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BMC Medical Research Methodology Dec 2023Prospective cohorts may be vulnerable to bias due to attrition. Inverse probability weights have been proposed as a method to help mitigate this bias. The current study...
BACKGROUND
Prospective cohorts may be vulnerable to bias due to attrition. Inverse probability weights have been proposed as a method to help mitigate this bias. The current study used the "All Our Families" longitudinal pregnancy cohort of 3351 maternal-infant pairs and aimed to develop inverse probability weights using logistic regression models to predict study continuation versus drop-out from baseline to the three-year data collection wave.
METHODS
Two methods of variable selection took place. One method was a knowledge-based a priori variable selection approach, while the second used Least Absolute Shrinkage and Selection Operator (LASSO). The ability of each model to predict continuing participation through discrimination and calibration for both approaches were evaluated by examining area under the receiver operating curve (AUROC) and calibration plots, respectively. Stabilized inverse probability weights were generated using predicted probabilities. Weight performance was assessed using standardized differences of baseline characteristics for those who continue in study and those that do not, with and without weights (unadjusted estimates).
RESULTS
The a priori and LASSO variable selection method prediction models had good and fair discrimination with AUROC of 0.69 (95% Confidence Interval [CI]: 0.67-0.71) and 0.73 (95% CI: 0.71-0.75), respectively. Calibration plots and non-significant Hosmer-Lemeshow Goodness of Fit Tests indicated that both the a priori (p = 0.329) and LASSO model (p = 0.242) were well-calibrated. Unweighted results indicated large (> 10%) standardized differences in 15 demographic variables (range: 11 - 29%), when comparing those who continued in the study with those that did not. Weights derived from the a priori and LASSO models reduced standardized differences relative to unadjusted estimates, with the largest differences of 13% and 5%, respectively. Additionally, when applying the same LASSO variable selection method to develop weights in future data collection waves, standardized differences remained below 10% for each demographic variable.
CONCLUSION
The LASSO variable selection approach produced robust weights that addressed non-response bias more than the knowledge-driven approach. These weights can be applied to analyses across multiple longitudinal waves of data collection to reduce bias.
Topics: Pregnancy; Female; Humans; Prospective Studies; Logistic Models; Probability; Data Collection
PubMed: 38097944
DOI: 10.1186/s12874-023-02121-1 -
Euro Surveillance : Bulletin Europeen... Aug 2023BackgroundInvasive infections with beta-haemolytic streptococci of Lancefield groups A (iGAS), B (iGBS) and C/G (iGCGS) are a major cause of morbidity and mortality...
BackgroundInvasive infections with beta-haemolytic streptococci of Lancefield groups A (iGAS), B (iGBS) and C/G (iGCGS) are a major cause of morbidity and mortality worldwide.AimWe studied incidence trends of invasive beta-haemolytic streptococcal infections in Finland, focusing on iGCGS.MethodsWe conducted a retrospective register-based study. Cases were defined as isolations from blood and/or cerebrospinal fluid and retrieved from the National Infectious Disease Register where all invasive cases are mandatorily notified.ResultsBetween 2006 and 2020, the mean annual incidence was 4.1 per 100,000 for iGAS (range: 2.1-6.7), 5.2 for iGBS (4.0-6.3) and 10.1 for iGCGS (5.4-17.6). The incidence displayed an increasing trend for all groups, albeit for iGBS only for individuals 45 years and older. The increase was particularly sharp for iGCGS (8% annual relative increase). The incidence rate was higher in males for iGCGS (adjusted incidence rate ratio (IRR) = 1.6; 95% confidence interval (CI): 1.5-1.8) and iGAS (adjusted IRR = 1.3; 95% CI: 1.1-1.4); for iGBS, the association with sex was age-dependent. In adults, iGCGS incidence increased significantly with age. Recurrency was seen for iGCGS and secondarily iGBS, but not for iGAS. Infections with iGCGS and iGBS peaked in July and August.ConclusionsThe incidence of invasive beta-haemolytic streptococcal infections in Finland has been rising since 2006, especially for iGCGS and among the elderly population. However, national surveillance still focuses on iGAS and iGBS, and European Union-wide surveillance is lacking. We recommend that surveillance of iGCGS be enhanced, including systematic collection and typing of isolates, to guide infection prevention strategies.
Topics: Adult; Male; Humans; Aged; Streptococcus pyogenes; Streptococcal Infections; Finland; Retrospective Studies; Data Collection; Incidence
PubMed: 37535473
DOI: 10.2807/1560-7917.ES.2023.28.31.2200807 -
Scientific Data Feb 2024Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that...
