Factors associated with nicotine replacement therapy use among hospitalised smokers.

INTRODUCTION AND AIMS: Nicotine replacement therapy (NRT) is recommended as a smoking cessation aid for hospitalised smokers. We examined factors associated with NRT use during hospitalisation and after discharge, and NRT uptake when systematically offered free of cost. DESIGN AND METHODS: A nested analysis was conducted using data from a clinical trial that evaluated the effectiveness of a pharmacist-led smoking cessation intervention in 600 hospitalised smokers. RESULTS: NRT was used at least once by 285 (48%) participants during hospitalisation and by 287 (48%) participants during the 12 months post-discharge. Heavy smokers and those who expressed interest in using NRT for their next quit attempt at baseline interview were more likely to use NRT during hospitalisation [odds ratio (OR) 1.94, 95% confidence interval (CI) 1.38, 2.74; OR 2.09, 95% CI 1.48, 2.95] and after discharge (OR 1.70, 95% CI 1.20, 2.41; OR 1.97, 95% CI 1.39, 2.79). Those using six or more medications were more likely to use NRT during hospitalisation (OR 1.65, 95% CI 1.05, 2.61). Post-discharge NRT users were more likely to have been initially admitted for a respiratory or cardiac problem (OR 1.51, 95% CI 1.05, 2.18). When NRT was offered free of cost to a subset of patients (n = 300), 157 (52%) used NRT during hospitalisation. Nicotine dependence and interest in using NRT predicted its use (OR 2.26, 95% CI 1.38, 3.70; OR 2.58, 95% CI 1.58, 4.20). DISCUSSION AND CONCLUSIONS: Targeting heavy smokers, those with cardio-respiratory conditions and those interested in using NRT regardless of regimen complexity could improve NRT uptake.

Medication Use and Fall-Related Hospital Admissions from Long-Term Care Facilities: A Hospital-Based Case-Control Study.

BACKGROUND: Falls are a leading cause of preventable hospitalizations from long-term care facilities (LTCFs). Polypharmacy and falls-risk medications are potentially modifiable risk factors for falling. OBJECTIVE: This study investigated whether polypharmacy and falls-risk medications are associated with fall-related hospital admissions from LTCFs compared with hospital admissions for other causes. METHODS: This was a hospital-based, case-control study of patients aged ≥65 years hospitalized from LTCFs. Cases were patients with falls and fall-related injuries, and controls were patients admitted for infections. Conditional logistic regression was used to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between polypharmacy (defined as the use of nine or more regular pre-admission medications) and falls-risk medications (categorized as psychotropic medications and those that can cause orthostatic hypotension) with fall-related hospital admissions. RESULTS: There was no association between polypharmacy and fall-related hospital admissions (adjusted OR 0.97, 95% CI 0.63-1.48); however, the adjusted odds of fall-related hospital admissions increased by 16% (95% CI 3-30%) for each additional falls-risk medication. Medications that can cause orthostatic hypotension (adjusted OR 1.25, 95% CI 1.06-1.46), but not psychotropic falls-risk medications (adjusted OR 1.02, 95% CI 0.88-1.18) were associated with fall-related hospital admissions. The association between medications that can cause orthostatic hypotension and fall-related hospital admissions was strongest among residents with polypharmacy (adjusted OR 1.44, 95% CI 1.08-1.92). CONCLUSION: Polypharmacy was not an independent risk factor for fall-related hospital admissions; however, medications that can cause orthostatic hypotension were associated with fall-related hospital admissions, particularly among residents with polypharmacy. Falls-risk should be considered when prescribing medications that can cause orthostatic hypotension.

Development and validation of a 21-item challenges to stopping smoking (CSS-21) scale.

OBJECTIVE: Identification of challenges associated with quitting and overcoming them may improve cessation outcomes. This study describes the development and initial validation of a scale for measuring challenges to stopping smoking. METHODS: The item pool was generated from empirical and theoretical literature and existing scales, expert opinion and interviews with smokers and ex-smokers. The questionnaire was administered to smokers and recent quitters who participated in a hospital-based smoking cessation trial. Exploratory factor analysis was performed to identify subscales in the questionnaire. Internal consistency, validity and robustness of the subscales were evaluated. RESULTS: Of a total of 182 participants with a mean age of 55 years (SD 12.8), 128 (70.3%) were current smokers and 54 (29.7%) ex-smokers. Factor analysis of the 21-item questionnaire resulted in a 2-factor solution representing items measuring intrinsic (9 items) and extrinsic (12 items) challenges. This structure was stable in various analyses and the 2 factors accounted for 50.7% of the total variance of the polychoric correlations between the items. Internal consistency (Cronbach's α) coefficients for the intrinsic and extrinsic subscales were 0.86 and 0.82, respectively. Compared with ex-smokers, current smokers had a higher mean score (± SD) for intrinsic (24.0 ± 6.4 vs 20.5 ± 7.4, p=0.002) and extrinsic subscales (22.3 ± 7.5 vs 18.6 ± 6.0, p=0.001). CONCLUSIONS: Initial evaluation suggests that the 21-item challenges to stopping smoking scale is a valid and reliable instrument that can be used in research and clinical settings to assess challenges to stopping smoking.

