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1 eing gathered regarding processes related to poor adherence.
2 rosis and identifies factors associated with poor adherence.
3 accepted, its effectiveness is undermined by poor adherence.
4 defined as good adherence and 80% or less as poor adherence.
5 65.0%, and 7.7%, respectively) for detecting poor adherence.
6 for inadequate clinical response because of poor adherence.
7 tion for a subset; predictors of good versus poor adherence.
8 to 1.55) were independently associated with poor adherence.
9 nd 9-month immunoglobulin G (IgG), which has poor adherence.
10 ercise have shown promise but are limited by poor adherence.
11 tients, due to interoperator variability and poor adherence.
12 orticosteroid dosing could indicate previous poor adherence.
13 pregnancy is often not well tolerated, with poor adherence.
14 as used to determine factors associated with poor adherence.
15 s, taking >= 1 medication, who self-reported poor adherence.
16 medically treated glaucoma and self-reported poor adherence.
17 k factors were statistically associated with poor adherence.
18 eness of sleep apnea treatment is limited by poor adherence.
19 failure rates in typical use, due largely to poor adherence.
20 for treatment of opioid use disorder due to poor adherence.
21 There were five cases of poor adherence.
22 ppointing results were attributed largely to poor adherence.
23 Twenty-seven percent of the sample reported poor adherence.
24 s (CIs) identifying barriers associated with poor adherence.
25 d toward patients with such risk factors for poor adherence.
26 s for whom poor asthma control is related to poor adherence.
27 ation schedule were barriers associated with poor adherence.
28 re shown to be an independent risk factor of poor adherence.
29 ucoma medication and factors associated with poor adherence.
30 efined, yet multiple studies have identified poor adherence.
31 oporosis treatments is determining causes of poor adherence.
32 ing medications, even at very high levels of poor adherence.
33 models, respectively); (2) persistently very poor adherence (14.9% and 23.4% of persons in the 1- and
35 iodemographic characteristics helped explain poor adherence (African Americans: low maternal educatio
37 participants, 20.0% (n = 147) self-reported poor adherence and 6.1% (n = 45) had EHR documentation o
44 mes by not including those at higher risk of poor adherence and reinfection--individuals for whom rea
46 e and costly for patients, consequently with poor adherence and restricted access to therapy for many
47 ch that first identifies patients at risk of poor adherence and then seeks to establish the support t
48 d concerns of adverse outcomes subsequent to poor adherence and/or self-cessation/loss-to-follow-up.
49 gnificant difference between good adherence, poor adherence, and dropout regarding level of understan
51 uate prescription of antiretroviral therapy, poor adherence, and repeated interfaces with congregate
52 a by health-care provider, and management of poor adherence; and patients in the control group receiv
56 land but is associated with side-effects and poor adherence by patients, and TMP-SMX alone is recomme
58 87 (10%) of the 854 treatment months showed poor adherence compared with 290 (37%) of the 795 months
59 g >=1 glaucoma medication, who self-reported poor adherence) completed a baseline survey that assesse
61 DH not controlled by gluten-free diet (with poor adherence), dapsone, and conventional immune-suppre
62 to mercaptopurine (57.1% vs 40.9%); however, poor adherence did not completely explain the associatio
63 oroquine, but they have limitations, such as poor adherence due to frequent oral administration and g
67 atients with RR/MDR-TB who exhibited initial poor adherence followed by subsequent improvement achiev
68 TDM represents a useful tool to discriminate poor adherence from real cases of resistant hypertension
69 regression slopes of viral RNA load for the poor-adherence group were significantly higher than thos
73 ective, low persistence in PrEP programs and poor adherence have limited its ability to reduce HIV in
74 hird had drug concentrations consistent with poor adherence, highlighting the need for novel approach
75 ght be a key noninvasive resource to address poor adherence in children and adolescents in a clinical
77 s associated with a lower risk of death than poor adherence in patients with CHF, irrespective of ass
80 positive airway pressure (CPAP) therapy, but poor adherence is common and is associated with worse pa
