Ascertainment Bias Research Articles

Testing magnetic tracers as indicators of sediment transport in a wave flume experiment

AbstractThe in situ measurement of sediment transport in wave‐dominated environments presents significant challenges and currently often relies upon the use of fluorescent sediment tracers. However, this method is constrained by challenges in conducting unbiased and representative sampling, as well as facing overall logistical complexities and labour‐intensive procedures. Whilst other tracer techniques are available, such as using magnetic tracers, their performance in tracking sediment transport has not been quantified. The objective of this study is to assess the effectiveness of magnetic tracers in evaluating net transport rates and tracer dispersal patterns. Conducted in a controlled large wave flume, the experiments simultaneously employed fluorescent and magnetic tracers, allowing a comprehensive comparison of the tracers' dispersion patterns and the net transport rates. Results show that the dispersal of magnetic and fluorescent tracers displays a high degree of spatial coherence in both horizontal and vertical dimensions. Similarly, net transport rates are comparable (<16% difference), both showing net transport in the direction of the wave propagation (towards onshore) driven by non‐linear and streaming effects. Magnetic tracer recovery rate (49%) was lower than for fluorescent tracers (73%) and is attributed to the loss of magnetic ink from particles; an aspect of the magnetic technique that requires improvement. This study therefore indicates that the use of magnetic tracers to quantify sediment transport is an effective method with the advantages of being significantly less labour‐intensive than using the commonly applied fluorescent sediment tracer method.

Evidence of population genetic structure in Ecuadorian Andean bears

Wildlife conservation in Andean countries is a global priority because of the high levels of biodiversity and endemism. Historically, these countries have had limited resources to monitor wildlife (e.g., through genetic tools) and establish conservation programs. Focusing on the study and emblematic use of a few charismatic species has been a strategic approach to direct efforts for conservation and development planning. Consequently, the Andean bear is a flagship and umbrella species for highly biodiverse Andean countries like Ecuador. The few studies exploring the population genetics of this species have concluded that it has low genetic diversity and few units for conservation as populations appear to be well connected. However, these results might be attributed to ascertainment bias as studies have been performed with heterologous molecular markers. Here, using both mtDNA sequences and species-specific microsatellite markers, we show that Andean bears in Ecuador have population structure. Additionally, we found through the study of three Ecuadorian populations that the species might have a higher genetic diversity than we previously thought. These results could support the revision of research priorities, conservation, and planning strategies to improve connectivity for this species which occurs in crucial biodiversity hotspots.

OP11 Exploring the potential clinical utility of NUDT15 pharmacogenetic testing in clinical practice: a ‘focused reverse phenotyping’ study in the UK IBD Bioresource

Abstract Background In a previous study we recruited patients with inflammatory bowel disease (IBD) and a history of thiopurine induced myelosuppression (TIM) and identified associated variants in NUDT15. This widely used phenotype-first approach, is limited by ascertainment and recall bias, which impacts understanding of penetrance, expressivity, and variant pathogenicity that are key to clinical implementation. The United Kingdom (UK) National Institute for Health Research (NIHR) IBD Bioresource allows investigators to select large numbers of subjects based on genomic variants of interest, rather than phenotypes, to overcome these biases. Using this ‘focused reverse phenotyping’ approach we sought to investigate the cumulative 6-month risk of myelosuppression in patients with NUDT15 variants. Methods Cases and controls were identified from whole exome sequencing data. Cases included all participants with a loss of function NUDT15 variant (*2, *3, *4, *5, *6 and *9). Control subjects were selected based on wild-type carriage of NUDT15 and TPMT, matched for ethnicity. Our primary outcome measure was time to TIM. Myelosuppression was defined as a white cell count (WCC) <3.5x109/L or a neutrophil count <2.0x109/L that occurred within six months of achieving the maximum thiopurine dose, or in the absence of blood test results, a decision to reduce the dose of or withdraw the thiopurine due to myelosuppression. Severe myelosuppression was defined as a WCC <2.5x109/L or neutrophil count <1.0x109/L and a decision to either reduce the dose of or stop the thiopurine. Results We screened 23,082 patients recruited to the UK NIHR IBD bioresource with whole exome sequence data and identified 451 patients with a loss of function NUDT15 variant. We matched, based on ethnicity, these patients to 916 controls. Overall, 271/21,136 (1.3%) Caucasians and 127/1,089 (11.7%) South Asian carried an NUDT15 variant allele. 239/451 (60%) cases had a history of thiopurine exposure. The median weight-adjusted maximum thiopurine dose amongst cases and controls was 1.78 and 1.79 mg/kg/day, respectively. The time to myelosuppression was shorter in patients with NUDT15 variants as shown in Figure 1. The risk of myelosuppression, severe myelosuppression, and hospitalisation was also higher in patients with NUDT15 variants as shown in table 1. Conclusion In this reverse phenotyping study, the time to myelosuppression was significantly shorter in patients who carried a loss of function NUDT15 variant. The overall risk of myelosuppression was lower than previously observed in phenotype-first studies. Prior to implementation further analysis of the cost-effectiveness of NUDT15 testing is required.

