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Background | Most mobile cessation studies have found that such interventions have a higher quitting rate than interventions providing minimal smoking cessation support. However, why such interventions are effective has been almost unstudied by researchers. | PMC10173036 | ||
Objective | This paper describes the principles of the personalized mobile cessation intervention-based WeChat app and used generalized estimated equations to assess why a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage than a nonpersonalized intervention. | PMC10173036 | ||
Methods | This is a 2-arm, double-blind, randomized controlled trial in five cities in China. The intervention group received a personalized mobile cessation intervention. The control group received a nonpersonalized SMS text message smoking cessation intervention. All information was sent by the WeChat app. The outcomes were the change in protection motivation theory construct scores and the change in transtheoretical model stages. | PMC10173036 | ||
Results | A total of 722 participants were randomly assigned to the intervention or control group. Compared with those who received the nonpersonalized SMS text message intervention, smokers who received the personalized intervention presented lower intrinsic rewards, extrinsic rewards, and response costs. Intrinsic rewards were determinants of stage change, thus explaining why the intervention group was more likely to promote smokers from the preparation stage to the action stage (odds ratio 2.65, 95% CI 1.41-4.98). | PMC10173036 | ||
Conclusions | This study identified the psychological determinants at different stages to facilitate smokers moving forward to the next stage of quitting behavior and provides a framework to explore why a smoking cessation intervention is effective. | PMC10173036 | ||
Trial Registration | Chinese Clinical Trial Registry ChiCTR2100041942; https://tinyurl.com/2hhx4m7f | PMC10173036 | ||
Introduction | PMT | Smoking kills more than 1 million people in mainland China every year, and the number is predicted to grow to 2 million by 2030 and 3 million by 2050 [A large number of studies have shown that mobile cessation interventions can improve the smoking cessation rate and have the potential to provide smoking cessation services broadly, but most previous studies have focused only on the quitting rate [Another dimension is the determinant of quitting behavior. Several recent studies have noted that some factors could be associated with short-term or long-term abstinence [To help fill this evidence gap, we conducted a randomized controlled trial (RCT) to provide valuable evidence on these topics. We found that a personalized and behavior change theory–based SMS text message smoking cessation intervention was more effective than a nonpersonalized SMS text message intervention (6.9% vs 3.0%; adjusted odds ratio [OR] 2.66, 95% CI 1.21-5.83). The effectiveness of our intervention has been reported in The purpose of this study was to evaluate the changes in protection motivation theory (PMT) subconstructs and the transtheoretical model (TTM) stages of change to provide insight into why a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage. To our knowledge, this study is the first RCT using personalized SMS text messages for a mobile cessation intervention with a positive control group design in a country with a limited tobacco control policy.The TTM has been widely used for health behavior change interventions. The theory identifies five stages of change: precontemplation, contemplation, preparation, action, and maintenance. It is an integrative behavior change model for intentional change focused on the decision-making of individuals. Given the systematic relationship between the stages and processes of change, several strategies have been used to strengthen behavior changes or to achieve the next stage [Many studies have found that personalized and behavior change theory–based interventions could be more effective than only providing broad, nonspecific advice [Our previous research used cross-sectional data and found that smokers have different psychological factors that influence their quitting intention or behavior [ | PMC10173036 | |
Methods | PMC10173036 | |||
Design and Inclusion | DISEASE, RECRUITMENT | We conducted a 2-arm, double-blind, RCT in five cities in China (Beijing, Dezhou, Baotou, Yakeshi, and Linzi). Participants were randomized to an intervention group or a control group between April 2021 and July 2021. Daily or weekly smokers 18 years or older who smoked more than 5 cigarettes per week were eligible for inclusion if they owned a mobile phone and used WeChat. We advertised the trial to smokers through paper advertisements (leaflets), digital advertisements (WeChat), and staff (teachers and leaders). Potential participants contacted the local Center for Disease Control and Prevention to register. All eligible smokers were told they needed to come to a specific place on a fixed date to finalize the recruitment process. Participants’ eligibility was double-checked, and they signed an informed consent form during the first face-to-face contact. | PMC10173036 | |
Ethics Approval | The trial was approved by the Ethics Committee of Peking University Health Science Center (IRB00001052-30063). All the participants signed informed consent forms before randomization and knew that they could withdraw from the study at any time. All patients’ information was accessible only to the personnel participating in the study. We did not provide money to the participants, but we provided gifts (a towel, an umbrella, or a cup) if the participants completed one follow-up visit. The clinical trial registration number is ChiCTR2100041942. | PMC10173036 | ||
