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1.
  • Langhelle, A., et al. (författare)
  • Recommended guidelines for reviewing, reporting, and conducting research on post-resuscitation care: the Utstein style
  • 2005
  • Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 66:3, s. 271-83
  • Tidskriftsartikel (refereegranskat)abstract
    • The aim of this report is to establish recommendations for reviewing, reporting, and conducting research during the post-resuscitation period in hospital. It defines data that are needed for research and more specialised registries and therefore supplements the recently updated Utstein template for resuscitation registries. The updated Utstein template and the out-of-hospital "Chain of Survival" describe factors of importance for successful resuscitation up until return of spontaneous circulation (ROSC). Several factors in the in-hospital phase after ROSC are also likely to affect the ultimate outcome of the patient. Large differences in survival to hospital discharge for patients admitted alive are reported between hospitals. Therapeutic hypothermia has been demonstrated to improve the outcome, and other factors such as blood glucose, haemodynamics, ventilatory support, etc., might also influence the result. No generally accepted, scientifically based protocol exists for the post-resuscitation period in hospital, other than general brain-oriented intensive care. There is little published information on this in-hospital phase. This statement is the result of a scientific consensus development process started as a symposium by a task force at the Utstein Abbey, Norway, in September 2003. Suggested data are defined as core and supplementary and include the following categories: pre-arrest co-morbidity and functional status, cause of death, patients' quality of life, in-hospital system factors, investigations and treatment, and physiological data at various time points during the first three days after admission. It is hoped that the publication of these recommendations will encourage research into the in-hospital post-resuscitation phase, which we propose should be included in the chain-of-survival as a fifth ring. Following these recommendations should enable better understanding of the impact of different in-hospital treatment strategies on outcome.
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2.
  • Hessulf, Fredrik, 1986, et al. (författare)
  • Predicting survival and neurological outcome in out-of-hospital cardiac arrest using machine learning: the SCARS model
  • 2023
  • Ingår i: eBioMedicine. - : Elsevier BV. - 2352-3964. ; 89
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: A prediction model that estimates survival and neurological outcome in out-of-hospital cardiac arrest patients has the potential to improve clinical management in emergency rooms.Methods: We used the Swedish Registry for Cardiopulmonary Resuscitation to study all out-of-hospital cardiac arrest (OHCA) cases in Sweden from 2010 to 2020. We had 393 candidate predictors describing the circumstances at cardiac arrest, critical time intervals, patient demographics, initial presentation, spatiotemporal data, socioeconomic status, medications, and comorbidities before arrest. To develop, evaluate and test an array of prediction models, we created stratified (on the outcome measure) random samples of our study population. We created a training set (60% of data), evaluation set (20% of data), and test set (20% of data). We assessed the 30-day survival and cerebral performance category (CPC) score at discharge using several machine learning frameworks with hyperparameter tuning. Parsimonious models with the top 1 to 20 strongest predictors were tested. We calibrated the decision threshold to assess the cut-off yielding 95% sensitivity for survival. The final model was deployed as a web application.Findings: We included 55,615 cases of OHCA. Initial presentation, prehospital interventions, and critical time intervals variables were the most important. At a sensitivity of 95%, specificity was 89%, positive predictive value 52%, and negative predictive value 99% in test data to predict 30-day survival. The area under the receiver characteristic curve was 0.97 in test data using all 393 predictors or only the ten most important predictors. The final model showed excellent calibration. The web application allowed for near-instantaneous survival calculations.Interpretation: Thirty-day survival and neurological outcome in OHCA can rapidly and reliably be estimated during ongoing cardiopulmonary resuscitation in the emergency room using a machine learning model incorporating widely available variables.
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3.
  • Lang, Margareta, et al. (författare)
  • Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest: a prospective multicentre study
  • 2024
  • Ingår i: Intensive Care Medicine. - : SPRINGER. - 0342-4642 .- 1432-1238.
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest. Methods: Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h <= 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey-white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4-6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated. Results: 140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59-76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90-100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77-0.91) did not significantly differ from manually obtained GWR. Conclusion: Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.
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4.