Infectious disease outbreaks transcend the medical and public health realms, triggering widespread panic and impeding socio-economic development. Considering that self-limiting diarrhoea of sporadic cases is usually underreported, the Salmonella outbreak (SO) study offers a unique opportunity for source tracing, spatiotemporal correlation, and outbreak prediction. To summarize the pattern of SO and estimate observational epidemiological indicators, 1,134 qualitative reports screened from 1949 to 2023 were included in the systematic review dataset, which contained a 506-study meta-analysis dataset. In addition to the dataset comprising over 50 columns with a total of 46,494 entries eligible for inclusion in systematic reviews or input into prediction models, we also provide initial literature collection datasets and datasets containing socio-economic and climate information for relevant regions. This study has a broad impact on advancing knowledge regarding epidemic trends and prevention priorities in diverse salmonellosis outbreaks and guiding rational policy-making or predictive modeling to mitigate the infringement upon the right to life imposed by significant epidemics.
Topics: Humans; China; Data Collection; Disease Outbreaks; Salmonella; Salmonella Food Poisoning; Salmonella Infections; Systematic Reviews as Topic; Meta-Analysis as Topic
PubMed: 38413596
DOI: 10.1038/s41597-024-03085-7 -
Journal of Nutritional Science 2023In nutritional epidemiological studies, it is imperative to collect high-quality data to ensure accurate dietary assessment. However, dietary data collection using... (Randomized Controlled Trial)
Randomized Controlled Trial
In nutritional epidemiological studies, it is imperative to collect high-quality data to ensure accurate dietary assessment. However, dietary data collection using traditional paper forms has several limitations that may compromise data quality. The aim of this study was to propose novel methods to design and develop software applications (Apps) for dietary data collection to assess the nutritional status of pregnant women and infants. This study is part of the M-SAKHI (Mobile-Solutions for Aiding Knowledge for Health Improvement) cluster randomised controlled trial (cRCT) implemented in central India. Three tablet-based software Apps were developed in this study: the ACEC (Automated Coding and Energy Calculation) App to establish a generic cooked food recipe database, the FFQ (Food Frequency Questionnaire), and the IDR (24 h Infant Dietary Recall) Apps to collect dietary data from pregnant women and their infants from rural area of Bhandara and Nagpur districts. Regional food lists, recipes, and portion resource kits were developed to support the data collection using the Apps. In conclusion, the Apps were user-friendly, required minimal prior training, had built-in validation checks for erroneous data entry and provided automated calculations. The Apps were successfully deployed in low-resource rural settings to accurately collect high-quality regional cooked food data and individual-level dietary data of pregnant women and their infants.
Topics: Infant; Humans; Female; Pregnancy; Mobile Applications; Pregnant Women; Diet; Cell Phone; Data Collection
PubMed: 38155806
DOI: 10.1017/jns.2023.95 -
Bulletin of the World Health... Dec 2023To evaluate the utility and quality of death registration data across countries.
OBJECTIVE
To evaluate the utility and quality of death registration data across countries.
METHODS
We compiled routine death and cause of death statistics data from 2015-2019 from national authorities. We estimated completeness of death registration using the Adair-Lopez empirical method. The quality of cause of death data was assessed by evaluating the assignment of usable causes of death among people younger than 80 years. We grouped data into nine policy utility categories based on data availability, registration completeness and diagnostic precision.
FINDINGS
Of an estimated 55 million global deaths in 2019, 70% of deaths were registered across 156 countries, but only 52% had medically certified causes and 42% of deaths were assigned a usable cause. In 54 countries, which are mostly high-income, there is complete and high-quality mortality data. In a further 29 countries, located across different regions, death registration is complete, but cause of death data quality remains suboptimal. Additionally, 37 countries possess functional death registration systems with cause of death data of poor to moderate quality. In 30 countries, death registration ranges from limited to nascent completeness, accompanied by poor or unavailable cause of death data. Furthermore, 38 countries lack accessible data altogether.
CONCLUSION
By implementing more proactive death notification processes, expanding the use of digitized data collection platforms, streamlining data compilation procedures and improving data quality assessment, governments could enhance the policy utility of mortality data. Encouraging the routine application of automated verbal autopsy methods is crucial for accurately determining the causes of deaths occurring at home.
Topics: Humans; Cause of Death; Global Health; Data Collection; Data Accuracy; Income
PubMed: 38046370
DOI: 10.2471/BLT.22.289036 -
Evidence-based Dentistry Mar 2024The search strategy involved three sequential stages. Initially, MEDLINE/PubMed was explored for relevant articles, identifying pertinent terms for formal searching.... (Meta-Analysis)
Meta-Analysis Review
DATA SOURCES
The search strategy involved three sequential stages. Initially, MEDLINE/PubMed was explored for relevant articles, identifying pertinent terms for formal searching. Using the terms ethnic, race, minoritised and dental caries, a strategy was formed and nine databases searched. Finally, hand-searching of reference lists of included articles and sourcing grey literature from relevant government reports, national oral health surveys, and registries which had comparative data for dental caries between racial groups, completed the search.
