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This paper presents a micromachined thermal convective accelerometer with low power and high reliability. This accelerometer comprises a heater and two thermistors. The central heater elevates the temperature of the chip above ambient levels while the symmetrically arranged thermistors monitor the temperature differentials induced by acceleration. The heater and thermistors are fabricated on a glass substrate using a standard micro-electromechanical systems (MEMS) process flow, and the fabricated sensor is installed on a rotation platform and a shaking table experimental setup to perform the experiment. The results indicate that the sensor has the capability to measure accelerations surpassing 80 m/s2, with an approximate linear sensitivity of 110.69 mV/g. This proposed thermal convective accelerometer offers promising potential for various applications requiring precise acceleration measurements in environments where low power consumption and high reliability are paramount.
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INTRODUCTION: This prospective, longitudinal, community-based study, EpidemiologiCal POpulatioN STudy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Lake CounTy, Illinois (CONTACT), investigated coronavirus disease 2019 (COVID-19) immunity, occupational risks related to SARS-CoV-2 exposure, and long-term immunoglobulin G (IgG) seroconversion kinetics. METHODS: At baseline and follow up (3, 6, and 9 months), non-hospitalized adult participants provided nasal and blood serum specimens for molecular [reverse transcription polymerase chain reaction (RT-PCR)] and serological (IgG) testing (4 November 2020-30 October 2021). RESULTS: At baseline, 6.4% (65/1008) had evidence of current/prior SARS-CoV-2 infection. At 3, 6, and 9 months, positive PCR tests were obtained from 0.4% (3/781), 0.4% (3/733), and 0% (0/673) of participants, respectively. Positive IgG occurred at baseline and 3, 6, and 9 months in 4.5% (45/1008), 6.0% (48/799), 5.4% (39/733), and 2.8% (19/673) of participants, respectively. Of participants positive for IgG at baseline, 28 had a negative IgG test at a follow-up visit; of those 28, 21 had their first negative IgG test within 6 months. Participants were more likely to retain positive IgG if they were 18-29 years of age, were male, or had medium-high/high-risk occupations. A high vaccination rate (70% received ≥ 1 dose by 9 months) was observed. Influence of occupational status or characteristics on transmission and IgG, and COVID-19 vaccination trends, are shown. CONCLUSIONS: This study expands on prior studies assessing COVID-19 immunity and IgG seroconversion by including both RT-PCR and serologic testing and longitudinal follow-up of study participants. We observed decreased infection rates over the 9 month follow-up period as well as a decline in IgG persistency after 6 months. The findings from this community-based study regarding vaccinate rates, infection rates by PCR, and IgG persistency over time can help improve our understanding of COVID-19 immunity, occupational risks related to SARS-CoV-2 exposure, and the kinetics of long-term IgG seroconversion, which is important to help guide local and national mitigation strategies. CLINICAL TRIAL REGISTRATION: NCT04611230.
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INTRODUCTION: Ascending aorta or hemi-arch replacement is a frequently used treatment for patients with acute type A thoracic aortic dissection, particularly those who are elderly or have multiple comorbidities. However, in cases where there are secondary entry tears in the aortic arch or descending aorta, this procedure may not fully resolve the issue. The true lumen may remain compressed due to perfusion of the false lumen and usually require reoperation. METHODS: Between January 2019 and July 2022, 18 patients underwent endovascular total aortic arch repair and fenestration technique without requiring median re-sternotomy. Aortic stent grafts were implanted via the femoral approach, utilizing prosthetic vessels as an appropriate proximal landing zone for aortic stent graft deployment. Based on the debranching conditions of the arch in previous surgery, single, double or triple in situ fenestrations (ISFs) were performed, respectively. RESULTS: All 18 cases were technically successful, with a median follow-up period of 20 months (range: 18-31 months). All patients had a favourable postoperative course, with no deaths within 30 days or during their hospital stay. There were no instances of disabling stroke, paraplegia, endo-leak, stent graft migration or stent graft-induced new entry. In addition, all patients exhibited complete thrombosis of the false lumen at the level of the aortic arch. CONCLUSION: Our preliminary experience suggests that endovascular total arch repair combined with ISF technique is a viable, effective and safe option for treatment. Our mid-term results have been promising, but we acknowledge the need for further evaluation to assess long-term outcomes and durability.
