[23] Religious influences,[21, 22, 32, 34] high expectations and negative perceptions and attitudes towards healthcare services and healthcare providers have also been identified across Opaganib mouse the studies as a potential cause of MRPs.[15, 20, 23] Lack of knowledge of the healthcare services and how to use them is also a further possible contributing factor for MRPs that has been identified; for example, some ethnic minority patients have no knowledge of the pharmaceutical care role of pharmacists which may lead to lack of regular monitoring and review of their medicines.[15, 20] According

to the literature, underestimating patients’ desire selleck products for information, which may be a consequence of a lack of awareness of the extent of patients’ decision-making regarding the use of their medicines and/or poor appreciation of their experience of MRPs,[36] may well cause MRPs. Some recommendations were made across the studies to support patients in the use of medicines. The recommendations involved providing patient counselling and education programmes about their disease, its management and medicines and the service available,[23, 35] providing an interpreter for ethnic minorities who cannot speak

English, using pictorial flashcards to provide information for illiterate people,[34] providing bilingual link-workers

who explain reasons for regular appointments and provide encouragement and a cultural bridge between healthcare professionals and patients,[34, 35] increasing involvement of ethnic minorities in decisions about healthcare provision and utilisation,[20] involving patients in evidence-informed decision making for safer and more effective disease and medicine managements.[32] Further recommendations included not only improving provider–patients communication by understanding of cultural factors that inform their beliefs and practices but also ensuring Lenvatinib that mechanisms are in place for the effective transfer of information,[35] encouraging pharmacists and patients to work together and share their experiences regarding the use of medicines as well as exchanging information that will support patients achieving optimal outcomes from their medicines,[36] encouraging effective reliable communication between secondary and primary care, surgeries, pharmacies and patients for the continuity of safe and effective therapy,[36] providing enhanced pharmaceutical services in areas of health inequalities and to such minority groups.[15] This review brings together the information in the current literature regarding medicine use and MRPs experienced by ethnic minority groups in the UK.

203), nor between AMS incidence and reading or understanding the written information (p = 0.942 and 0.500, respectively). Logistic regression analysis identified all these variables except the average increase in altitude as independently significant (Table 4). Travelers who experienced Kinase Inhibitor Library screening AMS on a previous journey were twice more likely to develop AMS. The risk for women was 1.5 times higher than for men, and the risk decreased with an OR of 0.984 for every year of age. The risk increased with an OR of 1.2 for every 500 m increase in maximum overnight altitude and it decreased with

an OR of 0.9 for every night that was spent between 1,500 and 2,500 m at the beginning of the journey. We found no relation between acetazolamide prevention and AMS selleck compound (p = 0.540) in this population, nor in the subgroup (N = 66) of those with a prior history of AMS (p = 0.787); but this sample has insufficient power for conclusions of absence of effect. In those with previous AMS, there

were no more risk factors in the subgroup of travelers who took acetazolamide preventively than in those who did not. Thus, mean-maximum altitude (p = 0.134), mean number of nights spent between 1,500 and 2,500 m (p = 0.151), and mean age (p = 0.759) were the same in both subgroups, which contained an equal number of women and men (p = 0.258). Nor was there a relation between acetazolamide treatment and the duration of AMS complaints (p = 0.169). Eleven percent reported an increased urine production and 30% reported side effects, of which a tingling sensation in hands and feet was the most common (25%), followed by gastrointestinal complaints (5%), headache (2%), taste alteration, muscle cramps, and coughing (each 1%). We found no relation between dosage and

the side effects (p = 0.336). This study shows that 25% of travelers who consulted our pre-travel clinics for a journey to an altitude above 2,500 TCL m developed AMS. Predictors were previous AMS, gender, age, maximum overnight altitude, and number of nights between 1,500 and 2,500 m. No more than about half of these travelers followed our advice regarding prevention and treatment. We found no effect of acetazolamide on AMS incidence or the duration of AMS complaints. We found an AMS incidence of 13% between 2,500 and 3,000 m, while Mairer found an incidence of 17% at an altitude of 2,800 m in trekkers in the Eastern Alps.14 They found an incidence of 38% at 3,500 m, compared with 22% between 3,500 and 4,000 m in our study. Wagner found 43% at 4,500 m on Mount Whitney, compared with 30% between 4,500 and 5,000 m in our study.15 Mairer and Wagner also used the Lake Louise definition on altitude illness, but added that the total score of symptoms had to be at least 3 (Wagner) or 4 (Mairer). As we did not use scores, we would have expected a higher incidence in our study.