A 3D urban scene reconstruction enhancement approach based on adaptive viewpoint selection of panoramic videos

AbstractThe widely used unmanned aerial vehicle oblique photogrammetry often suffers from information loss in complex urban environments, leading to geometric and textural defects in the resulting models. In this study, a close‐range panoramic optimal viewpoint selection assisted 3D urban scene reconstruction enhancement method is proposed for areas prone to defects. We first introduce the ground panoramic data acquisition equipment and strategy, which are different from those of the single‐lens supplementary photography method. Data acquisition is accomplished through a single and continuous surround‐style collection approach. The full coverage of the panoramic video in the space–time dimension enables the acquisition of texture details without considering camera station planning. Then, a panoramic multiview image generation approach is proposed. Adaptive viewpoint selection is achieved using unbiased sampling points from the rough scene model, and viewpoint optimisation is adopted to ensure sufficient image overlap and intersection effects, thus improving the scene reconstructability. Finally, the 3D model is generated by photogrammetric processing of the panoramic multiview images, resulting in an enhanced modelling effect. To validate the proposed method, we conducted experiments using real data from Qingdao, China. Both the qualitative and quantitative results demonstrate a significant improvement in the quality of geometric and textural reconstruction. The tie‐point reprojection errors are less than 1 pixel, and the registration accuracy with the model from oblique photogrammetry is comparable to that of optimised‐view photography. By eliminating the need for on‐site camera station planning or manual flight operations and effectively minimising the redundancy of panoramic videos, our approach significantly reduces the photography and computation costs associated with reconstruction enhancement. Thus, it presents a feasible technical solution for the generation of urban 3D fine models.

REVAMPING TRADITION WITH TECH: GUIDING INNOVATION IN ZAKAT FOR SOCIAL GOOD

As a pillar of Islam, zakat holds profound meaning and socioeconomic significance. However, oversight deficiencies have constrained its capacity for poverty alleviation. This paper explores emerging technologies - including blockchain, artificial intelligence, and mobile platforms - to strengthen zakat management. Through a qualitative literature review, we examine the digital transformation of zakat systems. We argue for cautious technology adoption to enhance transparency, efficiency, and inclusivity while aligning with Islamic ethics. Guiding principles grounded in maqasid al-shariah are offered, emphasizing human discretion and oversight. While risks around exclusion, security, and algorithmic bias necessitate vigilance, thoughtfully implemented technology can optimize zakat distribution and amplify impact. By leveraging innovation to uphold foundational values, zakat can fulfil its noble obligations of uplifting communities and promoting social justice.

Estimates of congenital cytomegalovirus-attributable infant mortality in high-income countries: A review.