Development of the Text Bank | PMT | The first stage was to develop the intervention message bank. Messages were developed by Peking University, School of Public Health, with the input of smokers and smoking cessation professionals. The messages had a three-layer framework. The first layer was divided based on time and consisted of the prequit message (1-7 days), quit day message (8 days), withdrawal symptom management message (9-18 days), early quit message (19-36 days), and late period message (37-90 days). The second layer was divided based on the TTM. Before the quit day, messages were classified as strong quitting intention or weak quitting intention. After the quit day, messages were classified as maintained abstinence or relapsed. The third layer was divided based on the PMT. Messages were classified as increased severity and susceptibility, decreased response cost and intrinsic and extrinsic rewards, and increased self-efficacy and response efficacy. The core motivational messages consisted of 14 subgroups with a total of 200 SMS text messages. There were also approximately 200 contact messages. The participants received partial information, and the information they received was different depending on their status. The WeChat app evaluated smokers’ status on day 0, day 19, day 36, day 45, day 60, and day 75 to decide what messages to send them. | PMC10173036 | |
Study Instruments | All messages were sent through the WeChat app (the most popular Chinese mobile chatting app) [The last stage was to deploy the message library on the WeChat platform by using IT. Our IT team completed the development process with several important considerations. First, the app needed to ensure the confidentiality of the data. Second, the system needed to be user-friendly with ease for quick data entry. Third, there needed to be a back-end server to store the data. Fourth, the information needed to be presented in a way that could be easily read and interpreted. | PMC10173036 | ||
Randomization and Blinding | RECRUITMENT | After recruitment, the participants were required to complete the baseline questionnaire and register through WeChat. A randomized block design was used, and the score of the Fagerström Test for Nicotine Dependence was treated as a stratified factor. The WeChat system automatically generated two blocks by the score of the test: (1) low or moderate nicotine dependence group (0-6 points) and (2) high dependence group (≥7 points) [ | PMC10173036 | |
Intervention and Control Group | Cancer | CANCER | All participants were informed that the eighth day after randomization would be their quit day. Participants who were allocated to the intervention group received the program of interventions. As described above, this consisted of 1-2 personalized SMS text messages per day for 3 months.Control group participants received a nonpersonalized SMS text message smoking cessation intervention developed by the National Cancer Institute. It was based on well-established cognitive behavioral cessation approaches and contained 91 messages. Participants received approximately 1 message per day for 3 months. The SMS text messages provided encouragement, practical advice to help maintain cessation, and information on the health effects of smoking. The details of the control group can be found elsewhere [ | PMC10173036 |
Measures | TTM | PMT | All participants in the two groups were instructed to attend face-to-face follow-ups with research staff 1 month, 3 months, and 6 months after randomization. The outcomes were the change in PMT construct scores and the change in TTM stages. TTM stages of change were measured by smoking status using the question “Are you going to quit smoking?”: “No, not thinking of quitting” (precontemplation; individual is not ready or thinking about making a change); “Yes, within the next 6 months” (contemplation; individual thinking about making a change but not in the immediate future); “Yes, within the next 30 days” (preparation; individual ready to change, intends to try to change in the immediate future, and might be making small preparatory changes); and action, the biochemically verified patient has not smoked since the last follow-up [ | PMC10173036 |
Statistical Analysis | PMC10173036 | |||
Sample Size Calculation | The sample size calculation was based on the formula for a 2-arm RCT. Based on earlier research, we estimated that biochemically verified continuous smoking abstinence at 6 months would be approximately 4% in the control group and 10% in the intervention group [
| PMC10173036 | ||
Data Analysis | PMT | Our data analysis was conducted in three steps. First, we used generalized estimating equations (GEEs) to analyze the changes in TTM stages by group. Second, we analyzed the associations between PMT construct scores and the change in TTM stages. Third, we assessed PMT construct score changes in the two groups to explore why a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage. A | PMC10173036 | |
Step 1 | A GEE was used to address the correlated nature of the repeated measures in the data [ | PMC10173036 | ||
Step 2 | REGRESSION, PMT | To examine the psychological determinants of movement from the precontemplation to the action period, we changed the explanatory variables to PMT construct scores. We used the second GEE to assess which PMT constructs were associated with the TTM stage of change. We chose an exchangeable correlation structure for the matrix structure and binary logistic regression for the model setting. | PMC10173036 | |
Step 3 | REGRESSION, PMT | We estimated the impact of the intervention on PMT construct scores in the last set of models to explore the reasons why the intervention group was more likely to promote smokers from the preparation stage to the action stage. The dependent variables included seven PMT constructs (severity, vulnerability, intrinsic rewards, extrinsic rewards, self-efficacy, response efficacy, and response cost). The explanatory variable was the group (intervention group=1; control group=0). We chose an exchangeable correlation structure for the matrix structure and linear regression for the model setting. | PMC10173036 | |
Discussion | PMC10173036 | |||
