Analysis Of Routine Data Research Articles

Creating opportunities out of challenges: assessment of adaptations to maintain uninterrupted access to antiretroviral therapy for HIV clients in West Africa during the first year of the COVID-19 pandemic

Background The COVID-19 pandemic imposed challenges to HIV service provision in Africa. The Ending AIDS in West Africa project (#EAWA), implemented in Burkina Faso and Togo, took measures to mitigate service provision disruptions due to COVID-19. We document the project’s strategies for ensuring an uninterrupted service provision to people living with HIV (PLHIV) during the COVID-19 pandemic. Methods Using reports from project staff, we summarized #EAWA’s service provision strategies during the pandemic. This finding was complemented by a descriptive analysis of routine program data collected from December 2019 to April 2021 to evaluate how well these measures performed. Results COVID-19-related travel restrictions, lockdowns, logistical challenges, and fear of health facilities restricted access to HIV care. Building on shifting policy environments in both countries, #EAWA adopted a contingency plan to accelerate the multi-month dispensing of ARVs (MMD) and differentiated drug delivery (DDD). Quantitative results show that the pandemic briefly disrupted ARV refills and MMD dispensation. The implementation of EAWA’s contingency plan corresponded to a rapid increase in drug refills and MMD in both countries. Conclusions Examination of programmatic data from this HIV program shows that COVID-19 provided the impetus to embrace MMD to ensure continuity of care. Despite an extremely challenging and shifting environment, the #EAWA project was able to respond nimbly to ensure clients stayed on treatment.

Homelessness and associated factors over a 13-year period among psychiatric inpatients in Berlin, Germany - A routine data analysis - CORRIGENDUM.

Homelessness and associated factors over a 13-year period among psychiatric inpatients in Berlin, Germany - A routine data analysis - CORRIGENDUM.

Are temporal trends in retained foreign object rates after surgery in Switzerland impacted by increasing coding intensity? A retrospective analysis of hospital routine data from 2000 to 2019

ObjectivesRetained foreign objects (RFOs) after surgery can cause harm to patients and negatively impact clinician and hospital reputation. RFO incidence based on administrative data is used as a metric of...

Implementation of flash glucose monitoring in four pediatric diabetes clinics: controlled before and after study to produce real-world evidence of patient benefit

AimsTo assess the real-world evidence for flash glucose monitoring (Abbott FreeStyle Libre) for children with type 1 diabetes in terms of glucose control, secondary healthcare resources and costs.Research design and...

Insights from linking police domestic abuse data and health data in South Wales, UK: a linked routine data analysis using decision tree classification

Exposure to domestic abuse can lead to long-term negative impacts on the victim's physical and psychological wellbeing. The 1998 Crime and Disorder Act requires agencies to collaborate on crime reduction strategies, including data sharing. Although data sharing is feasible for individuals, rarely are whole-agency data linked. This study aimed to examine the knowledge obtained by integrating information from police and health-care datasets through data linkage and analyse associated risk factor clusters. This retrospective cohort study analyses data from residents of South Wales who were victims of domestic abuse resulting in a Public Protection Notification (PPN) submission between Aug 12, 2015 and March 31, 2020. The study links these data with the victims' health records, collated within the Secure Anonymised Information Linkage databank, to examine factors associated with the outcome of an Emergency Department attendance, emergency hospital admission, or death within 12 months of the PPN submission. To assess the time to outcome for domestic abuse victims after the index PPN submission, we used Kaplan-Meier survival analysis. We used multivariable Cox regression models to identify which factors contributed the highest risk of experiencing an outcome after the index PPN submission. Finally, we created decision trees to describe specific groups of individuals who are at risk of experiencing a domestic abuse incident and subsequent outcome. After excluding individuals with multiple PPN records, duplicates, and records with a poor matching score or missing fields, the resulting clean dataset consisted of 8709 domestic abuse victims, of whom 6257 (71·8%) were female. Within a year of a domestic abuse incident, 3650 (41·9%) individuals had an outcome. Factors associated with experiencing an outcome within 12 months of the PPN included younger victim age (hazard ratio 1·183 [95% CI 1·053-1·329], p=0·0048), further PPN submissions after the initial referral (1·383 [1·295-1·476]; p<0·0001), injury at the scene (1·484 [1·368-1·609]; p<0·0001), assessed high risk (1·600 [1·444-1·773]; p<0·0001), referral to other agencies (1·518 [1·358-1·697]; p<0·0001), history of violence (1·229 [1·134-1·333]; p<0·0001), attempted strangulation (1·311 [1·148-1·497]; p<0·0001), and pregnancy (1·372 [1·142-1·648]; p=0·0007). Health-care data before the index PPN established that previous Emergency Department and hospital admissions, smoking, smoking cessation advice, obstetric codes, and prescription of antidepressants and antibiotics were associated with having a future outcome following a domestic abuse incident. The results indicate that vulnerable individuals are detectable in multiple datasets before and after involvement of the police. Operationalising these findings could reduce police callouts and future Emergency Department or hospital admissions, and improve outcomes for those who are vulnerable. Strategies include querying previous Emergency Department and hospital admissions, giving a high-risk assessment for a pregnant victim, and facilitating data linkage to identify vulnerable individuals. National Institute for Health Research.