As many as 5%-10% of infants with symptomatic congenital cytomegalovirus (cCMV) disease, or 0.4%-0.8% of all liveborn infants with cCMV infection, die in early infancy in high-income countries. However, estimates are uncertain due to several potential biases that can result from data limitations and study designs. First, infants with cCMV infections who die prior to diagnosis, which usually occurs at 1-4weeks after birth, may be excluded from both the count of deaths and the denominator of cCMV births, resulting in left truncation and immortal time biases. These 'biases' are features of the data and do not reflect bias on the part of researchers, but understanding the potential existence of threats to validity can help with interpretation of findings. Left truncation of infant deaths occurring prior to diagnosis of cCMV can result in understatement of the burden of infant deaths due to cCMV. Conversely, overestimation of infant deaths associated with symptomatic cCMV may occur in clinical case series owing to greater representation of relatively severely affected infants owing to ascertainment and referral biases. In this review, we summarise the characteristics of 26 studies that reported estimates of cCMV-associated infant deaths, including potential biases or limitations to which those estimates may have been subject. We discuss study designs whose implementation might generate improved estimates of infant deaths attributable to cCMV. More complete estimates of the overall public health impact of cCMV could inform current and future screening, prevention, and vaccine research.

Ascertainment Bias in the Genomic Test of Positive Selection on Regulatory Sequences.

Evolution of gene expression mediated by cis-regulatory changes is thought to be an important contributor to organismal adaptation, but identifying adaptive cis-regulatory changes is challenging due to the difficulty in knowing the expectation under no positive selection. A new approach for detecting positive selection on transcription factor binding sites (TFBSs) was recently developed, thanks to the application of machine learning in predicting transcription factor (TF) binding affinities of DNA sequences. Given a TFBS sequence from a focal species and the corresponding inferred ancestral sequence that differs from the former at n sites, one can predict the TF-binding affinities of many n-step mutational neighbors of the ancestral sequence and obtain a null distribution of the derived binding affinity, which allows testing whether the binding affinity of the real derived sequence deviates significantly from the null distribution. Applying this test genomically to all experimentally identified binding sites of 3 TFs in humans, a recent study reported positive selection for elevated binding affinities of TFBSs. Here, we show that this genomic test suffers from an ascertainment bias because, even in the absence of positive selection for strengthened binding, the binding affinities of known human TFBSs are more likely to have increased than decreased in evolution. We demonstrate by computer simulation that this bias inflates the false positive rate of the selection test. We propose several methods to mitigate the ascertainment bias and show that almost all previously reported positive selection signals disappear when these methods are applied.

Cancer Risk in Patients with Gaucher Disease Using Real-World Data.

The association between GD and cancer has been uncertain due to ascertainment bias in previously published studies. We analyzed cancer incidence using the Maccabi Healthcare Service (MHS) electronic health records among 264 patients with GD compared to 3440 matched controls. We ascertained cancers diagnosed before and after the index date (i.e., the first documentation of GD in cases and the corresponding date for controls). Before the index date, cancers were diagnosed in 18 individuals, with 11 (4.2%) in the GD group and 7 (0.2%) in the control group. After the index date, cancers were diagnosed in 57 individuals, with 20 (7.9%) in the GD group and 37 (1.1%) in the control group, with a median follow-up of almost 13 years in both groups. The most common cancers diagnosed in GD were non-melanoma skin cancer (NMSC) and hematological malignancies, with a clustering of diagnoses around the time of GD diagnosis. The incidence of cancers (excluding MNSC) was 4.1 (95% CI 2.2-7.1) and 0.7 (95% CI 0.4-0.9) per 1000 patient-years in the GD and control groups, respectively, with an incidence rate ratio of 6.37 (95% CI 3-12.7). Patients with GD underwent more cancer screening tests than their counterparts in the control group. While our study revealed an increased occurrence of cancers in patients with GD, this finding might be partly attributed to the more rigorous surveillance procedures employed in this patient population.

Epidemiology and Clinical Outcomes of Community-Acquired Acute Kidney Injury in the Emergency Department: A Multisite Retrospective Cohort Study

