Search bioRxiv⌕ Search

SEARCH · Search bioRxiv

Results for “epidemiology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,171 records · Page 65Linked to original sources
bioRxiv2018

Spatio-temporal modelling of Leishmania infantum infection among domestic dogs: a simulation study and sensitivity analysis applied to rural Brazil

BackgroundThe parasite Leishmania infantum causes zoonotic visceral leishmaniasis (VL), a potentially fatal vector-borne disease of canids and humans. Zoonotic VL poses a significant risk to public health, with regions of Latin America being particularly afflicted by the disease.\n\nLeishmania infantum parasites are transmitted between hosts during blood feeding by infected female phlebotomine sand flies. With a principal reservoir host of L. infantum being domestic dogs, limiting prevalence in this reservoir may result in a reduced risk of infection for the human population. To this end, a primary focus of research efforts has been to understand disease transmission dynamics among dogs. One way this can be achieved is through the use of mathematical models.\n\nMethodsWe have developed a stochastic, spatial, individual-based mechanistic model of L. infantum transmission in domestic dogs. The model framework was applied to a rural Brazilian village setting with parameter values informed by fieldwork and laboratory data. To ensure household and sand fly populations were realistic, we statistically fit distributions for these entities to existing survey data. To identify the model parameters of highest importance, we performed a stochastic parameter sensitivity analysis of the prevalence of infection among dogs to the model parameters.\n\nResultsWe computed parametric distributions for the number of humans and animals per household and a non-parametric temporal profile for sand fly abundance. The stochastic parameter sensitivity analysis determined prevalence of L. infantum infection in dogs to be most strongly affected by the sand fly associated parameters and the proportion of immigrant dogs already infected with L. infantum parasites.\n\nConclusionsEstablishing the model parameters with the highest sensitivity of average L. infantum infection prevalence in dogs to their variation helps motivate future data collection efforts focusing on these elements. Moreover, the proposed mechanistic modelling framework provides a foundation that can be expanded to explore spatial patterns of zoonotic VL in humans and to assess spatially targeted interventions.

epidemiology↗
bioRxiv2018

Caries Prevalence and Experience in Individuals with Osteogenesis Imperfecta

ObjectiveDentinogenesis Imperfecta (DI) forms a group of dental abnormalities frequently found associated with Osteogenesis Imperfecta (OI), a hereditary disease characterized by bone fragility. The objectives of this study was to quantify the caries experience among different OI-types and quantify how these values change due to DI. MethodsTo determine which clinical characteristics were associated with increased CPE in patients with OI, the adjusted DFT scores were used to account for frequent hypodontia, impacted teeth and retained teeth in OI population. ResultsThe stepwise regression analysis while controlling for all other variables demonstrated the presence of DI (OR 2.43; CI 1.37 to 4.32; p=0.002) as the significant independent predictor of CPE in the final model. ConclusionThis study found no evidence that CPE of OI subjects differs between the types of OI. The presence of DI when controlled for other factors was found to be the significant predictor of CPE.

epidemiology↗
bioRxiv2018

Physical illness, social disadvantage, and risky sexual behavior in adolescence and young adulthood

This study investigated the influence of illness on sexual risk behavior in adolescence and the transition to adulthood, both directly and through moderation of the impact of social disadvantage. We hypothesized positive effects for social disadvantages and illness on sexual risk behavior, consistent with the development of faster life history strategies among young people facing greater life adversity. Using the first two waves of the National Longitudinal Study of Adolescent Health, we developed a mixed effects multinomial logistic regression model predicting sexual risk behavior in three comparisons, risky nonmonogamous sex vs. 1) safer nonmonogamous sex, 2) monogamous sex, and 3) abstinence, by social characteristics, illness, interactions thereof, and control covariates. Multiple imputation was used to address a modest amount of missing data. Subjects reporting higher levels of illness had lower odds of having safer nonmonogamous sex (OR = 0.84, p < .001), monogamous sex (OR = 0.82, p < .001), and abstinence (OR = 0.74, p < .001) vs. risky nonmonogamous sex, relative to individuals in better health. Illness significantly moderated the sex (OR = 0.88, p < .01), race/ethnicity (e.g., OR = 1.21, p < .001), and childhood SES (OR = 0.94; p < .01) effects for the abstinent vs. risky nonmonogamous sex comparison. Substantive findings were generally robust across waves and in various sensitivity analyses. These findings offer general support for the predictions of life history theory. Illness and various social disadvantages are associated with increased sexual risk behavior in adolescence and the transition to adulthood. Analyses indicate that the buffering effects of several protective social statuses against sexual risk-taking are substantially eroded by illness.