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Aortic Aneurysm, Thoracic , Aortic Dissection , Blood Vessel Prosthesis Implantation , Endovascular Procedures , Humans , Aged , Blood Vessel Prosthesis , Aortic Aneurysm, Thoracic/diagnostic imaging , Aortic Aneurysm, Thoracic/surgery , Aortic Aneurysm, Thoracic/etiology , Blood Vessel Prosthesis Implantation/adverse effects , Blood Vessel Prosthesis Implantation/methods , Treatment Outcome , Aortic Dissection/diagnostic imaging , Aortic Dissection/surgery , Stents , Aorta, Thoracic/diagnostic imaging , Aorta, Thoracic/surgery , Retrospective Studies , Prosthesis DesignABSTRACT
INTRODUCTION: To evaluate factors associated with severe coronavirus disease 2019 (COVID-19) among patients with rheumatoid arthritis (RA) in the US. METHODS: Adults with RA who had a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, based on molecular or antigen test or clinical diagnosis, were identified from the Optum® COVID-19 Electronic Health Record dataset (March 1, 2020-April 28, 2021). The primary outcome was the occurrence of severe COVID-19 (hospitalization or death) within 30 days from SARS-CoV-2 infection. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression models to assess the association between severe COVID-19 and patient characteristics, including demographics, baseline comorbidities, and recent RA treatments. RESULTS: During the study period, 6769 SARS-CoV-2 infections were identified in patients with RA, among whom 1460 (22%) developed severe COVID-19. Multivariable logistic regression analysis showed that being older, male, and non-White and having diabetes and cardiovascular conditions are associated with greater odds of severe COVID-19. In addition, compared with no use, the adjusted odds of severe COVID-19 were lower with recent use of tumor necrosis factor inhibitors (aOR 0.60, 95% CI 0.41-0.86) and higher with recent use of corticosteroids (aOR 1.38, 95% CI 1.13-1.69) or rituximab (aOR 2.87, 95% CI 1.60-5.14), respectively. CONCLUSION: Nearly one in five patients with RA developed severe COVID-19 disease within 30 days after SARS-CoV-2 infection. In patients with RA, recent use of corticosteroids and rituximab were two factors associated with a greater risk of severe COVID-19 in addition to the risk factors among demographics and comorbidities previously identified in the general population.
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Arthritis, Rheumatoid , COVID-19 , Adult , Humans , Male , United States/epidemiology , SARS-CoV-2 , Cohort Studies , Rituximab , Electronic Health Records , Arthritis, Rheumatoid/complications , Arthritis, Rheumatoid/drug therapy , Arthritis, Rheumatoid/epidemiology , Adrenal Cortex Hormones/therapeutic useABSTRACT
INTRODUCTION: There are concerns that patients in an immunocompromised state may be at risk for increased coronavirus disease 2019 (COVID-19) severity. The aim of this study was to describe the characteristics of patients with COVID-19 and immune-mediated inflammatory diseases (IMIDs) or malignancies and evaluate their risk of developing severe COVID-19. METHODS: Cases of COVID-19 (ICD-10 code U07.1 or U07.2, or positive polymerase chain reaction or antigen test) among patients with IMIDs or malignancies were identified in the US-based Optum® Electronic Health Records database between 1 February 2020 and 3 March 2021. Age- and sex-standardized risks of severe COVID-19 were calculated by condition of interest. The risks were further adjusted by multiple covariates, and 95% confidence intervals were estimated. RESULTS: A total of 499,772 patients with COVID-19 were identified (mean [SD] age, 46.9 [20.7] years; 57.0% female). Patients with hematologic cancers (adjusted risk ratio [aRR] 2.0, 1.8-2.1), solid tumors (aRR 1.1, 1.1-1.1), or rheumatoid arthritis (aRR 1.2, 1.1-1.3) had a significantly higher risk of severe COVID-19 compared to the general population of patients with COVID-19. Patients with systemic lupus erythematosus (aRR 1.1, 0.9-1.2), psoriasis (aRR 1.0, 0.7-1.2), ulcerative colitis (aRR 0.9, 0.8-1.1), Crohn's disease (aRR 0.9, 0.7-1.0), or ankylosing spondylitis (aRR 0.8, 0.5-1.0) showed a comparable risk of severe COVID-19. Patients with atopic dermatitis (aRR 0.8, 0.7-0.9) or psoriatic arthritis (aRR 0.8, 0.6-1.0) showed a lower risk of severe COVID-19. CONCLUSIONS: The risk of developing severe COVID-19 varied between the studied IMIDs and malignancies. Patients with hematologic cancers, solid tumors, or rheumatoid arthritis had significantly increased risk for severe COVID-19 compared to the general population. These findings highlight the need to protect and monitor immunocompromised patients such as those with IMIDs or malignancies as part of the strategy to control the pandemic worldwide.