Principal Findings | adversity | PMT | This study engages in the debate in recent years over the effects of mobile cessation interventions. It provides a more comprehensive picture of the impact of personalized mobile cessation interventions from psychological change perspectives using Chinese data. It successfully shows that the intervention group had lower scores for the subconstructs of intrinsic rewards of smoking, extrinsic rewards of smoking, and response cost of quitting, and was more likely to promote smokers’ movement from the preparation stage to the action stage, confirming that personalized interventions can provide more positive psychological changes than a nonpersonalized SMS text message intervention. We believe that this finding is worth noting, as we extend the findings from target behavior to psychological change (first hypothesis).Regarding the second hypothesis, although we found that the psychological determinants varied at different stages to facilitate smokers’ movement from precontemplation to the action period, self-efficacy was the most significant variable associated with forward movement in each stage of change. Self-efficacy is the belief in one’s competence to manage adversity in specific demanding situations. A branch of the literature has suggested that self-efficacy plays an important role in determining health behavior; for example, a German study found that self-efficacy was the strongest factor that significantly predicted subsequent smoking-related behavioral intention [Another finding of our study is the identification of the psychological determinants at different stages to facilitate smokers moving forward to the next stage. The comparison between groups showed that the personalized intervention decreased the intrinsic rewards of smoking; this outcome is worth noting since it is a determinant of the movement from the preparation stage to the action stage. It also provides some indications of why a personalized intervention is more likely to promote smokers from the preparation stage to the action stage than a nonpersonalized intervention. Conversely, we found that our intervention did not lead to a significant change among smokers in the determinants that promoted smokers in moving forward from the precontemplation stage (self-efficacy and response efficacy) or contemplation stage (self-efficacy) to the next stage compared with the control group. This finding explains why our intervention had no better effect on promoting smokers to move forward from the precontemplation or contemplation stage, providing further direction for scaling up our intervention.As stated, this RCT is the first to use personalized SMS text messages for a mobile cessation intervention with a positive control group design in China. We believe that our study has policy and theoretical implications. First, we identified psychological determinants of forward movement in the stage of change, which could be an important reference for further intervention. Second, this study demonstrated a clear framework for the intervention through the systematic and transparent application of the PMT and the TTM. It not only allows other researchers to take advantage of our experience when designing mobile interventions but also provides a framework for exploring why such an intervention is effective.This study still has some limitations that could be addressed by further studies. First, although efforts were made to ensure that both the researchers and participants remained masked to the allocation, a risk of breaking the blinding was present. Second, some researchers believe that the definitions used for the TTM stages are arbitrary and that the categories are not qualitatively distinct [ | PMC10173036 |
Conclusion | This study reported clearly on the development of a mobile cessation intervention. GEE analysis identified the psychological determinants of forward movement in the stage of change and confirmed that a personalized mobile cessation intervention was more likely to promote smokers from the preparation stage to the action stage. The results of this empirical analysis could not only be equally applicable to the development of interventions targeting other health behaviors but also could provide a framework to explore why such an intervention is effective, thereby adding to earlier research on this topic.This work was supported by the National Natural Science Foundation of China (grant 82173637). We would like to thank all the participants of the study.Authors' Contributions: HL finished the first draft. YW, YX, YH, CZ, and TL conducted the survey. CC managed the study. All authors have approved the final paper for submission.Conflicts of Interest: None declared.Supplementary Table 1.CONSORT checklist. | PMC10173036 | ||
Abbreviations | generalized estimating equationodds ratioprotection motivation theoryrandomized controlled trialtranstheoretical model | PMC10173036 | ||
Data Availability | The data of the studies is accessible through the Peking University School of Public Health. | PMC10173036 | ||
Background | GDM | GDM, GESTATIONAL DIABETES MELLITUS | Edited by: Victor Khin Maung Han, Lawson Health Research Institute, CanadaReviewed by: Mengzhi Wang, Yangzhou University, China; Zhonghua Shi, Nanjing Medical University, ChinaThis article was submitted to Developmental Endocrinology, a section of the journal Frontiers in EndocrinologyGut microbiota of pregnant women change with the gestational week. On the one hand, they participate in the metabolic adaptation of pregnant women. On the other hand, the abnormal composition of gut microbiota of pregnant women is more likely to suffer from gestational diabetes mellitus (GDM). Therefore, gut microbiota targeted treatment through dietary supplements is particularly important for prevention or treatment. Prebiotic supplements containing galactooligosaccharides (GOS) may be an intervention method, but the effect is still unclear. | PMC9911812 |
Objective | This study aims to evaluate the feasibility and acceptability of prebiotic intervention in healthy pregnant women during pregnancy, and to explore the possible effects of intervention on pregnant women and the influence on gut microbiota as preliminaries. | PMC9911812 | ||
Methods | RECRUITMENT | After recruitment in first trimester, 52 pregnant women were randomly assigned to receive GOS intervention or placebo containing fructooligosaccharides. 16S rRNA sequencing technology was used to detect the composition, diversity and differential flora of gut microbiota. Lipid metabolism, glucose metabolism and inflammatory factors during pregnancy were also analyzed. | PMC9911812 | |
Results | weight gain, GDM, TG | GDM | The adverse symptoms of GOS intervention are mild and relatively safe. For pregnant women, there was no significant difference in the GDM incidence rates and gestational weight gain (GWG) in the GOS group compared with placebo (P > 0.05). Compared with the placebo group, the levels of FPG, TG, TC, HDL-C LDL-C, and IL-6 had no significant difference in GOS group (P > 0.05). For newborns, there was no significant difference between GOS group and placebo group in the following variables including gestational week, birth weight, birth length, head circumference, chest circumference, sex, and delivery mode (P > 0.05). And compared with the placebo group, the GOS group had a higher abundance of | PMC9911812 |
