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Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. In patients with a return of spontaneous circulation, brain injury is a leading cause of death. In this study, we propose an interpretable machine learning approach for predicting neurologic outcome after OHCA, using information available at the time of hospital admission. METHODS: The study population were 55 615 OHCA cases registered in the Swedish Cardiopulmonary Resuscitation Registry between 2010 and 2020. The dataset was split to training and validation sets (for model development) and test set (for evaluation of the final model). We used an XGBoost algorithm with stratified, repeated 10-fold cross-validation along with Optuna framework for hyperparameters tuning. The final model was trained on 10 features selected based on the importance scores and evaluated on the test set in terms of discrimination, calibration and bias-variance tradeoff. We used SHapley Additive exPlanations to address the 'black-box' model and align with eXplainable artificial intelligence. RESULTS: The final model achieved: area under the receiver operating characteristic value 0.964 (95% confidence interval (CI) [0.960-0.968]), sensitivity 0.606 (95% CI [0.573-0.634]), specificity 0.975 (95% CI [0.972-0.978]), positive predictive value (PPV) 0.664 (95% CI [0.625-0.696]), negative predictive value (NPV) 0.969 (95% CI [0.966-0.972]), macro F1 0.803 (95% CI [0.788-0.816]), and showed a very good calibration. SHAP features with the highest impact on the model's output were:'ROSC on arrival to hospital', 'Initial rhythm asystole' and 'Conscious on arrival to hospital'. CONCLUSIONS: The XGBoost machine learning model with 10 features available at the time of hospital admission showed good performance for predicting neurologic outcome after OHCA, with no apparent signs of overfitting.
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BACKGROUND: Takotsubo syndrome (TTS) is an acute heart failure syndrome with symptoms similar to acute myocardial infarction. TTS is often triggered by acute emotional or physical stress and is a significant cause of morbidity and mortality. Predictors of mortality in patients with TS are not well understood, and there is a need to identify high-risk patients and tailor treatment accordingly. This study aimed to assess the importance of various clinical factors in predicting 30-day mortality in TTS patients using a machine learning algorithm. METHODS: We analyzed data from the nationwide Swedish Coronary Angiography and Angioplasty Registry (SCAAR) for all patients with TTS in Sweden between 2015 and 2022. Gradient boosting was used to assess the relative importance of variables in predicting 30-day mortality in TTS patients. RESULTS: Of 3,180 patients hospitalized with TTS, 76.0% were women. The median age was 71.0 years (interquartile range 62-77). The crude all-cause mortality rate was 3.2% at 30 days. Machine learning algorithms by gradient boosting identified treating hospitals as the most important predictor of 30-day mortality. This factor was followed in significance by the clinical indication for angiography, creatinine level, Killip class, and age. Other less important factors included weight, height, and certain medical conditions such as hyperlipidemia and smoking status. CONCLUSIONS: Using machine learning with gradient boosting, we analyzed all Swedish patients diagnosed with TTS over seven years and found that the treating hospital was the most significant predictor of 30-day mortality.
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Coronary Angiography , Registries , Takotsubo Cardiomyopathy , Humans , Female , Sweden/epidemiology , Male , Aged , Takotsubo Cardiomyopathy/mortality , Takotsubo Cardiomyopathy/diagnostic imaging , Takotsubo Cardiomyopathy/therapy , Takotsubo Cardiomyopathy/diagnosis , Takotsubo Cardiomyopathy/physiopathology , Risk Factors , Middle Aged , Time Factors , Risk Assessment , Machine Learning , Prognosis , Predictive Value of Tests , Aged, 80 and over , HospitalsABSTRACT
BACKGROUND: It has been estimated that 80% of cases of out-of-hospital cardiac arrest (OHCA) are due to cardiac causes. It is well-documented that diabetes is a risk factor for conditions associated with sudden cardiac arrest. Type 1 diabetes (T1D) displays a threefold to fivefold increased risk of cardiovascular disease and death compared with the general population. OBJECTIVE: This study aims to assess the characteristics and survival outcomes of individuals with and without T1D who experienced an OHCA. Design: A registry-based nationwide observational study with two cohorts, patients with T1D and patients without T1D. Setting: All emergency medical services and hospitals in Sweden were included in the study. PARTICIPANTS: Using the Swedish Cardiopulmonary Resuscitation Registry, we enrolled 54 568 cases of OHCA where cardiopulmonary resuscitation was attempted between 2010 and 2020. Among them, 448 patients with T1D were identified using International Classification of Diseases-code: E10. METHODS: Survival analysis was performed using Kaplan-Meier and logistic regression. Multiple regression was adjusted for age, sex, cause of arrest, prevalence of T1D and time to cardiopulmonary resuscitation. MAIN OUTCOME MEASURES: The outcomes were discharge status (alive vs dead), 30 days survival and neurological outcome at discharge. RESULTS: There were no significant differences in patients discharged alive with T1D 37.3% versus, 46% among cases without T1D. There was also no difference in neurological outcome. Kaplan-Meier curves yielded no significant difference in long-term survival. Multiple regression showed no significant association with survival after accounting for covariates, OR 0.99 (95% CI 0.96 to 1.02), p value=0.7. Baseline characteristics indicate that patients with T1D were 5 years younger at OHCA occurrence and had proportionally fewer cases of heart disease as the cause of arrest (57.6% vs 62.7%). CONCLUSION: We conclude, with the current sample size, that there is no statistically significant difference in long-term or short-term survival between patients with and without T1D following OHCA.
