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BackgroundMeasuring the performance of models that predict individualized treatment effect is challenging because the outcomes of two alternative treatments are inherently unobservable in one patient. The C-for-benefit was proposed to measure discriminative ability. However, measures of calibration and overall performance are still lacking. We aimed to propose metrics of calibration and overall performance for models predicting treatment effect.MethodsSimilar to the previously proposed C-for-benefit, we defined observed pairwise treatment effect as the difference between outcomes in pairs of matched patients with different treatment assignment. We redefined the E-statistics, the cross-entropy, and the Brier score into metrics for measuring a model’s ability to predict treatment effect. In a simulation study, the metric values of deliberately “perturbed models” were compared to those of the data-generating model, i.e., “optimal model”. To illustrate these performance metrics, different modeling approaches for predicting treatment effect are applied to the data of the Diabetes Prevention Program: 1) a risk modelling approach with restricted cubic splines; 2) an effect modelling approach including penalized treatment interactions; and 3) the causal forest.ResultsAs desired, performance metric values of “perturbed models” were consistently worse than those of the “optimal model” (Eavg-for-benefit≥0.070 versus 0.001, E90-for-benefit≥0.115 versus 0.003, cross-entropy-for-benefit≥0.757 versus 0.733, Brier-for-benefit≥0.215 versus 0.212). Calibration, discriminative ability, and overall performance of three different models were similar in the case study. The proposed metrics were implemented in a publicly available R-package “HTEPredictionMetrics”.ConclusionThe proposed metrics are useful to assess the calibration and overall performance of models predicting treatment effect.

There is a discrepancy between successful recanalization and good clinical outcome after endovascular treatment (EVT) in acute ischemic stroke patients. During removal of a thrombus, a shower of microemboli may release and lodge to the distal circulation. The objective of this study was to determine the extent of damage on brain tissue caused by microemboli. In a rat model of microembolization, a mixture of microsphere (MS) sizes (15, 25 and 50 µm diameter) was injected via the left internal carotid artery. A 3D image of the left hemisphere was reconstructed and a point-pattern spatial analysis was applied based on G- and K-functions to unravel the spatial correlation between MS and the induced hypoxia or infarction. We show a spatial correlation between MS and hypoxia or infarction spreading up to a distance of 1000–1500 µm. These results imply that microemboli, which individually may not always be harmful, can interact and result in local areas of hypoxia or even infarction when lodged in large numbers.

Background Patients with major trauma might benefit from treatment in a trauma centre, but early identification of major trauma (Injury Severity Score (ISS) over 15) remains difficult. The aim of this study was to undertake an external validation of existing prognostic models for injured patients to assess their ability to predict mortality and major trauma in the prehospital setting. Methods Prognostic models were identified through a systematic literature search up to October 2017. Injured patients transported by Emergency Medical Services to an English hospital from the Trauma Audit and Research Network between 2013 and 2016 were included. Outcome measures were major trauma (ISS over 15) and in‐hospital mortality. The performance of the models was assessed in terms of discrimination (concordance index, C‐statistic) and net benefit to assess the clinical usefulness. Results A total of 154 476 patients were included to validate six previously proposed prediction models. Discriminative ability ranged from a C‐statistic value of 0·602 (95 per cent c.i. 0·596 to 0·608) for the Mechanism, Glasgow Coma Scale, Age and Arterial Pressure model to 0·793 (0·789 to 0·797) for the modified Rapid Emergency Medicine Score (mREMS) in predicting in‐hospital mortality (11 882 patients). Major trauma was identified in 52 818 patients, with discrimination from a C‐statistic value of 0·589 (0·586 to 0·592) for mREMS to 0·735 (0·733 to 0·737) for the Kampala Trauma Score in predicting major trauma. None of the prediction models met acceptable undertriage and overtriage rates. Conclusion Currently available prehospital trauma models perform reasonably in predicting in‐hospital mortality, but are inadequate in identifying patients with major trauma. Future research should focus on which patients would benefit from treatment in a major trauma centre., Currently available prehospital trauma models perform reasonably in predicting in‐hospital mortality, but are inadequate at identifying patients who have experienced major trauma. Future research should focus on which patients would benefit from treatment in a major trauma centre. TP, true‐positive; FP, false‐positive; MGAP, Mechanism, Glasgow Coma Scale, Age and Arterial Pressure; PSS, Physiologic Severity Score; T‐RTS, Triage Revised Trauma Score; PHI, Prehospital Index; mREMS, modified Rapid Emergency Medicine Score; KTS, Kampala Trauma Score. Useful in predicting mortality but not major trauma

