Incompatible and sterile insect techniques combined eliminate mosquitoes.

The radiation-based sterile insect technique (SIT) has successfully suppressed field populations of several insect pest species, but its effect on mosquito vector control has been limited. The related incompatible insect technique (IIT)-which uses sterilization caused by the maternally inherited endosymbiotic bacteria Wolbachia-is a promising alternative, but can be undermined by accidental release of females infected with the same Wolbachia strain as the released males. Here we show that combining incompatible and sterile insect techniques (IIT-SIT) enables near elimination of field populations of the world's most invasive mosquito species, Aedes albopictus. Millions of factory-reared adult males with an artificial triple-Wolbachia infection were released, with prior pupal irradiation of the released mosquitoes to prevent unintentionally released triply infected females from successfully reproducing in the field. This successful field trial demonstrates the feasibility of area-wide application of combined IIT-SIT for mosquito vector control.

Influence of lack of blinding on the estimation of medication-related harms: a retrospective cohort study of randomized controlled trials.

BACKGROUND: Empirical evidence suggests that lack of blinding may be associated with biased estimates of treatment benefit in randomized controlled trials, but the influence on medication-related harms is not well-recognized. We aimed to investigate the association between blinding and clinical trial estimates of medication-related harms. METHODS: We searched PubMed from January 1, 2015, till January 1, 2020, for systematic reviews with meta-analyses of medication-related harms. Eligible meta-analyses must have contained trials both with and without blinding. Potential covariates that may confound effect estimates were addressed by restricting trials within the comparison or by hierarchical analysis of harmonized groups of meta-analyses (therefore harmonizing drug type, control, dosage, and registration status) across eligible meta-analyses. The weighted hierarchical linear regression was then used to estimate the differences in harm estimates (odds ratio, OR) between trials that lacked blinding and those that were blinded. The results were reported as the ratio of OR (ROR) with its 95% confidence interval (CI). RESULTS: We identified 629 meta-analyses of harms with 10,069 trials. We estimated a weighted average ROR of 0.68 (95% CI: 0.53 to 0.88, P < 0.01) among 82 trials in 20 meta-analyses where blinding of participants was lacking. With regard to lack of blinding of healthcare providers or outcomes assessors, the RORs were 0.68 (95% CI: 0.53 to 0.87, P < 0.01 from 81 trials in 22 meta-analyses) and 1.00 (95% CI: 0.94 to 1.07, P = 0.94 from 858 trials among 155 meta-analyses) respectively. Sensitivity analyses indicate that these findings are applicable to both objective and subjective outcomes. CONCLUSIONS: Lack of blinding of participants and health care providers in randomized controlled trials may underestimate medication-related harms. Adequate blinding in randomized trials, when feasible, may help safeguard against potential bias in estimating the effects of harms.

Metastatic tumor antigen 1 contributes to hepatocarcinogenesis posttranscriptionally through RNA-binding function.

BACKGROUND AND AIMS: Both nuclear and cytoplasmic overexpression of metastatic tumor antigen 1 (MTA1) contributes to tumorigenesis of HCC. Most studies have focused on nuclear MTA1 whose function is mainly a chromatin modifier regulating the expression of various cancer-promoting genes. By contrast, the molecular mechanisms of cytoplasmic MTA1 in carcinogenesis remain elusive. Here, we reveal a role of MTA1 in posttranscriptional gene regulation. APPROACH AND RESULTS: We conducted the in vitro and in vivo RNA-protein interaction assays indicating that MTA1 could bind directly to the 3'-untranslated region of MYC RNA. Mutation at the first glycine of the conserved GXXG loop within a K-homology II domain-like structure in MTA1 (G78D) resulted in the loss of RNA-binding activity. We used gain- and loss-of-function strategy showing that MTA1, but not the G78D mutant, extended the half-life of MYC and protected it from the lethal -7-mediated degradation. The G78D mutant exhibited lower activity in promoting tumorigenesis than wild-type in vitro and in vivo. Furthermore, RNA-immunoprecipitation sequencing analysis demonstrated that MTA1 binds various oncogenesis-related mRNAs besides MYC . The clinical relevance of cytoplasmic MTA1 and its interaction with MYC were investigated using HBV-HCC cohorts with or without early recurrence. The results showed that higher cytoplasmic MTA1 level and MTA1- MYC interaction were associated with early recurrence. CONCLUSIONS: MTA1 is a generic RNA-binding protein. Cytoplasmic MTA1 and its binding to MYC is associated with early recurrence in patients with HBV-HCC. This function enables it to regulate gene expression posttranscriptionally and contributes to hepatocarcinogenesis.