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Cardiopulmonary Resuscitation , Diabetes Mellitus, Type 1 , Out-of-Hospital Cardiac Arrest , Registries , Humans , Out-of-Hospital Cardiac Arrest/mortality , Out-of-Hospital Cardiac Arrest/therapy , Sweden/epidemiology , Male , Female , Middle Aged , Diabetes Mellitus, Type 1/complications , Diabetes Mellitus, Type 1/mortality , Aged , Adult , Risk Factors , Emergency Medical Services/statistics & numerical data , Survival Analysis , Kaplan-Meier EstimateABSTRACT
BACKGROUND: Transcatheter aortic valve replacement (TAVR) is the most common treatment in patients with symptomatic severe aortic stenosis (AS). As concomitant coronary artery disease is common in AS patients, access to the coronary arteries following TAVR is of increasing importance. OBJECTIVES: This study evaluated the incidence and risk factors for unplanned coronary angiography following TAVR and, using fluoroscopic time as a surrogate, analyzed the complexity of coronary artery cannulation. METHODS: All patients who underwent TAVR in Sweden between 2008 and 2022 were identified using the SWEDEHEART registry. The cumulative incidence of coronary angiography after TAVR was analyzed with mortality as a competing risk. Angiography and PCI complexity were analyzed using fluoroscopic time and compared across different transcatheter heart valve designs. RESULTS: Out of 9806 patients, 566 subsequently required coronary angiography. The incidence was highest for three-vessel and/or left main disease. Younger age, the extent of prior coronary artery disease, and peripheral vascular disease were associated with an increased risk of coronary angiography. Fluoroscopy time was increased in TAVR patients compared to the control group with the longest fluoroscopy times observed in cases involving supra-annular and self-expanding valves. CONCLUSIONS: The incidence of coronary angiography following TAVR is still low. Younger patients and patients with concomitant coronary artery disease have a higher risk. Procedural time is longer in patients with a previous THV replacement. As TAVR is emerging as the first-line treatment in patients with longer life expectancy, facilitating coronary access is an important factor when considering which THV device to implant.
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BACKGROUND: A prediction model that estimates mortality at admission to the intensive care unit (ICU) is of potential benefit to both patients and society. Logistic regression models like Simplified Acute Physiology Score 3 (SAPS 3) and APACHE are the traditional ICU mortality prediction models. With the emergence of machine learning (machine learning) and artificial intelligence, new possibilities arise to create prediction models that have the potential to sharpen predictive accuracy and reduce the likelihood of misclassification in the prediction of 30-day mortality. METHODS: We used the Swedish Intensive Care Registry (SIR) to identify and include all patients ≥18 years of age admitted to general ICUs in Sweden from 2008 to 2022 with SAPS 3 score registered. Only data collected within 1 h of ICU admission was used. We had 153 candidate predictors including baseline characteristics, previous medical conditions, blood works, physiological parameters, cause of admission, and initial treatment. We stratified the data randomly on the outcome variable 30-day mortality and created a training set (80% of data) and a test set (20% of data). We evaluated several hundred prediction models using multiple ML frameworks including random forest, gradient boosting, neural networks, and logistic regression models. Model performance was evaluated by comparing the receiver operator characteristic area under the curve (AUC-ROC). The best performing model was fine-tuned by optimizing hyperparameters. The model's calibration was evaluated by a calibration belt. Ultimately, we simplified the best performing model with the top 1-20 predictors. RESULTS: We included 296,344 first-time ICU admissions. We found age, Glasgow Coma Scale, creatinine, systolic blood pressure, and pH being the most important predictors. The AUC-ROC was 0.884 in test data using all predictors, specificity 95.2%, sensitivity 47.0%, negative predictive value of 87.9% and positive predictive value of 70.7%. The final model showed excellent calibration. The ICU risk evaluation for 30-day mortality (ICURE) prediction model performed equally well to the SAPS 3 score with only eight variables and improved further with the addition of more variables. CONCLUSION: The ICURE prediction model predicts 30-day mortality rate at first-time ICU admission superiorly compared to the established SAPS 3 score.