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Arthritis, Rheumatoid , COVID-19 , Hematologic Neoplasms , Neoplasms , Humans , Female , United States/epidemiology , Middle Aged , Male , COVID-19/epidemiology , Retrospective Studies , Arthritis, Rheumatoid/complications , Arthritis, Rheumatoid/drug therapy , Arthritis, Rheumatoid/epidemiology , Neoplasms/epidemiology , Hematologic Neoplasms/epidemiologyABSTRACT
Urokinase is widely used in the dissolution of an acute pulmonary embolism due to its high biocatalytic effect. However, how to precisely regulate its dose, avoid the side effects of hemolysis or ineffective thrombolysis caused by too high or too low a dose, and seize the golden time of acute pulmonary embolism are the key factors for its clinical promotion. Therefore, based on the precise design of a molecular structure, an ultrasonic-responsive nanoliposome capsule was prepared in this paper. Singlet oxygen is continuously generated under the interaction of the ultrasonic cavitation effect and the sonosensitizer protoporphyrin, and the generated singlet oxygen will break the thiol acetone bond between the hydrophilic head and the hydrophobic tail of the liposome, and the lipid The body structure disintegrates rapidly, and the urokinase encapsulated inside is rapidly released, down-regulating the expression of fibrinogen in the body, and exerting a thrombolytic function. The in vitro and in vivo results show that the smart urokinase nanoliposomes prepared by us have sensitive and responsive cytocompatibility to ultrasound and good in vivo thrombolytic properties for acute pulmonary embolism, which provides a new strategy for clinical acute pulmonary embolism thrombolysis.
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PURPOSE: Supplementing investigator-specified variables with large numbers of empirically identified features that collectively serve as 'proxies' for unspecified or unmeasured factors can often improve confounding control in studies utilizing administrative healthcare databases. Consequently, there has been a recent focus on the development of data-driven methods for high-dimensional proxy confounder adjustment in pharmacoepidemiologic research. In this paper, we survey current approaches and recent advancements for high-dimensional proxy confounder adjustment in healthcare database studies. METHODS: We discuss considerations underpinning three areas for high-dimensional proxy confounder adjustment: (1) feature generation-transforming raw data into covariates (or features) to be used for proxy adjustment; (2) covariate prioritization, selection, and adjustment; and (3) diagnostic assessment. We discuss challenges and avenues of future development within each area. RESULTS: There is a large literature on methods for high-dimensional confounder prioritization/selection, but relatively little has been written on best practices for feature generation and diagnostic assessment. Consequently, these areas have particular limitations and challenges. CONCLUSIONS: There is a growing body of evidence showing that machine-learning algorithms for high-dimensional proxy-confounder adjustment can supplement investigator-specified variables to improve confounding control compared to adjustment based on investigator-specified variables alone. However, more research is needed on best practices for feature generation and diagnostic assessment when applying methods for high-dimensional proxy confounder adjustment in pharmacoepidemiologic studies.
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Machine Learning , Pharmacoepidemiology , Confounding Factors, Epidemiologic , Databases, Factual , Delivery of Health Care , HumansABSTRACT
In this paper, the effect of wind-induced vibration on measurement range of microcantilever anemometer is investigated for the first time. The microcantilever anemometer is composed of a flexible substrate and a piezoresistor. The wind speed can be detected through the airflow-induced deformation in the flexible substrate. Previous work indicated that the flexible substrate vibrates violently once the wind speed exceeds a critical value, resulting in severe output jitter. This wind-induced vibration limits the measurement range of the anemometer, and the relationship between the anemometer measurement range and its structural parameters has not been explored systematically. Therefore, this paper aims to reveal this relationship theoretically and experimentally, demonstrating that a shorter and thicker cantilever with larger stiffness can effectively suppress the wind-induced vibration, leading to the critical speed rising. By eliminating the wind-induced vibration, the measurement range of the microcantilever anemometer can be increased by up to 697%. These results presented in this paper can pave the way for the design and fabrication of wide-range mechanical anemometers.
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As the scientific research community along with healthcare professionals and decision makers around the world fight tirelessly against the coronavirus disease 2019 (COVID-19) pandemic, the need for comparative effectiveness research (CER) on preventive and therapeutic interventions for COVID-19 is immense. Randomized controlled trials markedly under-represent the frail and complex patients seen in routine care, and they do not typically have data on long-term treatment effects. The increasing availability of electronic health records (EHRs) for clinical research offers the opportunity to generate timely real-world evidence reflective of routine care for optimal management of COVID-19. However, there are many potential threats to the validity of CER based on EHR data that are not originally generated for research purposes. To ensure unbiased and robust results, we need high-quality healthcare databases, rigorous study designs, and proper implementation of appropriate statistical methods. We aimed to describe opportunities and challenges in EHR-based CER for COVID-19-related questions and to introduce best practices in pharmacoepidemiology to minimize potential biases. We structured our discussion into the following topics: (1) study population identification based on exposure status; (2) ascertainment of outcomes; (3) common biases and potential solutions; and (iv) data operational challenges specific to COVID-19 CER using EHRs. We provide structured guidance for the proper conduct and appraisal of drug and vaccine effectiveness and safety research using EHR data for the pandemic. This paper is endorsed by the International Society for Pharmacoepidemiology (ISPE).