epidemiology↗
bioRxiv2018

The wildlife-livestock interface modulates anthrax suitability in India

Anthrax is a potentially life-threatening bacterial disease that can circulate in wild and domestic animals and subsequently spillover to human contacts with devastating consequences for human and animal health, as well as livestock economies and ecosystem conservation. India has a high annual occurrence of anthrax in some regions, but a country-wide delineation of risk has not yet been undertaken. The current study modeled the geographic suitability of anthrax across India and its associated environmental features using a biogeographical application of machine learning. Both biotic and abiotic features contributed to risk across multiple scales of influence and the wildlife-livestock interface, using elephants as a wildlife sentinel species, was the dominant feature in delineating anthrax suitability. In addition, water-soil balance, soil chemistry, and historical forest loss were also influential. These findings suggest that the wildlife-livestock interface plays an important role in the cycling of anthrax in India. Prevention efforts targeted toward this interface, particularly within anthropogenic ecotones, may yield successes in reducing ongoing transmission between animal hosts and subsequent zoonotic transmission to humans.

epidemiology↗
bioRxiv2018

Bacteriology And Antibiotic Prescription Patterns In A Malawian Tertiary Hospital Burns Unit

IntroductionInfections are responsible for up to 85% of deaths in patients with burn injuries. Proper management of infections in patients with burns requires knowledge of local microbial landscape and antimicrobial resistance patterns. Most burns units in low to middle income countries lack this data to guide patient management.\n\nMethods and resultsWe conducted a retrospective audit of adult ([&ge;]17 years) patient records admitted between at 1st June 2007 and May 2017 at Queen Elizabeth Central Hospital Burns unit in Blantyre Malawi with an index complaint of burn injury. Descriptive statistical analysis was performed to determine antibiotic prescription patterns, microbial isolates and antimicrobial resistance patterns on the 500 patient files that met the inclusion criteria. Cephalosporins and Penicillins constituted 72.3% of the 328 antibiotic prescriptions given to 212 patients and 84% of all prescriptions were potentially inappropriate. A total of 102 bacterial isolates were identified and a majority (30.4%; n=31) were resistant to Aminoglycosides and Aminocyclitols (23.5%; n=24); seconded by Penicillins at 19.6% (n=20). Pseudomonas, staphylococcus and streptococcus species constituted 36.1%, 25% and 16.7% of all resistant bacteria that were isolated and they were thus the most common bacterial isolates. Drug resistance was more common among gram negative bacteria (48.8% versus 26.2%) and a greater proportion of patients (74.1%) that had antibiotic sensitivity testing were affected by drug resistant gram negative bacteria which appear on the World Health Organisation list of priority pathogens.\n\nConclusionThe results of our preliminary study point towards nosocomial gram negative bacteria which appear on the World Health Organisations list of priority pathogens as the more common sources of antibiotic resistance. This scenario is potentially driven by inappropriate antibiotic prescriptions as well as clinical and laboratory diagnostic imprecision in addition to the universally recognised post burn pathophysiological changes of hypermetabolism and immunosuppression. Improvements in the areas of antimicrobial stewardship, diagnostic capacity and burns related research are needed in order to achieve optimal therapeutic outcomes and resource utilisation.

epidemiology↗
bioRxiv2018

Predictive model in the presence of missing data: the centroid criterion for variable selection

