Fatigue is a common and distressing but poorly understood symptom among patients with heart failure (HF). This study sought to evaluate the prevalence, predictors, and prognostic value of clinically ...documented fatigue in newly diagnosed HF patients from the community.
This retrospective cohort study consisted of 12,285 newly diagnosed HF patients receiving health care services through the Geisinger Health System, with passive data collection through electronic medical records (EMR). Incident HF, fatigue, and other study variables were derived from coded data within EMRs. A collection of 87 candidate predictors were evaluated to ascertain the strongest independent predictors of fatigue using logistic regression. Patients were followed for all-cause mortality for an average of 4.8 years. The associations between fatigue and 6-month, 12-month, and overall mortality were evaluated via Cox proportional hazards regression models.
Clinically documented fatigue was found in 4827 (39%) newly diagnosed HF patients. Depression demonstrated the strongest association with fatigue. Fatigue was often part of a symptom cluster, as other HF symptoms including dyspnea, chest pain, edema, syncope, and palpitations were significant predictors of fatigue. Volume depletion, lower body mass index, and abnormal weight loss were also strong predictors of fatigue. Fatigue was not significantly associated with either 6-month (HR = 1.12, p = 0.16) or overall mortality (HR = 1.00, p = 0.89) in adjusted models.
Fatigue is a commonly documented symptom among newly diagnosed HF patients, and its origins may lie in both psychologic and physiologic factors. Though fatigue did provide a prognostic signal in the short-term, this was largely explained by physiologic confounders. Proper therapeutic remediation of fatigue in HF relies on identifying underlying factors.
Autologous NK cell therapy can treat a variety of malignancies, but is limited by patient-specific variations in potency and cell number expansion. In contrast, allogeneic NK cell lines can overcome ...many of these limitations. Cells from the permanent NK-92 line are constitutively activated, lack inhibitory receptors and appear to be safe based on two prior phase I trials.
We conducted a single-center, non-randomized, non-blinded, open-label, Phase I dose-escalation trial of irradiated NK-92 cells in adults with refractory hematological malignancies who relapsed after autologous hematopoietic cell transplantation (AHCT). The objectives were to determine safety, feasibility and evidence of activity. Patients were treated at one of three dose levels (1 × 10
cells/m
, 3 × 10
cells/m
and 5 × 10
cells/m
), given on day 1, 3 and 5 for a planned total of six monthly cycles.
Twelve patients with lymphoma or multiple myeloma who relapsed after AHCT for relapsed/refractory disease were enrolled in this trial. The treatment was well tolerated, with minor toxicities restricted to acute infusional events, including fever, chills, nausea and fatigue. Two patients achieved a complete response (Hodgkin lymphoma and multiple myeloma), two patients had minor responses and one had clinical improvement on the trial.
Irradiated NK-92 cells can be administered at very high doses with minimal toxicity in patients with refractory blood cancers, who had relapsed after AHCT. We conclude that high dose NK-92 therapy is safe, shows some evidence of efficacy in patients with refractory blood cancers and warrants further clinical investigation.
Background:Prediction models such as the Seattle Heart Failure Model (SHFM) can help guide management of heart failure (HF) patients, but the SHFM has not been validated in the office environment. ...This retrospective cohort study assessed the predictive performance of the SHFM among patients with new or pre-existing HF in the context of an office visit.Methods and Results:SHFM elements were ascertained through electronic medical records at an office visit. The primary outcome was all-cause mortality. A “warranty period” for the baseline SHFM risk estimate was sought by examining predictive performance over time through a series of landmark analyses. Discrimination and calibration were estimated according to the proposed warranty period. Low- and high-risk thresholds were proposed based on the distribution of SHFM estimates. Among 26,851 HF patients, 14,380 (54%) died over a mean 4.7-year follow-up period. The SHFM lost predictive performance over time, with C=0.69 and C<0.65 within 3 and beyond 12 months from baseline respectively. The diminishing predictive value was attributed to modifiable SHFM elements. Discrimination (C=0.66) and calibration for 12-month mortality were acceptable. A low-risk threshold of ∼5% mortality risk within 12 months reflects the 10% of HF patients in the office setting with the lowest risk.Conclusions:The SHFM has utility in the office environment.