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BACKGROUND: Non-shockable in-hospital cardiac arrest (IHCA) is a condition with diverse aetiology, predictive factors, and outcome. This study aimed to compare IHCA with initial asystole or pulseless electrical activity (PEA), focusing specifically on their aetiologies and the significance of predictive factors. METHODS: Using the Swedish Registry of Cardiopulmonary Resuscitation, adult non-shockable IHCA cases from 2018 to 2022 (n = 5788) were analysed. Exposure was initial rhythm, while survival to hospital discharge was the primary outcome. A random forest model with 28 variables was used to generate permutation-based variable importance for outcome prediction. RESULTS: Overall, 60% of patients (n = 3486) were male and the median age was 75 years (IQR 67-81). The most frequent arrest location (46%) was on general wards. Comorbidities were present in 79% of cases and the most prevalent comorbidity was heart failure (33%). Initial rhythm was PEA in 47% (n = 2702) of patients, and asystole in 53% (n = 3086). The most frequent aetiologies in both PEA and asystole were cardiac ischemia (24% vs. 19%, absolute difference [AD]: 5.4%; 95% confidence interval [CI] 3.0% to 7.7%), and respiratory failure (14% vs. 13%, no significant difference). Survival was higher in asystole (24%) than in PEA (17%) (AD: 7.3%; 95% CI 5.2% to 9.4%). Cardiopulmonary resuscitation (CPR) durations were longer in PEA, 18 vs 15 min (AD 4.9 min, 95% CI 4.0-5.9 min). The duration of CPR was the single most important predictor of survival across all subgroup and sensitivity analyses. Aetiology ranked as the second most important predictor in most analyses, except in the asystole subgroup where responsiveness at cardiac arrest team arrival took precedence. CONCLUSIONS: In this nationwide registry study of non-shockable IHCA comparing asystole to PEA, cardiac ischemia and respiratory failure were the predominant aetiologies. Duration of CPR was the most important predictor of survival, followed by aetiology. Asystole was associated with higher survival compared to PEA, possibly due to shorter CPR durations and a larger proportion of reversible aetiologies.
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Objectives: Recently, ILCOR unveiled the ground-breaking global initiative "Ten Steps Toward Improving In-Hospital Cardiac Arrest" (IHCA). Aim: To generate a baseline of how well the ten steps currently function in Sweden, in order to better target educational interventions. Material and methods: A survey was created using an online form application (Google Forms) and sent to CPR coordinators and physicians in charge of CPR at all 74 Swedish hospitals participating in the Swedish Registry for Cardiopulmonary Resuscitation (SRCR). Hospitals were asked to self-evaluate their functionality on each step on a ten-point scale ranging from 1 "Not present or not functioning at all" to 10 "Very well-functioning". Data regarding number of IHCA and their survival during 2018-2022 was gathered from the SRCR. Results: A total of 34 out of 74 (46%) Swedish hospitals participated in the survey, collectively representing 59% (7,113 out of 12,070) of IHCA cases in SRCR. The responding hospitals were satisfied with the functionality of just over half of the steps currently (median 60%, range 30-90%). The steps with the highest proportion of satisfied hospitals were found for step 6-rapid response systems (85%) and 7-guideline-based resuscitation (94%), while the steps with lowest proportion of satisfied hospitals were found for step 4-goals of treatment (32%) and step 9-person centred culture (18%). About half of participating hospitals expressed intent to prioritise upcoming years' work on step 1- infrastructure, step 3- effective education and step 5- stop preventable IHCA. Conclusion: The conclusion is that most hospitals judge themselves to be well-functioning on many of the ten steps, but steps involving effective education might need attention, as well as the tolerance for presence of preventable IHCA being low.