IntroductionIn many studies, covariates are not always fully observed because of missing data process. Usually, subjects with missing data are excluded from the analysis but the number of covariates can be greater than the size of the sample when the number of removed subjects is high. Subjective selection or imputation procedures are used but this leads to biased or powerless models.\n\nThe aim of our study was to develop a method based on the selection of the nearest covariate to the centroid of a homogeneous cluster of covariates. We applied this method to a forensic medicine data set to estimate the age of aborted fetuses.\n\nAnalysisO_ST_ABSMethodsC_ST_ABSWe measured 46 biometric covariates on 50 aborted fetuses. But the covariates were complete for only 18 fetuses.\n\nFirst, to obtain homogeneous clusters of covariates we used a hierarchical cluster analysis.\n\nSecond, for each obtained cluster we selected the nearest covariate to the centroid of the cluster, maximizing the sum of correlations [Formula] (the centroid criterion).\n\nThird, with the covariate selected this way, the sample size was sufficient to compute a classical linear regression model.\n\nWe have shown the almost sure convergence of the centroid criterion and simulations were performed to build its empirical distribution.\n\nWe compared our method to a subjective deletion method, two simple imputation methods and to the multiple imputation method.\n\nResultsThe hierarchical cluster analysis built 2 clusters of covariates and 6 remaining covariates. After the selection of the nearest covariate to the centroid of each cluster, we computed a stepwise linear regression model. The model was adequate (R2=90.02%) and the cross-validation showed low prediction errors (2.23 10-3).\n\nThe empirical distribution of the criterion provided empirical mean (31.91) and median (32.07) close to the theoretical value (32.03).\n\nThe comparisons showed that deletion and simple imputation methods provided models of inferior quality than the multiple imputation method and the centroid method.\n\nConclusionWhen the number of continuous covariates is greater than the sample size because of missing process, the usual procedures are biased. Our selection procedure based on the centroid criterion is a valid alternative to compose a set of predictors.

epidemiology↗
bioRxiv2018

RISK FACTORS OF MORTALITY OF HOSPITALISED ADULT BURN PATIENTS A MALAWIAN TERTIARY HOSPITAL BURNS UNIT

IntroductionMalawi has the highest rates of mortality directly or indirectly associated with burn injuries in Southern Africa. There is however no published literature on risk factors of mortality among adult patients.\n\nMethodsWe conducted a retrospective cross sectional audit records of patients admitted at the burns unit of Queen Elizabeth Central Hospital (QECH) between the years 2007 and 2017. Death due to burns was our outcome of interest. We collected patient data including demographic information, details of the burn injury and its management and determined how these factors were associated with the risk of death using Person Chi square tests in a univariate analysis and likelihood ratio tests in a multivariate logistic regression model. We also determined the odds ratios of death within the categories of the risk factors after adjusting for important variables using a logistic regression model.\n\nResultsAn analysis of 500 burns patient records showed that 132(26.4%) died during the 10-year period. The lethal area for 50% of burns (LA50) was 28.75% and mortality reached 100% at 40% total burn surface area. The following variables were found to be significantly associated with mortality after controlling for confounders: scalds (OR 0.13; 95% CI 0.05-0.33; <0.0001), increasing total burn surface area (p<0.0001), time lapse to hospital presentation between 48 hours and one week(OR 0.27; 95%CI 0.11-0.68; <0.0001), inhalation burns (OR 5.2; 95% CI 2.0-13.3 p 0.0004) and length of hospital stay greater than two months (OR 0.04 95, CI 0.01-0.15; P<0.0001).\n\nConclusionsRisk factors for mortality are connected by their association with post-burn hypermetabolism. Further studies to are needed to identify the best and cost-effective ways of preventing death in burn patients.

epidemiology↗
bioRxiv2018

Cohort Profile: Extended Cohort for E-health, Environment and DNA (EXCEED)