A growing epidemic of atrial fibrillation (AF) has been predicted, although no data on the AF burden has been reported for the United States since 2010. The objectives of this study were to (1) ...describe trends in AF incidence, prevalence, and postdiagnosis survival from 2004 to 2016 within a large health-care system and (2) extrapolate observed prevalence rates to the entire US population to estimate the national AF burden. This retrospective cohort study incorporates the patients and electronic medical record of the Geisinger Health System, an integrated health-care delivery system serving central and northeast Pennsylvania. Standardized incidence rates were calculated per 1,000 person-years by calendar year, and point prevalence rates estimated on July 1st of the respective years from 2004 to 2016. Rate ratios were estimated from Poisson regression as the annual relative change over time. A total of 464,363 patients met study inclusion criteria. Age- and sex-adjusted AF incidence rates increased over the study period: 4.7, 5.0, 5.8, and 6.2 in 2004, 2008, 2012, and 2016, respectively (rate ratio 1.03 per year, 95% confidence interval 1.02, 1.03). Age- and sex-adjusted prevalence rates increased consistently over time from 2.7%, 3.0%, 3.4%, to 4.1% in 2004, 2008, 2012, and 2016, respectively. In 2004, an estimated 6.1 million Americans had diagnosed AF, increasing to 6.7, 7.8, and 9.3 million in 2008, 2012, and 2016, respectively. Postdiagnosis survival has not improved in recent years. In conclusion, AF incidence and prevalence have increased steadily since 2004, whereas postdiagnosis survival has not improved.
Chest pain (CP) has been reported in 20% to 40% of patients 1 year after percutaneous coronary intervention (PCI), though rates of post-PCI health-care utilization (HCU) for CP in nonclinical trial ...populations are unknown. Furthermore, the contribution of noncardiac factors – such as pulmonary, gastrointestinal, and psychological – to post-PCI CP HCU is unclear. Accordingly, the objectives of this study were to describe long-term trajectories and identify predictors of post-PCI CP-related HCU in real-world patients undergoing PCI for any indication. This retrospective cohort study included patients receiving PCI for any indication from 2003 to 2017 through a single integrated health-care system. Post-PCI CP-related HCU tracked through electronic medical records included (1) office visits, (2) emergency department (ED) visits, and (3) hospital admissions with CP or angina as the primary diagnosis. The strongest predictors of CP-related HCU were identified from >100 candidate variables. Among 6386 patients followed an average of 6.7 years after PCI, 73% received PCI for acute coronary syndrome (ACS), 19% for stable angina, and 8% for other indications. Post-PCI CP-related HCU was common with 26%, 16%, and 5% of patients having ≥1 office visits, ED visits, and hospital admissions for CP within 2 years of PCI. The following factors were significant predictors of all 3 CP outcomes: ACS presentation, documented CP >7 days prior to the index PCI, anxiety, depression, and syncope. In conclusion, CP-related HCU following PCI was common, especially within the first 2 years. The strongest predictors of CP-related HCU included coronary disease attributes and psychological factors.
Atrial fibrillation (AF) is the most common cardiac arrhythmia, and multiple studies have reported increasing AF incidence rates over time, although the underlying explanations remain unclear.
To ...estimate AF incidence rates from 2006 to 2018 in a community-based setting and to investigate possible explanations for increasing AF by evaluating the changing features of incident AF cases and the pool of patients at risk for AF over time.
This cohort study included 500 684 patients who received primary care and other health care services for more than 2 years through a single integrated health care delivery network in Pennsylvania. Data collection was conducted from January 2003 to December 2018. The base study population had no documentation of AF in the electronic medical record for at least 2 years prior to baseline. Data analysis was conducted from May to December 2019.
Incident AF cases were identified through diagnostic codes recorded at inpatient or outpatient encounters. Age- and sex-adjusted AF incidence rates were estimated by calendar year from 2006 to 2018 both overall and across subgroups, including according to diagnostic setting (inpatient vs outpatient) and priority (primary vs secondary diagnosis).
