0001), with a slight improvement of the prognostic performance. In elderly patients admitted to SDU for suspected infection, sepsis or septic shock, aTnI slightly improves the accuracy of SOFA score of the in-hospital death prediction.

A Systematic Review of Anticoagulation Strategies for Patients with Atrial Fibrillation in Critical Care

BACKGROUND

 Atrial fibrillation (AF) is the most common cardiac arrhythmia in critically ill patients. There is a paucity of data assessing the impact of anticoagulation strategies on clinical outcomes for general critical care patients with AF. Our aim was to assess the existing literature to evaluate the effectiveness of anticoagulation strategies used in critical care for AF.

METHODS

 A systematic literature search was conducted using MEDLINE, EMBASE, CENTRAL, and PubMed databases. Studies reporting anticoagulation strategies for AF in adults admitted to a general critical care setting were assessed for inclusion.

RESULTS

 Four studies were selected for data extraction. A total of 44,087 patients were identified with AF, of which 17.8 to 49.4% received anticoagulation. The reported incidence of thromboembolic events was 0 to 1.4% for anticoagulated patients, and 0 to 1.3% in nonanticoagulated patients. Major bleeding events were reported in three studies and occurred in 7.2 to 8.6% of the anticoagulated patients and in up to 7.1% of the nonanticoagulated patients.

CONCLUSION

 There was an increased incidence of major bleeding events in anticoagulated patients with AF in critical care compared with nonanticoagulated patients. There was no significant difference in the incidence of reported thromboembolic events within studies between patients who did and did not receive anticoagulation. However, the outcomes reported within studies were not standardized, therefore, the generalizability of our results to the general critical care population remains unclear. Further data are required to facilitate an evidence-based assessment of the risks and benefits of anticoagulation for critically ill patients with AF.