Contains fulltext : 220823.pdf (Publisher’s version ) (Closed access) Before 2015, endovascular treatment (EVT) for acute ischemic stroke was considered a promising treatment option. Based on limited evidence, it was performed in several dedicated stroke centers worldwide on selected patients. Since 2015, EVT for patients with intracranial large vessel occlusion has quickly been implemented as standard treatment in many countries worldwide, supported by the revised international guidelines based on solid evidence from multiple clinical trials. We describe the development in use of EVT in the Netherlands before, during, and after the pivotal EVT trials. We used data from all patients who were treated with EVT in the Netherlands from January 2002 until December 2018. We undertook a time-series analysis to examine trends in the use of EVT using Poisson regression analysis. Incidence rate ratios per year with 95% CIs were obtained to demonstrate the impact and implementation after the publication of the EVT trial results. We made regional observation plots, adjusted for stroke incidence, to assess the availability and use of the treatment in the country. In the buildup to the MR CLEAN (Multicenter Clinical Trial of Endovascular Treatment of Acute Ischemic Stroke in the Netherlands), a slow increase of EVT patients was observed, with 0.2% of all ischemic stroke patients receiving EVT. Before the trial results were formally announced, a statistically significant increase in EVT-treated patients per year was observed (incidence rate ratio, 1.72 [95% CI, 1.46-2.04]), and after the trial publication, an immediate steep increase was seen, followed by a more gradual increase (incidence rate ratio, 2.14 [95% CI, 1.77-2.59]). In 2018, the percentage of ischemic stroke patients receiving EVT increased to 5.8%. A well-developed infrastructure, a pragmatic approach toward the use of EVT in clinical practice, in combination with a strict adherence by the regulatory authorities to national evidence-based guidelines has led to successful implementation of EVT in the Netherlands. Ongoing efforts are directed at further increasing the proportion of stroke patients with EVT in all regions of the country.

ObjectiveTo compare outcomes after endovascular treatment (EVT) for acute ischemic stroke with 3 different types of anesthetic management in clinical practice, as anesthetic management may influence functional outcome.MethodsData of patients with an anterior circulation occlusion, included in the Dutch nationwide, prospective Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands (MR CLEAN) Registry between March 2014 and June 2016, were analyzed. Patients were divided into 3 groups defined by anesthetic technique performed during EVT: local anesthesia only (LA), general anesthesia (GA), or conscious sedation (CS). Primary outcome was the modified Rankin Scale score at 90 days. To compare functional outcome between groups, we estimated a common odds ratio (OR) with ordinal logistic regression, adjusted for age, sex, prestroke modified Rankin Scale score, baseline NIH Stroke Scale score, collaterals, and time from onset to arrival at intervention center.ResultsA total of 1,376 patients were included. Performed anesthetic technique was LA in 821 (60%), GA in 381 (28%), and CS in 174 (13%) patients. Compared to LA, both GA and CS were associated with worse functional outcome on the modified Rankin Scale score at 90 days (GA cORadj 0.75; 95% confidence interval [CI] 0.58–0.97; CS cORadj 0.45; 95% CI 0.33–0.62). CS was associated with worse functional outcome than GA (cORadj 0.60; 95% CI 0.42–0.87).ConclusionsLA is associated with better functional outcome than systemic sedation in patients undergoing EVT for acute ischemic stroke. Whereas LA had a clear advantage over CS, this was less prominent compared to GA.Classification of evidenceThis study provides Class III evidence that for patients with acute ischemic stroke undergoing EVT, LA improves functional outcome compared to GA or CS.