The prevalence of community-acquired acute kidney injury (CA-AKI) in the United States and its clinical consequences are not well described. Our objective was to describe the epidemiology of CA-AKI and the associated clinical outcomes. Retrospective cohort study. 178,927 encounters by 139,632 adults at 5 US emergency departments (EDs) between July 1, 2017, and December 31,2022. CA-AKI identified using KDIGO (Kidney Disease: Improving Global Outcomes) serum creatinine (Scr)-based criteria. For encounters resulting in hospitalization, the in-hospital trajectory of AKI severity, dialysis initiation, intensive care unit (ICU) admission, and death. For all encounters, occurrence over 180 days of hospitalization, ICU admission, new or progressive chronic kidney disease, dialysis initiation, and death. Multivariable logistic regression analysis to test the association between CA-AKI and measured outcomes. For all encounters, 10.4% of patients met the criteria for any stage of AKI on arrival to the ED. 16.6% of patients admitted to the hospital from the ED had CA-AKI on arrival to the ED. The likelihood of AKI recovery was inversely related to CA-AKI stage on arrival to the ED. Among encounters for hospitalized patients, CA-AKI was associated with in-hospital dialysis initiation (OR, 6.2; 95% CI, 5.1-7.5), ICU admission (OR, 1.9; 95% CI, 1.7-2.0), and death (OR, 2.2; 95% CI, 2.0-2.5) compared with patients without CA-AKI. Among all encounters, CA-AKI was associated with new or progressive chronic kidney disease (OR, 6.0; 95% CI, 5.6-6.4), dialysis initiation (OR, 5.1; 95% CI, 4.5-5.7), subsequent hospitalization (OR, 1.1; 95% CI, 1.1-1.2) including ICU admission (OR, 1.2; 95% CI, 1.1-1.4), and death (OR, 1.6; 95% CI, 1.5-1.7) during the subsequent 180 days. Residual confounding. Study implemented at a single university-based health system. Potential selection bias related to exclusion of patients without an available baseline Scr measurement. Potential ascertainment bias related to limited repeat Scr data during follow-up after an ED visit. CA-AKI is a common and important entity that is associated with serious adverse clinical consequences during the 6-month period after diagnosis. Acute kidney injury (AKI) is a condition characterized by a rapid decline in kidney function. There are many causes of AKI, but few studies have examined how often AKI is already present when patients first arrive to an emergency department seeking medical attention for any reason. We analyzed approximately 175,000 visits to Johns Hopkins emergency departments and found that AKI is common on presentation to the emergency department and that patients with AKI have increased risks of hospitalization, intensive care unit admission, development of chronic kidney disease, requirement of dialysis, and death in the first 6 months after diagnosis. AKI is an important condition for health care professionals to recognize and is associated with serious adverse outcomes.

Are patients with primary glomerular disease at increased risk of malignancy?

Over the past decade, several observational studies and case series have provided evidence suggesting a connection between glomerular diseases and the development of malignancies, with an estimated risk ranging from 5 to 11%. These malignancies include solid organ tumours as well as haematologic malignancies such as lymphoma and leukaemia. However, these risk estimates are subject to several sources of bias, including unmeasured confounding from inadequate exploration of risk factors, inclusion of glomerular disease cases that were potentially secondary to an underlying malignancy, misclassification of glomerular disease type and ascertainment bias arising from an increased likelihood of physician encounters compared with the general population. Consequently, population-based studies that accurately evaluate the cancer risk in glomerular disease populations are lacking. While it is speculated that long-term use of immunosuppressive medications and glomerular disease activity measured by proteinuria and estimated glomerular filtration rate may be associated with cancer risk in patients with glomerular disease, the independent role of these risk factors remains largely unknown. The presence of these knowledge gaps could lead to a lack of awareness of cancer as a potential chronic complication of glomerular disease, underutilization of routine screening practices in clinical care that allow early diagnosis and treatment of malignancies and underrecognition of modifiable risk factors to decrease the risk of de novo malignancies over time. This review summarizes the current evidence on the risk of cancer in patients with glomerular diseases, explores the limitations of prior studies and discusses methodological challenges and potential solutions for obtaining accurate estimates of cancer risk and identifying modifiable risk factors unique to GN populations.