203), nor between AMS incidence and reading or understanding the written information (p = 0.942 and 0.500, respectively). Logistic regression analysis identified all these variables except the average increase in altitude as independently significant (Table 4). Travelers who experienced http://www.selleckchem.com/products/abc294640.html AMS on a previous journey were twice more likely to develop AMS. The risk for women was 1.5 times higher than for men, and the risk decreased with an OR of 0.984 for every year of age. The risk increased with an OR of 1.2 for every 500 m increase in maximum overnight altitude and it decreased with

an OR of 0.9 for every night that was spent between 1,500 and 2,500 m at the beginning of the journey. We found no relation between acetazolamide prevention and AMS Napabucasin chemical structure (p = 0.540) in this population, nor in the subgroup (N = 66) of those with a prior history of AMS (p = 0.787); but this sample has insufficient power for conclusions of absence of effect. In those with previous AMS, there

were no more risk factors in the subgroup of travelers who took acetazolamide preventively than in those who did not. Thus, mean-maximum altitude (p = 0.134), mean number of nights spent between 1,500 and 2,500 m (p = 0.151), and mean age (p = 0.759) were the same in both subgroups, which contained an equal number of women and men (p = 0.258). Nor was there a relation between acetazolamide treatment and the duration of AMS complaints (p = 0.169). Eleven percent reported an increased urine production and 30% reported side effects, of which a tingling sensation in hands and feet was the most common (25%), followed by gastrointestinal complaints (5%), headache (2%), taste alteration, muscle cramps, and coughing (each 1%). We found no relation between dosage and

the side effects (p = 0.336). This study shows that 25% of travelers who consulted our pre-travel clinics for a journey to an altitude above 2,500 Pyruvate dehydrogenase m developed AMS. Predictors were previous AMS, gender, age, maximum overnight altitude, and number of nights between 1,500 and 2,500 m. No more than about half of these travelers followed our advice regarding prevention and treatment. We found no effect of acetazolamide on AMS incidence or the duration of AMS complaints. We found an AMS incidence of 13% between 2,500 and 3,000 m, while Mairer found an incidence of 17% at an altitude of 2,800 m in trekkers in the Eastern Alps.14 They found an incidence of 38% at 3,500 m, compared with 22% between 3,500 and 4,000 m in our study. Wagner found 43% at 4,500 m on Mount Whitney, compared with 30% between 4,500 and 5,000 m in our study.15 Mairer and Wagner also used the Lake Louise definition on altitude illness, but added that the total score of symptoms had to be at least 3 (Wagner) or 4 (Mairer). As we did not use scores, we would have expected a higher incidence in our study.

Baseline plasma glucose concentrations prior to the initiation of the 2DG procedure were not different between drug-naïve controls and cocaine-experienced animals (controls, 144.2 ± 6.7 mg/mL; 48 h withdrawal from cocaine, 153.4 ± 17.0 mg/mL). click here Rates of local cerebral glucose metabolism were measured in 20 brain regions and the data are shown in Table 1. These rates were globally lower in animals with a history

of cocaine self-administration measured 48 h after the final self-administration session as compared with drug-naïve controls (84.5 ± 4.7 vs. 74.6 ± 4.4 μmol/100 g/min cocaine-withdrawal, t11 = 2.245, P < 0.05). This pattern was observed in all 20 of the regions in which glucose utilization rates were measured. In the cortex, two-way anova revealed a main effect of treatment (F1,11 = 5.95, P < 0.05) and brain region (F2,22 = 151.9, P < 0.001), but no interaction. In the basal ganglia, there was a main effect of treatment (F1,11 = 8.10 P < 0.05) and brain region (F5,55 = 125.67, P < 0.001), but no interaction. In limbic brain areas, there was a main effect of treatment (F1,11 = 6.10 P < 0.05) and brain region (F7,77 = 110.3, P < 0.001), and an interaction (F7,70 = 3.041, P < 0.05).

