Refining the Association Between Body Mass Index and Atrial Fibrillation: G-Formula and Restricted Mean Survival Times

Modelling anticoagulation and health-related quality of life in those with atrial fibrillation: a secondary analysis of AFFIRM

Associations of anticoagulation with primary endpoints in longitudinal studies are impacted by selection bias and time-varying covariates (e.g. comorbidities). We demonstrate how time-varying covariates and selection bias influence association estimates between anticoagulation and health-related quality of life (HRQoL) in patients with atrial fibrillation. We performed a secondary analysis of the Atrial Fibrillation Follow-up Investigation of Rhythm Management trial quality of life substudy. Dichotomized warfarin use was ascertained at the study baseline, 2 months later, and annually for up to 6 years. HRQoL was measured at every time point using a self-reported ordinal 5-point Likert-scale (lower score and lower odds ratio represents better health-related quality of life). Static and time-varying covariates were ascertained throughout the study period. Confounder-adjusted generalized mixed model and generalized estimating equation regressions were used to demonstrate traditional association estimates between anticoagulation and HRQoL. Inverse probability of treatment and censorship weights were used to ascertain the influence of time-varying confounding and selection bias. Age-stratified analysis (age ≥ 70 years) evaluated for effect modification. 656 individuals were included in the analysis, 601 on warfarin at baseline. The association of warfarin use with better HRQoL over time strengthened when accounting for time-varying confounding and selection bias (OR 0.30, 95% CI 0.14-0.55) compared to traditional analyses (OR 0.61, 95% CI 0.38-0.97), and was most pronounced in those ≥ 70 years upon stratified analysis. Anticoagulation is associated with higher HRQoL in patients with atrial fibrillation, with time-varying confounding and selection bias likely influencing longitudinal estimates in anticoagulation-HRQoL research.

Association of Dynamic Trajectories of Time-Series Data and Life-Threatening Mass Effect in Large Middle Cerebral Artery Stroke

BACKGROUND

Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.

METHODS

We curated a retrospective data set of 635 patients with large middle cerebral artery stroke totaling 95,463 data points for 10 longitudinal covariates and 40 time-independent covariates. We assessed trajectories of the 10 longitudinal variables during the 72 h preceding three outcomes representative of life-threatening mass effect: midline shift ≥ 5 mm, pineal gland shift (PGS) > 4 mm, and decompressive hemicraniectomy (DHC). We used a "backward-looking" trajectory approach. Patients were aligned based on outcome occurrence time and the trajectory of each variable was assessed before that outcome by accounting for cases and noncases, adjusting for confounders. We evaluated longitudinal trajectories with Cox proportional time-dependent regression.

RESULTS

Of 635 patients, 49.0% were female, and the mean age was 69 years. Thirty five percent of patients had midline shift ≥ 5 mm, 24.3% of patients had PGS > 4 mm, and 10.7% of patients underwent DHC. Backward-looking trajectories showed mild increases in white blood cell count (10-11 K/UL within 72 h), temperature (up to half a degree within 24 h), and sodium levels (1-3 mEq/L within 24 h) before the three outcomes of interest. We also observed a decrease in heart rate (75-65 beats per minute) 24 h before DHC. We found a significant association between increased white blood cell count with PGS > 4 mm (hazard ratio 1.05, p value 0.007).

CONCLUSIONS

Longitudinal profiling adjusted for confounders demonstrated that white blood cell count, temperature, and sodium levels appear to increase before radiographic and clinical indicators of space-occupying mass effect. These findings will inform the development of multivariable dynamic risk models to aid prediction of life-threatening, space-occupying mass effect.

Dynamic trajectories of life-threatening mass effect in patients with large middle cerebral artery stroke

Background

Life-threatening, space-occupying mass effect due to cerebral edema and/or hemorrhagic transformation is an early complication of patients with middle cerebral artery (MCA) stroke. Little is known about longitudinal trajectories of laboratory and vital signs leading up to radiographic and clinical deterioration related to this mass effect.

