The Value of Ischemic Cardiac Biomarkers to Predict Spontaneous Breathing Trial or Extubation Failure:A Systematic Review

Background: It is unclear whether other cardiac biomarkers than NT-proBNP can be useful in the risk stratification of patients weaning from mechanical ventilation. The aim of this study is to summarize the role of ischemic cardiac biomarkers in predicting spontaneous breathing trial (SBT) or extubation failure. Methods: We systematically searched Embase, MEDLINE, Web of Science, and Cochrane Central for studies published before January 2024 that reported the association between ischemic cardiac biomarkers and SBT or extubation failure. Data were extracted using a standardized form and methodological assessment was performed using the QUIPS tool. Results: Seven observational studies investigating four ischemic cardiac biomarkers (Troponin-T, Troponin-I, CK-MB, Myoglobin) were included. One study reported a higher peak Troponin-I in patients with extubation failure compared to extubation success (50 ng/L [IQR, 20–215] versus 30 ng/L [IQR, 10–86], p = 0.01). A second study found that Troponin-I measured before the SBT was higher in patients with SBT failure in comparison to patients with SBT success (100 ± 80 ng/L versus 70 ± 130 ng/L, p = 0.03). A third study reported a higher CK-MB measured at the end of the SBT in patients with weaning failure (SBT or extubation failure) in comparison to weaning success (8.77 ± 20.5 ng/mL versus 1.52 ± 1.42 ng/mL, p = 0.047). Troponin-T and Myoglobin as well as Troponin-I and CK-MB measured at other time points were not found to be related to SBT or extubation failure. However, most studies were underpowered and with high risk of bias. Conclusions: The association with SBT or extubation failure is limited for Troponin-I and CK-MB and appears absent for Troponin-T and Myoglobin, but available studies are hampered by significant methodological drawbacks. To more definitively determine the role of ischemic cardiac biomarkers, future studies should prioritize larger sample sizes, including patients at risk of cardiac disease, using stringent SBTs and structured timing of laboratory measurements before and after SBT.</p

Integrated care in patients with atrial fibrillation- a predictive heterogeneous treatment effect analysis of the ALL-IN trial

Introduction:Integrated care is effective in reducing all-cause mortality in patients with atrial fibrillation (AF) in primary care, though time and resource intensive. The aim of the current study was to assess whether integrated care should be directed at all AF patients equally. Methods:The ALL-IN trial (n = 1,240 patients, median age 77 years) was a cluster-randomized trial in which primary care practices were randomized to provide integrated care or usual care to AF patients aged 65 years and older. Integrated care comprised of (i) anticoagulation monitoring, (ii) quarterly checkups and (iii) easy-access consultation with cardiologists. For the current analysis, cox proportional hazard analysis with all clinical variables from the CHA2DS2-VASc score was used to predict all-cause mortality in the ALL-IN trial. Subsequently, the hazard ratio and absolute risk reduction were plotted as a function of this predicted mortality risk to explore treatment heterogeneity. Results:Under usual care, after a median of 2 years follow-up the absolute risk of all-cause mortality in the highest-risk quarter was 31.0%, compared to 4.6% in the lowest-risk quarter. On the relative scale, there was no evidence of treatment heterogeneity (p for interaction = 0.90). However, there was substantial treatment heterogeneity on the absolute scale: risk reduction in the lowest risk- quarter of risk 3.3% (95% CI -0.4% - 7.0) compared to 12.0% (95% CI 2.7% - 22.0) in the highest risk quarter. Conclusion:While the relative degree of benefit from integrated AF care is similar in all patients, patients with a high all-cause mortality risk have a greater benefit on an absolute scale and should therefore be prioritized when implementing integrated care.</p

Integrated management of atrial fibrillation in primary care:results of the ALL-IN cluster randomized trial

Aims To evaluate whether integrated care for atrial. fibrillation (AF) can be safely orchestrated in primary care. Methods and results The ALL-IN trial was a cluster randomized, open-label, pragmatic non-inferiority trial performed in primary care practices in the Netherlands. We randomized 26 practices: 15 to the integrated care intervention and 11 to usual care. The integrated care intervention consisted of (i) quarterly AF check-ups by trained nurses in primary care, also focusing on possibly interfering comorbidities, (ii) monitoring of anticoagulation therapy in primary care, and finally (iii) easy-access availability of consultations from cardiologists and anticoagulation clinics. The primary endpoint was all-cause mortality during 2 years of follow-up. In the intervention arm, 527 out of 941 eligible AF patients aged >65 years provided informed consent to undergo the intervention. These 527 patients were compared with 713 AF patients in the control arm receiving usual care. Median age was 77 (interquartile range 72-83) years. The all-cause mortality rate was 3.5 per 100 patient-years in the intervention arm vs. 6.7 per 100 patient-years in the control arm [adjusted hazard ratio (HR) 0.55; 95% confidence interval (CI) 0.37-0.82]. For non cardiovascular mortality, the adjusted HR was 0.47 (95% CI 0.27-0.82). For other adverse events, no statistically significant differences were observed. Conclusion In this cluster randomized trial, integrated care for elderly AF patients in primary care showed a 45% reduction in all-cause mortality when compared with usual care