Finally, in the brainstem, there was selective HDAC inhibitors a main effect of treatment (F1,11 = 12.48, P < 0.01) and brain region (F2,22 = 75.21, P < 0.001), but no interaction. Planned multiple comparisons showed that 48 h after cocaine self-administration functional activity was lower in the anterior cingulate cortex (−12%), dorsal caudate putamen (−16%), nucleus accumbens (-16%, Fig. 5), basolateral amygdala

(−16%), medial nucleus of the thalamus (−12%), hippocampal CA1 region (−24%, Fig. 5), dorsal raphe (−18%), locus coeruleus (−13%) and cerebellum (−15%), when compared with controls. Here we demonstrate that there are functional and behavioral reductions present 48 h after 5-day cocaine self-administration. The functional alterations were characterized by reduced brain activity, as indicated by lower rates PAK6 of cerebral glucose utilization, in circuits involved in learning and memory, attention, sleep, and reward processing. These data are consistent with human studies that have demonstrated marked reductions in functional brain activity, in particular prefrontal cortical and striatal regions, which occur early in the withdrawal period and last for up to 4 months following cocaine misuse (Volkow et al., 1992, 1993). Previously, we have shown that cocaine self-administration resulted in reductions in functional activity, but these effects were measured immediately following the final infusion at a time when cocaine levels were still high (Macey et al., 2004).

The 4-year stratification

was selected a priori based on the fact that the epidemic in IDUs began in 1998. The analysis was repeated using the year 1997 as an alternative cut-off in order to analyse the possible effect of cART. The interval 1998–2001 was defined as the first stage of the sub-epidemic among IDUs, whereas the interval 1985–1989 was defined as the first stage of the sub-epidemic among MSM and heterosexual cases. The other periods were defined as later stages of the epidemic. SPSS 15.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analysis. Chi-square tests, t-tests and Mann–Whitney tests were used to test for differences between the groups. Multivariate logistic regression analysis using backward and forward selection procedures served to identify factors independently associated with late HIV diagnosis and delayed entry to care. Variables

found to be significant BKM120 (P<0.2) in univariate analysis were included in the models. Out of all 934 cases, the reported transmission risk was IDU in 26%, heterosexual transmission in 31% and MSM in 42%. The transmission risk was other or unknown for 11 cases. The characteristics of the study population divided into 4-year calendar periods of HIV diagnosis are shown in Table 1. The study population Belnacasan represents 77% of IDU, 66% of MSM and 42% of heterosexually transmitted HIV cases reported to the NIDR surveillance system nationwide between 1985 and 2005 (n=1597). The annual number of newly diagnosed HIV cases in the study population follows the same trends as those for the whole country (Fig. Fludarabine mw 1). Out

of 934 patients, 62% had their CD4 cell count measured on the day of the first clinic visit or within 90 days after the visit. Thirty-eight per cent had their CD4 cell count measured prior to the clinic visit. The median CD4 count was 419 cells/μL. Of all cases, 21% presented with a CD4 count ≤200 cells/μL, 6% with CD4 <50 cells/μL and 9% presented with an AIDS-defining illness. Altogether, 23% were classified as diagnosed late (CD4 <200 cells/μL, or AIDS within 3 months of HIV diagnosis). Within the first year after HIV diagnosis, 11% had been diagnosed with AIDS. Late diagnosed cases by calendar year of diagnosis and HIV transmission risk are presented in Fig. 1. The proportions of individuals diagnosed late, and predictors of late diagnosis in the multivariate model are presented in Table 2. In the multivariate analyses, individuals diagnosed late were more often older, non-Finnish and less likely to have been tested previously. Compared with female IDUs, male IDUs, male heterosexuals and MSM were at risk of a late diagnosis. Cases diagnosed late were more often diagnosed in primary health care, secondary health care or at an unknown site compared with STD clinics, and in more recent calendar periods. Late diagnosis was rare before 1990 and between 1998 and 2001.

Oligosaccharides were then fluorescence-labeled with 2-aminopyridine (PA) according

to the manufacturer’s instructions (Takara Bio). The linkage structures were further analyzed by exoglycosidase digestion using α-1,2-mannosidase (from Aspergillus saitoi; Seikagaku Corp.), jack bean α-mannosidase (Seikagaku Corp.) and Tanespimycin mw β-mannosidase (from Achatina fulica; Seikagaku Corp.) according to the manufacturer’s instructions. Mannosylphosphorylated oligosaccharide samples were resuspended in 0.1 M HCl and heated at 100 °C for 2 h. The reaction was dried and dissolved in 50 mM Tris-HCl pH 9.5, 3 units of alkaline phosphatase (Takara Bio) were added, and the reaction was incubated overnight at 37 °C. High performance liquid chromatography (HPLC) analysis of N-linked oligosaccharides was performed using a TSK-gel Amide-80 column (4.6 mm inner diameter by 15 cm; Tosoh Corp.) at a flow rate of 1.0 mL min−1 with solvent A (acetronitrile) and solvent B (200 mM triethylamine acetate buffer). The HPLC column was equilibrated with solvent A. After injecting the sample, the concentration of solvent B was increased from 30% to 62% over 40 min. For phosphomannan analysis, HPLC profiling was performed using a Shodex Asahipak NH2P-50 4E column