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Background: Observational studies on long-term trends, risk factor association and importance are scarce for type 1 diabetes mellitus and peripheral arterial outcomes. We set out to investigate trends in non-coronary complications and their relationships with cardiovascular risk factors in persons with type 1 diabetes mellitus compared to matched controls. Methods: 34,263 persons with type 1 diabetes mellitus from the Swedish National Diabetes Register and 164,063 matched controls were included. Incidence rates of extracranial large artery disease, aortic aneurysm, aortic dissection, lower extremity artery disease, and diabetic foot syndrome were analyzed using standardized incidence rates and Cox regression. Findings: Between 2001 and 2019, type 1 diabetes mellitus incidence rates per 100,000 person-years were as follows: extracranial large artery disease 296.5-84.3, aortic aneurysm 0-9.2, aortic dissection remained at 0, lower extremity artery disease 456.6-311.1, and diabetic foot disease 814.7-77.6. Persons with type 1 diabetes mellitus with cardiometabolic risk factors at target range did not exhibit excess risk of extracranial large artery disease [HR 0.83 (95% CI, 0.20-3.36)] or lower extremity artery disease [HR 0.94 (95% CI, 0.30-2.93)], compared to controls. Persons with type 1 diabetes with all risk factors at baseline, had substantially elevated risk for diabetic foot disease [HR 29.44 (95% CI, 3.83-226.04)], compared to persons with type 1 diabetes with no risk factors. Persons with type 1 diabetes mellitus continued to display a lower risk for aortic aneurysm, even with three cardiovascular risk factors at baseline [HR 0.31 (95% CI, 0.15-0.67)]. Relative importance analyses demonstrated that education, glycated hemoglobin (HbA1c), duration of diabetes and lipids explained 54% of extracranial large artery disease, while HbA1c, smoking and systolic blood pressure explained 50% of lower extremity artery disease and HbA1c alone contributed to 41% of diabetic foot disease. Income, duration of diabetes and body mass index explained 66% of the contribution to aortic aneurysm. Interpretation: Peripheral arterial complications decreased in persons with type 1 diabetes mellitus, except for aortic aneurysm which remained low. Besides glycemic control, traditional cardiovascular risk factors were associated with incident outcomes. Risk of these outcomes increased with additional risk factors present. Persons with type 1 diabetes mellitus exhibited a lower risk of aortic aneurysm compared to controls, despite presence of cardiovascular risk factors. Funding: Swedish Governmental and the county support of research and education of doctors, the Swedish Heart and Lung Foundation, Sweden and Åke-Wibergs grant.
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Background: Few studies have explored long-term trends and risk factors for peripheral arterial complications in type 2 diabetes compared to the general population. Our research focuses on identifying optimal risk factors, their significance, risk associated with multifactorial risk factor control, and trends for these complications in diabetic patients versus general controls. Methods: This study included persons with type 2 diabetes mellitus entered into the Swedish National Diabetes Register 2001-2019 and controls matched for age-, sex- and county of residence. Outcomes comprised of extracranial large artery disease, aortic aneurysm, aortic dissection, lower extremity arterial disease and diabetes foot disease. Standardized incidence rates and Cox regression were used for analyses. Findings: The study comprises 655,250 persons with type 2 diabetes mellitus; average age 64.2; 43.8% women. Among persons with type 2 diabetes mellitus, the incidence rates per 100,000 person years for each non-coronary peripheral arterial complication event changed between 2001 and 2019 as follows: extracranial large artery disease 170.0-84.9; aortic aneurysm 40.6-69.2; aortic dissection 9.3 to 5.6; lower extremity artery disease from 338.8 to 190.8; and diabetic foot disease from 309.8 to 226.8. Baseline hemoglobin A1c (HbA1c), systolic blood pressure (SBP), smoking status and lipid levels were independently associated with all outcomes in the type 2 diabetes mellitus cohort. Within the cohort with type 2 diabetes mellitus, the risk for extracranial large artery disease and lower extremity artery disease increased in a stepwise fashion for each risk factor not within target. Excess risk for non-coronary peripheral arterial complications in the entire cohort for persons with type 2 diabetes mellitus, compared to matched controls, were as follows: extracranial large artery disease adjusted hazard ratio (HR) 1.69 (95% confidence interval (CI), 1.65-1.73), aortic aneurysm HR 0.89 (95% CI, 0.87-0.92), aortic dissection HR 0.51 (95% CI, 0.46-0.57) and lower extremity artery disease HR 2.59 (95% CI, 2.55-2.64). Interpretation: The incidence of non-coronary peripheral arterial complications has declined significantly among persons with type 2 diabetes mellitus, with the exception of aortic aneurysm. HbA1c, smoking and blood pressure demonstrated greatest relative contribution for outcomes and lower levels of cardiometabolic risk factors are associated with reduced relative risk of outcomes. Funding: Swedish Governmental and the County support of research and education of doctors, the Swedish Heart-Lung Foundation and Åke-Wibergs grant.
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AIMS: Previous studies have indicated a poorer survival among women following out-of-hospital cardiac arrest (OHCA), but the mechanisms explaining this difference remain largely uncertain.This study aimed to assess the survival after OHCA among women and men and explore the role of potential mediators, such as resuscitation characteristics, prior comorbidity, and socioeconomic factors. METHODS AND RESULTS: This was a population-based cohort study including emergency medical service-treated OHCA reported to the Swedish Registry for Cardiopulmonary Resuscitation in 2010-2020, linked to nationwide Swedish healthcare registries. The relative risks (RR) of 30-day survival were compared among women and men, and a mediation analysis was performed to investigate the importance of potential mediators. Total of 43 226 OHCAs were included, of which 14 249 (33.0%) were women. Women were older and had a lower proportion of shockable initial rhythm. The crude 30-day survival among women was 6.2% compared to 10.7% for men [RR 0.58, 95% confidence interval (CI) = 0.54-0.62]. Stepwise adjustment for shockable initial rhythm attenuated the association to RR 0.85 (95% CI = 0.79-0.91). Further adjustments for age and resuscitation factors attenuated the survival difference to null (RR 0.98; 95% CI = 0.92-1.05). Mediation analysis showed that shockable initial rhythm explained â¼50% of the negative association of female sex on survival. Older age and lower disposable income were the second and third most important variables, respectively. CONCLUSION: Women have a lower crude 30-day survival following OHCA compared to men. The poor prognosis is largely explained by a lower proportion of shockable initial rhythm, older age at presentation, and lower income.