The role of local government in tackling a global pandemic: A lesson from Nepal

This paper critically analyses the scope of leadership in Nepal at the local government level when tackling the wider impacts of COVID-19, with a particular focus on health service delivery in line with World Health Organisation (WHO) frameworks. In-depth interviews with 66 representatives from local governments (LG) in the Madhesh and Sudurpaschim provinces were conducted, along with analysis of routine data from health management information systems. We found that Maternal Child Health (MCH) services at local health institutions were largely unimpacted, stocks of essential medicine were available, and the LGs exhibited determination and capability in getting to grips with the crisis, despite inadequate knowledge and resources. Nevertheless, there was sizeable shrinkage in the utilisation of services, which triggered public health concerns of a different nature, the LGs were inadequately prepared in regards to the capacity and availability of human resources, and there were explicit gaps in terms of coordination among all three tiers of government and a lack of role clarity that delayed the response to the pandemic at the local level. Our recommendations include continued investment in local MCH services, capacity building for local leaders with a focus on human resource management in emergency contexts, and the simplification of public procurement processes, particularly during crises, enabling LGs and other local actors to expediate procurement and improve response times.

Potassium-39-derived 36Ar production during fission-neutron irradiation and its effect on 40Ar/39Ar ages

Various interference reactions producing unwanted Ar isotopes from K, Ca, Cl and Ar require correction to satisfy the 40Ar/39Ar age equation. Using GEANT4, we design and build a model Cadmium Lined In Core Irradiation Tube (CLICIT) irradiation facility, as used in the Oregon State TRIGA Reactor (OSTR). We illustrate the complexity of the irradiation of geologic samples within this framework and determine an overlooked production channel of 36Ar. The production of 36Ar is fed from the 39K(n,α)36Cl nuclear channel, 36Cl subsequently decays to 36Ar (39K(n,α,β) 36Ar). Simulations in this work using a 235U fission neutron energy spectrum and modelled CLICIT facility, determine a production ratio for this reaction (36Cl/39Ar)K = 0.40 ± 0.01 (1σ); greater than an order of magnitude larger than any other K interference. The magnitude of the resulting age bias for an unknown sample will be a function of the integrated neutron flux, the length of irradiation (fluence), the time elapsed since irradiation, and the age relationship between the unknown and neutron fluence monitor. We show using the raw data of (Niespolo et al., 2017) that the age of Alder Creek sanidine can be modified to be ca. 0.1% older (1σ), at the 2σ level of current analytical precision for the Alder Creek age for this study. The 39K(n,α,β)36Ar inference should be incorporated into routine data analysis and may be especially important in the intercalibration of the 40Ar/39Ar system with other chronometers (e.g., 206Pb/238U).

How important is it to avoid indices of deprivation that include health variables in analyses of health inequalities?