Methods

We curated a granular retrospective dataset of 635 patients with large middle cerebral artery (MCA) stroke totaling 108,547 data points for repeated measurements of 10 covariates, and 40 time-independent covariates. We assessed longitudinal trajectories of the 10 longitudinal variables during the 72 hours preceding three outcomes representative of life-threatening mass effect: midline shift (MLS) ≥5mm, pineal gland shift (PGS) >4mm, and decompressive hemicraniectomy (DHC). We used a "backward looking" trajectory approach. Patients were aligned according to the time of outcome occurrence and the trajectory of each variable was assessed prior to that outcome by accounting for both cases and non-cases.

Results

Of 635 patients, 49% were female, and mean age was 69 years. Thirty five percent of patients had MLS ≥ 5mm, 24.1% had PGS >4mm, and DHC occurred in 10.7%. For the three outcomes of interest, backward-looking trajectories showed mild increases in white blood cell count (10 up to 11 K/UL within 72 hours), temperature (up to half a degree within 24 hours), and sodium (1-3 mEq/L within 24 hours) leading up to outcomes. We also observed a decrease in heart rate (75 - 65 beats per minute) 24 hours prior to DHC.

Conclusions

Univariable longitudinal profiling showed that temperature, white blood cell count, and sodium increase prior to radiographic and clinical indicators of space-occupying mass effect. These findings will inform development of multivariable dynamic risk models to aid prediction of life-threatening space-occupying mass effect.

Hypothetical interventions and risk of atrial fibrillation by sex and education: application of the parametric g-formula in the Tromsø Study

AIMS

To use the parametric g-formula to estimate the long-term risk of atrial fibrillation (AF) by sex and education under hypothetical interventions on six modifiable risk factors.

METHODS AND RESULTS

We estimated the risk reduction under hypothetical risk reduction strategies for smoking, physical activity, alcohol intake, body mass index, systolic, and diastolic blood pressure in 14 923 women and men (baseline mean age 45.8 years in women and 47.8 years in men) from the population-based Tromsø Study with a maximum of 22 years of follow-up (1994-2016). The estimated risk of AF under no intervention was 6.15% in women and 13.0% in men. This cumulative risk was reduced by 41% (95% confidence interval 17%, 61%) in women and 14% (-7%, 30%) in men under joint interventions on all risk factors. The most effective intervention was lowering body mass index to ≤ 25 kg/m2, leading to a 16% (4%, 25%) lower risk in women and a 14% (6%, 23%) lower risk in men. We found significant sex-differences in the relative risk reduction by sufficient physical activity, leading to a 7% (-4%, 18%) lower risk in women and an 8% (-2%, -13%) increased risk in men. We found no association between the level of education and differences in risk reduction by any of the interventions.

CONCLUSION

The population burden of AF could be reduced by modifying lifestyle risk factors. Namely, these modifications could have prevented 41% of AF cases in women and 14% of AF cases in men in the municipality of Tromsø, Norway during a maximum 22-year follow-up period.

Step Count, Self-reported Physical Activity, and Predicted 5-Year Risk of Atrial Fibrillation: Cross-sectional Analysis

BACKGROUND

Physical inactivity is a known risk factor for atrial fibrillation (AF). Wearable devices, such as smartwatches, present an opportunity to investigate the relation between daily step count and AF risk.

OBJECTIVE

The objective of this study was to investigate the association between daily step count and the predicted 5-year risk of AF.

METHODS

Participants from the electronic Framingham Heart Study used an Apple smartwatch. Individuals with diagnosed AF were excluded. Daily step count, watch wear time (hours and days), and self-reported physical activity data were collected. Individuals' 5-year risk of AF was estimated, using the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF score. The relation between daily step count and predicted 5-year AF risk was examined via linear regression, adjusting for age, sex, and wear time. Secondary analyses examined effect modification by sex and obesity (BMI≥30 kg/m²), as well as the relation between self-reported physical activity and predicted 5-year AF risk.

