BACKGROUND: Cardiac etiologies arrest accounts for almost half of all in-hospital cardiac arrest (IHCA), and previous studies have shown that the location of IHCA is an important factor affecting patient outcomes. The aim was to compare the characteristics, causes and outcomes of cardiovascular disease in patients suffering IHCA from different departments of Fuwai hospital in Beijing, China.
METHODS: We included patients who were resuscitated after IHCA at Fuwai hospital between March 2017 and August 2022. We categorized the departments where cardiac arrest occurred as cardiac surgical or non-surgical units. Independent predictors of in-hospital survival were assessed by logistic regression.
RESULTS: A total of 119 patients with IHCA were analysed, 58 (48.7%) patients with cardiac arrest were in non-surgical units, and 61 (51.3%) were in cardiac surgical units. In non-surgical units, acute myocardial infarction/cardiogenic shock (48.3%) was the main cause of IHCA. Cardiac arrest in cardiac surgical units occurred mainly in patients who were planning or had undergone complex aortic replacement (32.8%). Shockable rhythms (ventricular fibrillation/ventricular tachycardia) were observed in approximately one-third of all initial rhythms in both units. Patients who suffered cardiac arrest in cardiac surgical units were more likely to return to spontaneous circulation (59.0% vs. 24.1%) and survive to hospital discharge (40.0% vs. 10.2%). On multivariable regression analysis, IHCA in cardiac surgical units (OR 5.39, 95% CI 1.90-15.26) and a shorter duration of resuscitation efforts (≤ 30 min) (OR 6.76, 95% CI 2.27-20.09) were associated with greater survival rate at discharge.
CONCLUSIONS: IHCA occurring in cardiac surgical units and a duration of resuscitation efforts less than 30 min were associated with potentially increased rates of survival to discharge.

OBJECTIVE: To describe the results of the application of a Machine Learning (ML) model to predict in-hospital cardiac arrests (ICA) 24 hours in advance in the hospital wards.
METHODS: Retrospective observational cohort study.
METHODS: Hospital Wards.
METHODS: Data were extracted from the hospital\'s Electronic Health Record (EHR). The resulting database contained a total of 750 records corresponding to 620 different patients (370 patients with ICA and 250 control), between may 2009 and december 2021.
METHODS: No.
METHODS: As predictors of ICA, a set of 28 variables including personal history, vital signs and laboratory data was employed.
METHODS: For the early prediction of ICA, predictive models based on the following ML algorithms and using the mentioned variables, were developed and compared: K Nearest Neighbours, Support Vector Machine, Multilayer Perceptron, Random Forest, Gradient Boosting and Custom Ensemble of Gradient Boosting estimators (CEGB).
METHODS: Model training and evaluation was carried out using cross validation. Among metrics of performance, accuracy, specificity, sensitivity and AUC were estimated.
RESULTS: The best performance was provided by the CEGB model, which obtained an AUC = 0.90, a specificity = 0.84 and a sensitivity = 0.81. The main variables with influence to predict ICA were level of consciousness, haemoglobin, glucose, urea, blood pressure, heart rate, creatinine, age and hypertension, among others.
CONCLUSIONS: The use of ML models could be of great support in the early detection of ICA, as the case of the CEGB model endorsed, which enabled good predictions of ICA.

Introduction: Cardiac arrests are traditionally classified according to the setting in which they occur, including out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA). However, cardiac arrests that occur in the emergency department (EDCA) could constitute a third category, due to the peculiar characteristics of the emergency department (ED). In recent years, the need to study EDCAs separately from other intra-hospital events has emerged. The aim of this study was to describe the characteristics and outcomes of a cohort of patients experiencing EDCA in an Italian hospital over a 14-year period. Methods: This was a single-centre retrospective observational study conducted in the ED of the Santa Croce e Carle Hospital in Cuneo, Italy. All adult patients who experienced EDCA between 1 January 2010 and 30 June 2023 were included. OHCA patients, those arriving in the ED with on-going resuscitation measures, patients with EDCA not undergoing resuscitation, and patients with post-traumatic cardiac arrest were excluded from the study. The main outcome of the study was survival at hospital discharge with a favourable neurological outcome. Results: 350 cases of EDCA were included. The median age was 78 (63-85) years, and the median Charlson Comorbidity Index score was 5 (3-6). A total of 35 patients (10%) survived to hospital discharge with a cerebral performance category (CPC) Score of 1-2; survival in the ED was 28.3%. The causes of cardiac arrests were identified in 212 cases (60.6%) and included coronary thrombosis (35%), hypoxia (22%), hypovolemia (17%), pulmonary embolism (11%), metabolic (8%), cardiac tamponade (4%), toxins (2%) and hypothermia (1%). Variables associated with survival with a favourable neurological outcome were young age, a lower Charlson Comorbidity Index, coronary thrombosis as the primary EDCA cause, and shockable presenting rhythm; however, only the latter was associated with the outcome in a multivariate age-weighted model. Conclusions: In a cohort of patients with EDCA over a period of more than a decade, the most frequent cause identified was coronary thrombosis; 10% of patients survived with a good neurological status, and the only factor associated with the best prognosis was presenting a shockable rhythm. EDCA should be considered an independent category in order to fully understand its characteristics and outcomes.

