Introduction: Atrial fi brillation (AF) poses a significant risk of stroke. Left atrial appendage occlusion (LAAO) is an alternative for patients with contraindications to oral anticoagulation (OAC) or with high risk of bleeding. This study aims to compare the outcomes of LAAO versus conventional stroke prevention in high-risk AF-patients. Methods: This secondary analysis incorporates data from the prospective Swiss-AF and Beat-AF cohorts, and the Zurich LAAO Registry. Cardinality matching was performed to create two comparable cohorts: conventional treatment (92% OAC) and LAAO. The primary endpoint was a composite of stroke, cardiovascular (CV) death, and clinically relevant bleeding. Kaplan-Meier method with competing risk analysis was used. Results: Each group included 468 patients (age 76.4 [70.5, 82.0] years, 33% female). The LAAO group exhibited higher baseline bleeding risk (HAS BLED 2.0 [1.0-3.0] versus 3.0 [3.0-4.0]; p < 0.001). Median follow-up time: 6.0 (4.7-7.0) years in conventional treatment group and 4.0 (1.5-6.1) in LAAO group. No significant difference in the primary composite endpoint (HR 0.87, 95% CI: 0.72-1.06, p = 0.18), stroke risk (HR 1.14, 95% CI: 0.66-1.97, p = 0.64), or CV mortality (HR 1.08, 95% CI: 0.82-1.42, p = 0.60) was observed between groups. LAAO correlated with a significantly lower risk of clinically relevant bleeding (HR 0.61, 95% CI: 0.47-0.80, p < 0.001). Conclusion: In this cardinality matched analysis with long-term follow-up, LAAO showed similar stroke and CV death rates but lower clinically relevant bleeding risk compared to conventional therapy in high-risk AF-patients. (c) 2024 The Author(s).

Anna Altermatt,* Tim Sinnecker,* Stefanie Aeschbacher, Anne Springer, Michael Coslovsky, Juerg Beer, Giorgio Moschovitis, Angelo Auricchio, Urs Fischer, Carole E. Aubert, Michael Kühne, David Conen, Stefan Osswald, Leo H. Bonati, Jens Wuerfel, for the Swiss-AF Study Investigators Medical Image Analysis Center (MIAC AG), Basel, Switzerland Department of Biomedical Engineering, University of Basel, Basel, Switzerland Department of Neurology, University Hospital Basel, Basel, Switzerland Cardiology Division, Department of Medicine, University Hospital Basel, University of Basel, Basel, Switzerland Cardiovascular Research Institute Basel, University Hospital Basel, University of Basel, Basel, Switzerland Clinical Trial Unit, Department of Clinical Research, University Hospital Basel, University of Basel, Basel, Switzerland Department of Medicine, Baden Cantonal Hospital, Baden, Switzerland Division of Cardiology, Department of Medicine, Ente Ospedaliero Cantonale (EOC), Regional Hospital of Lugano, Lugano, Switzerland Division of Cardiology, Fondazione Cardiocentro Ticino, Lugano, Switzerland Department of Neurology, Inselspital, University Hospital of Bern, University of Bern, Bern, Switzerland Department of General Internal Medicine, Inselspital, University Hospital of Bern, Bern, Switzerland Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI, USA Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA Population Health Research Institute, McMaster University, Hamilton, ON, Canada NeuroCure Research Center, Charité University Medicine Berlin, Berlin, Germany