Utility of accessible neuroimaging markers of cerebrovascular disease in identifying cerebral amyloidosis across the Alzheimer’s disease spectrum

AbstractBackgroundAlzheimer’s disease (AD) is defined by the presence of cognitive impairment and cerebral amyloidosis and is associated with several cerebrovascular disease (CVD) risk factors including age, apolipoprotein‐E ε4 (APOE‐ε4) genotype, hypertension, diabetes and hyperlipidemia. Despite this association, the clinical utility of individual CVD biomarkers in screening for AD pathology is understudied. Therefore, we sought to examine the relationship between cerebral amyloidosis and magnetic resonance imaging (MRI)‐based CVD measures, including cerebral microbleeds, ischemic infarction, and white matter hyperintensities (WMH). We hypothesized that CVD biomarker burden would be positively associated with amyloidosis. Given recent studies have shown plasma phospho‐tau181 (P‐tau181) is a promising early biomarker of amyloidosis, we further hypothesized that combining P‐tau181 with CVD biomarkers would predict amyloid status in cognitively unimpaired and impaired persons.MethodParticipant data were extracted from the Alzheimer’s Disease Neuroimaging Initiative database (N = 1,430). Volumetric data (WMH volume [WMHv], medial temporal lobe volume [MTLv]) were normalized and log‐transformed. Adjusted odds ratio (OR) was calculated using logistic regression with dichotomized amyloid‐PET status as the outcome. Area under the curve (AUC) was compared by the likelihood ratio test.ResultAfter adjustment for age, sex, APOE‐ε4 status, MTLv, cognition (MoCA), and other CVD biomarkers of interest, we found that WMHv alone was significantly associated with amyloidosis in both cognitively impaired (OR = 1.21) and unimpaired (OR = 1.25) persons. We then developed an accessible diagnostic model incorporating WMHv, significant covariates and plasma P‐tau181. Addition of P‐tau181 to the model improved diagnostic accuracy in cognitively impaired persons (AUC = 0.85 to 0.87, p < 0.001), and did not attenuate the relationship between WMHv and amyloidosis.ConclusionWe newly identify WMH, but not other CVD lesions, as predictive of amyloidosis in both preclinical and symptomatic AD. The current study adds to the literature regarding which CVD biomarkers are most predictive of AD pathology. Measurement of WMH alongside P‐tau181 and other biomarkers may produce an accessible screening algorithm for AD. Study generalizability is limited by ascertainment bias and lack of diversity. Future research will compare the performance of WMH to standard AD biomarkers in a more diverse, community‐based sample.

Improving estimates of pertussis burden in Ontario, Canada 2010-2017 by combining validation and capture-recapture methodologies.

An underestimation of pertussis burden has impeded understanding of transmission and disallows effective policy and prevention to be prioritized and enacted. Capture-recapture analyses can improve burden estimates; however, uncertainty remains around incorporating health administrative data due to accuracy limitations. The aim of this study is to explore the impact of pertussis case definitions and data accuracy on capture-recapture estimates. We used a dataset from March 7, 2010 to December 31, 2017 comprised of pertussis case report, laboratory, and health administrative data. We compared Chao capture-recapture abundance estimates using prevalence, incidence, and adjusted false positive case definitions. The latter was developed by removing the proportion of false positive physician billing code-only case episodes after validation. We calculated sensitivity by dividing the number of observed cases by abundance. Abundance estimates demonstrated that a high proportion of cases were missed by all sources. Under the primary analysis, the highest sensitivity of 78.5% (95% CI 76.2-80.9%) for those less than one year of age was obtained using all sources after adjusting for false positives, which dropped to 43.1% (95% CI 42.4-43.8%) for those one year of age or older. Most code-only episodes were false positives (91.0%), leading to considerably lower abundance estimates and improvements in laboratory testing and case report sensitivity using this definition. Accuracy limitations can be accounted for in capture-recapture analyses using different case definitions and adjustment. The latter enhanced the validity of estimates, furthering the utility of capture-recapture methods to epidemiological research. Findings demonstrated that all sources consistently fail to detect pertussis cases. This is differential by age, suggesting ascertainment and testing bias. Results demonstrate the value of incorporating real time health administrative data into public health surveillance if accuracy limitations can be addressed.