Subject(s)
Cardiopulmonary Resuscitation , Mediation Analysis , Out-of-Hospital Cardiac Arrest , Registries , Humans , Out-of-Hospital Cardiac Arrest/mortality , Out-of-Hospital Cardiac Arrest/therapy , Female , Male , Sweden/epidemiology , Aged , Sex Factors , Middle Aged , Cardiopulmonary Resuscitation/statistics & numerical data , Aged, 80 and over , Survival Rate , Risk Factors , Emergency Medical Services/statistics & numerical data , Socioeconomic Factors , Electric Countershock/instrumentation , Electric Countershock/mortalityABSTRACT
Aims: Out-of-hospital cardiac arrest (OHCA) is a major health concern worldwide. Although one-third of all patients achieve a return of spontaneous circulation and may undergo a difficult period in the intensive care unit, only 1 in 10 survive. This study aims to improve our previously developed machine learning model for early prognostication of survival in OHCA. Methods and results: We studied all cases registered in the Swedish Cardiopulmonary Resuscitation Registry during 2010 and 2020 (n = 55 615). We compared the predictive performance of extreme gradient boosting (XGB), light gradient boosting machine (LightGBM), logistic regression, CatBoost, random forest, and TabNet. For each framework, we developed models that optimized (i) a weighted F1 score to penalize models that yielded more false negatives and (ii) a precision-recall area under the curve (PR AUC). LightGBM assigned higher importance values to a larger set of variables, while XGB made predictions using fewer predictors. The area under the curve receiver operating characteristic (AUC ROC) scores for LightGBM were 0.958 (optimized for weighted F1) and 0.961 (optimized for a PR AUC), while for XGB, the scores were 0.958 and 0.960, respectively. The calibration plots showed a subtle underestimation of survival for LightGBM, contrasting with a mild overestimation for XGB models. In the crucial range of 0-10% likelihood of survival, the XGB model, optimized with the PR AUC, emerged as a clinically safe model. Conclusion: We improved our previous prediction model by creating a parsimonious model with an AUC ROC at 0.96, with excellent calibration and no apparent risk of underestimating survival in the critical probability range (0-10%). The model is available at www.gocares.se.
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AIMS: Takotsubo syndrome (TS) is a heart condition mimicking acute myocardial infarction. TS is characterized by a sudden weakening of the heart muscle, usually triggered by physical or emotional stress. In this study, we aimed to investigate the effect of pharmacological interventions on short- and long-term mortality in patients with TS. METHODS AND RESULTS: We analysed data from the SWEDEHEART (the Swedish Web System for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies) registry, which included patients who underwent coronary angiography between 2009 and 2016. In total, we identified 1724 patients with TS among 228 263 individuals in the registry. The average age was 66 ± 14 years, and 77% were female. Nearly half of the TS patients (49.4%) presented with non-ST-elevation acute coronary syndrome, and a quarter (25.9%) presented with ST-elevation myocardial infarction. Most patients (79.1%) had non-obstructive coronary artery disease on angiography, while 11.7% had a single-vessel disease and 9.2% had a multivessel disease. All patients received at least one pharmacological intervention; most of them used beta-blockers (77.8% orally and 8.3% intravenously) or antiplatelet agents [aspirin (66.7%) and P2Y12 inhibitors (43.6%)]. According to the Kaplan-Meier estimator, the probability of all-cause mortality was 2.5% after 30 days and 16.6% after 6 years. The median follow-up time was 877 days. Intravenous use of inotropes and diuretics was associated with increased 30 day mortality in TS [hazard ratio (HR) = 9.92 (P < 0.001) and HR = 3.22 (P = 0.001), respectively], while angiotensin-converting enzyme inhibitors and statins were associated with decreased long-term mortality [HR = 0.60 (P = 0.025) and HR = 0.62 (P = 0.040), respectively]. Unfractionated and low-molecular-weight heparins were associated with reduced 30 day mortality [HR = 0.63 (P = 0.01)]. Angiotensin receptor blockers, oral anticoagulants, P2Y12 antagonists, aspirin, and beta-blockers did not statistically correlate with mortality. CONCLUSIONS: Our findings suggest that some medications commonly used to treat TS are associated with higher mortality, while others have lower mortality. These results could inform clinical decision-making and improve patient outcomes in TS. Further research is warranted to validate these findings and to identify optimal pharmacological interventions for patients with TS.