IMPORTANCE Whether interprofessional collaboration is effective and safe in decreasing hospital length of stay remains controversial. OBJECTIVE To evaluate the outcomes and safety associated with an electronic interprofessional-led discharge planning tool vs standard discharge planning to safely reduce length of stay among medical inpatients with multimorbidity. DESIGN, SETTING, AND PARTICIPANTS This multicenter prospective nonrandomized controlled trial used interrupted time series analysis to examine medical acute hospitalizations at 82 hospitals in Switzerland. It was conducted from February 2017 through January 2019. Data analysis was conducted from March 2021 to July 2022. INTERVENTION After a 12-month preintervention phase (February 2017 through January 2018), an electronic interprofessional-led discharge planning tool was implemented in February 2018 in 7 intervention hospitals in addition to standard discharge planning. MAIN OUTCOMES AND MEASURES Mixed-effects segmented regression analyses were used to compare monthly changes in trends of length of stay, hospital readmission, in-hospital mortality, and facility discharge after the implementation of the tool with changes in trends among control hospitals. RESULTS There were 54 695 hospitalizations at intervention hospitals, with 27 219 in the preintervention period (median [IQR] age, 72 [59-82] years; 14 400 [52.9%] men) and 27 476 in the intervention phase (median [IQR] age, 72 [59-82] years; 14 448 [52.6%] men) and 438 791 at control hospitals, with 216 261 in the preintervention period (median [IQR] age, 74 [60-83] years; 109 770 [50.8%] men) and 222 530 in the intervention phase (median [IQR] age, 74 [60-83] years; 113 053 [50.8%] men). The mean (SD) length of stay in the preintervention phase was 7.6 (7.1) days for intervention hospitals and 7.5 (7.4) days for control hospitals. During the preintervention phase, population-averaged length of stay decreased by -0.344 hr/mo (95% CI, -0.599 to -0.090 hr/mo) in control hospitals; however, no change in trend was observed among intervention hospitals (-0.034 hr/mo; 95% CI, -0.646 to 0.714 hr/mo; difference in slopes, P = .09). Over the intervention phase (February 2018 through January 2019), length of stay remained unchanged in control hospitals (slope, -0.011 hr/mo; 95% CI, -0.281 to 0.260 hr/mo; change in slope, P = .03), but decreased steadily among intervention hospitals by -0.879 hr/mo (95% CI, -1.607 to -0.150 hr/mo; change in slope, P = .04, difference in slopes, P = .03). Safety analyses showed no change in trends of hospital readmission, in-hospital mortality, or facility discharge over the whole study time. CONCLUSIONS AND RELEVANCE In this nonrandomized controlled trial, the implementation of an electronic interprofessional-led discharge planning tool was associated with a decline in length of stay without an increase in hospital readmission, in-hospital mortality, or facility discharge.

Objective: To evaluate if subclinical thyroid dysfunction is associated with cardiovascular (CV) risk in patients with atrial fibrillation (AF). Methods: Swiss-AF is a prospective cohort of community-dwelling participants aged >= 65 years with AF. Primary outcome was a composite endpoint of CV events (myocardial infarctions, stroke/transitory ischemic events, systemic embolism, heart failure (HF) hospitalizations, CV deaths). Secondary outcomes were component endpoints, total mortality, and AF-progression. Exposures were thyroid dysfunction categories, TSH and fT4. Sensitivity analyses were performed for amiodarone use, thyroid hormones use, and competing events. Results: 2415 patients were included (mean age: 73.2 years; 27% women). 196 (8.4%) had subclinical hypothyroidism and 53 (2.3%) subclinical hyperthyroidism. Subclinical thyroid dysfunction was not associated with CV events, during a median follow-up of 2.1 years (max 5 years): age- and sex-adjusted hazard ratio (adjHR) of 0.99 (95% CI: 0.69-1.41) for subclinical hypothyroidism and 0.55 (95% CI: 0.23-1.32) for subclinical hyperthyroidism. Results remained robust following multivariable adjustment and sensitivity analyses. In euthyroid patients, fT4 levels were associated with an increased risk for the composite endpoint and HF (adjHR: 1.46, 95% CI: 1.04-2.05; adjHR: 1.70, 95% CI: 1.08-2.66, respectively, for the highest quintile vs the middle quintile). Results remained similar following multivariable adjustment and remained significant for HF in sensitivity analyses. No association between subclinical thyroid dysfunction and total mortality or AF-progression was found. Conclusions: Subclinical hypothyroidism was not associated with increased CV risk in AF patients. Higher levels of fT4 with normal TSH were associated with a higher risk for HF.