BACKGROUND AND PURPOSE: Thrombus CT characteristics might be useful for patient selection for intra-arterial treatment. Our objective was to study the association of thrombus CT characteristics with outcome and treatment effect in patients with acute ischemic stroke.MATERIALS AND METHODS: We included 199 patients for whom thin-section NCCT and CTA within 30 minutes from each other were available in the Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute ischemic stroke in the Netherlands (MR CLEAN) study. We assessed the following thrombus characteristics: location, distance from ICA terminus to thrombus, length, volume, absolute and relative density on NCCT, and perviousness. Associations of thrombus characteristics with outcome were estimated with univariable and multivariable ordinal logistic regression as an OR for a shift toward better outcome on the mRS. Interaction terms were used to investigate treatment-effect modification by thrombus characteristics.RESULTS: In univariate analysis, only the distance from the ICA terminus to the thrombus, length of >8 mm, and perviousness were associated with functional outcome. Relative thrombus density on CTA was independently associated with functional outcome with an adjusted common OR of 1.21 per 10% (95% CI, 1.02-1.43; P = .029). There was no treatment-effect modification by any of the thrombus CT characteristics.CONCLUSIONS: In our study on patients with large-vessel occlusion of the anterior circulation, CT thrombus characteristics appear useful for predicting functional outcome. However, in our study cohort, the effect of intra-arterial treatment was independent of the thrombus CT characteristics. Therefore, no arguments were provided to select patients for intra-arterial treatment using thrombus CT characteristics.

Objective The putative mechanism for the favourable effect of endovascular treatment (EVT) on functional outcome after acute ischaemic stroke is preventing follow-up infarct volume (FIV) progression. We aimed to assess to what extent difference in FIV explains the effect of EVT on functional outcome in a randomised trial of EVT versus no EVT (MR CLEAN). Methods FIV was assessed on non-contrast CT scan 5–7 days after stroke. Functional outcome was the score on the modified Rankin Scale at 3 months. We tested the causal pathway from intervention, via FIV to functional outcome with a mediation model, using linear and ordinal regression, adjusted for relevant baseline covariates, including stroke severity. Explained effect was assessed by taking the ratio of the log odds ratios of treatment with and without adjustment for FIV. Results Of the 500 patients included in MR CLEAN, 60 died and four patients underwent hemicraniectomy before FIV was assessed, leaving 436 patients for analysis. Patients in the intervention group had better functional outcomes (adjusted common odds ratio (acOR) 2.30 (95% CI 1.62–3.26) than controls and smaller FIV (median 53 vs. 81 ml) (difference 28 ml; 95% CI 13–41). Smaller FIV was associated with better outcome (acOR per 10 ml 0.60, 95% CI 0.52–0.68). After adjustment for FIV the effect of intervention on functional outcome decreased but remained substantial (acOR 2.05, 95% CI 1.44–2.91). This implies that preventing FIV progression explains 14% (95% CI 0–34) of the beneficial effect of EVT on outcome. Conclusion The effect of EVT on FIV explains only part of the treatment effect on functional outcome. Key Points • Endovascular treatment in acute ischaemic stroke patients prevents progression of follow-up infarct volume on non-contrast CT at 5–7 days. • Follow-up infarct volume was related to functional outcome, but only explained a modest part of the effect of intervention on functional outcome. • A large proportion of treatment effect on functional outcome remains unexplained, suggesting FIV alone cannot be used as an early surrogate imaging marker of functional outcome. Electronic supplementary material The online version of this article (10.1007/s00330-018-5578-9) contains supplementary material, which is available to authorized users.

OBJECTIVE:: External validation of prognostic models is crucial but rarely done. Our aim was to externally validate a prognostic model to predict 60-day case fatality after aneurysmal subarachnoid hemorrhage developed from the International Subarachnoid Aneurysm Trial in a retrospective unselected cohort of subarachnoid hemorrhage patients. DESIGN:: The model’s predictors were age, aneurysm size, Fisher grade, and World Federation of Neurological Surgeons grade. Two versions of the model were validated: one with World Federation of Neurological Surgeons grade scored at admission and the other with World Federation of Neurological Surgeons grade at treatment decision. The outcome was 60-day case fatality. Performance of the model was assessed by studying discrimination, expressed by the area under the receiver operating characteristic curve, and calibration. SETTING:: University hospital. PATIENTS:: We analyzed data from 307 consecutive aneurysmal subarachnoid hemorrhage patients admitted between 2007 and 2011 (validation cohort). INTERVENTIONS:: None. MEASUREMENTS AND MAIN RESULTS:: The observed 60-day case fatality rate was 30.6%. Discrimination was good, and differed between the model with World Federation of Neurological Surgeons grade at treatment decision (area under the receiver operating characteristic curve, 0.89) and at admission (area under the receiver operating characteristic curve, 0.82). Mean predicted probabilities were lower than observed: 17.0% (model with World Federation of Neurological Surgeons grade at admission) and 17.7% (model with World Federation of Neurological Surgeons grade at treatment decision). CONCLUSIONS:: The model discriminated well between patients who died or survived within 60 days. In addition, we found that using World Federation of Neurological Surgeons grade at moment of treatment decision of the ruptured aneurysm improved model performance. However, since predicted probabilities were much lower than observed probabilities, the International Subarachnoid Aneurysm Trial prediction model needs to be adapted to be used in clinical practice.