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Coronary Angiography , Registries , Takotsubo Cardiomyopathy , Humans , Female , Takotsubo Cardiomyopathy/drug therapy , Takotsubo Cardiomyopathy/mortality , Takotsubo Cardiomyopathy/diagnosis , Male , Sweden/epidemiology , Aged , Survival Rate/trends , Follow-Up Studies , Retrospective Studies , Adrenergic beta-Antagonists/therapeutic useABSTRACT
BACKGROUND: It is unclear whether an implantable cardioverter-defibrillator (ICD) is generally beneficial in survivors of out-of-hospital cardiac arrest (OHCA). OBJECTIVE: We studied the association between ICD implantation prior to discharge and survival in patients with cardiac aetiology or initial shockable rhythm in OHCA. DESIGN: We conducted a retrospective cohort study in the Swedish Registry for Cardiopulmonary Resuscitation. Treatment associations were estimated using propensity scores. We used gradient boosting, Bayesian additive regression trees, neural networks, extreme gradient boosting and logistic regression to generate multiple propensity scores. We selected the model yielding maximum covariate balance to obtain weights, which were used in a Cox regression to calculate HRs for death or recurrent cardiac arrest. PARTICIPANTS: All cases discharged alive during 2010 to 2020 with a cardiac aetiology or initial shockable rhythm were included. A total of 959 individuals were discharged with an ICD, and 2046 were discharged without one. RESULTS: Among those experiencing events, 25% did so within 90 days in the ICD group, compared with 52% in the other group. All HRs favoured ICD implantation. The overall HR (95% CI) for ICD versus no ICD was 0.38 (0.26 to 0.56). The HR was 0.42 (0.28 to 0.63) in cases with initial shockable rhythm; 0.18 (0.06 to 0.58) in non-shockable rhythm; 0.32 (0.20 to 0.53) in cases with a history of coronary artery disease; 0.36 (0.22 to 0.61) in heart failure and 0.30 (0.13 to 0.69) in those with diabetes. Similar associations were noted in all subgroups. CONCLUSION: Among survivors of OHCA, those discharged with an ICD had approximately 60% lower risk of death or recurrent cardiac arrest. A randomised trial is warranted to study this further.
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Cardiopulmonary Resuscitation , Emergency Medical Services , Out-of-Hospital Cardiac Arrest , Humans , Retrospective Studies , Bayes Theorem , Sweden/epidemiology , RegistriesABSTRACT
Background: In neurologic prognostication of comatose survivors from cardiac arrest, two independent predictors of poor outcome are the loss of the Pupillary light reflex (PLR) and the loss of the N20 response from Somatosensory Evoked potentials (SSEP). The PLR can be quantitatively assessed by pupillometry. Both tests depend on the midbrain, in which a dysfunction reflects a severe hypoxic injury. We reasoned that a certain level of defective PLR would be predictive of a bilaterally absent SSEP N20 response. Method: Neurological Pupil index (NPi) from the pupillometry and the SSEP N20 response were registered >48 h after cardiac arrest in comatose survivors. Clinical data were retrospectively analyzed. A receiver operating characteristic curve was used to evaluate the capacity of NPi to predict bilaterally absent SSEP N20 response. An NPi threshold value resulting in <5% false positive rate (FPR) for bilaterally absent N20 response was identified. Results: From February 2020 to August 2022, we included 54 patients out of which 49 had conclusive pupillometry and SSEP examinations. The NPi threshold value with FPR < 5% was 3.4, yielding 36% sensitivity (95% CI 18-55) and significantly discriminated between respective groups with preserved and bilaterally absent N20 response to SSEP (p-value <0.01). Conclusion: In this limited cohort, NPi < 3.4 in patients remaining comatose >48 hours after cardiac arrest predicted bilateral loss of the SSEP N20 response with a FPR < 5%. If validated in a larger cohort, an NPi threshold may be clinically applied in settings where SSEP is unavailable.
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The study aimed to identify the most predictive factors for the development of type 2 diabetes. Using an XGboost classification model, we projected type 2 diabetes incidence over a 10-year horizon. We deliberately minimized the selection of baseline factors to fully exploit the rich dataset from the UK Biobank. The predictive value of features was assessed using shap values, with model performance evaluated via Receiver Operating Characteristic Area Under the Curve, sensitivity, and specificity. Data from the UK Biobank, encompassing a vast population with comprehensive demographic and health data, was employed. The study enrolled 450,000 participants aged 40-69, excluding those with pre-existing diabetes. Among 448,277 participants, 12,148 developed type 2 diabetes within a decade. HbA1c emerged as the foremost predictor, followed by BMI, waist circumference, blood glucose, family history of diabetes, gamma-glutamyl transferase, waist-hip ratio, HDL cholesterol, age, and urate. Our XGboost model achieved a Receiver Operating Characteristic Area Under the Curve of 0.9 for 10-year type 2 diabetes prediction, with a reduced 10-feature model achieving 0.88. Easily measurable biological factors surpassed traditional risk factors like diet, physical activity, and socioeconomic status in predicting type 2 diabetes. Furthermore, high prediction accuracy could be maintained using just the top 10 biological factors, with additional ones offering marginal improvements. These findings underscore the significance of biological markers in type 2 diabetes prediction.