Managing the Increasing Burden of Atrial Fibrillation through Integrated Care in Primary Care: A Cost-Effectiveness Analysis

INTRODUCTION: Integrated care for patients with atrial fibrillation (AF) in primary care reduced mortality compared to usual care. We assessed the cost-effectiveness of this approach. METHODS: Dutch primary care practices were randomised to provide integrated care for AF patients or usual care. A cost-effectiveness analysis was performed from a societal perspective with a 2-year time horizon to estimate incremental costs and Quality Adjusted Life Years (QALYs). A sensitivity analysis was performed, imputing missing questionnaires for a large group of usual care patients. RESULTS: 522 patients from 15 intervention practices were compared to 425 patients from 11 usual care practices. No effect on QALYs was seen, while mean costs indicated a cost reduction between €865 (95% percentile interval (PI) -€5730 to €3641) and €1343 (95% PI -€6534 to €3109) per patient per 2 years. The cost-effectiveness probability ranged between 36% and 54%. In the sensitivity analysis, this increased to 95%-99%. DISCUSSION: Results should be interpreted with caution due to missing information for a large proportion of usual care patients. CONCLUSION: The higher costs from extra primary care consultations were likely outweighed by cost reductions for other resources, yet this study doesn't give sufficient clarity on the cost-effectiveness of integrated AF care

Safety of off-label dose reduction of non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation

Aim: To investigate the effects of off-label non-vitamin K oral anticoagulant (NOAC) dose reduction compared with on-label standard dosing in atrial fibrillation (AF) patients in routine care. Methods: Population-based cohort study using data from the United Kingdom Clinical Practice Research Datalink, comparing adults with non-valvular AF receiving an off-label reduced NOAC dose to patients receiving an on-label standard dose. Outcomes were ischaemic stroke, major/non-major bleeding and mortality. Inverse probability of treatment weighting and inverse probability of censoring weighting on the propensity score were applied to adjust for confounding and informative censoring. Results: Off-label dose reduction occurred in 2466 patients (8.0%), compared with 18 108 (58.5%) on-label standard-dose users. Median age was 80 years (interquartile range [IQR] 73.0-86.0) versus 72 years (IQR 66-78), respectively. Incidence rates were higher in the off-label dose reduction group compared to the on-label standard dose group, for ischaemic stroke (0.94 vs 0.70 per 100 person years), major bleeding (1.48 vs 0.83), non-major bleeding (6.78 vs 6.16) and mortality (10.12 vs 3.72). Adjusted analyses resulted in a hazard ratio of 0.95 (95% confidence interval [CI] 0.57-1.60) for ischaemic stroke, 0.88 (95% CI 0.57-1.35) for major bleeding, 0.81 (95% CI 0.67-0.98) for non-major bleeding and 1.34 (95% CI 1.12-1.61) for mortality. Conclusion: In this large population-based study, the hazards for ischaemic stroke and major bleeding were low, and similar in AF patients receiving an off-label reduced NOAC dose compared with on-label standard dose users, while non-major bleeding risk appeared to be lower and mortality risk higher. Caution towards prescribing an off-label reduced NOAC dose is therefore required

Clinical consequences of off-label reduced dosing of non-vitamin K antagonist oral anticoagulants in patients with atrial fibrillation: a systematic review and meta-analysis

OBJECTIVE: Postmarketing observational studies report that a substantial percentage of patients with atrial fibrillation (AF) receive a reduced non-vitamin K antagonist oral anticoagulant (NOAC) dose without a clear indication. Recently, increasing evidence has become available to explore the clinical consequences of such off-label reduced dosing (OLRD). This study aims to systematically review and meta-analyse observational studies that report clinical outcomes associated with OLRD of NOACs compared with on-label non-reduced dosing (OLNRD) of NOACs in patients with AF. METHODS AND ANALYSIS: We performed a systematic literature review and meta-analysis of observational studies reporting clinical outcomes in AF patients with OLRD of an NOAC compared with AF patients with OLNRD of an NOAC. Using random effects meta-analyses, we estimated the risk of stroke/thromboembolism, bleeding and all-cause mortality. RESULTS: We included 19 studies with a total of 170 394 NOAC users. In these studies, the percentage of OLRD among patients with an indication for an on-label non-reduced NOAC dose ranged between 9% and 53%. 7 of these 19 studies met the predefined criteria for meta-analysis (n=80 725 patients). The pooled HR associated with OLRD of NOACs was 1.04 (95% CI 0.83 to 1.29; 95% prediction interval (PI) 0.60 to 1.79) for stroke/thromboembolism, 1.10 (95% CI 0.95 to 1.29; 95% PI 0.81 to 1.50) for bleeding and 1.22 (95% CI 0.81 to 1.84; 95% PI 0.55 to 2.70) for all-cause mortality. CONCLUSION: This meta-analysis shows no statistically significant increased risk of stroke/thromboembolism, nor a decreased bleeding risk, nor a difference in risk of all-cause mortality in patients with OLRD of NOACs. Future research may focus on differences between NOACs