Single-balloon catheter with concomitant vaginal misoprostol is the most effective strategy for labor induction: a meta-review with network meta-analysis.

OBJECTIVE: Several systematic reviews and meta-analyses have been conducted to summarize the evidence for the efficacy of various labor induction agents. However, the most effective agents or strategies have not been conclusively determined. We aimed to perform a meta-review and network meta-analysis of published systematic reviews to determine the efficacy and safety of currently employed pharmacologic, mechanical, and combined methods of labor induction. DATA SOURCES: With the assistance of an experienced medical librarian, we performed a systematic search of the literature using PubMed, EMBASE, and the Cochrane Central Register of Control Trials. We systematically searched electronic databases from inception to May 31, 2021. STUDY ELIGIBILITY CRITERIA: We considered systematic reviews and meta-analyses of randomized controlled trials comparing different agents or methods for inpatient labor induction. METHODS: We conducted a frequentist random-effects network meta-analysis employing data from randomized controlled trials of published systematic reviews. We performed direct pairwise meta-analyses to compare the efficacy of the various labor induction agents and placebo or no treatment. We performed ranking to determine the best treatment using the surface under the cumulative ranking curve. The main outcomes assessed were cesarean delivery, vaginal delivery within 24 hours, operative vaginal delivery, hyperstimulation, neonatal intensive care unit admissions, and Apgar scores of <7 at 5 minutes of birth. RESULTS: We included 11 systematic reviews and extracted data from 207 randomized controlled trials with a total of 40,854 participants. When assessing the efficacy of all agents and methods, the combination of a single-balloon catheter with misoprostol was the most effective in reducing the odds of cesarean delivery and vaginal birth >24 hours (surface under the cumulative ranking curve of 0.9 for each). Among the pharmacologic agents, low-dose vaginal misoprostol was the most effective in reducing the odds of cesarean delivery, whereas high-dose vaginal misoprostol was the most effective in achieving vaginal delivery within 24 hours (surface under the cumulative ranking curve of 0.9 for each). Single-balloon catheter (surface under the cumulative ranking curve of 0.8) and double-balloon catheter (surface under the cumulative ranking curve of 0.9) were the most effective in reducing the odds of operative vaginal delivery and hyperstimulation. Buccal or sublingual misoprostol (surface under the cumulative ranking curve of 0.9) and the combination of single-balloon catheter and misoprostol (surface under the cumulative ranking curve of 0.9) most effectively reduced the odds of abnormal Apgar scores and neonatal intensive care unit admissions. CONCLUSION: The combination of a single-balloon catheter with misoprostol was the most effective method in reducing the odds for cesarean delivery and prolonged time to vaginal delivery. This method was associated with a reduction in admissions to the neonatal intensive care unit.

Outpatient cervical ripening and labor induction with low-dose vaginal misoprostol reduces the interval to delivery: a systematic review and network meta-analysis.

OBJECTIVE: Several systematic reviews and meta-analyses have summarized the evidence on the efficacy and safety of various outpatient cervical ripening methods. However, the method with the highest efficacy and safety profile has not been determined conclusively. We performed a systematic review and network meta-analysis of published randomized controlled trials to assess the efficacy and safety of cervical ripening methods currently employed in the outpatient setting. DATA SOURCES: With the assistance of an experienced medical librarian, we performed a systematic search of the literature using MEDLINE, Embase, Scopus, Web of Science, Cochrane Library, and ClinicalTrials.gov. We systematically searched electronic databases from inception to January 14, 2020. STUDY ELIGIBILITY CRITERIA: We considered randomized controlled trials comparing a variety of methods for outpatient cervical ripening. METHODS: We conducted a frequentist random effects network meta-analysis employing data from randomized controlled trials. We performed a direct, pairwise meta-analysis to compare the efficacy of various outpatient cervical ripening methods, including placebo. We employed ranking strategies to determine the most efficacious method using the surface under the cumulative ranking curve; a higher surface under the cumulative ranking curve value implied a more efficacious method. We assessed the following outcomes: time from intervention to delivery, cesarean delivery rates, changes in the Bishop score, need for additional ripening methods, incidence of Apgar scores <7 at 5 minutes, and uterine hyperstimulation. RESULTS: We included data from 42 randomized controlled trials including 6093 participants. When assessing the efficacy of all methods, 25 µg vaginal misoprostol was the most efficacious in reducing the time from intervention to delivery (surface under the cumulative ranking curve of 1.0) without increasing the odds of cesarean delivery, the need for additional ripening methods, the incidence of a low Apgar score, or uterine hyperstimulation. Acupressure (surface under the cumulative ranking curve of 0.3) and primrose oil (surface under the cumulative ranking curve of 0.2) were the least effective methods in reducing the time to delivery interval. Among effective methods, 50 mg oral mifepristone was associated with the lowest odds of cesarean delivery (surface under the cumulative ranking curve of 0.9). CONCLUSION: When balancing efficacy and safety, vaginal misoprostol 25 µg represents the best method for outpatient cervical ripening.