BACKGROUND: Extracorporeal cardiopulmonary resuscitation (ECPR) is an alternative method for patients with reversible causes of cardiac arrest (CA) after conventional cardiopulmonary resuscitation (CCPR). However, cardiopulmonary resuscitation (CPR) duration during ECPR can vary due to multiple factors. Healthcare providers need to understand these factors to optimize the resuscitation process and improve outcomes. The aim of this study was to examine the different variables impacting the duration of CPR in patients undergoing ECPR.
METHODS: This retrospective, single-center, observational study was conducted on adult patients who underwent ECPR due to in-hospital CA (IHCA) or out-of-hospital CA (OHCA) at Hamad General Hospital (HGH), the tertiary governmental hospital of Qatar, between February 2016 and March 2020. Univariate and multivariate binary logistic regression analyses were performed to identify the prognostic factors associated with CPR duration, including demographic and clinical variables, as well as laboratory tests.
RESULTS: The mean ± standard division age of the 48 participants who underwent ECPR was 41.50 ± 13.15 years, and 75% being male. OHCA and IHCA were reported in 77.1% and 22.9% of the cases, respectively. The multivariate analysis revealed that several factors were significantly associated with an increased CPR duration: higher age (OR: 1.981, 95%CI: 1.021-3.364, P = 0.025), SOFA score (OR: 3.389, 95%CI: 1.289-4.911, P = 0.013), presence of comorbidities (OR: 3.715, 95%CI: 1.907-5.219, P = 0.026), OHCA (OR: 3.715, 95%CI: 1.907-5.219, P = 0.026), and prolonged collapse-to-CPR time (OR: 1.446, 95%CI:1.092-3.014, P = 0.001). Additionally, the study found that the initial shockable rhythm was inversely associated with the duration of CPR (OR: 0.271, 95%CI: 0.161-0.922, P = 0.045). However, no significant associations were found between laboratory tests and CPR duration.
CONCLUSIONS: These findings suggest that age, SOFA score, comorbidities, OHCA, collapse-to-CPR time, and initial shockable rhythm are important factors influencing the duration of CPR in patients undergoing ECPR. Understanding these factors can help healthcare providers better predict and manage CPR duration, potentially improving patient outcomes. Further research is warranted to validate these findings and explore additional factors that may impact CPR duration in this population.

UNASSIGNED: Although early detection of patients\' deterioration may improve outcomes, most of the detection criteria use on-the-spot values of vital signs. We investigated whether adding trend values over time enhanced the ability to predict adverse events among hospitalized patients.
UNASSIGNED: Patients who experienced adverse events, such as unexpected cardiac arrest or unplanned ICU admission were enrolled in this retrospective study. The association between the events and the combination of vital signs was evaluated at the time of the worst vital signs 0-8 hours before events (near the event) and at 24-48 hours before events (baseline). Multivariable logistic analysis was performed, and the area under the receiver operating characteristic curve (AUC) was used to assess the prediction power for adverse events among various combinations of vital sign parameters.
UNASSIGNED: Among 24,509 in-patients, 54 patients experienced adverse events(cases) and 3,116 control patients eligible for data analysis were included. At the timepoint near the event, systolic blood pressure (SBP) was lower, heart rate (HR) and respiratory rate (RR) were higher in the case group, and this tendency was also observed at baseline. The AUC for event occurrence with reference to SBP, HR, and RR was lower when evaluated at baseline than at the timepoint near the event (0.85 [95%CI: 0.79-0.92] vs. 0.93 [0.88-0.97]). When the trend in RR was added to the formula constructed of baseline values of SBP, HR, and RR, the AUC increased to 0.92 [0.87-0.97].
UNASSIGNED: Trends in RR may enhance the accuracy of predicting adverse events in hospitalized patients.

