Baseline characteristics and the factors influencing successful smoking cessation: A comparison between a WeChat smoking cessation mini-program and an offline smoking cessation clinic.

INTRODUCTION: Smoking cessation (SC) clinics are a professional SC services in China. However, studies comparing the characteristics and SC rates of smoking populations in SC clinics with those using mobile SC programs are limited. We compared smokers' characteristics, 3-month SC rates, and the factors influencing 3-month SC success, between a large hospital SC clinic and a WeChat SC mini-program. METHODS: Between January and November 2021, 384 participants voluntarily enrolled in either the hospital SC clinic (Group A: n=243) or the WeChat SC mini-program (Group B: n=141). Both groups underwent a 3-month SC intervention, and their SC status was monitored at 24 hours, 1 week, 1 month, and 3 months after quitting. SC rate was defined as the self-reported rate of continuous SC. RESULTS: The 3-month SC rate was higher in Group A (42.4%) than in Group B (24.8%). Participants with middle school education had a lower likelihood of SC success than those with primary school or lower (p=0.014). Employees in the enterprise/business/services industries were more likely to have SC success than farmers (p=0.013). Participants with SC difficulty scores of 0-60 were more successful than those with scores >60 (p=0.001, p=0.000, respectively). Participants who quit smoking due to their illness, or other reasons, had a higher likelihood of SC success than those who quit due to concerns about their own and their family's health (p=0.006, p=0.098, respectively). While the likelihood of SC success was lower in those who quit because of the influence of their environment than in those who quit due to concerns about their own and their family's health (p=0.057). CONCLUSIONS: Both SC clinics and WeChat SC mini-programs achieved satisfactory SC rates. The high accessibility of mobile SC platforms, which save time spent on transportation and medical visits, renders them worth promoting and publicizing as additional SC options for smokers, particularly young smokers.

Evaluation of the smoking cessation effects of QuitAction, a smartphone WeChat platform.

INTRODUCTION: Many smokers in China desire to quit, though the success rate among adults is low. This study evaluated the effects of QuitAction, a WeChat smoking cessation platform, summarized the intervention experience of the smoking cessation platform, identified aspects of the platform that necessitated improvement, and provided references for further optimization of the smoking cessation platform. METHODS: This single-arm study was conducted in Hunan, China, from September 2020 to October 2021. Regular smokers, who were aged ≥15 years and willing to quit smoking using QuitAction, were recruited. An in-application questionnaire evaluated participants' baseline smoking status and intention to quit smoking. The QuitAction program included questionnaires regarding the participants' ongoing smoking cessation status at 24 hours, one week, one month and three months after quitting. The smoking cessation procedure was discontinued if the participant had no intention of continuing. The smoking cessation rate, influencing success factors, frequency of use satisfaction, and helpfulness of QuitAction were recorded. RESULTS: A total of 303 participants registered and logged into the QuitAction program, including 59 with incomplete information and 64 with no intention of quitting. The study finally included 180 participants. The smoking cessation rate was 33.9% at 24 hours, 27.2% at one week, 26.1% at one month, and 25.0% at three months. QuitAction was reported as helpful by 94.9% of participants and 95.7% were satisfied with the program. Participants with a quitting difficulty score of 80-100 were less likely to quit smoking than participants with a difficulty score of 0-60 (OR=0.28; 95% CI: 0.10-0.78; p=0.015). Participants using the platform ≥5 times were more likely to quit smoking than those who used the platform <5 times (OR=3.59; 95% CI: 1.51-8.52; p=0.004). CONCLUSIONS: The QuitAction platform provides smoking cessation services that can improve smokers' success rate and improve user experience satisfaction.

Comparison of the baseline characteristics and influencing factors of successful smoking cessation before and during the coronavirus disease pandemic.