Water birth: a systematic review and meta-analysis of maternal and neonatal outcomes.

OBJECTIVE: This systematic review and meta-analysis aimed to conduct a thorough and contemporary assessment of maternal and neonatal outcomes associated with water birth in comparison with land-based birth. DATA SOURCES: We conducted a comprehensive search of PubMed, EMBASE, CINAHL, and gray literature sources, from inception to February 28, 2023. STUDY ELIGIBILITY CRITERIA: We included randomized and nonrandomized studies that assessed maternal and neonatal outcomes in patients who delivered either conventionally or while submerged in water. METHODS: Pooled unadjusted odds ratios with 95% confidence intervals were calculated using a random-effects model (restricted maximum likelihood method). We assessed the 95% prediction intervals to estimate the likely range of future study results. To evaluate the robustness of the results, we calculated fragility indices. Maternal infection was designated as the primary outcome, whereas postpartum hemorrhage, perineal lacerations, obstetrical anal sphincter injury, umbilical cord avulsion, low Apgar scores, neonatal aspiration requiring resuscitation, neonatal infection, neonatal mortality within 30 days of birth, and neonatal intensive care unit admission were considered secondary outcomes. RESULTS: Of the 20,642 articles identified, 52 were included in the meta-analyses. Based on data from observational studies, water birth was not associated with increased probability of maternal infection compared with land birth (10 articles, 113,395 pregnancies; odds ratio, 0.93; 95% confidence interval, 0.76-1.14). Patients undergoing water birth had decreased odds of postpartum hemorrhage (21 articles, 149,732 pregnancies; odds ratio, 0.80; 95% confidence interval, 0.68-0.94). Neonates delivered while submerged in water had increased odds of cord avulsion (10 articles, 91,504 pregnancies; odds ratio, 1.75; 95% confidence interval, 1.38-2.24) and decreased odds of low Apgar scores (21 articles, 165,917 pregnancies; odds ratio, 0.69; 95% confidence interval, 0.58-0.82), neonatal infection (15 articles, 53,635 pregnancies; odds ratio, 0.64; 95% confidence interval, 0.42-0.97), neonatal aspiration requiring resuscitation (19 articles, 181,001 pregnancies; odds ratio, 0.60; 95% confidence interval, 0.43-0.84), and neonatal intensive care unit admission (30 articles, 287,698 pregnancies; odds ratio, 0.56; 95% confidence interval, 0.45-0.70). CONCLUSION: When compared with land birth, water birth does not appear to increase the risk of most maternal and neonatal complications. Like any other delivery method, water birth has its unique considerations and potential risks, which health care providers and expectant parents should evaluate thoroughly. However, with proper precautions in place, water birth can be a reasonable choice for mothers and newborns, in facilities equipped to conduct water births safely.

Sensitivity analysis with iterative outlier detection for systematic reviews and meta-analyses.

Meta-analysis is a widely used tool for synthesizing results from multiple studies. The collected studies are deemed heterogeneous when they do not share a common underlying effect size; thus, the factors attributable to the heterogeneity need to be carefully considered. A critical problem in meta-analyses and systematic reviews is that outlying studies are frequently included, which can lead to invalid conclusions and affect the robustness of decision-making. Outliers may be caused by several factors such as study selection criteria, low study quality, small-study effects, and so on. Although outlier detection is well-studied in the statistical community, limited attention has been paid to meta-analysis. The conventional outlier detection method in meta-analysis is based on a leave-one-study-out procedure. However, when calculating a potentially outlying study's deviation, other outliers could substantially impact its result. This article proposes an iterative method to detect potential outliers, which reduces such an impact that could confound the detection. Furthermore, we adopt bagging to provide valid inference for sensitivity analyses of excluding outliers. Based on simulation studies, the proposed iterative method yields smaller bias and heterogeneity after performing a sensitivity analysis to remove the identified outliers. It also provides higher accuracy on outlier detection. Two case studies are used to illustrate the proposed method's real-world performance.