Purpose Even when the revascularization and clinical status of a patient after endovascular treatment (EVT) for acute ischemic stroke is known, outcome is still highly variable and difficult to predict. We aimed to develop a prognostic model that can be applied within one day after EVT to predict functional outcome at three months. Methods We used data from patients in the treatment arms of seven randomized controlled trials within the HERMES collaboration (MR CLEAN, ESCAPE, REVASCAT, SWIFT-PRIME, EXTEND-IA, THRACE, and PISTE). Primary outcome was the ordinal modified Rankin Scale (mRS) score three months after EVT. Fifteen pre- and post-procedural variables, assessed within one day after EVT, were analyzed with univariable ordinal logistic regression analysis and multivariable ordinal logistic regression analysis with stepwise backward selection (p Results The final model, based on 781 patients, included nine variables and explained 62.4% of the variance in outcome. Pre-procedural variables included age, diabetes mellitus, pre-stroke mRS, collateral vessel grade, occlusion location, and time from stroke onset to groin puncture. Post-procedural variables included revascularization grade, stroke severity measured with the National Institutes of Health Stroke Scale (NIHSS), and symptomatic intracranial hemorrhage. The NIHSS was the strongest predictor with 53.9% explained variance. The internally validated c-statistic was 0.83 for the prediction of the ordinal mRS, 0.89 for functional independence, and 0.80 for survival, indicating good model performance. Conclusions This model, which can be applied within one day after EVT, accurately predicts functional outcome at three months. It may provide physicians, patients, and family members with improved outcome expectations and improve decision making by personalizing the patients’ treatment and rehabilitation plan. Disclosures V. Chalos: None. E. Venema: None. M. Mulder: None. B. Roozenbeek: None. S. Brown: 2; C; Medtronic. A. Demchuk: 1; C; Covidien (Medtronic). 6; C; Covidien (Medtronic). C. Majoie: 1; C; Stryker. K. Muir: 1; C; Medtronic, Codman, Stroke Association, National Institute of Health Research (NIHR) Health Technology Assessment programme. 2; C; Medtronic. A. Davalos: 2; C; Medtronic Neurovascular. P. Mitchell: 1; C; Covidien (Medtronic), Medtronic, Stryker, Codman Johnson and Johnson. 2; C; Codman Johnson and Johnson. S. Bracard: None. M. Hill: 1; C; Covidien (Medtronic), Heart and Stroke Foundation, Alberta Innovates Health Solutions, Alberta Health Services. 4; C; Calgary Scientific Incorporated. 6; C; Merck, Hoff mann-La Roche Canada ltd. P. White: 1; C; Medtronic, Codman, Stroke Association, National Institute of Health Research (NIHR) Health Technology Assessment programme. 6; C; Microvention Terumo, Codman. B. Campbell: 1; C; Covidien (Medtronic), National Health and Medical Research Council of Australia, Royal Australasian College of Physicians, Royal Melbourne Hospital Foundation, National Heart Foundation, National Stroke Foundation of Australia, Royal Melbourne Hospital Foundation. F. Guillemin: None. J. Saver: 1; C; Medtronic, Stryker. 2; C; Medtronic/Covidien, Neuravi, Stryker, BrainsGate, Pfizer, Squibb, Boehringer Ingelheim (prevention only), ZZ Biotech, St. Jude Medical, Genentech. 4; C; Cognition Medical. T. Jovin: 2; C; Codman Neurovascular, Stryker, Neuravi, Medtronic. 4; C; Blockade, Silk Road. M. Goyal: 1; C; Medtronic, Stryker. 6; C; Medtronic, Stryker, Microvention, GE Healthcare. A. van der Lugt: 1; C; Dutch Heart Foundation, Dutch Brain Foundation, Stryker, Medtronic, Penumbra. 2; C; Stryker. D. Dippel: 1; C; Dutch Heart Foundation, Dutch Brain Foundation, AngioCare BV, Medtronic/Covidien/EV3, MEDAC Gmbh/LAMEPRO, Penumbra Inc, Stryker, Top Medical/Concentric. 2; C; Stryker, Bracco Imaging. H. Lingsma: None.