Conclusions | GOS prebiotics appear to be safe and acceptable for the enrolled pregnancies. Although GOS intervention did not show the robust benefits on glucose and lipid metabolism. However, the intervention had a certain impact on the compostion of gut microbiota. GOS can be considered as a dietary supplement during pregnancy, and further clinical studies are needed to explore this in the future. | PMC9911812 | ||
Introduction | PROLIFERATION | With the change of gestational age, gut microbiota is participated in the physiological adaptation of maternal metabolism (Different from probiotics, galactooligosaccharides (GOS) is a kind of prebiotics that aren’t digested and absorbed by the host, but can selectively promote the metabolism and proliferation of beneficial bacteria in the body, particularly by Lactobacillus and Bifidobacterium (Therefore, prebiotics have the potential to promote health and regulate gut microbiota. However, the beneficial effects of prebiotics during pregnancy remain unclear, the study of GOS prebiotics intervention on pregnant women is still in the preliminary exploration stage. This pilot randomized controlled pilot study aims to evaluate the feasibility, acceptability, and safety of prebiotic intervention for healthy pregnant women, and preliminarily explore the possible benefits for pregnant women. | PMC9911812 | |
Materials and methods | PMC9911812 | |||
Study population | impaired fasting glucose, hypertension, chronic diseases, diabetes | HYPERTENSION, IMPAIRED GLUCOSE TOLERANCE, CHRONIC DISEASES, DIABETES | We conducted a prospective double-blinded randomized clinical trial involving singleton pregnancy women. Inclusion criteria were: 18-40 years of age; living in Beijing; understanding and willing to sign informed consent; singleton pregnancy; first prenatal care visit between 5-8 weeks of gestation. Exclusion criteria were: smoking, excessive alcohol or drug abuse; pregnancy complicated with chronic diseases (pre-existing diabetes, impaired glucose tolerance, impaired fasting glucose, chronic hypertension and so on); taken any prescribed chronic medications; steroids use.The trial was recruited at Peking University First Hospital (PUFH), which is a public hospital located in Beijing, China. This study protocol has been approved by PUFH Clinical Trial Ethics Committee (reference number: 164). All patients provided written informed consent. The clinical trial was registered on | PMC9911812 |
Study design and intervention | During this double-blinded, parallel-group clinical study, participants were randomly assigned to the control group and the intervention group at a 1:1 ratio. Women participants who meet the eligibility criteria were recruited and stratified according to their body mass index (BMI). All participants were divided into four groups underweight (BMI<18.5 kg/mSubsequently, participants took GOS supplements in the intervention group or placebo containing fructooligosaccharides (FOS) in the control group from the first trimester (T1). In intervention group, GOS (6 g/100 g) and sialic acid (3 g/100 g) were the primary ingredients. The control group mainly contained FOS (3 g/100 g). The purities of GOS and FOS were 90% and 93% (w/w) on dry matter respectively. The dietary supplements were provided by the Beijing Sanyuan Foods Co. Ltd, Beijing, China. The dosage of the supplements was 60g per day. In order to improve pregnancy health care and strengthen adherence, both the two groups were provided with supplements containing nutrients, minerals and vitamins at each visit timepoint. The trial process followed the double-blind principle of researchers and participants. | PMC9911812 | ||
Data and sample collection | BLOOD, STERILE | Participants were enrolled at 5-8 weeks of gestation. Blood and stool samples were collected and followed up at 11-13 weeks of gestation and 24-28 weeks of gestation. During the follow-up period, filled in the questionnaire during the corresponding pregnancy, and left the participants’ blood samples and stool samples at two time points. All the 52 participants who were finally included in the study took blood samples and stool samples in both periods. All samples were collected in sterile tubes and stored at -80 °C until testing. The data of biochemical indexes such as glucose and lipid metabolism of pregnant women were obtained through the medical record system. After blood samples were collected, the immunological parameters IL-6 level was detected in the laboratory department. Fecal samples were collected for gut microbiota analysis. | PMC9911812 | |
Study outcomes | weight gain, GDM, TG, diabetes | GDM, SECONDARY, ADVERSE REACTIONS, DIABETES | For the primary study outcomes, the effect of GOS on maternal gut microbiota were reported. At the same time, for those who have been followed up to the second trimester of pregnancy, based on the results of 75g oral glucose tolerance test (OGTT) at 24-28 gestational weeks (For pregnant women, baseline data such as age, gravidity, parity, BMI, history of GDM, and family history of diabetes were described. For secondary outcomes, the biochemical parameters of glucose and lipid metabolism (fasting plasma glucose (FPG), triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C)), IL-6, and gestational weight gain (GWG) in the intervention group and the control group were included respectively. As for Newborns, included gestational age, the mode of delivery, sex, birth length, birth weight, head circumference and chest circumference. We evaluated the safety and adverse reactions of prebiotics intervention. | PMC9911812 |
DNA extraction and V3–V4 region of 16SrRNA gene sequencing | A commercial kit (Qiagen, Hilden, Germany) were used to extract faecal DNA. Faecal DNA was amplified by PCR using 16S amplicon PCR forward primer and 16S amplicon PCR reverse primer. After PCR amplification, the amplicons in each library were purified by Qiagen for library preparation. Subsequently, the qualified library was sequenced by Illumina Hiseq 2500 high-throughput sequencing platform. Sequences were clustered into operational taxonomic units (OTUs) based on Silva database v128, at a similarity level of 97%. Alpha and Beta diversity were generated in Quantitative Insights Into Microbial Ecology (QIIME). And the abundance of bacterial OTUs were divided into several levels (phyla, class, order, family and genus). The laboratory technicians were blinded to the clinical status (intervention or control group) of study participants. | PMC9911812 | ||