RESULTS

We examined 923 electronic Framingham Heart Study participants (age: mean 53, SD 9 years; female: n=563, 61%) who had a median daily step count of 7227 (IQR 5699-8970). Most participants (n=823, 89.2%) had a <2.5% CHARGE-AF risk. Every 1000 steps were associated with a 0.08% lower CHARGE-AF risk (P<.001). A stronger association was observed in men and individuals with obesity. In contrast, self-reported physical activity was not associated with CHARGE-AF risk.

CONCLUSIONS

Higher daily step counts were associated with a lower predicted 5-year risk of AF, and this relation was stronger in men and participants with obesity. The utility of a wearable daily step counter for AF risk reduction merits further investigation.

The impact of age and comorbidity on localized pancreatic cancer outcomes: A US retrospective cohort analysis with implications for surgical centralization

Introduction

Age and comorbidity are independently associated with worse outcomes for pancreatic adenocarcinoma (PDAC). However, the effect of combined age and comorbidity on PDAC outcomes has rarely been studied. This study assessed the impact of age and comorbidity (CACI) and surgical center volume on PDAC 90-day and overall survival (OS).

Methods

This retrospective cohort study used the National Cancer Database from 2004 to 2016 to evaluate resected stage I/II PDAC patients. The predictor variable, CACI, combined the Charlson/Deyo comorbidity score with additional points for each decade lived ≥50 years. The outcomes were 90-day mortality and OS.

Results

The cohort included 29,571 patients. Ninety-day mortality ranged from 2 % for CACI 0 to 13 % for CACI 6+ patients. There was a negligible difference (1 %) in 90-day mortality between high- and low-volume hospitals for CACI 0-2 patients; however, there was greater difference for CACI 3-5 (5 % vs. 9 %) and CACI 6+ (8 % vs. 15 %). The overall survival for CACI 0-2, 3-5, and 6+ cohorts was 24.1, 19.8, and 16.2 months, respectively. Adjusted overall survival showed a 2.7 and 3.1 month survival benefit for care at high-volume vs. low-volume hospitals for CACI 0-2 and 3-5, respectively. However, there was no OS volume benefit for CACI 6+ patients.

Conclusions

Combined age and comorbidity are associated with short- and long-term survival for resected PDAC patients. A protective effect of higher-volume care was more impactful for 90-day mortality for patients with a CACI above 3. A centralization policy based on volume may have greater benefit for older, sicker patients.

Key message

Combined comorbidity and age are strongly associated with 90-day mortality and overall survival for resected pancreatic cancer patients. When assessing the impact of age and comorbidity on resected pancreatic adenocarcinoma outcomes, 90-day mortality was 7 % higher (8 % vs. 15 %) for older, sicker patients treated at high-volume vs. low-volume centers but only 1 % (3 % vs. 4 %) for younger, healthier patients.

Body Mass Index in Adolescence and Long-Term Risk of Early Incident Atrial Fibrillation and Subsequent Mortality, Heart Failure, and Ischemic Stroke

Background We sought to determine the role of obesity in adolescent men on development of atrial fibrillation (AF) and subsequent associated clinical outcomes in subjects diagnosed with AF. Methods and Results We conducted a nationwide, register-based, cohort study of 1 704 467 men (mean age, 18.3±0.75 years) enrolled in compulsory military service in Sweden from 1969 through 2005. Height and weight, blood pressure, fitness, muscle strength, intelligence quotient, and medical disorders were recorded at baseline. Records obtained from the National Inpatient Registry and the Cause of Death Register were used to determine incidence and clinical outcomes of AF. During a median follow-up of 32 years (interquartile range, 24-41 years), 36 693 cases (mean age at diagnosis, 52.4±10.6 years) of AF were recorded. The multivariable-adjusted hazard ratio (HR) for AF increased from 1.06 (95% CI, 1.03-1.10) in individuals with body mass index (BMI) of 20.0 to <22.5 kg/m² to 3.72 (95% CI, 2.44-5.66) among men with BMI of 40.0 to 50.0 kg/m², compared with those with BMI of 18.5 to <20.0 kg/m². During a median follow-up of ≈6 years in patients diagnosed with AF, we identified 3767 deaths, 3251 cases of incident heart failure, and 921 cases of ischemic stroke. The multivariable-adjusted HRs for all-cause mortality, incident heart failure, and ischemic stroke in AF-diagnosed men with baseline BMI >30 kg/m² compared with those with BMI <20 kg/m² were 2.86 (95% CI, 2.30-3.56), 3.42 (95% CI, 2.50-4.68), and 2.34 (95% CI, 1.52-3.61), respectively. Conclusions Increasing BMI in adolescent men is strongly associated with early AF, and with subsequent worse clinical outcomes in those diagnosed with AF with respect to all-cause mortality, incident heart failure, and ischemic stroke.