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

OBJECTIVE: To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Google Bard, and Chatsonic) in generating accurate references from existing obstetric literature. STUDY DESIGN: Between mid-March and late April 2023, ChatGPT, Google Bard, and Chatsonic were prompted to provide references for specific obstetrical randomized controlled trials (RCTs) published in 2020. RCTs were considered for inclusion if they were mentioned in a previous article that primarily evaluated RCTs published by the top medical and obstetrics and gynecology journals with the highest impact factors in 2020 as well as RCTs published in a new journal focused on publishing obstetric RCTs. The selection of the three AI models was based on their popularity, performance in natural language processing, and public availability. Data collection involved prompting the AI chatbots to provide references according to a standardized protocol. The primary evaluation metric was the accuracy of each AI model in correctly citing references, including authors, publication title, journal name, and digital object identifier (DOI). Statistical analysis was performed using a permutation test to compare the performance of the AI models. RESULTS: Among the 44 RCTs analyzed, Google Bard demonstrated the highest accuracy, correctly citing 13.6% of the requested RCTs, whereas ChatGPT and Chatsonic exhibited lower accuracy rates of 2.4 and 0%, respectively. Google Bard often substantially outperformed Chatsonic and ChatGPT in correctly citing the studied reference components. The majority of references from all AI models studied were noted to provide DOIs for unrelated studies or DOIs that do not exist. CONCLUSION: To ensure the reliability of scientific information being disseminated, authors must exercise caution when utilizing AI for scientific writing and literature search. However, despite their limitations, collaborative partnerships between AI systems and researchers have the potential to drive synergistic advancements, leading to improved patient care and outcomes. KEY POINTS: · AI chatbots often cite scientific articles incorrectly.. · AI chatbots can create false references.. · Responsible AI use in research is vital..

The normality assumption on between-study random effects was questionable in a considerable number of Cochrane meta-analyses.

BACKGROUND: Studies included in a meta-analysis are often heterogeneous. The traditional random-effects models assume their true effects to follow a normal distribution, while it is unclear if this critical assumption is practical. Violations of this between-study normality assumption could lead to problematic meta-analytical conclusions. We aimed to empirically examine if this assumption is valid in published meta-analyses. METHODS: In this cross-sectional study, we collected meta-analyses available in the Cochrane Library with at least 10 studies and with between-study variance estimates > 0. For each extracted meta-analysis, we performed the Shapiro-Wilk (SW) test to quantitatively assess the between-study normality assumption. For binary outcomes, we assessed between-study normality for odds ratios (ORs), relative risks (RRs), and risk differences (RDs). Subgroup analyses based on sample sizes and event rates were used to rule out the potential confounders. In addition, we obtained the quantile-quantile (Q-Q) plot of study-specific standardized residuals for visually assessing between-study normality. RESULTS: Based on 4234 eligible meta-analyses with binary outcomes and 3433 with non-binary outcomes, the proportion of meta-analyses that had statistically significant non-normality varied from 15.1 to 26.2%. RDs and non-binary outcomes led to more frequent non-normality issues than ORs and RRs. For binary outcomes, the between-study non-normality was more frequently found in meta-analyses with larger sample sizes and event rates away from 0 and 100%. The agreements of assessing the normality between two independent researchers based on Q-Q plots were fair or moderate. CONCLUSIONS: The between-study normality assumption is commonly violated in Cochrane meta-analyses. This assumption should be routinely assessed when performing a meta-analysis. When it may not hold, alternative meta-analysis methods that do not make this assumption should be considered.