STUDY SELECTION
Studies included were original primary research which reported dental caries and compared racially minoritised children, aged 5-11 years, to similarly aged from national, majority, or privileged populations. Dental caries had to be recorded from a clinical examination which assessed decayed, missing, and filled teeth (dmft) in primary dentitions. Studies were excluded if they used immigration status as a basis of racial status, or they were a case report, case series, in vitro study, or literature review.
DATA EXTRACTION AND SYNTHESIS
After removing duplicates, two independent researchers screened abstracts, prior to extracting critical data following full-text reviews of included articles. Information collected included study and participant characteristics, definitions of race, and dental caries measurement. The authors of studies which had missing data were contacted, whilst those not written in the English language were translated. Methodological quality of each study was independently assessed by two reviewers using a modified version of the Newcastle-Ottawa scale. All studies were included in the review regardless of quality. A narrative overview of all included studies was conducted. Meta-analyses were completed using studies that reported the mean and standard deviation of the caries outcomes in both groups. Caries outcomes included severity (defined as mean dmft) or prevalence (percentage of teeth with untreated dental caries > 0%). Due to anticipated heterogeneity, statistical analyses approaches such as I statistics were used to estimate between-study variability. Additional sub-group analyses were conducted based on country of study and world income index. Contour-enhanced funnel plots and trim-and-fill analysis were completed to explore potential publication bias. Sensitivity analyses were performed to ensure robustness of the findings.
RESULTS
Seventy-five studies were included from a variety of countries. A higher mean dmft score of 2.30 (0.45, 4.15) and prevalence of decayed teeth (d > 0) was 23% (95% CI: 16, 31) was noted amongst racially minoritised children compared to privileged children's populations. Notable disparities were reported in high-income countries, with minoritised children burdening the greatest distribution of caries incidence. The study faced challenges in consistent racial classification and encountered high heterogeneity in its findings, leading to varied GRADE assessment scores.
CONCLUSIONS
The study calls for global, social, and political changes to tackle the substantial disparities in dental caries among minoritised children to achieve oral health equity.
Topics: Child; Humans; Data Collection; Data Management; Dental Care; Dental Caries; Dental Health Surveys; Child, Preschool
PubMed: 38279035
DOI: 10.1038/s41432-024-00977-w -
Journal of Korean Medical Science Mar 2024Randomized controlled trials (RCTs) and real-world evidence (RWE) studies are crucial and complementary in generating clinical evidence. RCTs provide controlled settings... (Review)
Review
Randomized controlled trials (RCTs) and real-world evidence (RWE) studies are crucial and complementary in generating clinical evidence. RCTs provide controlled settings to validate the clinical effect of specific drugs or medical devices, while RWE integrates extrinsic factors, encompassing external influences affecting real-world scenarios, thus challenging RCT results in practical applications. In this study, we explore the impact of extrinsic factors on RWE outcomes, focusing on "dark data," which refers to data collected but not used or excluded from the analyses. Dark data can arise in many ways during research process, from selecting study samples to data collection and analysis. However, even unused or unanalyzed dark data hold potential insights, providing a comprehensive view of clinical contexts. Extrinsic factors lead to divergent RWE outcomes that could differ from RCTs beyond statistical correction's scope. Two main types of dark data exist: "known-unknown" and "unknown-unknown." The distinction between these dark data types highlights RWE's complexity. The transformation of into depends on data literacy-powerful utilization capabilities that can be interpreted based on medical expertise. Shifting the focus to excluded subjects or unused data in real-world contexts reveals unexplored potential. Understanding the significance of dark data is vital in reflecting the complexity of clinical settings. Connecting RCTs and RWEs requires medical data literacy, enabling clinicians to decipher meaningful insights. In the big data and artificial intelligence era, medical staff must navigate data complexities while promoting the core role of medicine. Prepared clinicians will lead this transformative journey, ensuring data value shapes the medical landscape.