Demographic Disparities in Clinical Trial Enrollment of US Patients with Newly-Diagnosed Multiple Myeloma

Background: Racial, ethnic and gender disparities impact the real-world reproducibility of clinical trials leading to drug approvals for hematologic malignancies. Interestingly, a prior abstract (Boisclair et al., 2022) has shown an equitable enrollment between US demographic groups in frontline trials for newly-diagnosed non-Hodgkin lymphoma. Although disparities in multiple myeloma (MM) trial participation have been oftentimes demonstrated, prior studies (Kanapuru et al., 2022; Alqazaqi et al., 2022) predominantly involved patients with relapsed/refractory MM (RRMM). To further assess this gap, we conducted a cross-sectional analysis of US demographic representation in phase II or III trials for newly-diagnosed MM (NDMM). Methods: Clinicaltrials.gov was searched for completed NDMM trials with a recruitment period between 01/01/2007-12/31/2020. Studies limited to phase I data (n=10), enrolling <30 patients (n=35), including RRMM or other malignancies (n=18), and/or recruiting outside the US (n=93) were excluded. We subdivided patients according to gender, race, and ethnicity. For each subgroup, total new cases of MM from 2007-2020 were identified via the Surveillance, Epidemiology and End Results (SEER) Cancer Statistics Explorer Network, with subsequent calculation of a trial enrollment fraction (TEF; number of trial enrollees divided by incident US cases). Pearson's chi-square test was used to compare TEF between subgroups, yielding odds ratio (OR) and 95% confidence interval (95%CI) values, with P<0.05 deemed significant. Results: Among the 194 trials found on initial review, 25 met the established criteria for inclusion (Figure 1). All studies (n=3,559) described the participants' gender, while only 18 (72%; n=3,129) reported race and 9 (36%; n=2,319) reported ethnicity. Overall, women showed a significantly lower TEF compared to men (OR, 0.88; 95%CI, 0.82-0.94; P<0.001). When compared to White Americans, TEF was significantly lower for African Americans (OR, 0.71; 95%CI, 0.64-0.78; P<0.001) and Asian Americans/Pacific Islanders (AAPIs; OR, 0.64; 95%CI, 0.22-0.41; P<0.001). In studies reporting ethnicity, TEF was significantly lower for Hispanics compared to non-Hispanics (OR, 0.18; 95%CI, 0.14-0.24; P<0.001). Conclusion: Our cross-sectional analysis reveals an underrepresentation of women, African Americans, AAPIs, and Hispanics in NDMM trials conducted around the US. These findings are complementary to the enrollment disparities previously shown in RRMM trials. Through the implementation of a comprehensive diversity plan, MM trials must include a more inclusive representation of the US population affected by this blood cancer. Such an approach will not only enhance the external validity of these trials but also mitigate the impact of ascertainment bias and promote healthcare equity.