Limited incremental predictive value of the frailty index and other vulnerability measures from routine care data for mortality risk prediction in older patients with COVID-19 in primary care

BACKGROUND: During the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of vulnerability measures in COVID-19 patients in primary care was lacking. Still, knowledge on the role of vulnerability is pivotal in understanding the resilience of older people during acute illness, and hence important for future pandemic preparedness. Therefore, we assessed the predictive value of different routine care-based vulnerability measures in addition to age and sex for 28-day mortality in an older primary care population of patients with COVID-19. METHODS: From primary care medical records using three routinely collected Dutch primary care databases, we included all patients aged 70 years or older with a COVID-19 diagnosis registration in 2020 and 2021. All-cause mortality was predicted using logistic regression based on age and sex only (basic model), and separately adding six vulnerability measures: renal function, cognitive impairment, number of chronic drugs, Charlson Comorbidity Index, Chronic Comorbidity Score, and a Frailty Index. Predictive performance of the basic model and the six vulnerability models was compared in terms of area under the receiver operator characteristic curve (AUC), index of prediction accuracy and the distribution of predicted risks. RESULTS: Of the 4,065 included patients, 9% died within 28 days after COVID-19 diagnosis. Predicted mortality risk ranged between 7-26% for the basic model including age and sex, changing to 4-41% by addition of comorbidity-based vulnerability measures (Charlson Comorbidity Index, Chronic Comorbidity Score), more reflecting impaired organ functioning. Similarly, the AUC of the basic model slightly increased from 0.69 (95%CI 0.66 - 0.72) to 0.74 (95%CI 0.71 - 0.76) by addition of either of these comorbidity scores. Addition of a Frailty Index, renal function, the number of chronic drugs or cognitive impairment yielded no substantial change in predictions. CONCLUSION: In our dataset of older COVID-19 patients in primary care, the 28-day mortality fraction was substantial at 9%. Six different vulnerability measures had little incremental predictive value in addition to age and sex in predicting short-term mortality

Integrated care in patients with atrial fibrillation- a predictive heterogeneous treatment effect analysis of the ALL-IN trial

INTRODUCTION: Integrated care is effective in reducing all-cause mortality in patients with atrial fibrillation (AF) in primary care, though time and resource intensive. The aim of the current study was to assess whether integrated care should be directed at all AF patients equally. METHODS: The ALL-IN trial (n = 1,240 patients, median age 77 years) was a cluster-randomized trial in which primary care practices were randomized to provide integrated care or usual care to AF patients aged 65 years and older. Integrated care comprised of (i) anticoagulation monitoring, (ii) quarterly checkups and (iii) easy-access consultation with cardiologists. For the current analysis, cox proportional hazard analysis with all clinical variables from the CHA2DS2-VASc score was used to predict all-cause mortality in the ALL-IN trial. Subsequently, the hazard ratio and absolute risk reduction were plotted as a function of this predicted mortality risk to explore treatment heterogeneity. RESULTS: Under usual care, after a median of 2 years follow-up the absolute risk of all-cause mortality in the highest-risk quarter was 31.0%, compared to 4.6% in the lowest-risk quarter. On the relative scale, there was no evidence of treatment heterogeneity (p for interaction = 0.90). However, there was substantial treatment heterogeneity on the absolute scale: risk reduction in the lowest risk- quarter of risk 3.3% (95% CI -0.4% - 7.0) compared to 12.0% (95% CI 2.7% - 22.0) in the highest risk quarter. CONCLUSION: While the relative degree of benefit from integrated AF care is similar in all patients, patients with a high all-cause mortality risk have a greater benefit on an absolute scale and should therefore be prioritized when implementing integrated care

Health insurance competition: the effect of group contracts

In countries like the US and the Netherlands health insurance is provided by private firms. These private firms can offer both individual and group contracts. The strategic and welfare implications of such group contracts are not well understood. Using a Dutch data set of about 700 group health insurance contracts over the period 2007-2008, we estimate a model to determine which factors explain the price of group contracts. We find that groups that are located close to an insurers' home turf pay a higher premium than other groups. This finding is not consistent with the bargaining argument in the literature as it implies that concentrated groups close to an insurer's home turf should get (if any) a larger discount than other groups. A simple Hotelling model, however, does explain our empirical results.health insurance; health-plan choice; managed competition