Sample size | RECRUITMENT, EARLY PREGNANCY | The purpose of this pilot study was to eavluate the feasibility and acceptability of prebiotics for pregnant women. A total of 52 pregnant women were considered enough to provide practical recruitment, feedback and compliance information. The findings will provide basis and support for future a large sample trial to evaluate the effects of prebiotics supplementation in early pregnancy on gut microbiota, glucose metabolism and immunity of pregnant women and newborns. | PMC9911812 | |
Statistical analysis | Data were represented as mean ± standard deviation (SD) or count (%). All data were input into SPSS (version 25.0) to analyze. GraphPad prism (version 8.0) was used to draw diagrams. χ2 and Fisher’s exact test was used for categorical variables, and t-test or non-parametric Wilcoxon test was used for continuous variables where appropriate. P < 0.05 was considered to be statistically significant. And bioinformatics analysis for microbiome used R software (Bell Laboratories). Alpha and beta diversities were generated in the Quantitative Insights Into Microbial Ecology (QIIME) and calculated based on weighted or unweighted Unifrac distance matrices. We used the linear discriminant analysis (LDA) effect size (LEfSe) method to identify species that show statistically significant differential abundances between groups. | PMC9911812 | ||
Results | PMC9911812 | |||
Participants enrollment and clinical baseline | GDM | GDM, GESTATIONAL DIABETES MELLITUS | Flow of participants through the study is shown in Flow chart of participants through the study.Baseline characteristics of study participants.Data presented are mean ± SD or n (%).P-values for comparisons between the 2 groups in t-tests for continuous variables, and χ2 and Fisher’s exact tests for categorical variables.GDM, gestational diabetes mellitus; BMI, body mass index. | PMC9911812 |
Effects of prebiotics on gut microbiota in pregnant women | PMC9911812 | |||
Overall microbial structures of gut microbiota | We studied gut microbiota of women in placebo and GOS groups. Relative abundance at the level of bacterial phylum. | PMC9911812 | ||
Changes of gut microbiota diversity | To assess the gut microbiota community structure, richness (Chao 1 index) and diversity (Simpson index, Shannon index) were calculated (Alpha and beta diversity of gut microbiota in placebo and GOS groups. To compare overall gut microbiota structure in pregnant women, PCoA according to OTUs of each sample were implemented to provide a glimpse of gut microbial dynamics between placebo and GOS groups. The results of PCoA were PC1 = 54.49% and PC2 = 11.26% of total variations ( | PMC9911812 | ||
Changes in specific bacterial taxa | For identify the changes in specific bacterial taxa after prebiotics supplemented intervention. We utilized the linear discriminant analysis (LDA) effect size (LEfSe) to compare the gut microbiota composition between placebo and GOS groups. The LDA score was selected to discriminate specific taxa in two groups. Compared with the placebo group, the GOS group had a higher abundance of Identification of the most differentially abundant analyzed by the LEfSe method. | PMC9911812 | ||
Participants clinical outcomes | PMC9911812 | |||
GDM diagnosis and OGTT values | GDM | GDM, GESTATIONAL DIABETES MELLITUS | Serum levels of FBG, 1-hour and, 2-hour OGTT plasma glucose measured at 24–28 weeks of pregnancy in women who received either GOS or placebo are illustrated in GDM diagnosis and OGTT values.GDM, gestational diabetes mellitus; OGTT, oral glucose tolerance test. | PMC9911812 |
Changes in weight and BMI during pregnancy | weight gain | With the change of gestational weeks, we collected the weight gain during pregnancy of two groups of pregnant women, and calculated the changes of BMI (Changes in weight and BMI during pregnancy.BW, body weight; BMI, body mass index; BW 1st, body weight at the beginning of 1st trimester; BW 3rd, body weight at the end of 3rd trimester; BMI 1st, BMI at the beginning of 1st trimester;BMI 3rd, body mass index at the end of 3rd trimester; GWG, gestational weight gain. | PMC9911812 | |
Clinical characteristics of neonates | To investigate the impact of the intervention on neonatal outcomes, we measured the following variables including gestational week, birth weight, birth length, head circumference, chest circumference, sex, and delivery mode. No significant difference was found between the GOS and placebo group (all P-values were > 0.05) (Clinical characteristics of neonates. | PMC9911812 | ||
Glucose metabolism, lipid metabolism and inflammatory factor levels | In order to further explore the effect of prebiotics intervention on glucose metabolism, lipid metabolism, and immunity, we analyzed the following indicators (Glucose metabolism, lipid metabolism and inflammatory factor levels.FPG, fasting plasma glucose; TG, triglyceride; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; IL-6, interleukin-6. | PMC9911812 | ||
Incidences of maternal and infant complications | COMPLICATIONS | Clinical data on the incidences of maternal and infant complications were also collected (Incidences of maternal and infant complications. | PMC9911812 | |
Safety of intervention | nausea | A questionnaire was used to record the possible severity of adverse symptoms in pregnant women and the relationship between symptoms and the ingestion of preparations. The results showed that one participant in GOS group had abdominal distension and one participant had nausea. These symptoms have little to do with the intake of prebiotic preparations, and may be related to appetite and hormone changes during pregnancy. Therefore, for the existing included cases, it can be considered that supplementing prebiotic preparations during pregnancy is relatively safe. | PMC9911812 | |