ObjectivesThis study aimed to quantify the difference in mortality inequalities using the Scottish Index of Multiple Deprivation (SIMD) and the Income and Employment Index (IEI; a subindex of SIMD, which excludes health) as ranking measures in Scotland. Study designThis ecological study was a cross-sectional analysis of routine administrative data. MethodsData from the 2020 SIMD and the subindex using data from only the Income and Employment domains, the IEI, were obtained. The correlation between data zones, percentage of data zones that changed deprivation tenth and differences in the Slope Index of Inequality (SII) and Relative Index of Inequality (RII) for Standardised Mortality Ratios (SMRs) across tenths were compared when data zones were ranked by SIMD and IEI. ResultsThere was a close correlation between data zones ranked by SIMD and IEI (R2 = 0.96). When data zones were ranked by IEI, 18.7% of data zones moved to a lower deprivation tenth, and 20.8% of data zones moved to a higher deprivation tenth, compared with SIMD. However, only a negligible number of data zones moved two or more tenths. The SMRs across deprivation tenths were very similar between the SIMD and IEI, as were the summary health inequality measures of SII (87.3 compared with 85.7) and RII (0.88 and 0.86). ConclusionAlthough there is a logical problem in using deprivation indices that include health outcomes to rank areas to calculate the scale of health inequalities, the impact of using an alternative subindex containing only data from the income and employment domains is minimal. For population-wide analyses of health inequalities in Scotland, the SIMD does not introduce a substantial bias in the health inequalities summary measures despite substantial movement of small areas between ranked population tenths. Although not examined here, this is likely to be relevant to other similar indices across the United Kingdom.

Pre-Hospital Emergency Medical Services Utilization Amid COVID-19 in 2020: Descriptive Study Based on Routinely Collected Dispatch Data in Bavaria, Germany.

The COVID-19 pandemic affected the utilization of health care services and posed organizational challenges. While many previous studies focused on the misuse of pre-hospital EMS for low-urgency health problems, the pandemic has put more emphasis on the avoidance of medically necessary calls. To compare the utilization of pre-hospital emergency medical services before and after specific pandemic periods. This was a retrospective, descriptive analysis of routine data from 26 dispatch centers in Bavaria, Germany. We investigated the number of emergencies per 100,000 population, as well as the relative change in the emergency rates and transport rates in 2020, compared to the two previous years. Boxplots showed the distributions across the Bavarian districts per calendar week. The mean rates and standard deviations as well as the relative changes were presented for the specific periods. A paired samples t-test was used to compare the rates. Compared to the average of the two previous years, the emergency rates in 2020 were lower in 35 out of 52 calendar weeks. The strongest reductions were observed during the first wave, where the average emergency rate declined by 12.9% (SD 6.8, p < 0.001). There was no statistically significant difference in the overall emergency rate during the summer holidays. Lower transport rates were observed throughout the year, especially during the first wave. Utilization of pre-hospital emergency medical services decreased in 2020, especially during the periods with strict measures. This could be due to the lower morbidity from the behavioral changes during the pandemic, but also to the avoidance of medical services for both less urgent and severe conditions. While a reduction in unnecessary care would be beneficial, patients must be encouraged to seek necessary urgent care, even during a pandemic.

Using GWAS summary data to impute traits for genotyped individuals.

Genome-wide association study (GWAS) summary data have become extremely useful in daily routine data analysis, largely facilitating new methods development and new applications. However, a severe limitation with the current use of GWAS summary data is its exclusive restriction to only linear single nucleotide polymorphism (SNP)-trait association analyses. To further expand the use of GWAS summary data, along with a large sample of individual-level genotypes, we propose a nonparametric method for large-scale imputation of the genetic component of the trait for the given genotypes. The imputed individual-level trait values, along with the individual-level genotypes, make it possible to conduct any analysis as with individual-level GWAS data, including nonlinear SNP-trait associations and predictions. We use the UK Biobank data to highlight the usefulness and effectiveness of the proposed method in three applications that currently cannot be done with only GWAS summary data (for SNP-trait associations): marginal SNP-trait association analysis under non-additive genetic models, detection of SNP-SNP interactions, and genetic prediction of a trait using a nonlinear model of SNPs.