EXCEED is a longitudinal population-based cohort which facilitates investigation of genetic, environmental and lifestyle-related determinants of a broad range of diseases and of multiple morbidity through data collected at baseline and via electronic healthcare record linkage. Recruitment has taken place in Leicester, Leicestershire and Rutland since 2013 and is ongoing, with 10 156 participants aged 30-69 to date. The population of Leicester is diverse and additional recruitment from the local South Asian community is ongoing. Participants have consented to follow-up for up to 25 years through electronic health records (EHR). Data available includes baseline demographics, anthropometry, spirometry, lifestyle factors (smoking and alcohol use) and longitudinal health information from primary care records, with additional linkage to other EHR datasets planned. Patients have consented to be contacted for recall-by-genotype and recall-by-phenotype sub-studies, providing an important resource for precision medicine research. We welcome requests for collaboration and data access by contacting the study management team via exceed@le.ac.uk.

epidemiology↗
bioRxiv2018

Molecular characterization of the viral structural gene of the first dengue virus type 1 outbreak in Xishuangbanna, a border area of China, Burma and Laos

In the context of recent arbovirus epidemics, dengue fever is becoming a greater concern around the world. In August 2017, Xishuangbanna, which is a border city of China, Burma and Laos, had its first major dengue outbreak. A total of 156 serum samples from febrile patients were collected; 97 DENV positive serum samples were screened out, and viral RNAs were successfully and directly extracted, including 77 cases from China and 20 cases from Myanmar. Phylogenetic analysis revealed that all of the strains were classified as DENV-1. There are eight epidemic dengue strains from Myanmar and 74 from Jinghong, Xishuangbanna, that were classified as cluster 1, which are the most similar to the strain of China Guangzhou 2011. There are three epidemic strains from Xishuangbanna Mengla that were classified as cluster 2, which have the closest relationship to the strain of China Hubei 2014. However, there are 12 epidemic strains from Myanmar that were classified as cluster 3, which have the closest relationship to the strain of Laos from 2008, which shows that there is a recycling epidemic trend of DENV in China. There were 236 mutations in the base, which caused 31 nonsynonymous mutations in the DENV structural protein C/prM/E genes when the strain of Xishuangbanna and Myanmar were compared with the DENV-1SS. There is no clear homologous recombination signal among these stains. Homology modeling possibly predicted a three-dimensional structure of the structural protein of these strains and revealed that they had the same three-dimensional structure and all had five predicted protein binding sites, but there are differences in binding site 434 (DENV-1SS: Thr434, DV-Jinghong: Ser434, DV-Myanmar: Ser434, DV-Mengla: Ser434). The results of the molecular clock phylogenetic and demographic reconstruction analysis show that DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017. In conclusion, our study lays the foundation for studying the global evolution and prevalence of DENV.\n\nAuthor SummaryDengue fever (DF) is a mosquito-borne illness caused by a flavivirus. Human infections with Dengue virus (DENV) could cause fever, cutaneous rash and malaise. Xishuangbanna, which is located in the southwestern Yunnan Province and is a border city with China, Burma and Laos, was reported to have outbreak of DENV in 2013 and 2015 with different types. However, there was a large outburst of dengue in May 2017. To understand the genetic characterization, potential source and evolution of the virus, 156 serum samples were analyzed. We focused on: (i) Phylogenetic analysis of the structural protein genes sequences; (ii) Mutation, recombination analysis and predicted protein binding sites of the structural protein genes; (iii) Molecular clock and demographic reconstruction of global dengue virus serotype 1(DENV-1). Our results indicated that this is the first outbreak of DENV-1 in Xishuangbanna, dengue epidemic strains on the Burma border of China show diversification, we found a virulence site changed from I to T(amino acid position: 440), which may lead to weakened virulence of the epidemic strains. We found that the evolution of DENV-1 is dominated by regional evolution. Whats more, DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017.