  • Lang, Margareta, et al. (författare)
  • Standardised and automated assessment of head computed tomography reliably predicts poor functional outcome after cardiac arrest : a prospective multicentre study
  • 2024
  • Ingår i: Intensive Care Medicine. - : SPRINGER. - 0342-4642 .- 1432-1238. ; 50:7, s. 1096-1107
  • Tidskriftsartikel (refereegranskat)abstract
    • Purpose: Application of standardised and automated assessments of head computed tomography (CT) for neuroprognostication after out-of-hospital cardiac arrest. Methods: Prospective, international, multicentre, observational study within the Targeted Hypothermia versus Targeted Normothermia after out-of-hospital cardiac arrest (TTM2) trial. Routine CTs from adult unconscious patients obtained > 48 h ≤ 7 days post-arrest were assessed qualitatively and quantitatively by seven international raters blinded to clinical information using a pre-published protocol. Grey–white-matter ratio (GWR) was calculated from four (GWR-4) and eight (GWR-8) regions of interest manually placed at the basal ganglia level. Additionally, GWR was obtained using an automated atlas-based approach. Prognostic accuracies for prediction of poor functional outcome (modified Rankin Scale 4–6) for the qualitative assessment and for the pre-defined GWR cutoff < 1.10 were calculated. Results: 140 unconscious patients were included; median age was 68 years (interquartile range [IQR] 59–76), 76% were male, and 75% had poor outcome. Standardised qualitative assessment and all GWR models predicted poor outcome with 100% specificity (95% confidence interval [CI] 90–100). Sensitivity in median was 37% for the standardised qualitative assessment, 39% for GWR-8, 30% for GWR-4 and 41% for automated GWR. GWR-8 was superior to GWR-4 regarding prognostic accuracies, intra- and interrater agreement. Overall prognostic accuracy for automated GWR (area under the curve [AUC] 0.84, 95% CI 0.77–0.91) did not significantly differ from manually obtained GWR. Conclusion: Standardised qualitative and quantitative assessments of CT are reliable and feasible methods to predict poor functional outcome after cardiac arrest. Automated GWR has the potential to make CT quantification for neuroprognostication accessible to all centres treating cardiac arrest patients.
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5.
  • May, Teresa L., et al. (författare)
  • Variability in functional outcome and treatment practices by treatment center after out-of-hospital cardiac arrest : analysis of International Cardiac Arrest Registry
  • 2019
  • Ingår i: Intensive Care Medicine. - : Springer Science and Business Media LLC. - 0342-4642 .- 1432-1238. ; 45:5, s. 637-646
  • Tidskriftsartikel (refereegranskat)abstract
    • PurposeFunctional outcomes vary between centers after out-of-hospital cardiac arrest (OHCA) and are partially explained by pre-existing health status and arrest characteristics, while the effects of in-hospital treatments on functional outcome are less understood. We examined variation in functional outcomes by center after adjusting for patient- and arrest-specific characteristics and evaluated how in-hospital management differs between high- and low-performing centers.MethodsAnalysis of observational registry data within the International Cardiac Arrest Registry was used to perform a hierarchical model of center-specific risk standardized rates for good outcome, adjusted for demographics, pre-existing functional status, and arrest-related factors with treatment center as a random effect variable. We described the variability in treatments and diagnostic tests that may influence outcome at centers with adjusted rates significantly above and below registry average.ResultsA total of 3855 patients were admitted to an ICU following cardiac arrest with return of spontaneous circulation. The overall prevalence of good outcome was 11-63% among centers. After adjustment, center-specific risk standardized rates for good functional outcome ranged from 0.47 (0.37-0.58) to 0.20 (0.12-0.26). High-performing centers had faster time to goal temperature, were more likely to have goal temperature of 33 degrees C, more likely to perform unconscious cardiac catheterization and percutaneous coronary intervention, and had differing prognostication practices than low-performing centers.ConclusionsCenter-specific differences in outcomes after OHCA after adjusting for patient-specific factors exist. This variation could partially be explained by in-hospital management differences. Future research should address the contribution of these factors to the differences in outcomes after resuscitation.
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6.