Review on Cleveland Heart Disease Dataset using Machine Learning

According to the World Health Organization (WHO), heart disease has been a foremost source of death worldwide for the past 15 years. Therefore Medical diagnosis is typically performed mostly by doctors due to their training and experience. In the field of medicine, computer-aided decision support systems are enormously significant. Therefore, it is necessary to develop prediction systems that give information of different categories to readers. According to the study, hybrid intelligent algorithms increase the heart disease prediction system’s accuracy. Hence, recognizing cardiovascular problems including heart attacks, coronary artery diseases, etc. by routine clinical data analysis is an important task; early identification of heart disease may save many lives. In this article, have reviewed various papers related to the Cleveland heart disease dataset that used one or more machine-learning algorithms to forecast congestive heart failure. In one of the above mention papers, the result of utilizing Random Forest is almost 100%. To ensure that predictions made using machine learning algorithms produce accurate outcomes. Applying machine learning algorithms to heart disease treatment data can produce results that are just as accurate as those found in heart disease diagnosis.

Homelessness and associated factors over a 13-year period among psychiatric in-patients in Berlin, Germany: routine data analysis.

Homeless patients in psychiatric hospitals are a scarcely studied and there is lack of knowledge about factors associated with homelessness and in-patient treatment. To determine the change over time in the number of homeless psychiatric in-patients and to examine factors associated with homelessness. Retrospective data analysis of 1205 selected electronic patient files on psychiatric in-patient treatment in a university psychiatric hospital in Berlin, Germany. The rate of patients experiencing homelessness over a 13-year period (2008-2021) and the sociodemographic and clinical factors associated with homelessness are analysed over time. Our study revealed a 15.1% increase in the rate of homeless psychiatric in-patients over the 13-year period. Of the whole sample, 69.3% people lived in secure private housing, 15.5% were homeless and 15.1.% were housed in sociotherapeutic facilities. Homelessness was significantly associated with being male (OR = 1.76 (95% CI 1.12-2.76), born outside of Germany (OR = 2.22, 95% CI 1.47-3.34), lack of out-patient treatment (OR = 5.19, 95% CI 3.35-7.63), psychotic disorders (OR = 2.46, 95% CI 1.16-5.18), reaction to severe stress (OR = 4.19, 95% CI 1.71-10.24), personality disorders (OR = 4.98, 95% CI 1.92-12.91), drug dependency (OR = 3.47, 95% CI 1.5-8.0) and alcohol dependency (OR = 3.57, 95% CI 1.67-7.62). The psychiatric care system is facing an increasing number of patients in precarious social situations. This should be considered in resource allocation planning in healthcare. Individual solutions for aftercare, along with supported housing, could counteract this trend.

Gains and gaps: addressing HIV in diverse sex worker groups

Over the past four decades of the HIV pandemic, diverse groups of sex workers have been disproportionately affected across settings. 1 UNAIDSHIV and sex work: human rights fact sheets series. https://www.unaids.org/sites/default/files/media_asset/05-hiv-human-rights-factsheet-sex-work_en.pdfDate: 2021 Date accessed: June 1, 2023 Google Scholar Social and structural factors including the criminalisation of sex work, financial insecurity, and intersectional stigma, discrimination, and violence have been identified as key drivers of sex workers' disproportionate HIV risk and poor treatment outcomes. 2 Shannon K Crago A-L Baral SD et al. The global response and unmet actions for HIV and sex workers. Lancet. 2018; 392: 698-710 Summary Full Text Full Text PDF PubMed Scopus (129) Google Scholar Although community-driven combination prevention interventions have shown promise in reducing new HIV infections and improving HIV care and treatment outcomes among sex workers, 3 Kerrigan D Kennedy CE Morgan-Thomas R et al. A community empowerment approach to the HIV response among sex workers: effectiveness, challenges, and considerations for implementation and scale-up. Lancet. 2015; 385: 172-185 Summary Full Text Full Text PDF PubMed Scopus (209) Google Scholar investments to bring these efforts to scale have lagged far behind historical and current needs. Temporal trends in, and risk factors for, HIV seroconversion among female sex workers accessing Zimbabwe's national sex worker programme, 2009–19: a retrospective cohort analysis of routinely collected HIV testing dataWe identified high rates of seroconversion shortly after linkage to programme services, which emphasises the need to strengthen HIV prevention programmes from first contact with female sex workers in Zimbabwe. New infections among female sex workers remain challenging to measure, but longitudinal analysis of routine testing data can provide valuable insights into seroconversion rates and associated risk factors. Full-Text PDF Open AccessHIV prevalence, risk behaviour, and treatment and prevention cascade outcomes among cisgender men, transgender women, and transgender men who sell sex in Zimbabwe: a cross-sectional analysis of programme dataThese unique data show that people who sell sex and identify as cisgender men, transgender women, or transgender men in sub-Saharan Africa have high HIV prevalences and risk of infection, with alarmingly low access to HIV prevention, testing, and treatment services. There is an urgent need for people-centred HIV interventions for these high-risk groups and for more inclusive HIV policies and research to ensure we truly attain universal access for all. Full-Text PDF

