Weak smoking cessation awareness in primary health care before surgery: a real-world, retrospective cohort study.

Objective: Tobacco smoking is a well-established risk factor for postoperative complications. Research on preoperative smoking cessation in primary health care is scarce.Design: This was a retrospective cohort study.Setting: The Stop Smoking before Surgery Project (SSSP) started in Porvoo, Finland, in May of 2016, involving both primary health care and specialized health care. The goals of the project were smoking awareness and preoperative smoking cessation.Subjects: Our study involved 1482 surgical patients operated at Porvoo Hospital between May and December of 2016.Main outcome measures: We studied the recording of smoking status in all patients, and ICD-10 diagnosis of nicotine dependency and the initiation of preoperative smoking cessation in current smokers. Variables were studied from electronic patient records, comparing primary health care referrals and surgical outpatient clinic records.Results: Smoking status was visible in 14.2% of primary health care referrals, and in 18.4% of outpatient clinic records. Corresponding rates for current smokers (n = 275) were 0.0 and 8.7% for ICD-10 diagnosis of nicotine dependence, and 2.2 and 15.3% for initiation of preoperative smoking cessation. The differences between primary health care referrals and outpatient clinic records were statistically significant for all three variables (p ≤ .001).Conclusion: In primary health care, very little attention was paid to preoperative smoking cessation. Rates were significantly better at the surgical outpatient clinic, but still low. We could not demonstrate any certain effect of the intervention. Our results call for future research on ways to improve smoking cessation rates.Key pointsTobacco smoking is a well-established risk factor for postoperative complications. Research on preoperative smoking cessation in primary health care is scarce.We found weak smoking awareness and weak smoking cessation intervention numbers among both primary and specialized health care doctors. Our results indicate an urgent need for an efficient preoperative smoking cessation model involving both primary and specialized health care.

Smoking is a predictor of complications in all types of surgery: a machine learning-based big data study.

BACKGROUND: Machine learning algorithms are promising tools for smoking status classification in big patient data sets. Smoking is a risk factor for postoperative complications in major surgery. Whether this applies to all surgery is unknown. The aims of this retrospective cohort study were to develop a machine learning algorithm for clinical record-based smoking status classification and to determine whether smoking and former smoking predict complications in all surgery types. METHODS: All surgeries performed in a Finnish hospital district from 1 January 2015 to 31 December 2019 were analysed. Exclusion criteria were age below 16 years, unknown smoking status, and unknown ASA class. A machine learning algorithm was developed for smoking status classification. The primary outcome was 90-day overall postoperative complications in all surgeries. Secondary outcomes were 90-day overall complications in specialties with over 10 000 surgeries and critical complications in all surgeries. RESULTS: The machine learning algorithm had precisions of 0.958 for current smokers, 0.974 for ex-smokers, and 0.95 for never-smokers. The sample included 158 638 surgeries. In adjusted logistic regression analyses, smokers had increased odds of overall complications (odds ratio 1.17; 95 per cent c.i. 1.14 to 1.20) and critical complications (odds ratio 1.21; 95 per cent c.i. 1.14 to 1.29). Corresponding odds ratios of ex-smokers were 1.09 (95 per cent c.i. 1.06 to 1.13) and 1.09 (95 per cent c.i. 1.02 to 1.17). Smokers had increased odds of overall complications in all specialties with over 10 000 surgeries. ASA class was the most important complication predictor. CONCLUSION: Machine learning algorithms are feasible for smoking status classification in big surgical data sets. Current and former smoking predict complications in all surgery types.

Investigating the rationale for COPD maintenance therapy prescription across Europe, findings from a multi-country study.

This study aims to understand healthcare professionals' thoughts and motivations about optimal management and treatment of patients with chronic obstructive pulmonary disease (COPD). We conducted a DELPHI survey through an online questionnaire distributed to 220 panellists from six European countries and a discrete choice experiment to describe the relationship between selected clinical criteria and the initial COPD treatment of choice. One hundred twenty-seven panellists (general practitioners [GPs] and pulmonologists) completed the survey. Despite the familiarity and use (89.8%) of the GOLD classification for initial treatment selection, a frequent use of LAMA/LABA/ICS was noted. In fact, panellists agreed that inhaled corticosteroids (ICS) are over-prescribed in the primary care setting. Our study showed that GPs felt less confident than pulmonologists with ICS withdrawal. This mismatch observed between best practice and behaviour indicates the need to increase awareness and efforts to improve the adherence to guidelines in clinical practice.

Smoking attenuates increase in exhaled nitric oxide in atopic but not in nonatopic young adults with asthma.