OBJECTIVE: This study aimed to identify factors associated with neurological and disability outcomes in patients who underwent ECMO following cardiac arrest.
METHODS: This retrospective, single-center, observational study included adult patients who received ECMO treatment for in-hospital cardiac arrest (IHCA) or out-of-hospital cardiac arrest (OHCA) between February 2016 and March 2020. Factors associated with neurological and disability outcomes in these patients who underwent ECMO were assessed.
METHODS: Hamad General Hospital, Qatar.
METHODS: Neurological disability outcomes were assessed using the Modified Rankin Scale (mRS) and the Cerebral Performance Category (CPC) scale.
RESULTS: Among the 48 patients included, 37 (77 %) experienced OHCA, and 11 (23 %) had IHCA. The 28-day survival rate was 14 (29.2 %). Of the survivors, 9 (64.3 %) achieved a good neurological outcome, while 5 (35.7 %) experienced poor neurological outcomes. Regarding disability, 5 (35.7 %) of survivors had no disability, while 9 (64.3 %) had some form of disability. The results showed significantly shorter median time intervals in minutes, including collapse to cardiopulmonary resuscitation (CPR) (3 vs. 6, P = 0.001), CPR duration (12 vs. 35, P = 0.001), CPR to extracorporeal cardiopulmonary resuscitation (ECPR) (20 vs. 40, P = 0.001), and collapse-to-ECPR (23 vs. 45, P = 0.001), in the good outcome group compared to the poor outcome group.
CONCLUSIONS: This study emphasizes the importance of minimizing the time between collapse and CPR/ECMO initiation to improve neurological outcomes and reduce disability in cardiac arrest patients. However, no significant associations were found between outcomes and other demographic or clinical variables in this study. Further research with a larger sample size is needed to validate these findings.
CONCLUSIONS: The study underscores the significance of reducing the time between collapse and the initiation of CPR and ECMO. Shorter time intervals were associated with improved neurological outcomes and reduced disability in cardiac arrest patients.

BACKGROUND: The impact of the chronological sequence of events, including cardiac arrest (CA), initial cardiopulmonary resuscitation (CPR), return of spontaneous circulation (ROSC), and extracorporeal cardiopulmonary resuscitation (ECPR) implementation, on clinical outcomes in patients with both out-of-hospital cardiac arrest (OHCA) and in-hospital cardiac arrest (IHCA), is still not clear. The aim of this study was to investigate the prognostic effects of the time interval from collapse to start of CPR (no-flow time, NFT) and the time interval from start of CPR to implementation of ECPR (low-flow time, LFT) on patient outcomes under Extracorporeal Membrane Oxygenation (ECMO).
METHODS: This single-center, retrospective observational study was conducted on 48 patients with OHCA or IHCA who underwent ECMO at Hamad General Hospital (HGH), the tertiary governmental hospital of Qatar, between February 2016 and March 2020. We investigated the impact of prognostic factors such as NFT and LFT on various clinical outcomes following cardiac arrest, including 24-hour survival, 28-day survival, CPR duration, ECMO length of stay (LOS), ICU LOS, hospital LOS, disability (assessed using the modified Rankin Scale, mRS), and neurological status (evaluated based on the Cerebral Performance Category, CPC) at 28 days after the CA.
RESULTS: The results of the adjusted logistic regression analysis showed that a longer NFT was associated with unfavorable clinical outcomes. These outcomes included longer CPR duration (OR: 1.779, 95%CI: 1.218-2.605, P = 0.034) and decreased survival rates for ECMO at 24 h (OR: 0.561, 95%CI: 0.183-0.903, P = 0.009) and 28 days (OR: 0.498, 95%CI: 0.106-0.802, P = 0.011). Additionally, a longer LFT was found to be associated only with a higher probability of prolonged CPR (OR: 1.818, 95%CI: 1.332-3.312, P = 0.006). However, there was no statistically significant connection between either the NFT or the LFT and the improvement of disability or neurologically favorable survival after 28 days of cardiac arrest.
CONCLUSIONS: Based on our findings, it has been determined that the NFT is a more effective predictor than the LFT in assessing clinical outcomes for patients with OHCA or IHCA who underwent ECMO. This understanding of their distinct predictive abilities enables medical professionals to identify high-risk patients more accurately and customize their interventions accordingly.