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Diabetes Mellitus, Type 2 , Humans , Diabetes Mellitus, Type 2/epidemiology , Biological Specimen Banks , UK Biobank , Machine Learning , Biological FactorsABSTRACT
OBJECTIVES: We studied short-term (30-day) and long-term (up to ten-year) survival among children and young adults following out-of-hospital cardiac arrest (OHCA) in Sweden over the course of the past 30 years. We also studied the causes of OHCA in children and examined predictors of survival. SETTING: This was a nationwide, registry-based cohort study, using the Swedish Registry of Cardiopulmonary Resuscitation. Our study comprised a cohort of 4,804 individuals aged 0 to 30 years who suffered OHCA between 1990 and 2020, in whom cardiopulmonary resuscitation (CPR) was initiated. We stratified the study cohort to distinct age groups and time periods. RESULTS: We found an increase in 30-day survival from 7% to 20% over the span of 30 years. In those under 1 year of age, survival increased from 2% to 19%. Time to CPR decreased from 14 to 2 min. The 10-year survival was high among those who survived 30 days. The etiology of cardiac arrests exhibited significant variations across different age groups but remained relatively consistent over time. Causes linked to mental illness constituted a substantial percentage of these cases. Compared to the reference period (1990-1994), the odds of survival in 2015-2020 was 3.00 (95% CI: 1.43, 6.94; p = 0.006). CONCLUSION: Survival rate after OHCA in children and young adults has increased three-fold over the past 30 years. Still overall mortality is high underscoring the need for continued efforts to mitigate risk factors and optimize survival.
Subject(s)
Cardiopulmonary Resuscitation , Emergency Medical Services , Out-of-Hospital Cardiac Arrest , Child , Humans , Young Adult , Out-of-Hospital Cardiac Arrest/etiology , Out-of-Hospital Cardiac Arrest/therapy , Cohort Studies , RegistriesABSTRACT
Aim: The aim of this study was to present a comprehensive overview of out-of-hospital cardiac arrests (OHCA) in young adults. Methods: The data set analyzed included all cases of OHCA from 1990 to 2020 in the age-range 16-49 years in the Swedish Registry of Cardiopulmonary Resuscitation (SRCR). OHCA between 2010 and 2020 were analyzed in more detail. Clinical characteristics, survival, neurological outcomes, and long-time trends in survival were studied. Logistic regression was used to study 30-days survival, neurological outcomes and Utstein determinants of survival. Results: Trends were assessed in 11,180 cases. The annual increase in 30-days survival during 1990-2020 was 5.9% with no decline in neurological function among survivors. Odds ratio (OR) for heart disease as the cause was 0.55 (95% CI 0.44 to 0.67) in 2017-2020 compared to 1990-1993. Corresponding ORs for overdoses and suicide attempts were 1.61 (95% CI 1.23-2.13) and 2.06 (95% CI 1.48-2.94), respectively. Exercise related OHCA was noted in roughly 5%. OR for bystander CPR in 2017-2020 vs 1990-1993 was 3.11 (95% CI 2.57 to 3.78); in 2020 88 % received bystander CPR. EMS response time increased from 6 to 10 minutes. Conclusion: Survival has increased 6% annually, resulting in a three-fold increase over 30 years, with stable neurological outcome. EMS response time increased with 66% but the majority now receive bystander CPR. Cardiac arrest due to overdoses and suicide attempts are increasing.
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BACKGROUND: Out-of-hospital cardiac arrest (OHCA) has a dismal prognosis with overall survival around 10%. Previous studies have shown conflicting results regarding the prevalence and significance of comorbidities in OHCA, as well as the underlying causes. Previously, 80% of sudden cardiac arrest have been attributed to coronary artery disease. We studied comorbidities and discharge diagnoses in OHCA in all of Sweden. METHODS: We used the Swedish Registry of Cardiopulmonary Resuscitation, merged with the Inpatient Registry and Outpatient Registry to identify patients with OHCA from 2010 to 2020 and to collect all their comorbidities as well as discharge diagnoses (among those admitted to hospital). Patient characteristics were described using means, medians and SD. Survival curves were performed among hospitalised patients with acute myocardial infarction (AMI) as well as heart failure. RESULTS: A total of 54 484 patients with OHCA were included, of whom 35 894 (66%) were men. The most common comorbidities prior to OHCA were hypertension (43.6%), heart failure (23.6%), chronic ischaemic heart disease (23.6%) and atrial fibrillation (22.0%). Previous AMI was prevalent in 14.8% of men and 10.9% of women. Among women, 18.0% had type 2 diabetes, compared with 19.6% of the men. Among hospitalised patients, 30% were diagnosed with AMI, 27% with hypertension, 20% with ischaemic heart disease and 18% with heart failure as discharge diagnoses. CONCLUSION: In summary, we find evidence that nowadays a minority of cardiac arrests are due to coronary artery disease and AMIs and its complications. Only 30% of all cases of OHCA admitted to hospital were diagnosed with AMI. Coronary artery disease is now likely in the minority with regard to causes of OHCA.