epidemiology↗
bioRxiv2018

Effects of annual rainfall on dengue incidence in the Indian state of Rajasthan

Dengue has become a major public health problem in the last few decades with India contributing significantly to the overall disease burden. Most of the cases of Dengue from India are reported during Monsoon season. The vector population of dengue is affected by seasonal rainfall, temperature and humidity fluctuations. Rajasthan is northwestern state of India, which has shown several dengue outbreaks in the past. In this paper we have tried to analyze the effects of annual cumulative rainfall on Dengue incidence in one of the largest and severely affected states of India. Retrospective data for Dengue incidence and Rainfall for the state of Rajasthan was collected and Pearsons coefficient correlation was calculated as a measure of association between the variables. Our results indicate that annual cumulative rainfall shows a strong positive correlation with dengue incidence in the state of Rajasthan. Such analyses have the potential to inform public health official about the control and preparedness for vector control during monsoon season. This is the first study from the Indian state of Rajasthan to assess the impact of annual rainfall on dengue incidence, which has seen several dengue outbreaks in the past.

epidemiology↗
bioRxiv2018

Successes and failures of the live-attenuated influenza vaccine, can we do better?

Live-attenuated vaccines are usually highly effective against many acute viral infections. However, the effectiveness of the live attenuated influenza vaccine (LAIV) can vary widely, ranging from 0% effectiveness in some studies done in the United States to 50% in studies done in Europe. The reasons for these discrepancies remain largely unclear. In this paper we use mathematical models to explore how the efficacy of LAIV is affected by the degree of mismatch with the currently circulating influenza strain and interference with pre-existing immunity. The model incorporates two key antigenic distances - the distance between pre-existing immunity and the currently circulating strain as well as the LAIV strain. Our models show that a LAIV that is matched with the currently circulating strain is likely to have only modest efficacy. Our results suggest that the efficacy of the vaccine would be increased (optimized) if, rather than being matched to the circulating strain, it is antigenically slightly further from pre-existing immunity compared with the circulating strain. The models also suggest two regimes in which LAIV that is matched to circulating strains may provide effective protection. The first is in children before they have built immunity from circulating strains. The second is in response to novel strains (such as antigenic shifts) which are at substantial antigenic distance from previously circulating strains. Our models provide an explanation for the variation in vaccine effectiveness, both between children and adults as well as between studies of vaccine effectiveness observed during the 2014-15 influenza season in different countries.\n\nSignificance StatementThe live-attenuated influenza vaccine, in principle provides an important intervention for the control of both seasonal and pandemic influenza. However vaccine effectiveness studies have found seemingly contradictory results with effectiveness ranging from 0 to 50%. Based on mathematical models we suggest that a major factor responsible for the variable efficacy of the vaccine is negative interference - where pre-existing immunity precludes the vaccine from working. Our models suggest that there are broad regimes for which LAIV will fail to be immunogenic, but also allow us to make suggestions for the choice of vaccine strain that will allow optimization of protective immunity in different scenarios.

epidemiology↗
bioRxiv2018

Oral Health-Related Quality of Life in Children and Adolescents with Osteogenesis Imperfecta: cross-sectional study

BackgroundOsteogenesis imperfecta (OI) affects dental and craniofacial development and may therefore impair Oral Health-Related Quality of Life (OHRQoL). However, little is known about OHRQoL in children and adolescents with OI. The aim of this study was to explore the influence of OI severity on oral health-related quality of life in children and adolescents.\n\nMethodsChildren and adolescents aged 8-14 years were recruited in the context of a multicenter longitudinal study (Brittle Bone Disease Consortium) that enrolls individuals with OI in 10 centers across North America. OHRQoL was assessed using the Child Perceptions Questionnaire (CPQ) versions for 8 to 10-year-olds (CPQ8-10) and for 11 to 14-year-olds (CPQ11-14).\n\nResultsA total of 138 children and adolescents (62% girls) diagnosed with OI types I, III, IV, V and VI (n=65, 30, 37, 4 and 2, respectively) participated in the study. CPQ8-10 scores were similar between OI types in children aged 8 to 10 years. In the 11 to 14-year-old group, CPQ11-14-scores were significantly higher (i.e. worse) for OI types III (24.7 [SD 12.5]) and IV (23.1 [SD 14.8]) than for OI type I (16.5 [SD 12.8]) (P<0.05). The difference between OI types was due to the association between OI types and the functional limitations domain, as OI types III and IV were associated with significantly higher grade of functional limitations compared to OI type I.\n\nConclusionThe severity of OI impacts OHRQoL in adolescents aged 11 to 14 years, but not in children age 8 to 10 years.