(4.6 mm inner diameter by 25 cm; Showa Denko K.K) at a flow rate of 1.0 mL min−1. The HPLC column was equilibrated with solvent A. After sample injection, the proportion of solvent B was increased linearly up to 70% over 60 min. this website PA-oligosaccharides were

detected by measuring fluorescence (320 nm excitation wavelength and 400 nm emission wavelength). Among 47 isolates of Pichia spp. available from BCC, 11 were found to be rapid-growing methanol-utilizing strains and zeocin-sensitive, and were therefore further investigated for their potential as heterologous expression hosts. The AOX1 promoter from P. pastoris in pPICZαA was first exploited for heterologous protein expression in these yeast strains. The recombinant plasmid, pPICZαA-rPhyA170 was integrated into the yeast genome by electroporation as described. However, only one strain, identified as P. thermomethanolica BCC16875, exhibited stable transformation and integration of DNA insert (data not shown). In addition, this strain selleck inhibitor tolerates a wide temperature range from 10 to 37 °C (Limtong et al., 2005). Further investigation demonstrated that this strain was able to grow in temperatures as high as 40 °C (data not shown). Pichia thermomethanolica BCC16875 has the ability to be transformed with efficiency of 1 × 104 CFU μg−1 DNA. Recombinant phytase (rPHY) was readily expressed from both AOX1 and GAP promoters as secreted functional proteins (Fig. 1a). rPHY expressed from both systems was larger than its predicted molecular weight of 51 kDa, suggesting that the enzyme is post-translationally modified.

Escherichia coli HS996/pSC101-BAD-gbaA (Wang et al., 2006) was provided by Youming Zhang, Gene Bridges, Germany. Escherichia coli DH10B was used for the functional recombineering elements’ selleck screening library integration. Escherichia coli strains were routinely grown in Luria–Bertani (LB) media. Antibiotics were added at the following concentrations for plasmid selection (μg mL−1): gentamicin (25), tetracycline (12.5), ampicillin (100), kanamycin (30) and chloramphenicol (12.5). Strains containing pSC101-BAD-gbaA were incubated at 30 °C unless otherwise mentioned. Escherichia coli strain culture, competent cell preparation, DNA transformation,

plasmid extraction, restriction enzyme digestion and agarose gel electrophoresis were performed as per standard protocols (Sambrook & Russel, 2001). Amplification of the homology arm (in recombineering research, the short homologous DNA sequence used for the recombination is often called the ‘homology arm’) flanked neo was performed in a 50-μL reaction with 100 ng of pKD4, 0.2 mM dNTP each, 0.25 μM of each sense and antisense primer

and 2.5 U of Pfu (NEB). The PCR cycling conditions consisted of an initial denaturation step at 95 °C for 5 min, followed by 30 cycles of 95 °C for 45 s, 60 °C for 60 s and 72 °C for 2 min and a final extension step at 72 °C for 10 min. The PCR product was analyzed by agarose gel electrophoresis, followed by ethanol precipitation and dissolved in a suitable volume of 10 mM Tris-Cl (pH 8.0); the DNA concentration was adjusted to 100 ng μL−1. Tanespimycin mw Short primers (≤60-mer) were purchased from Sangon Co. Ltd (China) and long primers (>60-mer) were purchased from Integrated DNA Technologies Inc. The primers used in this study are