INTRODUCTION: Travel and living environment restrictions, which may have positive or negative effects on smoking-related behaviors, were implemented to limit the COVID-19 pandemic. This study aimed to compare the baseline clinical characteristics and smoking cessation (SC) rate at 3 months of patients in an SC clinic in Hunan Province, China before and during the COVID-19 pandemic and identify influencing factors of successful SC. METHODS: Healthy patients at the SC clinic aged ≥18 years before the COVID-19 pandemic and during the COVID-19 pandemic were divided into groups A and B, respectively. The two groups' demographic data and smoking characteristics were compared, and SC interventions were applied by the same medical staff team through telephone follow-up and counselling during the SC procedure. RESULTS: Groups A and B included 306 and 212 patients, respectively, with no significant differences in demographic data. The SC rates of group A (pre COVID-19) and group B (during the COVID-19 pandemic) at 3 months were 23.5% and 30.7%, respectively, after the first SC visit. Those who chose to quit immediately or within 7 days were more successful than those who did not choose a quit date (p=0.002, p=0.000). Patients who learned about the SC clinic via network resources and other methods were more likely to succeed than those who learned about the clinic from their doctor or hospital publications (p=0.064, p=0.050). CONCLUSIONS: Planning to quit smoking immediately or within 7 days of visiting the SC clinic and learning about the SC clinic via the network media or other methods improved the likelihood of successful SC. SC clinics and the harm of tobacco should be promoted via network media. During consultation, the smokers should be encouraged to quit smoking immediately and establish an SC plan, which would help them to quit smoking.

Results of the Adult COVID-19 Lifestyle Matching Study.

Objective: The aim of our case-control study was to find the influence of lifestyle and comorbidities on COVID-19 susceptibility, identify risk factors and protective factors, and identify ways to encourage people to adopt a healthy lifestyle. Methods: Patients with COVID-19 were matched with non-COVID-19 participants in a ratio of 1:2. Univariate analysis was performed using the chi-square test, and multivariate analysis was performed using conditional logistic regression. Results: Multivariate analysis using conditional logistic regression found that alcohol consumption (AC) and a bland diet increased the risk of COVID-19, while college degrees and above, smoking, drinking tea, and exercise, especially walking, significantly reduced the risk of COVID-19. Conclusion: After removing the effects of demographic factors, the study demonstrated that AC significantly reduced the ability of the body to resist COVID-19 infection. Moreover, following a bland diet increased the susceptibility to COVID-19. Notably, people who drank tea and performed regular exercises, especially walking, were significantly less likely to be infected with COVID-19. College degree or above relative illiteracy is COVID-19 protective factors of infection.

Characteristics and Predictors of Abstinence Among Smokers of a Smoking Cessation Clinic in Hunan China.

Background: More than 300 million smokers make China the largest cigarette consumer globally, which is a huge economic burden. Smoking cessation (SC) clinics can offer counseling and follow-up services. The operational experience of SC clinics in China needs to be summarized and improved based on research evidence. Purpose: The objectives of this study were to describe quit rates among attendees of SC clinics in Hunan and assess predictors of successful SC. Methods: The participants in this study were smokers who visited the SC clinic of Hunan Cancer Hospital from February 1, 2015 to September 30, 2018. Individuals who received individual counseling and assessment from the SC clinic staff and were willing to quit smoking were eligible for inclusion. Those with critical illness or cancer were excluded. Application of smoking cessation clinic registration form (unified by Chinese Center for Disease Control and Prevention) was used to assess participants at the consultation. Follow-ups and counseling were performed over telephone at 1 week, 1 month, and 3 months after the initial cessation consultation or in times of need. Successful SC was checked for at 3 months after the start of SC. Results: A total of 328 smokers (mean age 45.67 ± 12.38 years) had participated. The abstinence rate at 3 months was 28.4%. Binary regression analysis revealed significant independent predictors to be the total numbers of SC follow up sessions, previous SC attempts, and participants' decision on when to quit smoking (The relative to quit immediately group, quit within 30 days, quit after 30 days, and undecided quit were less likely to succeed in quitting. while quit within seven days had no statistical significance. Conclusion: SC clinics can achieve a desirably high quit rate. Participant's previous attempts at quitting, three or more follow-ups, and the decision to quit immediately or within seven days were factors helpful in predicting the success of SC.

COVID-19 and Smoking: What Evidence Needs Our Attention?