epidemiology↗
bioRxiv2018

Clinicians management of patients potentially exposed to rabies in high-risk areas in Bhutan: A cross-sectional study

BackgroundRabies is endemic in southern Bhutan, associated with 1-2 human deaths annually and accounting for about 6% of annual national expenditure on essential medicines. A WHO-adapted National Rabies Management Guidelines (NRMG) is available to aid clinicians in PEP prescription. An understanding of clinical practice in the evaluation of rabies risk in endemic areas could contribute to improve clinicians PEP decision-making.\n\nMethodsA cross-sectional survey of clinicians was conducted in 13 health centers in high-rabies-risk areas of Bhutan during February-March 2016. Data were collected from 273 patients examined by 50 clinicians.\n\nResultsThe majority (69%) of exposure was through dog bites. Half the patients were children under 18 years of age. Consultations were conducted by health assistants or clinical officers (55%), or by medical doctors (45%), with a median age of clinicians of 31 years. Rabies vaccines were prescribed in 91% of exposure cases. The overall agreement between clinicians rabies risk assessment and the NRMG for the corresponding exposure was low (kappa =0.203, p<0.001). Clinicians were more likely to underestimate the risk of exposure than overestimate it. Male health assistants were the most likely to make an accurate risk assessment and female health assistants were the least likely. Clinicians from district or regional hospitals were more likely to conduct accurate risk assessments compared to clinicians in Basic Health Units (Odds Ratios of 7.8 and 17.6, respectively).\n\nConclusionsThis study highlighted significant discrepancies between clinical practice and guideline recommendations for rabies risk evaluation. Regular training about rabies risk assessment and PEP prescription should target all categories of clinicians. An update of the NRMG with more specific criterions for the prescription of RIG might contribute to increase the compliance, along with a regular review of decision-making criteria to monitor adherence to the NRMG.\n\nAuthor summaryHuman rabies remains an important public health threat in Bhutan, especially in southern regions where canine rabies is endemic. The steady increase in number of patients reporting to hospitals following dog bites means escalating costs of post-exposure prophylaxis for the country. We investigated attitudes and practices of clinicians who manage patients with potential rabies exposure, in the endemic area. The risk of rabies exposure in the study area is mostly associated with dog bites, involving children half the time. Rabies vaccines were prescribed in 9 out of 10 exposure cases, while immuno-globulins were rarely prescribed. The study confirmed the perceived lack of compliance of clinicians with guideline recommendations for assessing rabies risk. This results in under-estimating the rabies risk in potentially risky exposures in high-rabies-risk areas. Our work underscore the importance of targeted training of female health assistants, doctors, and clinicians in basic health units to improve the management of rabies exposure. In particular there is need to update the national guidelines regarding indications and use of rabies immune-globulins.

epidemiology↗
bioRxiv2018

Connecting surveillance and population-level influenza incidence

There is substantial interest in estimating and forecasting influenza incidence. Surveillance of influenza is challenging as one needs to demarcate influenza from other respiratory viruses, and due to asymptomatic infections. To circumvent these challenges, surveillance data often targets influenza-like-illness, or uses context-specific normalisations such as test positivity or per-consultation rates. Specifically, influenza incidence itself is not reported. We propose a framework to estimate population-level influenza incidence, and its associated uncertainty, using surveillance data and hierarchical observation processes. This new framework, and forecasting and forecast assessment methods, are demonstrated for three Australian states over 2016 and 2017. The framework allows for comparison within and between seasons in which surveillance effort has varied. Implementing this framework would improve influenza surveillance and forecasting globally, and could be applied to other diseases for which surveillance is difficult.

epidemiology↗
bioRxiv2018

Coverage and timeliness of vaccination and the validity of routine estimates: Insights from a Vaccine Registry in Kenya