listed in Table 1. The vector pGR harboring the functional recombineering elements for E. coli DH10B genome integration was constructed as follows: first, 0.8 kb aacC1 was amplified from pBAD322G with primers GRK1 and GRK2, 1.1 kb araC was amplified with primers GRK3 and GRK4 from pKD46, then the XhoI- and SacI-digested aacC1 and the SacI- and BamHI-digested araC were ligated and cloned into the XhoI- and BamHI-treated pBluescript KS(−), creating pKAC. With E. coli DH10B genomic DNA as a template, 420 bp endA1 upstream sequences were amplified with the primers EA1 and EA2 and digested with EcoRI and XhoI, and 370 bp endA1 not downstream sequences were amplified with primers EA3 and EA4 and digested with XhoI and KpnI. The two fragments were then ligated and cloned into EcoRI- and KpnI-treated pBluescript KS(−) to obtain pENLR. Finally, 3.2 kb λ Red genes and the recA containing XhoI–BamHI fragment excised from pSC101-BAD-gbaA and the 2.0 kb aacC1 and the araC containing BamHI–XhoI fragment excised from pKAC were ligated and cloned into the XhoI site of pENLR, generating pGR. Recombineering experiments with pKD46 (Datsenko & Wanner, 2000) and pSC101-BAD-gbaA (Wang et al.

Both dPSS and iPSS attempt to express the sum of the phenotypically

active ARV drugs in the patients’ new regimen. In the dPSS, the activity of each new drug in the regimen was estimated as follows: if fold-change (FC) was less than the lower CCO (i.e. susceptible), the drug contributed 1 point; if FC was higher than the lower CCO (i.e. resistant), the drug contributed 0 points to the dPSS. The iPSS was calculated in a similar fashion but also accounts for partial or intermediate susceptibility of new ARV drugs (FC between check details the upper and lower CCOs): each fully active drug (FC < lower CCO) gets a score of 1, and each partially active drug (lower CCO < FC < upper CCO) gets a score of 0.5. In both dPSS and iPSS, if the FC was < 0.4 for a specific drug (i.e. the virus was considered to be hypersusceptible to the drug), that drug contributed 1.5 points to the dPSS or iPSS. The primary objective was to evaluate the predictive value of RC or Natural Product Library ic50 either PSS for virological or immunological outcomes at weeks 12 to 48 following randomization. The sample size estimates for this substudy were based on assumptions made regarding RC changes during ARDFP. Compilation of RC data from published studies [15, 27]

and unpublished observations suggested that mean log10 RC increases by 0.3 [standard deviation (SD) = 0.38] after 2 months of ARDFP. According to these data, we estimated that the available sample size provided 90% power to detect a mean change of 0.20 in log10 RC. The intended duration of ARDFP in OPTIMA was 12 weeks, so that an increase in RC after the ARDFP greater than 0.3 might be anticipated. Pearson correlation analysis was used to analyse baseline RC in response to salvage ARV therapy and/or Galactosylceramidase treatment interruption. Multivariate regression analysis was performed in order to evaluate changes in (a) CD4 cell count using baseline viral load, RC and PSS as independent variables and (b) viral load using baseline

CD4 cell count, RC and PSS as independent variables. P-values of < 0.05 were chosen a priori to be indicative of statistical significance. The statistical software used was sas version 9.1 (SAS Institute, Cary, NC). A total of 283 patients had samples available for RC and PSS measurements at baseline and were included in the analysis. Baseline demographic characteristics, previous and on-study ARV use, and baseline CD4 cell counts and HIV RNA of these patients are presented in Table 1. As reported elsewhere [25], no significant differences were found in the primary outcome measure by treatment arm. For the purpose of this substudy, we combined the subgroups receiving standard and mega-ARV regimens within the no-ARDFP group (n = 146) and the ARDFP group (n = 137). Mean week 0 RC was low: 50.8% (SD = 44.6) in the no-ARDFP patients and 52.4% (SD = 40.2) in the ARDFP patients. There was no significant difference in week 0 CD4 cell count, viral load or RC between groups (P = 0.774, P = 0.594 and P = 0.

