Method: The nature of patient-pharmacist counseling interactions was explored with seven patients (one focus group), and 10 practicing pharmacists (two focus groups, three semi-structured interviews). The themes identified informed the development of an online survey that was advertised online to patients and pharmacists across Australia.
Results: A total of 95 patients and 208 pharmacists completed the survey. Overall, more than half of patients (77/95) were satisfied with the care provided by their pharmacist, but only a third (71/205) of pharmacists were satisfied with the care they provided to patients. The majority of patients (67/94) reported that pharmacists provided good information about medications. This aligned with pharmacists' responses, as most reported focusing on medication side effects (118/188) and instructions for taking pain medication (93/183) during patient interactions. However, when asked about empathy and rapport from pharmacists, only half to two-thirds (48-61/95) of patients expressed positive views. Overall, half of the patients (39/75) wanted a caring, empathetic, respectful, and private conversation with the pharmacist, and nearly half (40/89) perceived the pharmacist's role as providing (new) information on alternative pharmacological and non-pharmacological therapies, including general advice on pain management.
Conclusion: There was a disparity in the nature of the interaction and information that patients wanted from pharmacists, compared to what was provided by pharmacists. Training and education may help pharmacists to better engage in patient-centered care when interacting with people living with persistent pain, thereby improving health outcomes for these patients.
METHODS: Plasma SPM were measured in samples obtained from two double-blind controlled interventions. The first, included 51 women mean age 53 ± 1.5 years, undergoing breast surgery allocated to either intravenous saline, or dexamethasone (4 mg or 8 mg) after induction of anaesthesia. The second study included 31 women of mean age 44 ± 0.5 years undergoing laparoscopic gynecological surgery that were allocated to either saline, or dexamethasone (4 mg). SPM (18-HEPE, 17-HDHA, RvE2, RvD1 17R-RvD1 and RvD2) were measured in plasma collected prior to induction of anaesthesia and at 24 h, and 6 weeks post-surgery. Pain was assessed using a verbal analogue scale at discharge from the post-anaesthesia recovery unit. The data from each study was combined to examine the effect of dexamethasone on plasma SPM. The relationship between pain score and SPM was examined using ordinal logistic regression.
RESULTS: The SPM 18-HEPE, 17-HDHA, RvE2, RvD1 17R-RvD1 and RvD2 were detectable in all plasma samples. There was no significant difference in any SPM due to dexamethasone over the duration of the study. There was a fall in 17-HDHA between baseline and 24 h in both the dexamethasone and saline groups (P = 0.003) but no change in the downstream SPM (RvD1, 17R-RvD1 and RvD2) or 18-HEPE and RvE2. Pain score was negatively related to levels of RvE2 measured prior to induction of anaesthesia (rho = -0.2991, P = 0.006) and positively related to BMI (rho = 0.279, P = 0.011). In ordinal logistic regression the odds ratio for RvE2 was 0.931 (CI 0.880, 0.986; P = 0.014); after adjusting for the effect of BMI indicating that an increase in RvE2 of 1 pg/ml would result in a 6.9 % fall in pain score. Allocation to a dexamethasone group did not influence the pain score or the relationship between RvE2 and pain score.
CONCLUSION: Dexamethasone administered as an anti-emetic does not affect plasma SPM levels. An elevated RvE2 level prior to surgery is predictive of a lower perceived pain score post-anaesthesia.
METHODS: Thirty-two healthy volunteers were randomly allocated to receive saline (Control) or dexamethasone 2 mg, 4 mg or 8 mg intravenously. Venous blood samples were collected at baseline before administration of treatment, and at 4 h, 24 h and one-week post-treatment. At each time point, measurements included blood glucose and macrophage migration inhibition factor (MMIF), full blood count including lymphocyte subsets, monocytes, neutrophils, eosinophils and basophils by flow cytometry, and plasma SPM using liquid chromatography tandem mass spectrometry. The effect of dexamethasone dose and time on all measures was analysed using linear mixed models.
RESULTS: There was a dose-dependent increase in neutrophil count after dexamethasone that persisted for 24 h. In contrast, there was a dose-dependent reduction in counts of monocytes, lymphocytes, basophils and eosinophils 4 h after dexamethasone, followed by a rebound increase in cell counts at 24 h. Seven days after administration of dexamethasone, all cell counts were similar to baseline levels. MMIF concentration, glucose and natural killer cell counts were not significantly affected by dexamethasone. There was a significant gender effect on plasma SPM such that levels of 17-HDHA, RvD1, 17R-RvD1 and RvE2 in females were on average 14%-50% lower than males. In a linear mixed model that adjusted for neutrophil count, there was a significant interaction between the dose of dexamethasone and time, on plasma 17R-RvD1 such that plasma 17R-RvD1 fell in a dose-dependent manner until 4 h after administration of dexamethasone. There were no significant effects of dexamethasone on the other plasma SPM (18-HEPE, RvE2, 17-HDHA, RvD1, RvD2 and 14-HDHA) measured.
DISCUSSION: This is the first study in healthy volunteers to demonstrate that commonly employed antiemetic doses of dexamethasone affect immune cell populations and plasma levels of 17R-RvD1 an SPM with anti-nociceptive properties. If similar changes occur in surgical patients, then this may have implications for acute infection risk in the post-operative period.
OBJECTIVE: To analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.
EVIDENCE REVIEW: The incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.
FINDINGS: In 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.
CONCLUSIONS AND RELEVANCE: In this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.