Quitting experiences and preferences for a future quit attempt: a study among inpatient smokers.

OBJECTIVE: Understanding smokers' quit experiences and their preferences for a future quit attempt may aid in the development of effective cessation treatments. The aims of this study were to measure tobacco use behaviour; previous quit attempts and outcomes; methods used to assist quitting; difficulties experienced during previous attempts; the motives and preferred methods to assist quitting in a future attempt; identify the factors associated with preferences for smoking cessation. DESIGN: Face-to-face interview using a structured questionnaire. SETTING: Inpatient wards of three Australian public hospitals. PARTICIPANTS: Hospitalised smokers enrolled in a smoking cessation trial. RESULTS: Of 600 enrolled patients (42.8% participation rate), 64.3% (n=386) had attempted quitting in the previous 12 months. On a scale of 1 (low) to 10 (high), current motivation to quit smoking was high (median 9; IQR 6.5-10), but confidence was modest (median 5; IQR 3-8). Among 386 participants who reported past quit attempts, 69.9% (n=270) had used at least one cessation aid to assist quitting. Nicotine replacement therapy (NRT) was most commonly stated (222, 57.5%), although the majority had used NRT for <4 weeks. Hypnotherapy was the most common (68, 17.6%) non-pharmacological treatment. Over 80% (n=311) experienced withdrawal symptoms; craving and irritability were commonly reported. Most participants (351, 58.5%) believed medications, especially NRT (322, 53.7%), would assist them to quit in the future. History of previous smoking cessation medication use was the only independent predictor of interest in using medications for a future quit attempt. CONCLUSIONS: The majority of smokers had attempted quitting in the previous 12 months; NRT was a popular cessation treatment, although it was not used as recommended by most. This suggests a need for assistance in the selection and optimal use of cessation aids for hospitalised smokers. TRIAL REGISTRATION NUMBER: Australian and New Zealand Clinical Trials Registry: ACTRN12612000368831.

A standard weight descriptor for dose adjustment in the obese patient.

OBJECTIVE: To develop a standard weight descriptor that can be used for estimation of patient size for obese patients. PATIENTS AND METHODS: Data were available from 3849 patients: 2839 from oncology patients (index data set) and 1010 from general medical patients (validation data set). The patients had a wide range of age (16-100 years), weight (25-165 kg) and body mass index (BMI) [12-52 kg/m2] in both data sets. From the normal-weight patients in the oncology data set, an equation for male and female patients was developed to predict their normal weight as the sum of the lean body mass and normal fat body mass. The equations were evaluated by predicting the weight of patients in the general medical data set who had a normal BMI (<25 kg/m2). In addition, the clinical utility of the predicted normal weight (PNWT) descriptor was assessed by (i) comparing body surface area and allometric scaling calculations based on actual weight of obese patients versus PNWT; and (ii) comparing the predictive performance of creatinine clearance using the Cockcroft and Gault equation when using actual weight of obese patients versus PNWT to predict gentamicin clearance. RESULTS: The PNWT equations developed from the oncology data set predicted accurately the actual weight of normal weighted (BMI <25 kg/m2) general medical patients (R2 = 0.968 men, R2 = 0.946 women). Using actual weight when computing body surface area and when allometric scaling for obese patients results in significant overestimation of patient size, especially for female patients and those with BMIs >35 kg/m2. The use of PNWT in the Cockcroft and Gault equation provided better predictions of gentamicin clearance than when using actual weight. CONCLUSIONS: A standard weight descriptor has been developed that can be used in dosing algorithms for patients who are obese (BMI >30 kg/m2).

Off-label prescribing in oncology.

Off-label prescribing occurs when a practitioner prescribes a drug for a use, or in a manner, not listed in the 'approved product information' (API) for that drug. The literature suggests that this is a frequent occurrence in many areas of medicine, but data are limited in the hospitalized oncology setting. The aim of this study was to quantify the extent of off-label prescribing in a hospitalized oncology population in Australia. The study was conducted at Peter MacCallum Cancer Centre, Australia. On a single day the medication charts of all hospitalized patients were prospectively reviewed. Drug prescribing was assessed for licensing status by comparison with the API as approved by the Therapeutic Goods Administration of Australia. Prescriptions were classified as licensed, off-label or unlicensed. Medication charts of 130 patients were assessed. There were 1351 prescriptions. In 293 (22%) of the prescriptions the drug was either off-label (242, 18%) or unlicensed (51, 4%). Among the 130 patients, 110 (85%) received at least one drug that was prescribed off-label or that was unlicensed. Off-label dosing was the most frequent reason for a drug being off-label (139, 10% of all prescriptions). Off-label due to use for an unapproved indication was found in 118 prescriptions (9%), and off-label due to an unapproved route of administration was found in 38 prescriptions (3%). Off-label prescribing is widespread in the acute hospitalized oncology population, with approximately 22% of all prescriptions being for off-label or unlicensed medication. Such prescribing affects a significant proportion of patients.