BACKGROUND: The 2022 AHA/ACC/HFSA guidelines for the management of heart failure (HF) makes therapeutic recommendations based on HF status. We investigated whether the prognosis of in-hospital cardiac arrest (IHCA) could be stratified by HF stage and left ventricular ejection fraction (LVEF).
METHODS: This single-center retrospective study analyzed the data of patients who experienced IHCA between 2005 and 2020. Based on admission diagnosis, past medical records, and pre-arrest echocardiography, patients were classified into general IHCA, at-risk for HF, pre-HF, HF with preserved ejection fraction (HFpEF), and HF with mildly reduced ejection fraction or HF with reduced ejection fraction (HFmrEF-or-HFrEF) groups.
RESULTS: This study included 2,466 patients, including 485 (19.7%), 546 (22.1%), 863 (35.0%), 342 (13.9%), and 230 (9.3%) patients with general IHCA, at-risk for HF, pre-HF, HFpEF, and HFmrEF-or-HFrEF, respectively. A total of 405 (16.4%) patients survived to hospital discharge, with 228 (9.2%) patients achieving favorable neurological recovery. Multivariable logistic regression analysis indicated that pre-HF and HFpEF were associated with better neurological (pre-HF, OR: 2.11, 95% confidence interval [CI]: 1.23-3.61, p = 0.006; HFpEF, OR: 1.90, 95% CI: 1.00-3.61, p = 0.05) and survival outcomes (pre-HF, OR: 2.00, 95% CI: 1.34-2.97, p < 0.001; HFpEF, OR: 1.91, 95% CI: 1.20-3.05, p = 0.007), compared with general IHCA.
CONCLUSIONS: HF stage and LVEF could stratify patients with IHCA into different prognoses. Pre-HF and HFpEF were significantly associated with favorable neurological and survival outcomes after IHCA. Further studies are warranted to investigate whether HF status-directed management could improve IHCA outcomes.

No established predictive or risk classification tool exists for the neurological outcomes of post-cardiac arrest syndrome (PCAS) in patients with in-hospital cardiac arrest (IHCA). This study aimed to investigate whether the revised post-cardiac arrest syndrome for therapeutic hypothermia score (rCAST), which was developed to estimate the prognosis of PCAS patients with out-of-hospital cardiac arrest (OHCA), was applicable to patients with IHCA. A retrospective, multicenter observational study of 140 consecutive adult IHCA patients admitted to three intensive care units. The area under the receiver operating characteristic curves (AUCs) of the rCAST for poor neurological outcome and mortality at 30 days were 0.88 (0.82-0.93) and 0.83 (0.76-0.89), respectively. The sensitivity and specificity of the risk classification according to rCAST for poor neurological outcomes were 0.90 (0.83-0.96) and 0.67 (0.55-0.79) for the low, 0.63 (0.54-0.74) and 0.67 (0.55-0.79) for the moderate, and 0.27 (0.17-0.37) and 1.00 (1.00-1.00) for the high-severity grades. All 22 patients classified with a high-severity grade showed poor neurological outcomes. The rCAST showed excellent predictive accuracy for neurological prognosis in patients with PCAS after IHCA. The rCAST may be useful as a risk classification tool for PCAS after IHCA.

OBJECTIVE: We sought to investigate the relationship between mechanical cardiopulmonary resuscitation (CPR) during in-hospital cardiac arrest and survival to hospital discharge.
METHODS: Utilizing the prospectively collected American Heart Association\'s Get With The Guidelines database, we performed an observational study. Data from 153 institutions across the United States were reviewed with a total of 351,125 patients suffering cardiac arrest between 2011 and 2019 were screened. After excluding patients with cardiac arrests lasting less than 5 minutes, and patients who had incomplete data, a total of 111,143 patients were included. Our primary exposure was mechanical vs. manual CPR, and the primary outcome was survival to hospital discharge. Multivariate logistic regression models and propensity weighted analyses were used.
RESULTS: 11.8% of patients who received mechanical CPR survived to hospital discharge versus 16.9% in the manual CPR group. Patients who received mechanical CPR had a lower probability of survival to discharge compared to patients who received manual CPR (OR 0.66 95% CI 0.58-0.75; p < 0.001). This association persisted with multi-variable adjustment (OR 0.57 95% CI 0.46-0.70, p < 0.0001) and propensity weighted analysis (OR 0.68 95% CI 0.44-0 0.92, p < 0.0001). Mechanical CPR was associated with decrease likelihood of return of spontaneous circulation after multivariate adjustment (OR 0.68, 95% CI 0.60-0.76; p < 0.001).
CONCLUSIONS: Mechanical CPR was associated with a decreased likelihood of survival to hospital discharge and ROSC compared to manual CPR. This finding should be interpreted within the context of important limitations of this study and randomized trials are needed to better investigate this relationship.