Cancer Risk in Patients with Gaucher Disease Using Real-World Data

Gaucher disease (GD), a rare autosomal recessive disorder, is characterized by the deficiency of the lysosomal enzyme β-glucocerebrosidase, leading to the accumulation of glucosylceramide in macrophages throughout the body. Accordingly, the primary disease features are hepatosplenomegaly, hypersplenism, anemia, thrombocytopenia, and bone involvement. There are three types of GD, with a combined estimated occurrence ranging from 0.45 to 25.0 per 100,000 live births. However, among individuals with Ashkenazi Jewish heritage, type 1 GD is considerably more prevalent, with an estimated occurrence of 1 in 850 live births. Considerable controversy exists regarding the co-occurrence and risk of other diseases in patients with GD compared to the general population, GD-related and GD-unrelated, respectively. While Parkinson disease and cholelithiasis are clear examples of GD-related co-morbidities, there is uncertainty regarding the association between GD and cancer, a topic that raises great concern for patients and their families. The aim of the current study was to evaluate the risk of cancer in patients pre- and post- diagnosis of GD compared to a group of matched controls in a population-based comprehensive clinical database. This study utilized electronic health records from the Maccabi Healthcare Service (MHS), Israel's second-largest health maintenance organization, to study cancer risk in 264 patients with GD compared to 3441 controls matched by sex, year of birth, and socioeconomic status (SES). Cancer diagnoses were extracted from the MHS cancer register, which captures all cancer types, updated until January 31, 2021. Additional data extracted included ICD-9 codes for family history of cancer, smoking, splenectomy, the use of Gaucher-specific medication, and MHS codes for colonoscopy, mammography, occult blood in stool, Papanicolaou (PAP) smear, prostate-specific antigen (PSA), and skin screen. We analyzed cancer occurrence before and after the index date for GD diagnosis (i.e., the first documentation of GD in the MHS database). For the controls, the index date used was the index date for the GD diagnosis of the matched patient. The study design received approval from the MHS Institutional Review Board. Patient consent was waived since aggregated, de-identified, and anonymized data were utilized Cancer was diagnosed in 18 individuals before the index date; 11 (4.2%) in GD compared to 7 (0.2%) in controls (p< 0.001). The main types of cancers in patients with GD were non-melanoma skin and hematological cancers, with clustering of the diagnoses around the time of GD diagnosis. Cancer was diagnosed in 57 individuals (20 (7.9%) in GD and 37 (1.1%) in control) after the index data, with a median follow-up of almost 13 years (Table). Patients with GD had a significantly higher risk of developing cancer than controls (Figure). The age and sex-adjusted incidence of cancer (excluding non-melanoma skin cancer) was 4.1 (95% CI 1.9-6.4) per 1,000 patients-years in patients with GD compared to 0.65 (95% CI 0.4-0.9) per 1,000 patients-years in controls, with an incidence rate ratio of 6.4. The median (range) age at cancer diagnosis was 62 (36-79) and 46 (26.5-91) years in patients with GD and controls, respectively (p=0.02). Multiple primary tumors were reported in four patients with GD but none in controls. Patients with GD underwent more cancer screening tests, e.g., colonoscopy, prostate-specific antigen, and skin screening, compared to controls. No difference in the rate of family history of cancer or smoking between patients with GD and controls. In a multivariate analysis among patients with GD, including age, sex, SES, the use of Gaucher-specific medication, and splenectomy, age was the only risk factor for cancer. The primary significance of this matched case-control study is that it addresses the cohort/selection bias present in previous reports regarding the potentially heightened cancer risk among individuals with GD, where compression of rates was done with non-matched cohorts. We herein show that the increased occurrence of cancer in patients with GD can be attributed partly to a more rigorous surveillance approach and frequent screening. However, the higher rates of cancers without early detection measures, such as multiple myeloma, indicate that there is indeed an elevated risk of developing cancer in individuals with GD that is not related to an ascertainment bias.

Validating pertussis data measures using electronic medical record data in Ontario, Canada 1986–2016

BackgroundPertussis is a reportable disease in many countries, but ascertainment bias has limited data accuracy. This study aims to validate pertussis data measures using a reference standard that incorporates different suspected case severities, allowing for the impact of case severity on accuracy and detection to be explored. MethodsWe evaluated 25 pertussis detection algorithms in a primary care electronic medical record database between January 1, 1986 and December 30, 2016. We estimated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). We used sensitivity analyses to explore areas of uncertainty and evaluated reasons for lack of detection. ResultsThe algorithm including all data measures achieved the highest sensitivity at 20.6%. Sensitivity increased to 100% after reclassifying symptom-only cases as non-cases, but the PPV remained low. Age at first episode was significantly associated with detection in half of the tested scenarios, and false negatives often had some history of immunization. ConclusionsSensitivity improved by reclassifying symptom-only cases but remained low unless multiple data sources were used. Results demonstrate a trade-off between PPV and sensitivity. EMRs can enhance detection through patient history and clinical note data. It is essential to improve case identification of older individuals with vaccination history to reduce ascertainment bias.

Efektivitas Media Teka-Teki Silang Terhadap Penguasaan Kosakata Bahasa Jepang Siswa SMA

This study was inspired by the researcher's observation that pupils struggle to learn and remember Japanese terminology. The goal of this research was to examine the impact of crossword media on high school students' ability to learn Japanese vocabulary. This study employed a quantitative approach and a Pre Experimental Design for its investigation. The study employed a pre- and post-test design with a single group. Twenty-five students from IPS 1 in Grade 12 made up the study's sample. This research employed a systematic, unbiased sampling strategy. The information in this study comes from before and after examinations. The method of information gathering is a multiple-choice test with as many as 30 questions. The results of the Paired Samples T-Test show that the crossword game medium is significantly effective on the Japanese vocabulary mastery of students in class XII at IPS 1 SMAN 13 Padang, with a sig (2-tailed) value of 0.000 < 0.05. Additionally, pupils improved their Japanese vocabulary knowledge after utilising crossword puzzles as a learning tool. The average score before the test was 70.76, thus this boost from that to 83.32 is clear.