Among 514 293 patients meeting criteria for the base study population, the mean (SD) age at baseline was 47 (18) years and 282 103 (54.9%) were women; 13 609 (2.6%) met AF diagnostic criteria on or prior to the baseline date and were excluded. Among 500 684 patients free of AF at baseline, standardized AF incidence rates from 2006 to 2018 increased from 4.74 (95% CI, 4.58-4.90) to 6.82 (95% CI, 6.65-7.00) cases per 1000 person-years, increasing significantly over time (P < .001). Incidence rates increased in all age and sex subgroups, although absolute rate increases were largest among those aged 85 years or older. The fraction of incident AF cases among individuals aged 85 years or older increased from 135 of 1075 (12.6%) in 2006 to 451 of 2427 (18.6%) in 2017. Patients with incident AF were more likely over time to have high body mass index (1351 of 3389 patients 39.9% in 2006-2008 vs 4504 of 9214 48.9% in 2015-2018; P < .001), hypertension (2764 81.6% in 2006-2008 vs 7937 86.1% in 2015-2018; P < .001), and ischemic stroke (328 9.7% in 2006-2008 vs 1455 15.8% in 2015-2018; P < .001), but less likely to have coronary artery disease (1533 45.2% in 2006-2008 vs 3810 41.4% in 2015-2018; P < .001). Among 22 077 new cases of AF, 9146 (41.4%) were diagnosed as inpatients and 5731 (26.0%) as the primary diagnosis. Incidence rates of AF increased significantly in all diagnostic setting and priority pairings (eg, inpatient, primary: rate ratio, 1.07; 95% CI, 1.06-1.08; P < .001). Among patients at risk for AF, high BMI and hypertension increased over time (BMI: 71 433 of 198 245 36.0% in 2007 to 130 218 of 282 270 46.1% in 2017; hypertension: 79 977 40.3% in 2007 to 134 404 47.6% in 2017). Documentation of short-term ECG increased over time (23 297 of 207 349 11.2% in 2008 to 45 027 16.0% in 2017); however, long-term ECG monitoring showed no change (1871 0.9% in 2007 to 4036 1.4% in 2017).
In this community-based study, AF incidence rates increased significantly during the study period. Concurrent increases were observed in AF risk factors in the at-risk population and short-term ECG use.
Background Although ambient air pollution has been linked to reduced lung function in healthy children, longitudinal analyses of pollution effects in asthmatic patients are lacking. Objective We ...sought to investigate pollution effects in a longitudinal asthma study and effect modification by controller medications. Methods We examined associations of lung function and methacholine responsiveness (PC20 ) with ozone, carbon monoxide (CO), nitrogen dioxide, and sulfur dioxide concentrations in 1003 asthmatic children participating in a 4-year clinical trial. We further investigated whether budesonide and nedocromil modified pollution effects. Daily pollutant concentrations were linked to ZIP/postal code of residence. Linear mixed models tested associations of within-subject pollutant concentrations with FEV1 and forced vital capacity (FVC) percent predicted, FEV1 /FVC ratio, and PC20 , adjusting for seasonality and confounders. Results Same-day and 1-week average CO concentrations were negatively associated with postbronchodilator percent predicted FEV1 (change per interquartile range, −0.33 95% CI, −0.49 to −0.16 and −0.41 95% CI, −0.62 to −0.21, respectively) and FVC (−0.19 95% CI, −0.25 to −0.07 and −0.25 95% CI, −0.43 to −0.07, respectively). Longer-term 4-month CO averages were negatively associated with prebronchodilator percent predicted FEV1 and FVC (−0.36 95% CI, −0.62 to −0.10 and −0.21 95% CI, −0.42 to −0.01, respectively). Four-month averaged CO and ozone concentrations were negatively associated with FEV1 /FVC ratio ( P < .05). Increased 4-month average nitrogen dioxide concentrations were associated with reduced postbronchodilator FEV1 and FVC percent predicted. Long-term exposures to sulfur dioxide were associated with reduced PC20 (percent change per interquartile range, −6% 95% CI, −11% to −1.5%). Treatment augmented the negative short-term CO effect on PC20. Conclusions Air pollution adversely influences lung function and PC20 in asthmatic children. Treatment with controller medications might not protect but rather worsens the effects of CO on PC20 . This clinical trial design evaluates modification of pollution effects by treatment without confounding by indication.
Survival characteristics of patients who have recurrent nonsmall-cell lung cancer after surgical resection are not well understood. Little objective evidence exists to justify treatment for these ...patients.
We prospectively followed 1,361 consecutive patients with nonsmall-cell lung cancer who underwent complete surgical resection at our institution from January 1997 to December 2001. Only patients having recurrent cancer were included in the analysis. Multivariable Cox proportional hazards models were used to evaluate the effect of prognostic factors on postrecurrence survival.
