OBJECTIVE: This study aims to evaluate the effectiveness of carbon monoxide measurement feedback and the standard brief motivation adopted to encourage the smoker to quit.
METHODS: A single-blind, cluster randomised controlled trial was conducted at ten tertiary colleges in Selangor. The study recruited young adult smokers at the precontemplation and contemplation stages. The subjects in the control group received a standard brief motivational strategy. On the other hand, the intervention group received additional carbon monoxide measurement and a motivational feedback module. A follow up was conducted at the first, third and sixth month to measure changes in smoking cessation stage. Subsequently, the secondary outcomes of a mean number of cigarette consumption and quit smoking attempt were analysed. A total of 160 subjects were required to detect the expected difference of 17% in primary outcomes between the groups. This study utilised Generalised Estimating Equations (GEE) to handle the clustering effects.
CONCLUSION: Biomedical risk assessment feedback mechanism by using carbon monoxide is a promising aid to motivate the smoker to quit. This mechanism is a relatively easy, quick and non-invasive technique. Thus, it can be utilised as a reinforcement relating to the harmful effect of smoking. Besides, it can also increase the smokers' selfefficacy and decisional balance to adopt behavioural changes.
SETTING: Five medical and cardiology wards of a tertiary care center in Malaysia.
SUBJECTS: Five hundred cardiac inpatients, who received ACEIs concomitantly with other interacting drugs.
METHOD: This was a prospective cohort study of 500 patients with cardiovascular diseases admitted to Penang Hospital between January to August 2006, who received ACEIs concomitantly with other interacting drugs. ACEI-drug interactions of clinical significance were identified using available drug information resources. Drug Interaction Probability Scale (DIPS) was used to assess the causality of association between ACEI-drug interactions and the adverse outcome (hyperkalemia).
MAIN OUTCOME MEASURE: Hyperkalemia as an adverse clinical outcome of the interaction was identified from laboratory investigations.
RESULTS: Of the 489 patients included in the analysis, 48 (9.8%) had hyperkalemia thought to be associated with ACEI-drug interactions. Univariate analysis using binary logistic regression revealed that advanced age (60 years or more), and taking more than 15 medications were independent risk factors significantly associated with hyperkalemia. However, current and previous smoking history appeared to be a protective factor. Risk factors identified as predictors of hyperkalemia secondary to ACEI-drug interactions by multi-logistic regression were: advanced age (adjusted OR 2.3, CI 1.07-5.01); renal disease (adjusted OR 4.7, CI 2.37-9.39); hepatic disease (adjusted OR 5.2, CI 1.08-25.03); taking 15-20 medications (adjusted OR 4.4, CI 2.08-9.19); and taking 21-26 medications (adjusted OR 9.0, CI 1.64-49.74).
CONCLUSION: Cardiac patients receiving ACEIs concomitantly with potentially interacting drugs are at high risk of experiencing hyperkalemia. Old age, renal disease, hepatic disease, and receiving large number of medications are factors that may significantly increase their vulnerability towards this adverse outcome; thus, frequent monitoring is advocated.
OBJECTIVES: The aim of this study was to assess the self-reported presence of oral lesions by COVID-19-infected young adults and the differences in the association between oral lesions and COVID-19 infection in smokers and non-smokers.
METHODS: This cross-sectional multi-country study recruited 18-to-23-year-old adults. A validated questionnaire was used to collect data on COVID-19-infection status, smoking and the presence of oral lesions (dry mouth, change in taste, and others) using an online platform. Multi-level logistic regression was used to assess the associations between the oral lesions and COVID-19 infection; the modifying effect of smoking on the associations.
RESULTS: Data was available from 5,342 respondents from 43 countries. Of these, 8.1% reported COVID-19-infection, 42.7% had oral manifestations and 12.3% were smokers. A significantly greater percentage of participants with COVID-19-infection reported dry mouth and change in taste than non-infected participants. Dry mouth (AOR=, 9=xxx) and changed taste (AOR=, 9=xxx) were associated with COVID-19- infection. The association between COVID-19-infection and dry mouth was stronger among smokers than non-smokers (AOR = 1.26 and 1.03, p = 0.09) while the association with change in taste was stronger among non-smokers (AOR = 1.22 and 1.13, p = 0.86).
CONCLUSION: Dry mouth and changed taste may be used as an indicator for COVID-19 infection in low COVID-19-testing environments. Smoking may modify the association between some oral lesions and COVID-19-infection.
METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.
CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.
METHODS: Secondary analysis of data extracted from the British Household Panel Survey, a national longitudinal survey (n=5547). Analysis to ascertain whether patterns of attendance for dental check-ups for a period of 10 years (1991-2001) were associated with risk factors for oral cancer such as age, sex, education, social class, smoking status and smoking intensity.
RESULTS: Males, aged over 40 years, less educated manual workers and smokers were significantly less likely to attend for dental check-ups compared with females and younger, higher educated, higher socio-economic class non-smokers (p < 0.05). Throughout the 10-year period, young people, more than older people, had progressively lower odds ratios of attending. Those with more education used dental services more. Heavy smokers were infrequent attendees.
CONCLUSIONS: This study suggests that opportunistic oral cancer screening by dentists is not feasible to include high-risk groups as they are not regular attendees over 10 years. Those who would be screened would be the low-risk groups. However, dentists should continue screening all patients as oral precancers are also found in regular attendees. More should be done to encourage the high-risk groups to visit their dentists.