Background Benefit of endovascular treatment (EVT) varies between individual patients with acute ischemic stroke. The MR PREDICTS decision tool, previously developed in the MR CLEAN trial, predicts outcome with and without EVT based on baseline patient characteristics. We externally validated this model with data from recent EVT trials. Methods Individual patient data was derived from the six other randomized controlled trials within the HERMES collaboration (ESCAPE, REVASCAT, SWIFT-PRIME, EXTEND-IA, THRACE and PISTE). Outcome of the ordinal logistic regression model was the modified Rankin Scale (mRS) at 90 days after stroke. Discriminative performance was measured with the c-statistic, which ranges from 0.5 to 1.0. Model coefficients were updated after calibration. Results We included 1243 patients (633 assigned to EVT, 610 assigned to control). The observed probability of functional independence (defined as mRS 0–2) was higher than predicted for treated patients (35% vs 26%) and controls (54% vs 40%), but the observed treatment benefit was comparable. The c-statistic was 0.67 (95% confidence interval (CI) 0.65–0.69) for the ordinal mRS and 0.73 (95% CI 0.70–0.76) for functional independence, similar to previous performance. figure 1 shows a screenshot of the decision tool for use in clinical practice. Conclusion MR PREDICTS predicted outcome in a large heterogeneous trial population with discriminative value comparable to other well-known prediction tools. The updated model might be used to support clinical judgment in selection of patients for EVT. Disclosures E. Venema: None. M. Mulder: None. B. Roozenbeek: None. S. Brown: 2; C; Medtronic. C. Majoie: 1; C; Stryker. A. Demchuk: 1; C; Covidien (Medtronic). 6; C; Covidien (Medtronic). K. Muir: 1; C; Medtronic, Codman, Stroke Association, National Institute of Health Research (NIHR) Health Technology Assessment programme. 2; C; Medtronic. A. Davalos: 2; C; Medtronic Neurovascular. P. Mitchell: 1; C; Covidien (Medtronic), Codman Johnson and Johnson, Medtronic, Stryker. 2; C; Codman Johnson and Johnson. S. Bracard: None. M. Hill: 1; C; Covidien (Medtronic), Heart and Stroke Foundation, Alberta Innovates Health Solutions, Alberta Health Services. 4; C; Calgary Scientific Incorporated. 6; C; Merck, Hoff mann-La Roche Canada ltd. P. White: 1; C; Medtronic, Codman, Stroke Association, National Institute of Health Research (NIHR) Health Technology Assessment programme. 6; C; Microvention Terumo, Codman. B. Campbell: 1; C; National Health and Medical Research Council of Australia, Royal Australasian College of Physicians, Royal Melbourne Hospital Foundation, National Heart Foundation, National Stroke Foundation of Australia, Covidien (Medtronic). F. Guillemin: None. J. Saver: 1; C; Medtronic, Stryker. 2; C; Medtronic/Covidien, Stryker, Neuravi, BrainsGate, Pfizer, Squibb, Boehringer Ingelheim (prevention only), ZZ Biotech, St. Jude Medical, Genentech. 4; C; Cognition Medical. T. Jovin: 2; C; Codman Neurovascular, Stryker, Neuravi, Medtronic. 4; C; Blockade, Silk Road. M. Goyal: 1; C; Medtronic, Stryker. 6; C; Medtronic, Stryker, Microvention, GE Healthcare. A. van der Lugt: 1; C; Dutch Heart Foundation, Dutch Brain Foundation, Stryker, Medtronic, Penumbra. 2; C; Stryker. D. Dippel:1; C; Dutch Heart Foundation, Dutch Brain Foundation, AngioCare BV, Medtronic/Covidien/EV3, MEDAC Gmbh/LAMEPRO, Penumbra Inc, Stryker, Top Medical/Concentric. 2; C; Stryker, Bracco Imaging. H. Lingsma: None.