Intrapartum amnioinfusion reduces meconium aspiration syndrome and improves neonatal outcomes in patients with meconium-stained fluid: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to reassess the effect of prophylactic transcervical amnioinfusion for intrapartum meconium-stained amniotic fluid on meconium aspiration syndrome and other adverse neonatal and maternal outcomes. DATA SOURCES: From inception to November 2021, a systematic search of the literature was performed in PubMed, Embase, Web of Science, and Scopus databases and gray literature sources. STUDY ELIGIBILITY CRITERIA: We identified randomized controlled trials of patients with intrapartum moderate to thick meconium-stained amniotic fluid that evaluated the effect of amnioinfusion on adverse neonatal and maternal outcomes. METHODS: Of note, 2 reviewers independently abstracted data and gauged study quality by assigning a modified Jadad score. Meconium aspiration syndrome constituted the primary outcome. The secondary outcomes were meconium below the cords, Apgar scores of <7 at 5 minutes, neonatal acidosis, cesarean delivery, cesarean delivery for fetal heart rate abnormalities, neonatal intensive care unit admission, and postpartum endometritis. This study calculated the odds ratios with 95% confidence intervals for categorical outcomes and weighted mean differences with 95% confidence intervals for continuous outcomes. RESULTS: A total of 24 randomized studies with 5994 participants met the inclusion criteria. The overall odds of meconium aspiration syndrome was reduced by 67% in the amnioinfusion group (pooled odds ratio, 0.33; 95% confidence interval, 0.21-0.51). Except for postpartum endometritis, amnioinfusion was associated with a significant reduction in all secondary outcomes. CONCLUSION: Our study found that the use of intrapartum amnioinfusion in the setting of meconium-stained amniotic fluid significantly reduces the odds of meconium aspiration syndrome and other adverse neonatal outcomes.

Assessing the robustness of results from clinical trials and meta-analyses with the fragility index.

The fragility index has been increasingly used to assess the robustness of the results of clinical trials since 2014. It aims at finding the smallest number of event changes that could alter originally statistically significant results. Despite its popularity, some researchers have expressed several concerns about the validity and usefulness of the fragility index. It offers a comprehensive review of the fragility index's rationale, calculation, software, and interpretation, with emphasis on application to studies in obstetrics and gynecology. This article presents the fragility index in the settings of individual clinical trials, standard pairwise meta-analyses, and network meta-analyses. Moreover, this article provides worked examples to demonstrate how the fragility index can be appropriately calculated and interpreted. In addition, the limitations of the traditional fragility index and some solutions proposed in the literature to address these limitations were reviewed. In summary, the fragility index is recommended to be used as a supplemental measure in the reporting of clinical trials and a tool to communicate the robustness of trial results to clinicians. Other considerations that can aid in the fragility index's interpretation include the loss to follow-up and the likelihood of data modifications that achieve the loss of statistical significance.

Bayesian hierarchical models incorporating study-level covariates for multivariate meta-analysis of diagnostic tests without a gold standard with application to COVID-19.

When evaluating a diagnostic test, it is common that a gold standard may not be available. One example is the diagnosis of SARS-CoV-2 infection using saliva sampling or nasopharyngeal swabs. Without a gold standard, a pragmatic approach is to postulate a "reference standard," defined as positive if either test is positive, or negative if both are negative. However, this pragmatic approach may overestimate sensitivities because subjects infected with SARS-CoV-2 may still have double-negative test results even when both tests exhibit perfect specificity. To address this limitation, we propose a Bayesian hierarchical model for simultaneously estimating sensitivity, specificity, and disease prevalence in the absence of a gold standard. The proposed model allows adjusting for study-level covariates. We evaluate the model performance using an example based on a recently published meta-analysis on the diagnosis of SARS-CoV-2 infection and extensive simulations. Compared with the pragmatic reference standard approach, we demonstrate that the proposed Bayesian method provides a more accurate evaluation of prevalence, specificity, and sensitivity in a meta-analytic framework.

The association of sensitivity and specificity with disease prevalence: analysis of 6909 studies of diagnostic test accuracy.