Follow-up was achieved in 1,073 patients, and recurrent cancer developed in 445. Complete information was available on 390 patients for analysis. There were 262 men and 128 women. Median age at time of recurrence was 69 years. Median time from surgical resection to recurrence was 11.5 months, and median postrecurrence survival was 8.1 months. Recurrence was intrathoracic in 171 patients, extrathoracic in 172, and a combination of both in 47. Treatments after recurrence included surgery in 43 patients, chemotherapy in 59, radiation in 73, and a combination in 96. All patients who received treatment survived longer than those who received no treatment. Preoperative chemotherapy and postoperative radiotherapy for the primary lung cancer, poor Eastern Cooperative Oncology Group Performance Status, decreased disease-free interval from initial resection to recurrence, symptoms at recurrence, and certain location of recurrence significantly decreased postrecurrence survival.
In our experience, treatment for recurrent nonsmall-cell lung cancer significantly prolongs survival. Various treatment modalities including surgery should be considered in patients with postoperative recurrent nonsmall-cell lung cancer.
Type 2 diabetes (T2D) is a strong risk factor for cardiovascular (CV) disease. CV outcomes in T2D have generally been improving over time but recent data from the US suggest attenuation of trends in ...older adults with reversal of trends in younger adults. However, published data are only reported through 2015.
To quantify trends over time in CV outcomes from 2001 to 2018, and describe changes over time in health care costs in T2D.
This retrospective cohort study incorporated data from a regional health insurance plan. Study outcomes included acute myocardial infarction (AMI), ischemic stroke, hemorrhagic stroke, heart failure hospitalization (HFH), percutaneous coronary intervention, coronary artery bypass surgery, and all-cause mortality. Poisson regression estimated rate ratios across the entire 17-year study period (RR17).
Among 79,392 T2D members tracked on average 4.1 years, overall trends in AMI (RR17 = 0.69; 95% CI: 0.64, 0.74), HFH (RR17 = 0.82; 0.79, 0.86), and all-cause mortality (RR17 = 0.87; 0.84, 0.91) improved while ischemic stroke (RR17 = 2.36; 2.16, 2.57) worsened. For AMI, HFH, and all-cause mortality, trends in older age groups were significantly better than in younger age groups (interaction P-values < .001). Health care costs related to pharmaceuticals (+15%/year) and emergency department (ED) visits (>15%/year) increased at faster rates than other utilization metrics (+10%/year).
In T2D, overall trends in most CV outcomes improved but smaller improvements or worsening trends were observed in younger patients. Health care costs accelerated at faster rates for medications and ED visits.
The goal of this study was to use machine learning to more accurately predict survival after echocardiography.
Predicting patient outcomes (e.g., survival) following echocardiography is primarily ...based on ejection fraction (EF) and comorbidities. However, there may be significant predictive information within additional echocardiography-derived measurements combined with clinical electronic health record data.
Mortality was studied in 171,510 unselected patients who underwent 331,317 echocardiograms in a large regional health system. The authors investigated the predictive performance of nonlinear machine learning models compared with that of linear logistic regression models using 3 different inputs: 1) clinical variables, including 90 cardiovascular-relevant International Classification of Diseases, Tenth Revision, codes, and age, sex, height, weight, heart rate, blood pressures, low-density lipoprotein, high-density lipoprotein, and smoking; 2) clinical variables plus physician-reported EF; and 3) clinical variables and EF, plus 57 additional echocardiographic measurements. Missing data were imputed with a multivariate imputation by using a chained equations algorithm (MICE). The authors compared models versus each other and baseline clinical scoring systems by using a mean area under the curve (AUC) over 10 cross-validation folds and across 10 survival durations (6 to 60 months).
Machine learning models achieved significantly higher prediction accuracy (all AUC >0.82) over common clinical risk scores (AUC = 0.61 to 0.79), with the nonlinear random forest models outperforming logistic regression (p < 0.01). The random forest model including all echocardiographic measurements yielded the highest prediction accuracy (p < 0.01 across all models and survival durations). Only 10 variables were needed to achieve 96% of the maximum prediction accuracy, with 6 of these variables being derived from echocardiography. Tricuspid regurgitation velocity was more predictive of survival than LVEF. In a subset of studies with complete data for the top 10 variables, multivariate imputation by chained equations yielded slightly reduced predictive accuracies (difference in AUC of 0.003) compared with the original data.
Machine learning can fully utilize large combinations of disparate input variables to predict survival after echocardiography with superior accuracy.
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