Discussion | GDM, disorder of gut microbiota | OF PREGNANCY COMPLICATIONS, METABOLIC DISEASES, GDM | During pregnancy, the disorder of gut microbiota and abnormal glucose metabolism may be the possible mechanism of pregnancy complications such as GDM (The preliminary conclusion of this study is that GOS intervention has no significant effect on reducing the incidence of GDM and improving glucose and lipid metabolism. GOS a kind of prebiotics that can be selectively and selectively utilized by host microorganisms that confer a health benefit, while probiotics are defined as live microorganisms (Both the intervention group and the control group have similar relative abundances at the phylum level, including Several strengths and limitations should be taken into consideration. First, this study is a randomized controlled pilot trial. Subsequently, 16S rRNA gene was sequenced by Illumina Hiseq 2500 sequencing platform, a widely and reliable used high-throughput sequencing platform, which can ensure gut microbiota can be successfully identified. Secondly, the quality control in the process of sample collection can be guaranteed, which makes the sequencing quality high and accurate. However, some limitations should also be considered. The sample size of our pilot study is limited, and some confounding factors such as diet and exercise have caused some interference. Although it is difficult to control these confounding factors, we recorded these situations in the form of health education and questionnaire records. Moreover, this study was recruited in the same hospital, and the potential regional differences of microbiota cannot be evaluated. In general, our study provides an important basis for the intervention of prebiotic dietary supplements targeting gut microbiota in pregnancy on metabolic diseases of pregnancy. In the future, clinical trials with higher quality and larger sample size are needed to further verify the effect of prebiotic supplements. | PMC9911812 |
Conclusion | GOS prebiotics appear to be safe and acceptable for the enrolled pregnancies. Although GOS intervention did not show the robust benefits on glucose and lipid metabolism. However, the intervention had a certain impact on the compostion of gut microbiota. GOS can be considered as a dietary supplement during pregnancy, and further clinical studies are needed to explore this in the future. | PMC9911812 | ||
Data availability statement | The raw sequence data of the 16S rRNA gene supporting the results of this article are available in the NCBI database, SRA data (Accession number: PRJNA925813). | PMC9911812 | ||
Ethics statement | The studies involving human participants were reviewed and approved by Clinical Trial Ethics Committee, Peking University First Hospital, Beijing, China. The patients/participants provided their written informed consent to participate in this study. | PMC9911812 | ||
Author contributions | HY | JW collected the data, prepared tables and figures, and drafted the paper. LA and ZR analyzed the data and prepared tables. SW, LA, HY, and JM conceived and designed the research. JM revised the manuscript. HY and JM provided clinical supervision. All authors contributed to the article and approved the submitted version. | PMC9911812 | |
Acknowledgments | The authors would like to thank all the participants in this study, the Beijing Natural Science Foundation—San Yuan Joint Research Fund for providing technical support and the Institute of Microbiology, Chinese Academy of Sciences for providing support in sequencing analysis. We thank all the staff at the Department of Obstetrics and Gynecology in the Peking University First Hospital. | PMC9911812 | ||
Conflict of interest | The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. | PMC9911812 | ||
Publisher’s note | All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | PMC9911812 | ||
References | PMC9911812 | |||
Key Points | PMC10425831 | |||
Question | acute ischemic stroke, AIS | Does ginkgo diterpene lactone meglumine (GDLM) improve the functional outcome at 90 days in patients with acute ischemic stroke (AIS)? | PMC10425831 | |
Findings | 3448 | ADVERSE EVENTS | This randomized clinical trial included 3448 patients with AIS who received GDLM or placebo injections within 48 hours after symptoms for 14 days; the proportion of patients achieving a favorable outcome, defined as the 90-day modified Rankin Scale score of 1 or 0, was 50.8% in the GDLM group, significantly higher than 44.1% in the placebo group. The rate of adverse events was similar between the 2 groups. | PMC10425831 |
Meaning | Among patients with AIS, ginkgo diterpene lactone meglumine improved the proportion of patients achieving favorable clinical outcomes at 90 days compared with placebo. | PMC10425831 | ||
Importance | acute ischemic stroke, AIS | ISCHEMIC STROKE | Ginkgo diterpene lactone meglumine (GDLM) has attracted much attention because of its potential neuroprotective properties in ischemic stroke. The efficacy of GDLM in patients with acute ischemic stroke (AIS) needs to be verified by well-designed randomized clinical trials. | PMC10425831 |
Objective | To assess the efficacy and safety of GDLM in patients with AIS. | PMC10425831 | ||
Design, Setting, and Participants | stroke, stroke disability, death, Stroke | STROKE, MAY, STROKE | This multicenter, randomized, double-blind, placebo-controlled, parallel-group trial involved 3448 patients who had AIS, were aged 18 to 80 years, had a clinically diagnosed AIS symptom within 48 hours of onset, had a modified Rankin Scale (mRS) score of 0 or 1 prior to onset, and had a National Institutes of Health Stroke Scale score ranging from 4 to 24. The trial took place at 100 centers in China from February 1, 2016, to May 1, 2018. The mRS is a global stroke disability scale with scores ranging from 0 (no symptoms or completely recovered) to 6 (death). The National Institutes of Health Stroke Scale is a tool used by clinicians to quantify impairment caused by stroke (range, 0-42, with higher scores indicating greater severity). Data were analyzed from January 2019 to December 2022. | PMC10425831 |
Interventions | Patients were randomized to receive GDLM or placebo once daily via intravenous infusion in a 1:1 ratio. The treatment was dispensed within 48 hours after symptoms and continued for 14 days. Interventions of thrombolysis and thrombectomy were not permitted during the treatment. | PMC10425831 | ||
Main Outcomes and Measures | ADVERSE EVENTS | The primary outcome was the proportion of patients with an mRS of 0 or 1 on day 90 after randomization. Safety outcomes included adverse events and serious adverse events. | PMC10425831 | |
Results | A total of 3448 patients were randomized, with 1725 patients assigned to the GDLM group and 1723 patients assigned to the placebo group. The median (IQR) age of the patients was 63 (55-71) years, and 1232 (35.7%) were women. The primary outcome on day 90 occurred in 877 patients (50.8%) in the GDLM group, and 759 patients (44.1%) in the placebo group (risk difference, 6.79%; 95% CI, 3.46%-10.10%; odds ratio, 1.31; 95% CI, 1.15-1.50; relative risk, 1.15; 95% CI, 1.08-1.24; | PMC10425831 | ||