Lingsma HF, Steyerberg EW, Scholte op Reimer WJM, van Domburg R, Dippel DWJ, the Netherlands Stroke Survey Investigators. Statin treatment after a recent TIA or stroke: is effectiveness shown in randomized clinical trials also observed in everyday clinical practice? Acta Neurol Scand: 2010: 122: 15–20. © 2009 The Authors Journal compilation © 2009 Blackwell Munksgaard. Aim and background – The benefit of statin treatment in patients with a previous ischemic stroke or transient ischemic attack (TIA) has been demonstrated in randomized clinical trials (RCT). However, the effectiveness in everyday clinical practice may be decreased because of a different patient population and less controlled setting. We aim to describe statin use in an unselected cohort of patients, identify factors related to statin use and test whether the effect of statins on recurrent vascular events and mortality observed in RCTs is also observed in everyday clinical practice. Methods – In 10 centers in the Netherlands, patients admitted to the hospital or visiting the outpatient clinic with a recent TIA or ischemic stroke were prospectively and consecutively enrolled between October 2002 and May 2003. Statin use was determined at discharge and during follow-up. We used logistic regression models to estimate the effect of statins on the occurrence of vascular events (stroke or myocardial infarction) and mortality within 3 years. We adjusted for confounders with a propensity score that relates patient characteristics to the probability of using statins. Results – Of the 751 patients in the study, 252 (34%) experienced a vascular event within 3 years. Age, elevated cholesterol levels and other cardiovascular risk factors were associated with statin use at discharge. After 3 years, 109 of 280 (39%) of the users at discharge had stopped using statins. Propensity score adjusted analyses showed a beneficial effect of statins on the occurrence of the primary outcome (odds ratio 0.8, 95% CI: 0.6–1.2). Conclusion – In our study, we found poor treatment adherence to statins. Nevertheless, after adjustment for the differences between statin users and non-statin users, the observed beneficial effect of statins on the occurrence of vascular events within 3 years, although not statistically significant, is compatible with the effect observed in clinical trials.

Background Comparing and ranking hospitals based on health outcomes is becoming increasingly popular, although case-mix differences between hospitals and random variation are known to distort interpretation. The aim of this study was to explore whether surgical-site infection (SSI) rates are suitable for comparing hospitals, taking into account case-mix differences and random variation. Methods Data from the national surveillance network in the Netherlands, on the eight most frequently registered types of surgery for the year 2009, were used to calculate SSI rates. The variation in SSI rate between hospitals was estimated with multivariable fixed- and random-effects logistic regression models to account for random variation and case mix. ‘Rankability’ (as the reliability of ranking) of the SSI rates was calculated by relating within-hospital variation to between-hospital variation. Results Thirty-four hospitals reported on 13 629 patients, with overall SSI rates per surgical procedure varying between 0 and 15·1 per cent. Statistically significant differences in SSI rate between hospitals were found for colonic resection, caesarean section and for all operations combined. Rankability was 80 per cent for colonic resection but 0 per cent for caesarean section. Rankability was 8 per cent in all operations combined, as the differences in SSI rates were explained mainly by case mix. Conclusion When comparing SSI rates in all operations, differences between hospitals were explained by case mix. For individual types of surgery, case mix varied less between hospitals, and differences were explained largely by random variation. Although SSI rates may be used for monitoring quality improvement within hospitals, they should not be used for ranking hospitals.

ObjectivesThe aim of this study is to investigate whether variation in mortality at hospital level reflects differences in quality of care of peripheral vascular surgery patients.DesignObservational study.MaterialsIn 11 hospitals in the Netherlands, 711 consecutive vascular surgery patients were enrolled.MethodsMultilevel logistic regression models were used to relate patient characteristics, structure and process of care to mortality at 1 year. The models were constructed by consecutively adding age, sex and Lee index, then remaining risk factors, followed by structural measures for quality of care and finally, selected process of care parameters.ResultsTotal 1-year mortality was 11%, ranging from 6% to 26% in different hospitals. Large differences in patient characteristics and quality indicators were observed between hospitals (e.g., age>70 years: 28–58%; beta-blocker therapy: 39–87%). Adjusted analyses showed that a large part of variation in mortality was explained by age, sex and the Lee index (Akaike’s information criterion (AIC)=59, p