The benefits of childhood vaccines are critically dependent on vaccination coverage. We used a vaccine registry (as gold standard) in Kenya to quantify errors in routine coverage methods (surveys and administrative reports), to estimate the magnitude of survivor bias, contrast coverage with timeliness and use both measures to estimate population immunity.\n\nWe found coverage surveys in the 2nd year of life overestimate coverage by 2%. Compared to mean coverage in infants, static coverage at 12 months was exaggerated by 7-8% for third doses of oral polio, pentavalent (Penta3) and pneumococcal conjugate vaccines, and by 24% for the measles vaccine. Surveys and administrative coverage also underestimated the proportion of the fully immunised child by 10-14%. For BCG, Penta3 and measles, timeliness was 23-44% higher in children born in a health facility but 20-37% lower in those who first attended during vaccine stock outs.\n\nCoverage surveys in 12-23 month old children overestimate protection by ignoring timeliness, and survivor and recall biases.

epidemiology↗
bioRxiv2018

Characterizing Inpatient Medicine Resident Electronic Health Record Usage Patterns Using Event Log Data

Amid growing rates of burnout, physicians report increasing electronic health record (EHR) usage alongside decreasing clinical facetime with patients. There exists a pressing need to improve physician-computer-patient interactions by streamlining EHR workflow.\n\nTo identify interventions to improve EHR design and usage, we systematically characterize EHR activity among internal medicine residents at a tertiary academic hospital across various inpatient rotations and roles from June 2013 to November 2016.\n\nLogged EHR timestamps were extracted from Stanford Hospitals EHR system (Epic) and cross-referenced against resident rotation schedules. We tracked the quantity of EHR logs across 24-hour cycles to reveal daily usage patterns. In addition, we decomposed daily EHR time into time spent on specific EHR actions (e.g. chart review, note entry and review, results review).\n\nIn examining 24-hour usage cycles from general medicine day and night team rotations, we identified a prominent trend in which night team activity promptly ceased at the shifts end, while day team activity tended to linger post-shift. Across all rotations and roles, residents spent on average 5.38 hours (standard deviation=2.07) using the EHR. PGY1 (post-graduate year one) interns and PGY2+ residents spent on average 2.4 and 4.1 times the number of EHR hours on information review (chart, note, and results review) as information entry (note and order entry).\n\nAnalysis of EHR event log data can enable medical educators and programs to develop more targeted interventions to improve physician-computer-patient interactions, centered on specific EHR actions.

epidemiology↗
bioRxiv2018

Biomarker de-Mendelization: principles, potentials and limitations of a strategy to improve biomarker prediction by reducing the component of variance explained by genotype

In observational studies, the Mendelian randomization approach can be used to circumvent confounding, bias and reverse causation, and to assess a potential causal association between a biomarker and risk of disease. If, on the other hand, a substantial component of variance of a non-causal biomarker is explained by genotype, then genotype could potentially attenuate the observational association and the strength of the prediction. In order to reduce the component of variance explained by genotype, an approach that can be seen as the inverse of Mendelian randomization - biomarker de-Mendelization - appears plausible.Plasma YKL-40 is a good candidate for demonstrating principles of biomarker de-Mendelization because it is a non-causal biomarker with a substantial component of variance explained by genotype. This approach is an attempt to improve the observational association and the strength of a predictive biomarker; it is explicitly not aimed at detection of causal effects.\n\nWe studied 21 161 individuals form the Danish general population with measurements of YKL-40 concentration and rs4950928 genotype. Four different methods for biomarker de-Mendelization are explored for alcoholic liver cirrhosis and lung cancer.\n\nDe-Mendelization methods only improved predictive ability slighly. We observed an interaction between genotype and markers of developing disease with respect to YKL-40 concentration.\n\nEven when genotype explains 14% of the variance in a non-causal biomarker, we found no useful empirical improvement in risk prediction by biomarker de-Mendelization. This could reflect the predictive interaction between genotype and disease development being removed which counterbalanced any beneficial properties of the method in this situation.

epidemiology↗