Association of Weight at Different Ages and All-Cause Mortality Among Older Adults in the US

Objective: Assess the association of BMI and BMI change with mortality. Methods: Using data from the Wisconsin Longitudinal Study (WLS) on participants born mainly in 1939 (n=4922), we investigated the associations between various measures of BMI across the life course (age 54 BMI; age 65 BMI; age 72 BMI; lifetime maximum BMI; BMI change between ages 54 and 65; BMI change between ages 65 and 72) and mortality. We also assessed whether these associations are mediated by late life health. Results: BMI at age 54 was more strongly associated with late life mortality than BMI at older ages. The association between BMI change and mortality varied based on the timing of weight change. Health at age 72, particularly self-rated health, diabetes, and physical functioning, mediated the observed associations. Conclusion: Knowing older people's weight at midlife and how their weight has changed may be more important in assessing late life mortality risk than their current weight.

Temporal trends in cause-specific mortality among individuals with newly diagnosed atrial fibrillation in the Framingham Heart Study

BACKGROUND

All-cause mortality following atrial fibrillation (AF) has decreased over time. Data regarding temporal trends in causes of death among individuals with AF are scarce. The aim of our study was to analyze temporal trends in cause-specific mortality and predictors for cardiovascular (CVD) and non-CVD deaths among participants with incident AF in the Framingham Heart Study.

METHODS

We categorized all newly diagnosed AF cases according to age at AF diagnosis (< 70, 70 to < 80, and ≥ 80 years) and epoch of AF diagnosis (< 1990, 1990-2002, and ≥ 2003). We followed participants until death or the last follow-up. We categorized death causes into CVD, non-CVD, and unknown causes. For each age group, we tested for trends in the cumulative incidence of cause-specific death across epochs. We fit multivariable Fine-Gray models to assess subdistribution hazard ratios (HR) between clinical risk factors at AF diagnosis and cause-specific mortality.

RESULTS

We included 2125 newly diagnosed AF cases (mean age 75.5 years, 47.8% women). During a median follow-up of 4.8 years, 1657 individuals with AF died. There was evidence of decreasing CVD mortality among AF cases diagnosed < 70 years and 70 to < 80 years (p_trend < 0.001) but not ≥ 80 years (p = 0.76). Among the cases diagnosed < 70 years, the cumulative incidence of CVD death at 75 years was 67.7% in epoch 1 and 13.9% in epoch 3; among those 70 to < 80 years, the incidence at 85 years was 58.9% in epoch 1 and 18.9% in epoch 3. Advancing age (HR per 1 SD increase 6.33, 95% CI 5.44 to 7.37), prior heart failure (HR 1.49, 95% CI 1.14-1.94), and prior myocardial infarction (HR 1.44, 95% CI 1.15-1.80) were associated with increased rate of CVD death.

CONCLUSIONS

In this community-based cohort, CVD mortality among AF cases decreased over time. Most deaths in individuals with AF are no longer CVD-related, regardless of age at AF diagnosis.

Estimation and modeling of the restricted mean time lost in the presence of competing risks

Survival data with competing or semi-competing risks are common in observational studies. As an alternative to cause-specific and subdistribution hazard ratios, the between-group difference in cause-specific restricted mean times lost (RMTL) gives the mean difference in life expectancy lost to a specific cause of death or in disease-free time lost, in the case of a nonfatal outcome, over a prespecified period. To adjust for covariates, we introduce an inverse probability weighted estimator and its variance for the marginal difference in RMTL. We also introduce an inverse probability of censoring weighted regression model for the RMTL. In simulation studies, we examined the finite sample performance of the proposed methods under proportional and nonproportional subdistribution hazards scenarios. We illustrated both methods with competing risks data from the Framingham Heart Study. We estimated sex differences in atrial fibrillation (AF)-free times lost over 40 years. We also estimated sex differences in mean lifetime lost to cardiovascular disease (CVD) and non-CVD death over 10 years among individuals with AF.

