in which certain therapies have adequate, even overwhelming if not unequivocal, evidence of effectiveness. 5 Clinical inertia occurs, for example, when the patient fails to attain a biomarker goal (e.g., blood pressure less than 140/90 millimeters of mercury [mm Hg]) due at least in part to failure to intensify pharmacotherapy through upward dosing and/or addition of drugs to the therapeutic regimen. O'Connor et al. attributed clinical inertia 50% to physician factors, 30% to patient factors, and 20% to office-system factors. 4 We might consider the latter category even more broadly to include all health-system factors (Table 1). While we are uncertain about the relative weights for these 3 categories of factors that contribute to clinical inertia, we propose that this conceptual model, including relative weights, should become a focal point in research in nonadherence and failure to attain biomarker and other clinical goals.While acknowledging access, cost, and patient nonadherence, Phillips et al. emphasized the role of clinicians when they wrote in 2001 that clinical inertia occurs when health care providers recognize the problem (failure to attain therapeutic targets in patients with hypertension, dyslipidemia, or diabetes) but fail to act (to initiate or intensify therapy). Clinical inertia is more than failure to act, and it has been shown that other factors such as clinician communication affect adherence. Zolnierek and DiMatteo (2009) discovered in a meta-analysis of 127 studies that the odds of adherence for patients whose physicians had been trained in communication skills were 1.62 times those of patients whose physicians did not receive communication training.
Fatigue after myocardial infarction (MI) is a barrier to secondary prevention behaviors such as engaging in recommended levels of physical activity. However, little is known about physiologic factors that may contribute to fatigue. The purpose of this study was to describe the prevalence of fatigue in older adults after MI and to examine the associations of physiological factors of cardiac function (b-natriuretic peptide [BNP], mean arterial pressure, heart rate), inflammation (IL-6), BMI, and hemoglobin (Hgb) with self-reported fatigue.
Methods:
A convenience sample of women (
n
=49) and men (
n
=49) ages ≤65 completed questionnaires and underwent physiologic measures 6 – 8 months after discharge post MI. Subjects completed a demographic health form and fatigue measures (Revised Piper Fatigue Scale and the Multidimensional Assessment of Fatigue Scale functional items), and had height, weight, pulse, and blood pressure measured. Fatigue was measured as a total score (range 0 –310) and as 5 subscales (behavior/severity, affective, sensory, cognitive/mood, and function). Blood samples were also taken, and Hgb, IL-6, and BNP were measured in the same laboratory using standardized procedures.
Results:
Patients were an average of 75.69 ± 6.45 years of age. Fatigue was reported by 75 (77%) with a mean score of 102.46 (SD=57.7; range 8 –235). More women (84%) reported fatigue than men (69%), though this difference was not statistically significant. Patients reported higher fatigue scores on the behavior/severity and sensory subscales compared to the other fatigue subscales. Bivariate correlations of physiological factors and the total fatigue score revealed one significant physiological correlate, IL-6 (
r
=.29). Controlling for age and gender, a multiple linear regression model explained 8.7% of the variance in fatigue (
F
= 2.769
; p
<.05) with IL-6 as the only significant independent variable (
p
=.010). An unexpected finding was that BNP did not correlate with fatigue.
Discussion:
Fatigue is prevalent in the majority of older adults after MI. Results indicate that inflammation may play a stronger role in fatigue than other physiological factors. Further research is needed to examine how inflammation and other physiologic factors may influence fatigue post MI.
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