BACKGROUND: Sensitivity and specificity are characteristics of a diagnostic test and are not expected to change as the prevalence of the target condition changes. We sought to evaluate the association between prevalence and changes in sensitivity and specificity. METHODS: We retrieved data from meta-analyses of diagnostic test accuracy published in the Cochrane Database of Systematic Reviews (2003-2020). We used mixed-effects random-intercept linear regression models to evaluate the association between prevalence and logit-transformed sensitivity and specificity. The model evaluated all meta-analyses as nested within each systematic review. RESULTS: We analyzed 6909 diagnostic test accuracy studies from 552 meta-analyses that were included in 92 systematic reviews. For sensitivity, compared with the lowest quartile of prevalence, the second, third and fourth quartiles were associated with significantly higher odds of identifying a true positive case (odds ratio [OR] 1.17, 95% confidence interval [CI] 1.09-1.26; OR 1.32, 95% CI 1.23-1.41; OR 1.47, 95% CI 1.37-1.58; respectively). For specificity, compared with the lowest quartile of prevalence, the second, third and fourth quartiles were associated with significantly lower odds of identifying a true negative case (OR 0.74, 95% CI 0.69-0.80; OR 0.65, 95% CI 0.60-0.70; OR 0.47, 95% CI 0.44-0.51; respectively). Pooled regression coefficients from bivariate models conducted within each meta-analysis showed that prevalence was positively associated with sensitivity and negatively associated with specificity. Findings were consistent across subgroups. INTERPRETATION: In this large sample of diagnostic studies, higher prevalence was associated with higher estimated sensitivity and lower estimated specificity. Clinicians should consider the implications of disease prevalence and spectrum when interpreting the results from studies of diagnostic test accuracy.

Measuring the impact of zero-cases studies in evidence synthesis practice using the harms index and benefits index (Hi-Bi).

OBJECTIVES: In evidence synthesis practice, dealing with studies with no cases in both arms has been a tough problem, for which there is no consensus in the research community. In this study, we propose a method to measure the potential impact of studies with no cases for meta-analysis results which we define as harms index (Hi) and benefits index (Bi) as an alternative solution for deciding how to deal with such studies. METHODS: Hi and Bi are defined by the minimal number of cases added to the treatment arm (Hi) or control arm (Bi) of studies with no cases in a meta-analysis that lead to a change of the direction of the estimates or its statistical significance. Both exact and approximating methods are available to calculate Hi and Bi. We developed the "hibi" module in Stata so that researchers can easily implement the method. A real-world investigation of meta-analyses from Cochrane reviews was employed to evaluate the proposed method. RESULTS: Based on Hi and Bi, our results suggested that 21.53% (Hi) to 26.55% (Bi) of Cochrane meta-analyses may be potentially impacted by studies with no cases, for which studies with no cases could not be excluded from the synthesis. The approximating method shows excellent specificity (100%) for both Hi and Bi, moderate sensitivity (68.25%) for Bi, and high sensitivity (80.61%) for Hi compared to the exact method. CONCLUSIONS: The proposed method is practical and useful for systematic reviewers to measure whether studies with no cases impact the results of meta-analyses and may act as an alternative solution for review authors to decide whether to include studies with no events for the synthesis or not.

A Bayesian model for combining standardized mean differences and odds ratios in the same meta-analysis.

In meta-analysis practice, researchers frequently face studies that report the same outcome differently, such as a continuous variable (e.g., scores for rating depression) or a binary variable (e.g., counts of patients with depression dichotomized by certain latent and unreported depression scores). For combining these two types of studies in the same analysis, a simple conversion method has been widely used to handle standardized mean differences (SMDs) and odds ratios (ORs). This conventional method uses a linear function connecting the SMD and log OR; it assumes logistic distributions for (latent) continuous measures. However, the normality assumption is more commonly used for continuous measures, and the conventional method may be inaccurate when effect sizes are large or cutoff values for dichotomizing binary events are extreme (leading to rare events). This article proposes a Bayesian hierarchical model to synthesize SMDs and ORs without using the conventional conversion method. This model assumes exact likelihoods for continuous and binary outcome measures, which account for full uncertainties in the synthesized results. We performed simulation studies to compare the performance of the conventional and Bayesian methods in various settings. The Bayesian method generally produced less biased results with smaller mean squared errors and higher coverage probabilities than the conventional method in most cases. Nevertheless, this superior performance depended on the normality assumption for continuous measures; the Bayesian method could lead to nonignorable biases for non-normal data. In addition, we used two case studies to illustrate the proposed Bayesian method in real-world settings.

Mortality burden based on the associations of ambient PM2.5 with cause-specific mortality in China: Evidence from a death-spectrum wide association study (DWAS).