Trends in excess mortality associated with atrial fibrillation over 45 years (Framingham Heart Study): community based cohort study

OBJECTIVE

To assess temporal trends in the association between newly diagnosed atrial fibrillation and death.

DESIGN

Community based cohort study.

SETTING

Framingham Heart Study cohort, in 1972-85, 1986-2000, and 2001-15 (periods 1-3, respectively), in Framingham, MA, USA.

PARTICIPANTS

Participants with no atrial fibrillation, aged 45-95 in each time period, and identified with newly diagnosed atrial fibrillation (or atrial flutter) during each time period.

MAIN OUTCOME MEASURES

The main outcome was all cause mortality. Hazard ratios for the association between time varying atrial fibrillation and all cause mortality were calculated with adjustment for time varying confounding factors. The difference in restricted mean survival times, adjusted for confounders, between participants with atrial fibrillation and matched referents at 10 years after a diagnosis of atrial fibrillation was estimated. Meta-regression was used to test for linear trends in hazard ratios and restricted mean survival times over the different time periods.

RESULTS

5671 participants were selected in time period 1, 6177 in period 2, and 6174 in period 3. Adjusted hazard ratios for all cause mortality between participants with and without atrial fibrillation were 1.9 (95% confidence interval 1.7 to 2.2) in time period 1, 1.4 (1.3 to 1.6) in period 2, and 1.7 (1.5 to 2.0) in period 3 (P_trend=0.70). Ten years after diagnosis of atrial fibrillation, the adjusted difference in restricted mean survival times between participants with atrial fibrillation and matched referents decreased by 31%, from -2.9 years (95% confidence interval -3.2 to -2.5) in period 1, to -2.1 years (-2.4 to -1.8) in period 2, to -2.0 years (-2.3 to -1.7) in period 3 (P_trend=0.03).

CONCLUSIONS

No evidence of a temporal trend in hazard ratios for the association between atrial fibrillation and all cause mortality was found. The mean number of life years lost to atrial fibrillation at 10 years had improved significantly, but a two year gap compared with individuals without atrial fibrillation still remained.

Refining the Association Between Body Mass Index and Atrial Fibrillation: G-Formula and Restricted Mean Survival Times

Background

Previous studies assessing the association between body mass index (BMI) and atrial fibrillation (AF) did not account for time‐varying covariates, which may be affected by previous BMI. We illustrate how the g‐formula can account for time‐varying confounding.

Methods and Results

We included 4392 participants from the Framingham Heart Study who were AF free at ages 45 to 55 years, and followed them for up to 20 years. We estimated hazard ratios (HRs) comparing time‐varying nonobese versus obese with Cox models. We used the g‐formula to compare nonobese versus obese and 10% annual decrease in BMI (until normal weight is reached) versus natural course. We estimated HRs and differences in restricted mean survival times, the mean difference in time alive and AF free. We adjusted for sex, age, and time‐varying risk factors. Cox models indicated that nonobese participants had a decreased rate of AF versus obese participants (HR, 0.83; 95% CI, 0.72–0.97). G‐formula analyses comparing everyone had they been nonobese versus obese yielded stronger associations (HR, 0.73; 95% CI, 0.58–0.91). The restricted mean survival time was 19.22 years had everyone been nonobese and 19.03 years had everyone been obese (difference, 2.25 months; 95% CI, −0.66 to 5.16). When assessing a 10% annual decrease in BMI, the association was weaker (HR 0.96; 95% CI, 0.86–1.08).

Conclusions

Decreased BMI was associated with a lower rate of AF after accounting for time‐varying covariates that depend on previous exposure using the g‐formula, which Cox models cannot accommodate. Absolute measures like the restricted mean survival time difference offer context to relative measures of association.