  • Robba, Chiara, et al. (författare)
  • Oxygen targets and 6-month outcome after out of hospital cardiac arrest : a pre-planned sub-analysis of the targeted hypothermia versus targeted normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial
  • 2022
  • Ingår i: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535 .- 1466-609X. ; 26, s. 1-13
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Optimal oxygen targets in patients resuscitated after cardiac arrest are uncertain. The primary aim of this study was to describe the values of partial pressure of oxygen values (PaO2) and the episodes of hypoxemia and hyperoxemia occurring within the first 72 h of mechanical ventilation in out of hospital cardiac arrest (OHCA) patients. The secondary aim was to evaluate the association of PaO2 with patients’ outcome. Methods: Preplanned secondary analysis of the targeted hypothermia versus targeted normothermia after OHCA (TTM2) trial. Arterial blood gases values were collected from randomization every 4 h for the first 32 h, and then, every 8 h until day 3. Hypoxemia was defined as PaO2 < 60 mmHg and severe hyperoxemia as PaO2 > 300 mmHg. Mortality and poor neurological outcome (defined according to modified Rankin scale) were collected at 6 months. Results: 1418 patients were included in the analysis. The mean age was 64 ± 14 years, and 292 patients (20.6%) were female. 24.9% of patients had at least one episode of hypoxemia, and 7.6% of patients had at least one episode of severe hyperoxemia. Both hypoxemia and hyperoxemia were independently associated with 6-month mortality, but not with poor neurological outcome. The best cutoff point associated with 6-month mortality for hypoxemia was 69 mmHg (Risk Ratio, RR = 1.009, 95% CI 0.93–1.09), and for hyperoxemia was 195 mmHg (RR = 1.006, 95% CI 0.95–1.06). The time exposure, i.e., the area under the curve (PaO2-AUC), for hyperoxemia was significantly associated with mortality (p = 0.003). Conclusions: In OHCA patients, both hypoxemia and hyperoxemia are associated with 6-months mortality, with an effect mediated by the timing exposure to high values of oxygen. Precise titration of oxygen levels should be considered in this group of patients. Trial registration: clinicaltrials.gov NCT02908308, Registered September 20, 2016.
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7.
  • Andersson, Peder, et al. (författare)
  • Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm
  • 2021
  • Ingår i: Critical Care. - : Springer Science and Business Media LLC. - 1364-8535. ; 25:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BackgroundPrognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers.MethodsWe performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients' background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1-2 whilst a poor outcome was defined as CPC 3-5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets.ResultsAUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p<0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions.ConclusionsIn this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.
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8.
  • Berglund, Sara, et al. (författare)
  • Cardiorenal function and survival in in-hospital cardiac arrest : A nationwide study of 22,819 cases
  • 2022
  • Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 172, s. 9-16
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: We studied the association between cardiorenal function and survival, neurological outcome and trends in survival after in-hospital Methods: We included cases aged 18 years in the Swedish Cardiopulmonary Resuscitation Registry during 2008 to 2020. The CKD-EPI equation was used to calculate estimated glomerular filtration rate (eGFR). A history of heart failure was defined according to contemporary guideline criteria. Logistic regression was used to study survival. Neurological outcome was assessed using cerebral performance category (CPC). Results: We studied 22,819 patients with IHCA. The 30-day survival was 19.3%, 16.6%, 22.5%, 28.8%, 39.3%, 44.8% and 38.4% in cases with eGFR < 15, 15-29, 30-44, 45-59, 60-89, 90-130 and 130-150 ml/min/1.73 m2, respectively. All eGFR levels below and above 90 ml/min/1.73 m2 were associated with increased mortality. Probability of survival at 30 days was 62% lower in cases with eGFR < 15 ml/min/1.73 m2, compared with normal kidney function. At every level of eGFR, presence of heart failure increased mortality markedly; patients without heart failure displayed higher mortality only at eGFR below 30 ml/min/1.73 m2. Among survivors with eGFR < 15 ml/min/1.73 m2, good neurological outcome was noted in 87.2%. Survival increased in most groups over time, but most for those with eGFR < 15 ml/min/1.73 m2, and least for those with normal eGFR. Conclusions: All eGFR levels below and above normal range are associated with increased mortality and this association is modified by the presence of heart failure. Neurological outcome is good in the majority of cases, across kidney function levels and survival is increasing.
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9.
  • Bergström, Mattias, et al. (författare)
  • Pulseless electrical activity is associated with improved survival in out-of-hospital cardiac arrest with initial non-shockable rhythm.