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COVID-19 , Comparative Effectiveness Research , Humans , Comparative Effectiveness Research/methods , Electronic Health Records , Pharmacoepidemiology , Pandemics/prevention & controlABSTRACT
INTRODUCTION: EpidemiologiCal POpulatioN STudy of SARS-CoV-2 in Lake CounTy, Illinois (CONTACT) is an observational, epidemiological study with a 9-month longitudinal follow-up of nonhospitalized persons aged 18 years or older currently living or employed in Lake County, IL. We describe the study design and report baseline characteristics of the study participants, including the proportion of participants with acute or previous SARS-CoV-2 infection at enrollment. METHODS: At enrollment and subsequent timepoints, participants recruited through digital and paper-based advertising campaigns reported their occupational and school-based exposure, risk factors, and behaviors, and provided nasal and serum specimens. Stratified enrichment was used to enhance enrollment into medium- and higher-risk groups within four occupational risk groups for SARS-CoV-2 infection. RT-PCR and serologic (IgG) testing were conducted to detect acute or previous SARS-CoV-2 infection in participants, respectively. RESULTS: Between November 2020 and January 2021, 1008 participants (female 70.7%, mean age ± SD 51 ± 13.8 years) completed the questionnaire and diagnostic testing. Among participants, 41.8% (n = 421) were considered low risk, 24.6% (n = 248) were medium-to-low risk, 22.3% (n = 225) were medium-to-high risk, and 11.3% (n = 114) were high risk. Of 56 (5.6%) participants with evidence of acute or previous SARS-CoV-2 infection at baseline, 11 (19.6%) were RT-PCR-positive, 36 (64.3%) were IgG-seropositive, and 9 (16.1%) were positive by both assays. Participants who were adherent vs nonadherent to social distancing measures (odds ratio [95% CI] 0.8 [0.4-1.8]) were less likely, while those in higher vs lower occupational risk groups (2.0 [1.0-4.4]) were more likely to have evidence for acute or previous SARS-CoV-2 infection. CONCLUSION: In fall/winter 2020/21, 5.6% of adults in a Lake County convenience sample had evidence for acute or previous SARS-CoV-2 infection at baseline. Nonadherence to social distancing measures and high-risk professions were associated with SARS-CoV-2 infection. The study is ongoing and future analyses will assess infection status over time. CLINICAL TRIAL REGISTRATION: NCT04611230.
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An important step of somatic variant calling algorithms for deep sequencing data is quantifying the errors. For targeted sequencing in which hotspot mutations are of interest, site-specific error estimation allows more accurate calling. The site-specific error rates are often estimated from a panel of normal samples, which has limited size and is subject to sampling bias and variance. We propose a novel statistical validation method for single-nucleotide variation (SNV) calling based on historical data. The validation method extracts the high-quality reads from the Binary Alignment/Map (BAM) files, finds the negative samples in the data, and builds a statistical model to call individual samples. It is particularly useful in detecting low-frequency variants that may be missed by traditional panel of normal-based SNV methods. The proposed method makes it possible to launch a simple and parallel validation pipeline for SNV calling and improve the detection limit.