Temporal trends in, and risk factors for, HIV seroconversion among female sex workers accessing Zimbabwe's national sex worker programme, 2009–19: a retrospective cohort analysis of routinely collected HIV testing data

The frequency of new HIV infections among female sex workers in sub-Saharan Africa is poorly understood. We used routinely collected data that enable unique identification of repeat HIV testers to assess temporal trends in seroconversion and identify associated risk factors for female sex workers accessing Sisters with a Voice, Zimbabwe's national sex worker programme. We pooled HIV testing data gathered between Sept 15, 2009, and Dec 31, 2019, from 36 Sisters programme sites in Zimbabwe. We included female sex workers aged 16 years or older with an HIV-negative test and at least one subsequent programme test. We calculated HIV seroconversion rates (using the midpoint between the HIV-positive test and the last negative test as the seroconversion date) and estimated rate ratios to compare 2-year periods by using Poisson regression, with robust SEs to account for clustering by site and adjusting for age and testing frequency to assess temporal trends. We did sensitivity analyses to explore assumptions about seroconversion dates and the effects of variation in follow-up time on our conclusions. Our analysis included data for 6665 female sex workers, 441 (7%) of whom seroconverted. The overall seroconversion rate was 3·8 (95% CI 3·4-4·2) per 100 person-years at risk. Seroconversion rates fell with time since first negative HIV test. After adjustment, there was evidence of a decrease in seroconversion rates from 2009 to 2019 (p=0·0053). In adjusted analyses, being younger than 25 years, and having a sexually transmitted infection diagnosis at a previous visit, were significantly associated with increased seroconversion rates. Our findings were mostly robust to sensitivity analyses, but when 1 month before an HIV-positive test was used as the seroconversion date, seroconversion rates no longer fell with time. We identified high rates of seroconversion shortly after linkage to programme services, which emphasises the need to strengthen HIV prevention programmes from first contact with female sex workers in Zimbabwe. New infections among female sex workers remain challenging to measure, but longitudinal analysis of routine testing data can provide valuable insights into seroconversion rates and associated risk factors. UN Population Fund, Deutsche Gesellschaft für Internationale Zusammenarbeit, the Bill & Melinda Gates Foundation, The Global Fund to Fight AIDS, Tuberculosis and Malaria, US President's Emergency Plan for AIDS Relief, US Agency for International Development, and the Elton John AIDS Foundation.

HIV prevalence, risk behaviour, and treatment and prevention cascade outcomes among cisgender men, transgender women, and transgender men who sell sex in Zimbabwe: a cross-sectional analysis of programme data