  • 2018
  • Ingår i: Resuscitation. - : Elsevier BV. - 0300-9572 .- 1873-1570. ; 133, s. 147-152
  • Tidskriftsartikel (refereegranskat)abstract
    • OBJECTIVE: To describe the prevalence, baseline characteristics and factors associated with survival in out-of-hospital cardiac arrest (OHCA) with initial non-shockable rhythm sub-grouped into pulseless electrical activity (PEA) and asystole as presenting rhythm.METHODS: The Swedish Registry of Cardiopulmonary Resuscitation is a prospectively recorded nationwide registry of modified Utstein parameters, including all patients with attempted resuscitation after OHCA. Data between 1990-2016 were analyzed.RESULTS: After exclusions, the study population consisted of 48,707 patients presenting with either PEA or asystole. The proportion of PEA increased from 12% to 22% during the study period with a fivefold increase in 30-day survival reaching 4.9%. Survival in asystole showed a modest increase from 0.6% to 1.3%. In the multivariable analysis, PEA was independently associated with survival at 30 days (OR 1.54, 95% CI 1.26-1.88).CONCLUSION: Between 1990 and 2016, the proportion of PEA as the first recorded rhythm doubled with a five-fold increase in 30-day survival, while survival among patients with asystole remained at low levels. PEA and asystole should be considered separate entities in clinical decision-making and be reported separately in observational studies and clinical trials.
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10.
  • Blennow Nordström, Erik, et al. (författare)
  • Neuropsychological outcome after cardiac arrest : results from a sub-study of the targeted hypothermia versus targeted normothermia after out-of-hospital cardiac arrest (TTM2) trial
  • 2023
  • Ingår i: Critical Care. - : BioMed Central (BMC). - 1364-8535 .- 1466-609X. ; 27:1
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Cognitive impairment is common following out-of-hospital cardiac arrest (OHCA), but the nature of the impairment is poorly understood. Our objective was to describe cognitive impairment in OHCA survivors, with the hypothesis that OHCA survivors would perform significantly worse on neuropsychological tests of cognition than controls with acute myocardial infarction (MI). Another aim was to investigate the relationship between cognitive performance and the associated factors of emotional problems, fatigue, insomnia, and cardiovascular risk factors following OHCA.METHODS: This was a prospective case-control sub-study of The Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial. Eight of 61 TTM2-sites in Sweden, Denmark, and the United Kingdom included adults with OHCA of presumed cardiac or unknown cause. A matched non-arrest control group with acute MI was recruited. At approximately 7 months post-event, we administered an extensive neuropsychological test battery and questionnaires on anxiety, depression, fatigue, and insomnia, and collected information on the cardiovascular risk factors hypertension and diabetes.RESULTS: Of 184 eligible OHCA survivors, 108 were included, with 92 MI controls enrolled. Amongst OHCA survivors, 29% performed z-score ≤ - 1 (at least borderline-mild impairment) in ≥ 2 cognitive domains, 14% performed z-score ≤ - 2 (major impairment) in ≥ 1 cognitive domain while 54% performed without impairment in any domain. Impairment was most pronounced in episodic memory, executive functions, and processing speed. OHCA survivors performed significantly worse than MI controls in episodic memory (mean difference, MD = - 0.37, 95% confidence intervals [- 0.61, - 0.12]), verbal (MD = - 0.34 [- 0.62, - 0.07]), and visual/constructive functions (MD = - 0.26 [- 0.47, - 0.04]) on linear regressions adjusted for educational attainment and sex. When additionally adjusting for anxiety, depression, fatigue, insomnia, hypertension, and diabetes, executive functions (MD = - 0.44 [- 0.82, - 0.06]) were also worse following OHCA. Diabetes, symptoms of anxiety, depression, and fatigue were significantly associated with worse cognitive performance.CONCLUSIONS: In our study population, cognitive impairment was generally mild following OHCA. OHCA survivors performed worse than MI controls in 3 of 6 domains. These results support current guidelines that a post-OHCA follow-up service should screen for cognitive impairment, emotional problems, and fatigue.TRIAL REGISTRATION: ClinicalTrials.gov, NCT03543371. Registered 1 June 2018.
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