84 engthy and onerous, and hence complicated by poor adherence leading to drug resistance and disease re
87 sive treatment regimens that compensated for poor adherence led to better improvements in glycemic co
88 o accessibility to subsequent cART regimens, poor adherence limiting scope to switch regimens, and th
89 etween those with physiologically predicted "poor" adherence (lowest quartile of predicted adherence)
90 th CML treated with imatinib for some years, poor adherence may be the predominant reason for inabili
91 o receive samples will be considered to have poor adherence), misidentification of newly treated pati
93 icult as there are no existing biomarkers of poor adherence or inadequate treatment earlier than 2 mo
94 or 100-fold concentration differences due to poor adherence or less frequent prescribed dosing, vagin
95 the concept of pseudo-resistance, linked to poor adherence or other factors, and provide an algorith
97 elect for a resistant subpopulation, whereas poor adherence or second-line therapy resulted in the re
98 ause patients do not take their medications (poor adherence) or because providers do not increase med
101 rved in 60% of cases and was associated with poor adherence (p<0.001) and subsequent development of d
103 chieve HIV RNA suppression by 6 months, with poor adherence, rather than HIV drug resistance, driving
105 th persistent low CD4 cell counts because of poor adherence, resistance to antiretroviral drugs, or b
106 (RR, 6.75; 95% CI, 1.11-70.9; P = .036) and poor adherence (RR, 7.50; 95% CI, 1.23-78.7; P = .026).
107 e identify several variables associated with poor adherence such as glaucoma progression, LTF, younge
108 ns in addressing modifiable risk factors for poor adherence (such as depression, stress, and lower ed
111 cholesterolemia) that could be attributed to poor adherence to a healthy lifestyle, we calculated the
116 od, hygiene, and shelter needs), followed by poor adherence to antiretroviral therapy, not having a c
120 that IPs reported inadequate drug provision, poor adherence to clinical national guidelines, and that
121 symptoms can be poorly controlled because of poor adherence to controller therapy, and this might be
123 tions may be acceptable to veterans who have poor adherence to existing evidence-based treatments for
134 l or other drug abuse problems combined with poor adherence to medication may signal a higher risk of
137 e term hypertension or its cause, leading to poor adherence to medications and limiting other effecti
139 of more than 1000 copies per mL (signifying poor adherence to oral drugs, and often associated with
141 Fifty-eight percent of patients exhibited poor adherence to prescribed antihypertensive medication
142 he limited efficacy of existing medications, poor adherence to prescribed regimens, and a heightened
144 zability of these findings is complicated by poor adherence to reporting guidelines and high risk of
148 e over the course of the trial, resulting in poor adherence to the assigned study treatment and a red
149 Subtherapeutic drug levels can be caused by poor adherence to the drug regimen, interactions with ot
151 se aspects of care; however, physicians show poor adherence to the guidelines despite the evidence th
152 Plasma tenofovir concentrations demonstrated poor adherence to the study product among study subjects
154 (<8.0 g/dL; AHR, 3.1; 95% CI, 2.3-4.0), and poor adherence to therapy (AHR, 2.9; 95% CI, 2.2-3.9).
162 provider reliance on clinical diagnosis and poor adherence to treatment policy, especially in first
167 he proportion of patients with self-reported poor adherence was compared between the EHR extraction a
171 40, taking >=1 medication, who self-reported poor adherence were recruited from the University of Mic
172 nhanced hand hygiene protocols were met with poor adherence, whereas pharmacists consistently engaged
173 utcome variability, especially the impact of poor adherence, which is critical to manage PrEP in the
174 in patients with cystic fibrosis, indicating poor adherence, which is particularly common in adolesce
175 ble for isoniazid preventive therapy and the poor adherence with a complete regimen among those we in
177 ack of health insurance, and no access to or poor adherence with controller medications such as inhal
178 amivudine-dolutegravir (TLD) can result from poor adherence with or without resistance; however, geno
179 nt to at least 30% of surveyed patients with poor adherence, with most identifying multiple barriers