Conclusions and Relevance | Among patients with AIS in this randomized clinical trial, GDLM improved the proportion of patients achieving favorable clinical outcomes at 90 days compared with placebo. | PMC10425831 | ||
Trial Registration | acute ischemic stroke | ClinicalTrials.gov Identifier: This randomized clinical trial assesses the safety and functional outcomes at 90 days of ginkgo diterpene lactone meglumine, a neuroprotective agent, in patients with acute ischemic stroke. | PMC10425831 | |
Introduction | excitotoxicity, acute ischemic stroke, AIS | INFLAMMATION | Neuroprotection has emerged as a potential therapeutic approach in patients with acute ischemic stroke (AIS). Multiple pathological and physiological processes are involved in the occurrence and progression of AIS, including excitotoxicity, oxidative and nitrosative stress, cell apoptosis, and inflammation. | PMC10425831 |
Methods | PMC10425831 | |||
Trial Design | bleeding | BLEEDING, EVENT, MAY, SECONDARY, EVENTS | This was a multicenter, randomized, double-blind, placebo-controlled, parallel-group trial conducted at 100 centers in China from February 1, 2016, to May 1, 2018. Details of the trial rationale, design, and methods were provided in the trial protocol (The steering committee was responsible for the design and supervision of the trial, the development of and amendments to the protocol, and the interpretation of the data. The steering committee was also responsible for ensuring the integrity of the data, analysis, presentation of results, and the fidelity of the trial to the protocol. An independent clinical event adjudication committee, whose members were unaware of the trial group assignments, adjudicated the primary and secondary efficacy outcomes and bleeding events. An independent data and safety monitoring committee monitored the progress of the trial, with regular assessment of safety outcomes, overall trial integrity, and trial conduct. | PMC10425831 |
Patient Eligibility Criteria | stroke, stroke disability, death, Stroke | STROKE, STROKE | Patients were eligible if they were aged 18 to 80 years, had a clinically diagnosed AIS symptom within 48 hours of onset, had a modified Rankin Scale (mRS) score of 0 or 1 prior to onset, had a National Institutes of Health Stroke Scale (NIHSS) score between 4 and 24 after onset (indicating moderate stroke), had an upper and lower limb motor deficit score on the NIHSS of at least 2, and signed informed consent. The mRS is a global stroke disability scale with scores ranging from 0 (no symptoms or completely recovered) to 6 (death). The NIHSS is a tool used by clinicians to quantify impairment caused by stroke (range, 0-42, with higher scores indicating greater severity). The motor arm and leg deficits are subcategories of the NIHSS, scored on a 0 to 4 scale, with higher scores indicating greater severity. The detailed exclusion criteria are shown in eTable 1 in | PMC10425831 |
Randomization and Blinding | Within 48 hours after symptom onset, eligible patients were randomly assigned in a 1:1 ratio to receive GDLM or placebo by a computerized block randomization method with randomly selected block sizes of 4. The randomization number was stimulated centrally by an independent statistician. The 2 forms of drugs were visually identical and cannot be distinguishable in appearance. Both researchers and patients were blinded to the treatment. | PMC10425831 | ||
Treatment | STERILE | Patients in the GDLM group received a GDLM injection of 5 mL (active ingredient GDLM, 25 mg) once daily via intravenous infusion for 14 consecutive days. Patients in the placebo group received a GDLM mimic injection (physiological saline) of 5 mL once daily via intravenous infusion for 14 consecutive days. Both the GDLM and placebo were diluted in 250 mL of sterile 0.9% sodium chloride injection. Treatment was dispensed within 48 hours after symptoms. Treatment was discontinued when the patients were discharged prior to 14 days. All of the patients were followed up to day 90 after randomization. | PMC10425831 | |
Outcomes | ADVERSE EVENTS, SECONDARY | The primary efficacy outcome was the proportion of patients with a mRS score of 0 or 1 on day 90 after randomization. The secondary outcomes included the proportion of patients with an mRS score of 2 or less on day 90 after randomization, the proportion of patients with a decrease in NIHSS score of at least 4 points from baseline to day 7 and day 14 after randomization, the proportion of patients with an increase in NIHSS score of 4 or more points, 3 points, 2 points, or 1 point from baseline to day 7 after randomization. Safety outcomes, including adverse events, serious adverse events within 90 days, changes in vital signs, and results of laboratory examinations (routine blood, routine urine, and blood biochemistry examinations) from baseline to day 14 after randomization were systematically recorded. | PMC10425831 | |
Statistical Analysis | We determined that a total of 3452 patients would provide 80% power to detect a 45% rate of patients with mRS scores of 0 or 1 on day 90 after randomization in the placebo groupAll the analyses were performed in the modified intention-to-treat population, which comprised all the patients who had undergone randomization and had at least 1 assessment of efficacy after baseline. Baseline data were presented according to treatment assignment. Continuous variables were presented as mean (SD) or median (IQR) according to the distribution, and categorical variables were presented as frequency and proportion. The differences in the proportions for the dichotomous outcomes between treatment groups and their corresponding 95% CIs were estimated based on the Newcombe-Wilson score method. | PMC10425831 | ||
Results | PMC10425831 | |||
Baseline Characteristics | A total of 3452 patients with AIS were enrolled at 100 centers in China. A total of 1726 were assigned to receive GDLM, and 1726 were assigned to receive placebo ( | PMC10425831 | ||
Flowchart of the Study | stroke, Stroke | STROKE, STROKE | Abbreviations: GDLM, ginkgo diterpene lactone meglumine; NIHSS, National Institutes of Health Stroke Scale. The NIHSS is a tool used by clinicians to quantify impairment caused by stroke (range, 0-42, with higher scores indicating greater severity).The characteristics of the patients at baseline were well balanced between the 2 groups ( | PMC10425831 |