Although studies have estimated the associations of PM2.5 with total mortality or cardiopulmonary mortality, few have comprehensively examined cause-specific mortality risk and burden caused by ambient PM2.5. Thus, this study investigated the association of short-term exposure to PM2.5 with cause-specific mortality using a death-spectrum wide association study (DWAS). Individual information of 5,450,764 deaths during 2013-2018 were collected from six provinces in China. Daily PM2.5 concentration in the case and control days were estimated by a random forest model. A time-stratified case-crossover study design was applied to estimate the associations (access risk, ER) of PM2.5 with cause-specific mortality, which was then used to calculate the population-attributable fraction (PAF) of mortality and the corresponding mortality burden caused by PM2.5. Each 10 µg/m3 increase in PM2.5 concentration (lag03) was associated with a 0.80 % [95 % confidence interval (CI): 0.73 %, 0.86 %] rise in total mortality. We found greater mortality effect at PM2.5 concentrations < 50 µg/m3. Stratified analyses showed greater ERs in females (1.01 %, 95 %CI: 0.91 %, 1.11 %), children ≤ 5 years (2.17 %, 95 %CI: 0.85 %, 3.51 %), and old people ≥ 70 years. We identified 33 specific causes (level 2) of death which had significant associations with PM2.5, including 16 circulatory diseases, 9 respiratory diseases, and 8 other causes. The PAF estimated based on the overall association between PM2.5 and total mortality was 3.16 % (95 %CI: 2.89 %, 3.40 %). However, the PAF was reduced to 2.88 % (95 %CI: 1.88 %, 3.81 %) using the associations of PM2.5 with 33 level 2 causes of death, based on which 250.15 (95 %CI: 163.29, 330.93) thousand deaths were attributable to short-term PM2.5 exposure across China in 2019. Overall, this study provided a comprehensive picture on the death-spectrum wide association between PM2.5 and morality in China. We observed robust positive cause-specific associations of PM2.5 with mortality risk, which may provide more precise basis in assessing the mortality burden of air pollution.

Commissioning and validation of a Monte Carlo algorithm for spine stereotactic radiosurgery.

PURPOSE: A 6FFF Monte Carlo (MC) dose calculation algorithm was commissioned for spine stereotactic radiosurgery (SRS). Model generation, validation, and ensuing model tuning are presented. METHODS: The model was generated using in-air and in-water commissioning measurements of field sizes between 10 and 400 mm2 . Commissioning measurements were compared to simulated water tank MC calculations to validate output factors, percent depth doses (PDDs), profile sizes and penumbras. Previously treated Spine SRS patients were re-optimized with the MC model to achieve clinically acceptable plans. Resulting plans were calculated on the StereoPHAN phantom and subsequently delivered to the microDiamond and SRSMapcheck to verify calculated dose accuracy. Model tuning was performed by adjusting the model's light field offset (LO) distance between physical and radiological positions of the MLCs, to improve field size and StereoPHAN calculation accuracy. Following tuning, plans were generated and delivered to an anthropomorphic 3D-printed spine phantom featuring realistic bone anatomy, to validate heterogeneity corrections. Finally, plans were validated using polymer gel (VIPAR based formulation) measurements. RESULTS: Compared to open field measurements, MC calculated output factors and PDDs were within 2%, profile penumbra widths were within 1 mm, and field sizes were within 0.5 mm. Calculated point dose measurements in the StereoPHAN were within 0.26% ± 0.93% and -0.10% ± 1.37% for targets and spinal canals, respectively. Average SRSMapcheck per-plan pass rates using a 2%/2 mm/10% threshold relative gamma analysis was 99.1% ± 0.89%. Adjusting LOs improved open field and patient-specific dosimetric agreement. Anthropomorphic phantom measurements were within -1.29% ± 1.00% and 0.27% ± 1.36% of MC calculated for the vertebral body (target) and spinal canal, respectively. VIPAR gel measurements confirmed good dosimetric agreement near the target-spine junction. CONCLUSION: Validation of a MC algorithm for simple fields and complex SRS spine deliveries in homogeneous and heterogeneous phantoms has been performed. The MC algorithm has been released for clinical use.

Effect of integrated intervention to prevent child drowning in rural areas of Guangdong, China: a cluster randomized controlled trial.