There is a paucity of evidence on HIV vulnerabilities and service engagements among people who sell sex in sub-Saharan Africa and identify as cisgender men, transgender women, or transgender men. We aimed to describe sexual risk behaviours, HIV prevalence, and access to HIV services among cisgender men, transgender women, and transgender men who sell sex in Zimbabwe. We did a cross-sectional analysis of routine programme data that were collected between July 1, 2018, and June 30, 2020, from cisgender men who sell sex, transgender women who sell sex, and transgender men who sell sex, as part of accessing sexual and reproductive health and HIV services provided through the Sisters with a Voice programme, at 31 sites across Zimbabwe. All people who sell sex reached by the programme had routine data collected, including routine HIV testing, and were referred using a network of peer educators. Sexual risk behaviours, HIV prevalence, and HIV services uptake during the period from July, 2018, to June, 2020, were analysed through descriptive statistics by gender group. A total of 1003 people who sell sex were included in our analysis: 423 (42·2%) cisgender men, 343 (34·2%) transgender women, and 237 (23·6%) transgender men. Age-standardised HIV prevalence estimates were 26·2% (95% CI 22·0-30·7) among cisgender men, 39·4% (34·1-44·9) among transgender women, and 38·4% (32·1-45·0) among transgender men. Among people living with HIV, 66·0% (95% CI 55·7-75·3) of cisgender men, 74·8% (65·8-82·4) of transgender women, and 70·2% (59·3-79·7) of transgender men knew their HIV status, and 15·5% (8·9-24·2), 15·7% (9·5-23·6), and 11·9% (5·9-20·8) were on antiretroviral therapy, respectively. Self-reported condom use was consistently low across gender groups, ranging from 26% (95% CI 22-32) for anal sex among transgender women to 32% (27-37) for vaginal sex among cisgender men. These unique data show that people who sell sex and identify as cisgender men, transgender women, or transgender men in sub-Saharan Africa have high HIV prevalences and risk of infection, with alarmingly low access to HIV prevention, testing, and treatment services. There is an urgent need for people-centred HIV interventions for these high-risk groups and for more inclusive HIV policies and research to ensure we truly attain universal access for all. Aidsfonds Netherlands.

In search of a composite biomarker for chronic pain by way of EEG and machine learning: where do we currently stand?

Machine learning is becoming an increasingly common component of routine data analyses in clinical research. The past decade in pain research has witnessed great advances in human neuroimaging and machine learning. With each finding, the pain research community takes one step closer to uncovering fundamental mechanisms underlying chronic pain and at the same time proposing neurophysiological biomarkers. However, it remains challenging to fully understand chronic pain due to its multidimensional representations within the brain. By utilizing cost-effective and non-invasive imaging techniques such as electroencephalography (EEG) and analyzing the resulting data with advanced analytic methods, we have the opportunity to better understand and identify specific neural mechanisms associated with the processing and perception of chronic pain. This narrative literature review summarizes studies from the last decade describing the utility of EEG as a potential biomarker for chronic pain by synergizing clinical and computational perspectives.

Mental health service use and costs associated with complex emotional needs and a diagnosis of personality disorder: analysis of routine data.

We aimed to estimate the costs of care for people with a personality disorder diagnosis and compare service use and costs for those receiving specialist input and those receiving generic care. Service use data were obtained from records and costs calculated. Comparisons were made between those who received care from specialist personality disorder teams and those who did not. Demographic and clinical predictors of costs were identified with regression modelling. Mean total costs before diagnosis were £10 156 for the specialist group and £11 531 for the non-specialist group. Post-diagnosis costs were £24 017 and £22 266 respectively. Costs were associated with specialist care, comorbid conditions and living outside of London. Receiving increased support from a specialist service may reduce the need for in-patient care. This may be clinically appropriate and results in a distribution of costs.

"Together against Tuberculosis": Cascade of Care of Patients Referred by the Private Health Care Providers in the Kyrgyz Republic.

Until 2021, in the Kyrgyz Republic, tuberculosis (TB) was diagnosed and treated only in the public sector. With funding support of the STOP-TB partnership, the private providers in four regions of the country and Bishkek city were mapped, trained and incentivized to screen for and identify presumptive TB patients and refer them to the public facilities for diagnosis and treatment. In this study, we describe the cascade of care of such patients. This was a cohort study involving secondary analysis of routine data. Of 79,352 patients screened during February 2021-March 2022, 2511 (3%) had presumptive TB, of whom 903 (36%) were not tested for TB [pre-diagnostic loss to follow-up]. A total of 323 (13%) patients were diagnosed with TB, of whom, 42 (13%) were not started on treatment [pre-treatment loss to follow-up]. Among 257 patients eligible for outcome assessment, 197 (77%) had treatment success, 29 (11%) were lost-to-follow-up, 13 (5%) died, 4 (2%) had treatment failure and 14 (5%) were not evaluated. While this donor-funded, pioneering initiative was successful in engaging the private sector, we recommend that the national TB programme scales up the initiative nationally with dedicated budgets, activities and plans to monitor progress. Qualitative research is urgently needed to understand the reasons for the gaps in the care cascade.