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England.

Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions. We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results. Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

Does artificial light at night alter moth community composition?

Ecological studies investigating the effects of artificial light at night (ALAN) have primarily focused on single or a few species, and seldom on community-level dynamics. As ALAN is a potential cause of insect and biodiversity declines, community-level perspectives are essential. We empirically tested the hypothesis that moth species differentially respond to ALAN and that these responses can cause shifts in community composition. We sampled moths from prairie fragments in Colorado, USA. We tested whether local light sources, sky glow, site area and/or vegetation affected moth community diversity. We found that increased sky glow decreased moth abundance and species richness and shifted community composition. Increased sky glow shifted moth community composition when light and bait traps were combined; notably this result appears to be driven entirely by moths sampled at bait traps, which is an unbiased sampling technique. Our results show that ALAN has significant effects on moth communities and that local light sources have contrasting effects on moth community composition compared to sky glow. It is imperative that we better understand the contrasting effects of types of ALAN to comprehend the overall impacts of light pollution on biodiversity declines. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Using a severity threshold to improve occupational injury surveillance: Assessment of a severe traumatic injury-based occupational health indicator across the International Classification of Diseases lexicon transition.

Traumatic injury is a leading cause of death and disability among USworkers. Severe injuries are less subject to systematic ascertainment bias related to factors such as reporting barriers, inpatient admission criteria, and workers' compensation coverage. A state-based occupational health indicator (OHI #22) was initiated in 2012 to track work-related severe traumatic injury hospitalizations. After 2015, OHI #22 was reformulated to account for the transition from the International Classification of Diseases, 9thRevision, Clinical Modification (ICD-9-CM) to ICD-10-CM. This study describes rates and trends in OHI #22, alongside corresponding metrics for all work-related hospitalizations. Seventeen states used hospital discharge data to calculate estimates for calendar years 2012-2019. State-panel fixed-effects regression was used to model linear trends in annual work-related hospitalization rates, OHI #22 rates, and the proportion of work-related hospitalizations resulting from severe injuries. Models included calendar year and pre- to post-ICD-10-CM transition. Work-related hospitalization rates showed a decreasing monotonic trend, with no significant change associated with the ICD-10-CM transition. In contrast, OHI #22 rates showed a monotonic increasing trend from 2012 to 2014, then a significant 50% drop, returning to a near-monotonic increasing trend from 2016 to 2019. On average, OHI #22 accounted for 12.9% of work-related hospitalizations before the ICD-10-CM transition, versus 9.1% post-transition. Although hospital discharge data suggest decreasing work-related hospitalizations over time, work-related severe traumatic injury hospitalizations are apparently increasing. OHI #22 contributes meaningfully to state occupational health surveillance efforts by reducing the impact of factors that differentially obscure minor injuries; however, OHI #22 trend estimates must account for the ICD-10-CM transition-associated structural break in 2015.

Vendi sampling for molecular simulations: Diversity as a force for faster convergence and better exploration.

Molecular dynamics (MD) is the method of choice for understanding the structure, function, and interactions of molecules. However, MD simulations are limited by the strong metastability of many molecules, which traps them in a single conformation basin for an extended amount of time. Enhanced sampling techniques, such as metadynamics and replica exchange, have been developed to overcome this limitation and accelerate the exploration of complex free energy landscapes. In this paper, we propose Vendi Sampling, a replica-based algorithm for increasing the efficiency and efficacy of the exploration of molecular conformation spaces. In Vendi sampling, replicas are simulated in parallel and coupled via a global statistical measure, the Vendi Score, to enhance diversity. Vendi sampling allows for the recovery of unbiased sampling statistics and dramatically improves sampling efficiency. We demonstrate the effectiveness of Vendi sampling in improving molecular dynamics simulations by showing significant improvements in coverage and mixing between metastable states and convergence of free energy estimates for four common benchmarks, including Alanine Dipeptide and Chignolin.