BACKGROUND: Drowning is the leading cause of death for children under the age of 15 years in Guangdong Province, China. This serious public health issue also exists in low- and middle-income countries (LMICs), which have few value-integrated intervention programs. The current study presents an integrated intervention project that aims to explore an effective pattern of prevention for child drowning in rural areas and feasibility to perform in other LMICs. METHODS: We conducted a cluster randomized controlled trial by comparing the incidence of non-fatal drowning among children in two groups in rural areas of southern China. We recruited the participants in two phases and reached a total of 10 687 students from 23 schools at two towns in Guangdong Province, China. At the first and second phases, 8966 and 1721 students were recruited, respectively. RESULTS: The final evaluation questionnaires were collected after 18 months of integrated intervention, where we obtained 9791 data from Grades 3-9. The incidence of non-fatal drowning between the intervention and control groups after intervention did not differ significantly from the baseline according to the total number of students, male students, female students and Grades 6-9 [0.81; 95% confidence interval (CI): [0.66, 1.00]; p = 0.05, 1.17; 95% CI: [0.90, 1.51]; p = 0.25, 1.40; 95% CI: [0.97, 2.02]; p = 0.07 and 0.97; 95% CI: [0.70, 1.34]; p = 0.86], except for Grades 3-5 (1.36; 95% CI: [1.02, 1.82]; p = 0.037). The study observed a significantly positive benefit of awareness and risk behaviours of non-fatal drowning between the intervention and control groups (0.27, 95% CI: [0.21, 0.33]; p = 0.00, -0.16; 95% CI: [-0.24, -0.08]; p = 0.00). CONCLUSIONS: The integrated intervention exerted a significant impact on the prevention and management of child non-fatal drowning, especially in rural areas.

Chlorination of microcystin-LR in natural water: Kinetics, transformation products, and genotoxicity.

Microcystin-LR (MC-LR), a type of cyanotoxin commonly found in natural water bodies (sources of drinking water), poses a threat to human health due to its high toxicity. It is essential to successfully remove this cyanotoxin from drinking water sources. In this study, chlorine was used to oxidize MC-LR in Milli-Q water (MQ) (control test) and natural water collected from Lake Longhu (LLW) as a drinking water source. The removal efficiency, proposed transformation pathways, and genotoxicity were investigated. In the chlorine dose range investigated (4.0 mg L-1 - 8.0 mg L-1), the apparent second-order rate constants for MC-LR chlorination varied from 21.3 M-1s-1 to 31.9 M-1s-1 in MQ, higher than that in LLW (9.06 M-1s-1 to 17.7 M-1s-1) due to a faster chlorine decay attributed to the water matrix (e.g., natural organic matter) of LLW. Eleven transformation products (TPs) of MC-LR were identified in the two waters. The conjugated diene moieties and benzene ring of Adda moiety (3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid), and the double bond of Mdha moiety (N-methyldehydroalanine) were the major susceptible reaction sites. Attacking unsaturated bonds by hydroxyl and chlorine radicals to generate monochloro-hydroxy-MC-LR was the primary initial transformation pathway, followed by nucleophilic substitution, dehydration, and cleavage in MC-LR. Chlorine substitution on the benzene ring was also observed. Based on the bacterial reverse-mutation assay (Ames assay), TPs in treated natural water did not induce genotoxicity/mutagenicity. These findings shed light on the role of chlorination in controlling the risk of cyanotoxins in drinking water treatment plants.

THE EFFECT DIRECTION SHOULD BE TAKEN INTO ACCOUNT WHEN ASSESSING SMALL-STUDY EFFECTS.

OBJECTIVE: Studies with statistically significant results are frequently more likely to be published than those with non-significant results. This phenomenon leads to publication bias or small-study effects and can seriously affect the validity of the conclusion from systematic reviews and meta-analyses. Small-study effects typically appear in a specific direction, depending on whether the outcome of interest is beneficial or harmful, but this direction is rarely taken into account in conventional methods. METHODS: We propose to use directional tests to assess potential small-study effects. The tests are built on a one-sided testing framework based on the existing Egger's regression test. We performed simulation studies to compare the proposed one-sided regression tests, conventional two-sided regression tests, as well as two other competitive methods (Begg's rank test and the trim-and-fill method). Their performance was measured by type I error rates and statistical power. Three real-world meta-analyses on measurements of infrabony periodontal defects were also used to examine the various methods' performance. RESULTS: Based on simulation studies, the one-sided tests could have considerably higher statistical power than competing methods, particularly their two-sided counterparts. Their type I error rates were generally controlled well. In the case study of the three real-world meta-analyses, by accounting for the favored direction of effects, the one-sided tests could rule out potential false-positive conclusions about small-study effects. They also are more powerful in assessing small-study effects than the conventional two-sided tests when true small-study effects likely exist. CONCLUSION: We recommend researchers incorporate the potential favored direction of effects into the assessment of small-study effects.