Subject(s)
Coronary Artery Disease , Diabetes Mellitus, Type 2 , Heart Failure , Hypertension , Myocardial Infarction , Myocardial Ischemia , Out-of-Hospital Cardiac Arrest , Male , Humans , Female , Patient Discharge , Out-of-Hospital Cardiac Arrest/diagnosis , Out-of-Hospital Cardiac Arrest/epidemiology , Out-of-Hospital Cardiac Arrest/therapy , Coronary Artery Disease/diagnosis , Coronary Artery Disease/epidemiology , Coronary Artery Disease/therapy , Diabetes Mellitus, Type 2/complications , Myocardial Infarction/complications , Myocardial Ischemia/complications , Heart Failure/diagnosis , Heart Failure/epidemiology , Heart Failure/complications , Hypertension/complications , SurvivorsABSTRACT
INTRODUCTION: Rapid response teams (RRTs) are designed to improve the "chain of prevention" of in-hospital cardiac arrest (IHCA). We studied the 30-day survival of patients reviewed by RRTs within 24 hours prior to IHCA, as compared to patients not reviewed by RRTs. METHODS: A nationwide cohort study based on the Swedish Registry of Cardiopulmonary Resuscitation, between January 1st, 2014, and December 31st, 2021. An explorative, hypothesis-generating additional in-depth data collection from medical records was performed in a small subgroup of general ward patients reviewed by RRTs. RESULTS: In all, 12,915 IHCA patients were included. RRT-reviewed patients (n = 2,058) had a lower unadjusted 30-day survival (25% vs 33%, p < 0.001), a propensity score based Odds ratio for 30-day survival of 0.92 (95% Confidence interval 0.90-0.94, p < 0.001) and were more likely to have a respiratory cause of IHCA (22% vs 15%, p < 0.001). In the subgroup (n = 82), respiratory distress was the most common RRT trigger, and 24% of the RRT reviews were delayed. Patient transfer to a higher level of care was associated with a higher 30-day survival rate (20% vs 2%, p < 0.001). CONCLUSION: IHCA preceded by RRT review is associated with a lower 30-day survival rate and a greater likelihood of a respiratory cause of cardiac arrest. In the small explorative subgroup, respiratory distress was the most common RRT trigger and delayed RRT activation was frequent. Early detection of respiratory abnormalities and timely interventions may have a potential to improve outcomes in RRT-reviewed patients and prevent further progress into IHCA.
Subject(s)
Heart Arrest , Hospital Rapid Response Team , Respiratory Distress Syndrome , Humans , Cohort Studies , Heart Arrest/therapy , HospitalsABSTRACT
BACKGROUND: Data on de novo aneurysm formation after treatment for intracranial aneurysms remains scarce. We studied the incidence of de novo aneurysm formation in patients who had undergone aneurysm treatment more than 18 years prior to follow-up. As it is a disease affecting a younger patient population more specific guidelines are needed when planning a follow-up regime. METHODS: The rate of de novo aneurysm formation was assessed with Magnetic Resonance Angiography (MRA) follow-up >18 years after endovascular or microsurgical treatment for an intracranial aneurysm. Variables associated with de novo aneurysm formation were studied using logistic regression. Missing data were imputed using chained random forests. A data-driven model for the prediction of de novo aneurysm was created to calculate the relative variable importance of ten clinical features. RESULTS: De novo aneurysms were identified in 11/81 (13.6 %) patients, of whom 1 was male, over a median follow-up of 20 years. Sex was the most important variable associated with de novo aneurysm formation. Regarding the development of de novo aneurysm, men displayed an odds ratio (OR) of 0.16 (0.01-0.97), compared with women. OR for mRS score 2 or more was 0.20 (95 % CI 0.01-1.34), and OR for smokers was 3.70 (0.54-31.18). Six out of 11 patients (54.5 %) needed treatment; 1 underwent endovascular treatment (EVT) and 5 underwent microsurgical treatment (MST). The overall annual de novo aneurysm formation rate was 0.92 %. CONCLUSIONS: This study highlights the need for a longer follow-up imaging monitoring of patients that have previously undergone treatment for an intracranial aneurysm. These data are useful to take into consideration when planning a follow-up strategy.