BACKGROUND: Measurement of fractional exhaled nitric oxide (FENO) is useful in assessing eosinophilic airway inflammation. Smoking may modify airway inflammation and reduce FENO levels, compromising the diagnostic value of FENO in smokers. How smoking influences FENO in atopic versus nonatopic asthmatics is unknown. The aim of the present study was to compare FENO in atopic and nonatopic steroid-naive young asthmatic adults and in healthy subjects in terms of smoking. METHODS: Forty-six (30 atopic) smoking and 70 (54 atopic) nonsmoking steroid-naive army conscripts (mean age 20 years) with current symptomatic asthma underwent FENO measurement, skin prick tests, spirometry with a bronchodilation test, bronchial histamine challenge, and a standardized exercise test. Ten healthy smokers and 9 healthy nonsmokers underwent FENO measurement, spirometry and bronchial histamine challenge. RESULTS: Smokers with asthma showed significantly higher FENO than did healthy smokers and nonsmokers (p = 0.001, both comparisons). Among atopic asthmatics, FENO was lower in smokers than in nonsmokers (p = 0.002) whereas among nonatopic asthmatics no such difference was detectable (p = 0.89). However, even among nonatopic asthmatic smokers FENO was significantly higher than among healthy controls (p = 0.01). CONCLUSION: Smoking seems to attenuate the increase in FENO in atopic but not in nonatopic asthmatics. This finding suggests differences in biochemical mechanisms of NO formation in atopic and nonatopic asthma. However, FENO was significantly higher both in atopic and nonatopic asthmatic smokers than in healthy controls. This suggests that FENO can be applied for diagnostic purposes also in young adult smokers.

Re-treatment with varenicline is a cost-effective aid for smoking cessation.

OBJECTIVE: One quit attempt with varenicline has been found to be a cost-effective smoking cessation intervention. The purpose of this study was to analyze varenicline's cost-effectiveness in patients who relapse during or after the first treatment. A comparison was made between re-treatment schema with varenicline and re-treatment schema with bupropion, NRT and unaided cessation, and treatment once with varenicline in a Finnish context. METHODS: The two-quit version of BENESCO Markov model was used to follow a cohort of smokers making up to two quit attempts over a lifetime. The abstinence rates of the interventions were derived from a Cochrane review. Gender- and age-specific data on the incidence and prevalence of five smoking-related diseases were included in the model. Quality-adjusted life-years, total expected costs, and the lifetime cumulative incidence of smoking-related morbidities and mortality were the primary outcomes evaluated. RESULTS: The study cohort comprised 116,533 smokers who were willing to make a quit attempt. In the lifetime simulation, re-treatment with varenicline yielded 6,150-20,250 extra quitters, depending on the comparator. Among these quitters it was possible to prevent 899-2,972 additional cases of smoking-related diseases, and 395-1,307 deaths attributable to smoking. Re-treatment with varenicline resulted in cost savings of up to 54.9 million Euros. Re-treatment with varenicline dominated all the other smoking cessation interventions used in the analysis. Sensitivity analysis supported the robustness of the base case results. LIMITATIONS: The analysis did not consider adverse events, and included only five major smoking-related diseases, which is a conservative approach, and probably leads to under-estimation of cost-effectiveness of cessation interventions. Furthermore, assumptions of constant relative risks for smoking-related diseases for each smoking status and the proxy values used as efficacy estimates of second quit attempts for other interventions than varenicline are limitations. CONCLUSIONS: A second quitting effort with varenicline is economically justifiable.

Equally elevated concentrations of exhaled nitric oxide in nonatopic and low-sensitized atopic asthmatics.

BACKGROUND: Some studies show concentrations of exhaled nitric oxide (FENO) in nonatopic asthma and in healthy subjects to be similar, but include asthmatics on inhaled steroids, which is likely to interfere with the results. AIM: Comparison of FENO between nonatopic asthmatics, low-sensitized and high-sensitized atopic asthmatics, and healthy controls. METHODS: We studied 85 non-smoking, steroid-naive young men with recently diagnosed symptomatic asthma and 10 healthy controls. FENO was measured according to European Respiratory Society Guidelines. In skin prick tests of 13 common aeroallergens, subjects with a total sum of prick wheals 3-10mm were regarded as low-sensitized and those with >10mm, as high-sensitized. Flow-volume spirometry, standardized histamine challenge, and an exercise test were also carried out. RESULTS: Prick tests revealed 14 subjects to be nonatopic and 71 atopic. In high-sensitized subjects with atopic asthma, the FENO median (25-75 quartiles) was significantly higher, 34.9 (21.3-53.8) parts per billion (ppb), than in subjects with nonatopic asthma, 15.2 (9.7-24.7)ppb (p<0.001), both being significantly higher than in healthy controls, 6.6 (5.2-8.5)ppb (p<0.001). FENO levels were similar in nonatopic and in low-sensitized atopic asthmatics, with no difference between them in bronchial responsiveness to histamine and exercise. CONCLUSION: Among steroid-naive young male asthmatics, FENO was equally elevated in nonatopic asthma and in low-sensitized atopic asthma but lower than in those with high-sensitized atopic asthma. These differences in FENO between asthma groups parallel the differences in airway function disturbance in terms of responsiveness to histamine or exercise.