Alternative allele frequency recallibration after NGS data analysis.

3077 Background: With the spread of NGS in routine clinical practice data analysis methods actively evolve to increase and refine information yield. Not much attention is given to variant allele fraction (VAF) estimation though it impacts clinical insignificance of subclonal somatic variants and identification of variant origin. Methods: Real-world sequencing data of 2379 samples (including 781 tumor-only and 1598 blood-only sequencing datasets) obtained via amplicon-based sequencing was used for the retrospective analysis of variant allele frequency estimation of identified genetic variants employing different methods including ITVC, SiNVICT, Mutect2 and SGA. Original method (AODvAF) utilizing alignment-free algorithm based on wild-type and alternative genome subsequence abundance estimation was developed and compared with the original output from NGS data analysis software. Anticipated VAF estimation was based on analyte type and database annotation. Results: Across 3447 identified potentially germline variations (PGV) VAF estimations provided by ITVC, SiNVICT and SGA were highly correlated (Pearson correlation coefficient [PCC] 1.00), while Mutect2 and AODvAF demonstrated discordant results (Mutect2/AODvAF vs ITVC PCC 0.87/0.82). VAF miscalculation defined by absolute difference between estimated and anticipated VAF of 10% and more was noted for 25%, 26%, 22%, 15% and 7% for ITVC, SiNVICT, SGA, Mutect2 and AODvAF respectively. Across 308 pathogenic BRCA1, BRCA2, PALB2 mutations identified in blood-only sequencing 25, 15, 16, 10 and 5 were characterized by VAF of 30% and lower based on ITVC, SiNVICT, SGA, Mutect2 and AODvAF estimations respectively (54, 49, 33, 51 and 9 for VAF 40% and lower), which may lead to misinterpretation of these variants as post-zygotic. Automatic in-silico annotation of variant origin (germline vs somatic) based on ISOWN was correct for 89%, 91%, 94%, 93% and 98% of these variants. Variant origin for 55 pathogenic variants of genes associated with hereditary cancer syndromes identified in tumor-only sequencing was verified by Sanger sequencing. Cohen's kappa coefficient for variant origin discrimination (Sanger vs in-silico prediction) was 0.91, 0.90, 0.91, 0.94 and 0.97 based on VAF provided by ITVC, SiNVICT, SGA, Mutect2 and AODvAF respectively. Conclusions: Accurate VAF calculation allows precise variant origin identification and impacts interpretation of variants. Developed method allows correction of VAF after NGS data core analysis.

A focus on dominant negative variants in a series of 170 heterozygous FXI-deficient patients.

Dominant-negative effects have been described for 10F11 variants in the literature. The current study aimed at identifying putative dominant-negative F11 variants. This research consisted in a retrospective analysis of routine laboratory data. In a series of 170patients with moderate/mild factorXI (FXI) deficiencies, we identified heterozygous carriers of previously reported dominant-negative variants (p.Ser243Phe, p.Cys416Tyr, and p.Gly418Val) with FXI activities inconsistent with a dominant-negative effect. Our findings also do not support a dominant-negative effect of p.Gly418Ala. We also identified a set of patients carrying heterozygous variants, among which five out of 11 are novel, with FXI activities suggesting a dominant-negative effect (p.His53Tyr, p.Cys110Gly, p.Cys140Tyr, p.Glu245Lys, p.Trp246Cys, p.Glu315Lys, p.Ile421Thr, p.Trp425Cys, p.Glu565Lys, p.Thr593Met, and p.Trp617Ter). However, for all but two of these variants, individuals with close to half normal FXI coagulant activity (FXI:C) were identified, indicating an inconstant dominant effect. Our data show that for some F11 variants recognized has having dominant-negative effects, such effects actually do not occur in many individuals. The present data suggest that for these patients, the intracellular quality control mechanisms eliminate the variant monomeric polypeptide before homodimer assembly, thereby allowing only the wild-type homodimer to assemble and resulting in half normal activities. In contrast, in patients with markedly decreased activities, some mutant polypeptides might escape this first quality control. In turn, assembly of heterodimeric molecules as well as mutant homodimers would result in activities closer to 1:4 of FXI:C normal range.