Philipp Krisai, Ceylan Eken, Stefanie Aeschbacher, Michael Coslovsky, Vinzent Rolny, Desirée Carmine, Lorenzo Grazioli Gauthier, Jürg Beer, Laurent Roten, Oliver Baretella, Nicolas Rodondi, Leo H. Bonati, Christine S. Zuern, Christian Müller, David Conen, Michael Kühne, Stefan Osswald, for the Swiss-AF study investigators Cardiovascular Research Institute Basel, University Hospital Basel, Basel, Switzerland Electrophysiology and Ablation Unit and L’Institut de Rythmologie et Modélisation Cardiaque (LIRYC), University Hospital Bordeaux, BordeauxPessac, France Department of Cardiology, University Hospital Basel, Basel, Switzerland Roche Diagnostics GmbH, Penzberg, Germany Department of Internal Medicine, Regional Hospital Lugano, Ticino, Switzerland Department of Internal Medicine, Cantonal Hospital Baden, Baden, Switzerland Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland Institute of Primary Health Care (BIHAM), University of Bern, Bern, Switzerland Department of Neurology, University Hospital Basel, Basel, Switzerland Population Health Research Institute, McMaster University, Hamilton, ON, Canada Journal of Stroke 2021;23(3):449-452 https://doi.org/10.5853/jos.2021.02068

Background Impaired heart rate variability (HRV) is associated with increased mortality in sinus rhythm. However, HRV has not been systematically assessed in patients with atrial fibrillation (AF). We hypothesized that parameters of HRV may be predictive of cardiovascular death in patients with AF. Methods and Results From the multicenter prospective Swiss‐AF (Swiss Atrial Fibrillation) Cohort Study, we enrolled 1922 patients who were in sinus rhythm or AF. Resting ECG recordings of 5‐minute duration were obtained at baseline. Standard parameters of HRV (HRV triangular index, SD of the normal‐to‐normal intervals, square root of the mean squared differences of successive normal‐to‐normal intervals and mean heart rate) were calculated. During follow‐up, an end point committee adjudicated each cause of death. During a mean follow‐up time of 2.6±1.0 years, 143 (7.4%) patients died; 92 deaths were attributable to cardiovascular reasons. In a Cox regression model including multiple covariates (age, sex, body mass index, smoking status, history of diabetes mellitus, history of hypertension, history of stroke/transient ischemic attack, history of myocardial infarction, antiarrhythmic drugs including β blockers, oral anticoagulation), a decreased HRV index ≤ median (14.29), but not other HRV parameters, was associated with an increase in the risk of cardiovascular death (hazard ratio, 1.7; 95% CI, 1.1–2.6; P=0.01) and all‐cause death (hazard ratio, 1.42; 95% CI, 1.02–1.98; P=0.04). Conclusions The HRV index measured in a single 5‐minute ECG recording in a cohort of patients with AF is an independent predictor of cardiovascular mortality. HRV analysis in patients with AF might be a valuable tool for further risk stratification to guide patient management. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.

Emerging evidence suggests that atrial fibrillation is associated with cognitive dysfunction independently of stroke, but the underlying mechanisms remain unclear. In this cross-sectional analysis from the Swiss-atrial fibrillation Study (NCT02105844), we investigated the association of serum neurofilament light protein, a neuronal injury biomarker, with (i) the CHA(2)DS(2)-VASc score (congestive heart failure, hypertension, age 65-74 or >75 years, diabetes mellitus, stroke or transient ischaemic attack, vascular disease, sex), clinical and neuroimaging parameters and (ii) cognitive measures in atrial fibrillation patients. We measured neurofilament light in serum using an ultrasensitive single-molecule array assay in a sample of 1379 atrial fibrillation patients (mean age, 72 years; female, 27%). Ischaemic infarcts, small vessel disease markers and normalized brain volume were assessed on brain MRI. Cognitive testing included the Montreal cognitive assessment, trail-making test, semantic verbal fluency and digit symbol substitution test, which were summarized using principal component analysis. Results were analysed using univariable and multivariable linear regression. Neurofilament light was associated with the CHA(2)DS(2)-VASc score, with an average 19.2% [95% confidence interval (17.2%, 21.3%)] higher neurofilament per unit CHA(2)DS(2)-VASc increase. This association persisted after adjustment for age and MRI characteristics. In multivariable analyses, clinical parameters associated with neurofilament light were higher age [32.5% (27.2%, 38%) neurofilament increase per 10 years], diabetes mellitus, heart failure and peripheral artery disease [26.8% (16.8%, 37.6%), 15.7% (8.1%, 23.9%) and 19.5% (6.8%, 33.7%) higher neurofilament, respectively]. Mean arterial pressure showed a curvilinear association with neurofilament, with evidence for both an inverse linear and a U-shaped association. MRI characteristics associated with neurofilament were white matter lesion volume and volume of large non-cortical or cortical infarcts [4.3% (1.8%, 6.8%) and 5.5% (2.5%, 8.7%) neurofilament increase per unit increase in log-volume of the respective lesion], as well as normalized brain volume [4.9% (1.7%, 8.1%) higher neurofilament per 100 cm(3) smaller brain volume]. Neurofilament light was inversely associated with all cognitive measures in univariable analyses. The effect sizes diminished after adjusting for clinical and MRI variables, but the association with the first principal component was still evident. Our results suggest that in atrial fibrillation patients, neuronal loss measured by serum neurofilament light is associated with age, diabetes mellitus, heart failure, blood pressure and vascular brain lesions, and inversely correlates with normalized brain volume and cognitive function.