Topics: Humans; Literacy; Biomedical Research; Data Collection
PubMed: 38469965
DOI: 10.3346/jkms.2024.39.e92 -
Sensors (Basel, Switzerland) Feb 2024Livestock's live body dimensions are a pivotal indicator of economic output. Manual measurement is labor-intensive and time-consuming, often eliciting stress responses... (Review)
Review
Livestock's live body dimensions are a pivotal indicator of economic output. Manual measurement is labor-intensive and time-consuming, often eliciting stress responses in the livestock. With the advancement of computer technology, the techniques for livestock live body dimension measurement have progressed rapidly, yielding significant research achievements. This paper presents a comprehensive review of the recent advancements in livestock live body dimension measurement, emphasizing the crucial role of computer-vision-based sensors. The discussion covers three main aspects: sensing data acquisition, sensing data processing, and sensing data analysis. The common techniques and measurement procedures in, and the current research status of, live body dimension measurement are introduced, along with a comparative analysis of their respective merits and drawbacks. Livestock data acquisition is the initial phase of live body dimension measurement, where sensors are employed as data collection equipment to obtain information conducive to precise measurements. Subsequently, the acquired data undergo processing, leveraging techniques such as 3D vision technology, computer graphics, image processing, and deep learning to calculate the measurements accurately. Lastly, this paper addresses the existing challenges within the domain of livestock live body dimension measurement in the livestock industry, highlighting the potential contributions of computer-vision-based sensors. Moreover, it predicts the potential development trends in the realm of high-throughput live body dimension measurement techniques for livestock.
Topics: Animals; Livestock; Computers; Image Processing, Computer-Assisted; Surveys and Questionnaires; Industry
PubMed: 38475040
DOI: 10.3390/s24051504 -
Vaccine Mar 2024The U.S. Centers for Disease Control and Prevention (CDC) developed and implemented the CDC COVID-19 Vaccine Pregnancy Registry (C19VPR) to monitor vaccine safety.... (Review)
Review
The U.S. Centers for Disease Control and Prevention (CDC) developed and implemented the CDC COVID-19 Vaccine Pregnancy Registry (C19VPR) to monitor vaccine safety. Potential participants who received a COVID-19 vaccine in pregnancy or up to 30 days prior to their pregnancy-associated last menstrual period were eligible to participate in the registry, which monitored health outcomes of participants and their infants through phone interviews and review of available medical records. Data for select outcomes, including birth defects, were reviewed by clinicians. In certain cases, medical records were used to confirm and add detail to participant-reported health conditions. This paper serves as a description of CDC C19VPR protocol. We describe the development and implementation for each data collection aspect of the registry (i.e., participant phone interviews, clinical review, and medical record abstraction), data management, and strengths and limitations. We also describe the demographics and vaccinations received among eligible and enrolled participants. There were 123,609 potential participants 18-54 years of age identified from January 2021 through mid-June 2021; 23,339 were eligible and enrolled into the registry. Among these, 85.3 % consented to medical record review for themselves and/or their infants. Participants were majority non-Hispanic White (79.1 %), residents of urban areas (93.3 %), and 48.3 % were between 30 and 34 years of age. Most participants completed the primary series of vaccination by the end of pregnancy (89.7 %). Many participants were healthcare personnel (44.8 %), possibly due to the phased roll-out of the vaccination program. The registry continues to provide important information about the safety of COVID-19 vaccination among pregnant people, a population with higher risk of poor outcomes from COVID-19 who were not included in pre-authorization clinical trials. Lessons learned from the registry may guide development and implementation of future vaccine safety monitoring efforts for pregnant people and their infants.
Topics: Female; Humans; Infant; Pregnancy; Centers for Disease Control and Prevention, U.S.; COVID-19; COVID-19 Vaccines; Data Collection; Registries; United States; Vaccination; Vaccines; Adolescent; Young Adult; Adult; Middle Aged
PubMed: 38057207
DOI: 10.1016/j.vaccine.2023.11.061 -
Euro Surveillance : Bulletin Europeen... Nov 2023Many organisations struggle to keep pace with public health evidence due to the volume of published literature and length of time it takes to conduct literature reviews.... (Review)
Review
Many organisations struggle to keep pace with public health evidence due to the volume of published literature and length of time it takes to conduct literature reviews. New technologies that help automate parts of the evidence synthesis process can help conduct reviews more quickly and efficiently to better provide up-to-date evidence for public health decision making. To date, automated approaches have seldom been used in public health due to significant barriers to their adoption. In this Perspective, we reflect on the findings of a study exploring experiences of adopting automated technologies to conduct evidence reviews within the public health sector. The study, funded by the European Centre for Disease Prevention and Control, consisted of a literature review and qualitative data collection from public health organisations and researchers in the field. We specifically focus on outlining the challenges associated with the adoption of automated approaches and potential solutions and actions that can be taken to mitigate these. We explore these in relation to actions that can be taken by tool developers (e.g. improving tool performance and transparency), public health organisations (e.g. developing staff skills, encouraging collaboration) and funding bodies/the wider research system (e.g. researchers, funding bodies, academic publishers and scholarly journals).
Topics: Humans; Public Health; Data Collection
PubMed: 37943502
DOI: 10.2807/1560-7917.ES.2023.28.45.2300183