Baseline Characteristics | stroke, Stroke | STROKE, STROKE | Abbreviations: GDLM, ginkgo diterpene lactone meglumine; NIHSS, National Institutes of Health Stroke Scale.Body mass index is calculated as weight in kilograms divided by height in meters squared.The NIHSS is a tool used by clinicians to quantify impairment caused by stroke (range, 0-42, with higher scores indicating greater severity). | PMC10425831 |
Outcomes | PMC10425831 | |||
Primary Outcome | In the modified intention-to-treat analysis, 877 (50.8%) of 1725 patients in the GDLM group and 759 (44.1%) of 1723 patients in the placebo group reached the primary outcome (mRS score of 0 or 1 at 90 days; risk difference, 6.79%; 95% CI, 3.46%-10.10%; OR, 1.31; 95% CI, 1.15-1.50; RR, 1.15; 95% CI, 1.08-1.24; | PMC10425831 | ||
Efficacy Outcomes | stroke, stroke disability, Stroke | REGRESSION, STROKE, STROKE | Abbreviations: GDLM, ginkgo diterpene lactone meglumine; mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale.The mRS is a global stroke disability scale with scores ranging from 0 (no symptoms or completely recovered) to 6 (death).The NIHSS is a tool used by clinicians to quantify impairment caused by stroke (range, 0-42, with higher scores indicating greater severity). A decrease in score indicates a functional improvement, while an increase in score indicates symptom regression.The number of patients with missing data was similar in the 2 treatment groups. Missing data for NIHSS score on day 7 occurred in 61 patients in the GDLM group and 67 patients in the placebo group.The number of patients with missing data was similar in the 2 treatment groups. Missing data for NIHSS score on day 14 occurred in 95 patients in the GDLM group and 110 patients in the placebo group. | PMC10425831 |
Distribution of 90-Day Modified Rankin Scale (mRS) Score | stroke disability, death | The mRS is a global stroke disability scale with scores ranging from 0 (no symptoms or completely recovered) to 6 (death). Each cell corresponds to a score on the mRS; the width of the cell indicates the proportion of patients with equivalent scores. The percentage of patients in each category is shown within the cell. GDLM indicates ginkgo diterpene lactone meglumine. | PMC10425831 | |
Secondary Outcomes | SECONDARY | With respect to secondary outcomes, the proportion of patients with a favorable functional outcome (mRS score of 0-2) in the GDLM group was 83.8% compared with 69.5% in the placebo group (risk difference, 14.35%; 95% CI, 11.56%-17.12%; OR, 2.28; 95% CI, 1.93-2.68; RR, 1.21; 95% CI, 1.16-1.25; | PMC10425831 | |
Odds Ratio for the Primary Outcome in Prespecified Subgroups | The | PMC10425831 | ||
Safety Outcomes | ADVERSE EVENTS | The GDLM group and the placebo group had a similar incidence of adverse events (303 [17.6%] vs 298 [17.3%]; risk difference, −0.27%; 95% CI, −2.26%-2.80%; OR, 1.02; 95% CI, 0.85-1.21; RR, 1.02; 95% CI, 0.88-1.17; | PMC10425831 | |
Discussion | cardiocerebrovascular diseases | ACUTE ISCHEMIC STROKE | In this randomized, double-blind, placebo-controlled, parallel-group clinical trial, GDLM dispensed within 48 hours after symptoms for patients with AIS improved the proportion of patients achieving a 90-day favorable functional outcome, which was defined as an mRS score of 0 or 1, compared with placebo.Neuroprotective agents, which could target cerebral parenchyma in the acute ischemic phase and restore neuronal function in the after-stroke phase, have been widely acknowledged as a promising option for AIS treatment.Recently, the exploratory analysis of the ESCAPE-NA1 (Efficacy and Safety of Nerinetide for the Treatment of Acute Ischemic Stroke) trial indicated a potential efficacy of nerinetide for patients who didn’t receive treatment of alteplase.Ginkgolide-related intravenous preparation is a class of multitargeted neuroprotectants widely used for the treatment of cardiocerebrovascular diseases in China,Ginkgo diterpene lactone meglumine has shown a multipathway neuroprotective and reparative effect in preclinical animal trials. For instance, it was reported to exert its neuroprotective effect through antioxidation, increasing the level of antioxidant enzymes, maintaining the dynamic balance of oxygen free radical formation, and restraining the trigger of lipid peroxidation. | PMC10425831 |
Limitations | ischemic stroke | ISCHEMIC STROKE | Several limitations in the present study need to be addressed. First, because the current trial was mainly conducted among patients with Han Chinese backgrounds, caution should be taken when generalizing these findings to other ethnic groups. Additionally, patients with ischemic stroke in this trial did not receive intravenous thrombolysis or mechanical thrombectomy. However, given the increasing popularity of recanalization therapy, further research on the efficacy and safety of GDLM based on successful recanalization is warranted. | PMC10425831 |
Conclusions | The current randomized clinical trial indicated that among patients with AIS treated within 48 hours after onset, the 14-day treatment of GDLM could improve the proportion of patients achieving good clinical outcomes at 90 days compared with placebo. | PMC10425831 | ||
Acknowledgements | Hilary North prepared the manuscript. | PMC10176668 | ||
Author contributions | LSS, NJI, ABH | Trial, analysis conceived by SMC, SD, LSS, and MG (YIS assisted). ABH and YIS conducted trial operations. AOC, RM, and MG monitored trial safety. KB and HZ conducted Aβ monomer ELISA in CSF; MEH analyzed data. CMY, HME, WDG, and JRC developed, validated AβO MIE assay and conducted CSF sample measurements and analysis. KML, NJI, LW, and RY developed, validated AβO gel electrophoresis/native WB assay, and KML, NJI, LW, RY, and MEH conducted CSF sample measurements and data analysis. RJG performed the pharmacokinetic analysis. All authors interpreted data. CSD contributed to statistical analysis. SMC, KML, MEH, MG, and NJI wrote the paper. All authors read and approved the final manuscript. | PMC10176668 | |
Funding | This work was supported by grants from the National Institute on Aging (AG057780 to SMC) and by Cognition Therapeutics, Inc. Content is solely the authors’ and does not represent the National Institutes of Health. | PMC10176668 | ||
Availability of data and materials | All data needed to evaluate the conclusions are presented here or available upon request. | PMC10176668 |
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