A comprehensive in-hospital patient management with reasonable and economic resource allocation is arguably the major challenge of health-care systems worldwide, especially in elderly, frail, and polymorbid patients. The need for patient management tools to improve the transition process and allocation of health care resources in routine clinical care particularly for the inpatient setting is obvious. To address these issues, a large prospective trial is warranted. The “Integrative Hospital Treatment in Older patients to benchmark and improve Outcome and Length of stay” (In-HospiTOOL) study is an investigator-initiated, multicenter effectiveness trial to compare the effects of a novel in-hospital management tool on length of hospital stay, readmission rate, quality of care, and other clinical outcomes using a time-series model. The study aims to include approximately 35`000 polymorbid medical patients over an 18-month period, divided in an observation, implementation, and intervention phase. Detailed data on treatment and outcome of polymorbid medical patients during the in-hospital stay and after 30 days will be gathered to investigate differences in resource use, inter-professional collaborations and to establish representative benchmarking data to promote measurement and display of quality of care data across seven Swiss hospitals. The trial will inform whether the “In-HospiTOOL” optimizes inter-professional collaboration and thereby reduces length of hospital stay without harming subjective and objective patient-oriented outcome markers. Many of the current quality-mirroring tools do not reflect the real need and use of resources, especially in polymorbid and elderly patients. In addition, a validated tool for optimization of patient transition and discharge processes is still missing. The proposed multicenter effectiveness trial has potential to improve interprofessional collaboration and optimizes resource allocation from hospital admission to discharge. The results will enable inter-hospital comparison of transition processes and accomplish a benchmarking for inpatient care quality.

Background A comprehensive in-hospital patient management with reasonable and economic resource allocation is arguably the major challenge of health-care systems worldwide, especially in elderly, frail, and polymorbid patients. The need for patient management tools to improve the transition process and allocation of health care resources in routine clinical care particularly for the inpatient setting is obvious. To address these issues, a large prospective trial is warranted. Methods The “Integrative Hospital Treatment in Older patients to benchmark and improve Outcome and Length of stay” (In-HospiTOOL) study is an investigator-initiated, multicenter effectiveness trial to compare the effects of a novel in-hospital management tool on length of hospital stay, readmission rate, quality of care, and other clinical outcomes using a time-series model. The study aims to include approximately 35`000 polymorbid medical patients over an 18-month period, divided in an observation, implementation, and intervention phase. Detailed data on treatment and outcome of polymorbid medical patients during the in-hospital stay and after 30 days will be gathered to investigate differences in resource use, inter-professional collaborations and to establish representative benchmarking data to promote measurement and display of quality of care data across seven Swiss hospitals. The trial will inform whether the “In-HospiTOOL” optimizes inter-professional collaboration and thereby reduces length of hospital stay without harming subjective and objective patient-oriented outcome markers. Discussion Many of the current quality-mirroring tools do not reflect the real need and use of resources, especially in polymorbid and elderly patients. In addition, a validated tool for optimization of patient transition and discharge processes is still missing. The proposed multicenter effectiveness trial has potential to improve interprofessional collaboration and optimizes resource allocation from hospital admission to discharge. The results will enable inter-hospital comparison of transition processes and accomplish a benchmarking for inpatient care quality.