The current COVID-19 pandemic has caused severe morbidity and mortality worldwide. Although relevant studies show that the smoking rate of COVID-19 patients is relatively low, the current smoking status of people with COVID-19 cannot be accurately measured for reasons. Thus, it is difficult to assess the relationship between smoking and COVID-19. Smoking can increase the risk of severe COVID-19 symptoms and aggravate the condition of patients with COVID-19. Nicotine upregulates the expression of ACE2, which can also increase susceptibility to COVID-19, aggravatiing the disease. Although nicotine has certain anti-inflammatory effects, there is no evidence that it is related to COVID-19 treatment; therefore, smoking cannot be considered a preventative measure. Furthermore, smokers gathering and sharing tobacco may promote the spread of viruses. Despite the COVID-19 epidemic, the findings suggested that COVID-19 has not encouraged smokers to quit. Additionally, there is evidence that isolation at home has contributed to increased smoking behavior and increased quantities. Therefore, it is recommended that governments increase smoking cessation messaging as part of public health measures to contain the COVID-19 pandemic. This review analyzes the existing research on smoking's impact on COVID-19 so that governments and medical institutions can develop evidence-based smoking-related prevention and control measures for COVID-19.

Smoking cessation rate and factors affecting the success of quitting in a smoking cessation clinic using telephone follow-up.

INTRODUCTION: China has the largest number of smokers in the world. The great majority of China's smokers desire to quit smoking (QS); however, the success rate of self-quitting is low. This study investigated the effects of smoking cessation (SC) clinics in a cancer hospital in Hunan province and determined the influencing factors of successful SC. METHODS: Smokers were recruited to QS by healthcare workers in the SC clinic from February 2015 to February 2019. SC counseling was provided and telephone follow-up was conducted at 1 week, and at 1, 3 and 6 months. Patients who continued SC during the follow-up period were considered to have QS. RESULTS: Of the 344 patients included in this study, 16.3% QS at one week, 26.5% at one month, 27.6% at three months, and 31.7% at six months. Age ≥60 years, previous SC attempts, immediate quit dates, and telephone follow-up times (3-4 calls) were predictive factors for smokers to SC at six months. CONCLUSIONS: Age, previous attempts to QS, immediate quit dates and telephone follow-up times were independent predictors of SC success at six months. SC clinics and frequent telephone follow-up improve the success rate of SC, especially in patients who have previously tried to QS or in those who set immediate quit dates.

Clinical observation of flexible ureteroscopy combined with physical vibration lithecbole in treatment of massive upper urinary calculi / 中国内镜杂志

Objective To evaluate the clinical efficacy of flexible ureteroscopy combined with physical vibration lithecbole in treatment of massive upper urinary calculi. Methods The clinical data of 62 cases with massive upper urinary calculi from Feb 2016 to Mar 2017 were analyzed retrospectively. The average diameter of stones were (656.70 ± 275.40) mm2. The removal rate of stones, general conditions during the operation, the postoperative adverse reactions and renal function changes were observed. Results All 62 patients had successfully completed flexible ureteroscopy operation, and had physical vibration stone removal treatment after 1 week. The rate of stone removal was 61.29％ in the next day (38/62), 85.48％ (53/62) in the next 1 week and 96.77％ (60/62) in the next 3 weeks. Postoperative fever occurred in 2 cases, the overall complication rate was 3.23％. 18 patients had improved renal function while 4 patients keep stable after operation. Conclusion The flexible ureteroscopy combined with physical vibration lithecbole is a safe and effective therapeutic method for massive upper urinary calculi. It has high stone removal rate, less complications, little impact on renal function. It is valuable to advocate clinically.

Determination of Ochratoxin A in Pig Kidneys by Immunoaffinity Cleanup and Ultra-High Performance Liquid Chromatography.

An accurate method was developed for determining ochratoxin A (OTA) in pig kidney using an immunoaffinity column for cleanup and ultra-HPLC/MS/MS for identification and quantification. Mean recoveries of OTA from kidney samples fortified at 0.10-5 µg/kg levels ranged from 74 to 92%, with RSDs of 4.6-7.5%. The LOD was estimated to be 0.03 µg/kg and the LOQ was 0.10 µg/kg based on an S/N in kidney of 3:1 and 10:1, respectively. The developed method was used for the determination of OTA in pig kidney. A survey of the OTA content of pig kidneys slaughtered in Chongqing, China, revealed that 35 out of 40 analyzed samples were contaminated; the OTA concentration in kidney ranged from trace level (0.03-0.1) to 0.323 µg/kg. This method was shown to be useful for accurately evaluating the intake of OTA from pig kidneys.