Both dPSS and iPSS attempt to express the sum of the phenotypically

active ARV drugs in the patients’ new regimen. In the dPSS, the activity of each new drug in the regimen was estimated as follows: if fold-change (FC) was less than the lower CCO (i.e. susceptible), the drug contributed 1 point; if FC was higher than the lower CCO (i.e. resistant), the drug contributed 0 points to the dPSS. The iPSS was calculated in a similar fashion but also accounts for partial or intermediate susceptibility of new ARV drugs (FC between selleck kinase inhibitor the upper and lower CCOs): each fully active drug (FC < lower CCO) gets a score of 1, and each partially active drug (lower CCO < FC < upper CCO) gets a score of 0.5. In both dPSS and iPSS, if the FC was < 0.4 for a specific drug (i.e. the virus was considered to be hypersusceptible to the drug), that drug contributed 1.5 points to the dPSS or iPSS. The primary objective was to evaluate the predictive value of RC or click here either PSS for virological or immunological outcomes at weeks 12 to 48 following randomization. The sample size estimates for this substudy were based on assumptions made regarding RC changes during ARDFP. Compilation of RC data from published studies [15, 27]

and unpublished observations suggested that mean log10 RC increases by 0.3 [standard deviation (SD) = 0.38] after 2 months of ARDFP. According to these data, we estimated that the available sample size provided 90% power to detect a mean change of 0.20 in log10 RC. The intended duration of ARDFP in OPTIMA was 12 weeks, so that an increase in RC after the ARDFP greater than 0.3 might be anticipated. Pearson correlation analysis was used to analyse baseline RC in response to salvage ARV therapy and/or new treatment interruption. Multivariate regression analysis was performed in order to evaluate changes in (a) CD4 cell count using baseline viral load, RC and PSS as independent variables and (b) viral load using baseline

CD4 cell count, RC and PSS as independent variables. P-values of < 0.05 were chosen a priori to be indicative of statistical significance. The statistical software used was sas version 9.1 (SAS Institute, Cary, NC). A total of 283 patients had samples available for RC and PSS measurements at baseline and were included in the analysis. Baseline demographic characteristics, previous and on-study ARV use, and baseline CD4 cell counts and HIV RNA of these patients are presented in Table 1. As reported elsewhere [25], no significant differences were found in the primary outcome measure by treatment arm. For the purpose of this substudy, we combined the subgroups receiving standard and mega-ARV regimens within the no-ARDFP group (n = 146) and the ARDFP group (n = 137). Mean week 0 RC was low: 50.8% (SD = 44.6) in the no-ARDFP patients and 52.4% (SD = 40.2) in the ARDFP patients. There was no significant difference in week 0 CD4 cell count, viral load or RC between groups (P = 0.774, P = 0.594 and P = 0.

A small number of pharmacists were permitted to move groups, and this may have had an impact on findings.

The ITT analysis, based on allocated group, suggests that this was not the case The reduction in illicit heroin use in all patients is in line with Thiazovivin chemical structure multiple studies of methadone maintenance treatment.[19] The absolute reduction in heroin use in this study (15%) was in line with other cohort studies.[17] However, there was no significant difference between the groups, indicating EPS did not further reduce illicit heroin use. There was better retention in the intervention group (87.7%) than the control group (80.8%), but the between-group difference was not statistically significant, although retention was very high overall. Retention in this study compared favourably to other methadone studies which ranged from 19–90%.[19] However, it is not entirely appropriate to compare retention with other studies because our participants were not necessarily recruited at the very start of treatment and there may be more attrition in the early weeks. Whilst successful outcomes have been reported from the use of MI in interventions addressing alcohol,[5, 6] smoking[20] and drug dependence[7] it has not always

demonstrated benefits. When used as part of an integrated intervention with cognitive behavioural therapy for people with psychosis and co-morbid substance abuse, it was unable signaling pathway to improve patient outcomes.[21] Other studies also suggest that MI can in fact be counter-productive in people who are already highly motivated.[22] The lack of effect in the

current study may also be because participants were already highly motivated to reduce their heroin use, making it unlikely that this pharmacy intervention service would have a significant impact. Physical health was actually significantly poorer at follow-up in the intervention group compared to control. This may be due to statistical chance. Alternatively, it may reflect an increased awareness by patients of their health as a result of communication with pharmacists, a finding reported in other studies.[23] The intervention may have increased health awareness but was not aimed at addressing other health problems. Psychological health was slightly Protein tyrosine phosphatase worse at follow-up in the intervention group. This is contrary to the NTORS[17] which found these parameters improved over time in a general UK treatment cohort. Although there was no significant difference in treatment satisfaction between groups at follow-up, there was a significant improvement in treatment satisfaction over time in the intervention group. This corresponds with increased treatment retention and may be because intervention patients felt happier in the pharmacy owing to more and possibly ‘better’ communication with the pharmacist. Ideally some qualitative follow-up would have been conducted to explore this further. The suggestion of improved treatment retention and satisfaction are important for policy makers.