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High-Throughput Nucleotide Sequencing , Neoplasms , Algorithms , High-Throughput Nucleotide Sequencing/methods , Humans , Neoplasms/diagnosis , Neoplasms/genetics , Nucleotides , Polymorphism, Single Nucleotide/genetics , Retrospective StudiesABSTRACT
Background: Nosocomial infection (NI) prolongs hospital stay and heightens mortality among patients who underwent cardiac surgery. We constructed a retrospective study to explore the prevalence of Staphylococcus aureus and methicillin-resistant Staphylococcus aureus (SA/MRSA) nasal colonization, as well as the effects of SA/MRSA decolonization bundle measures on SA/MRSA-related infection among Chinese cardiac patients. Methods: After reviewing the medical records, we divided cardiovascular surgery patients treated at our central campus into two groups: the baseline group (treated between January 2012 and December 2013) and the intervention group (treated between May 2014 and December 2020). Intervention measures consisted of preoperative nasal screening and targeted decolonization bundle therapy. The medical records of patients at our southern campus (treated between January 2017 and December 2020) were collected as an additional control group, since we did not implement SA intervention measures at this location. The incidences of SA/MRSA-related NI were then compared between the groups. Results: There were 794 patients in the baseline group and 2,826 in the intervention group. A total of 131 (4.6%) patients had SA nasal colonization, and among them, 33 patients (1.2%) were MRSA colonized. SA/MRSA was cleared in approximately 95% of the carriers. The total level of SA-related infection was significantly lower in the intervention group compared to the baseline group [0.354% vs. 1.133%, respectively; P=0.021; risk ratio (RR): 0.312; 95% confidence interval (CI): 0.127-0.766]. The incidence of MRSA-related infection followed the same trend (0.212% vs. 0.756%, respectively; P=0.030; RR: 0.281; 95% CI: 0.091-0.860). When compared to the southern campus, SA intervention measures at the central campus resulted in a significant reduction in total SA-related infection (1.132% vs. 0.284%, respectively; P=0.035; RR: 0.251; 95% CI: 0.077-0.820). Conclusions: The prevalence of SA/MRSA colonization is relatively low among Chinese patients who received cardiovascular surgery. Targeted decolonization bundle therapy was associated with cleared colonization and reduced incidence of SA/MRSA-related infection.
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BACKGROUND & AIMS: Although gastroparesis carries a considerable health care and patient burden, associated epidemiological data are limited. To provide new real-world evidence for gastroparesis, we estimated disease prevalence, and investigated patient demographics and disease etiology in a large US claims database. METHODS: This retrospective, cross-sectional analysis used de-identified, longitudinal patient-level enrollment and billing data for adults from the Optum Clinformatics Data Mart database, a large US national administrative health insurance claims database. Prevalence was age-, sex-, and geographical region-standardized using the 2018 US census. Descriptive analyses of demographic and clinical variables and underlying disease etiologies were performed. RESULTS: The overall standardized prevalence of gastroparesis was 267.7 (95% confidence interval [CI] 264.8-270.7) per 100,000 US adults, whereas prevalence of "definite" gastroparesis (individuals diagnosed within 3 months of gastric emptying scintigraphy testing with persistent symptoms for more than 3 months) was 21.5 (95% CI 20.6-22.4) per 100,000 persons. Patients with gastroparesis had an overall Charlson Comorbidity Index score of 4.2, indicating substantial comorbidity burden. The most frequently documented comorbidities were chronic pulmonary disease (46.4%), diabetes with chronic complication (37.3%), and peripheral vascular disease (30.4%). Patients most commonly had a diabetic etiology (57.4%; type 1, 5.7% and type 2, 51.7%), followed by postsurgical (15.0%), drug-induced (11.8%), and idiopathic (11.3%) etiologies. CONCLUSIONS: New evidence is provided regarding the prevalence, patient demographics, and etiology of gastroparesis in the US general population. Wider availability of reliable objective gastric emptying measures and further education of medical professionals in recognizing and diagnosing gastroparesis would benefit future studies and improve understanding of disease epidemiology.
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Gastroparesis/epidemiology , Administrative Claims, Healthcare , Adolescent , Adult , Age Factors , Aged , Comorbidity , Cross-Sectional Studies , Databases, Factual , Female , Gastric Emptying , Gastroparesis/diagnosis , Gastroparesis/physiopathology , Gastroparesis/therapy , Humans , Male , Middle Aged , Predictive Value of Tests , Prevalence , Retrospective Studies , Risk Assessment , Risk Factors , Sex Factors , Time Factors , Treatment Outcome , United States , Young AdultABSTRACT
ABSTRACT: In precision oncology, immune check point blockade therapy has quickly emerged as novel strategy by its efficacy, where programmed death ligand 1 (PD-L1) expression is used as a clinically validated predictive biomarker of response for the therapy. Automating pathological image analysis and accelerating pathology evaluation is becoming an unmet need. Artificial Intelligence and deep learning tools in digital pathology have been studied in order to evaluate PD-L1 expression in PD-L1 immunohistochemistry image. We proposed a Dual-scale Categorization (DSC)-based deep learning method that employed 2 VGG16 neural networks, 1 network for 1 scale, to critically evaluate PD-L1 expression. The DSC-based deep learning method was tested in a cohort of 110 patients diagnosed as non-small cell lung cancer. This method showed a concordance of 88% with pathologist, which was higher than concordance of 83% of 1-scale categorization-based method. Our results show that the DSCbased method can empower the deep learning application in digital pathology and facilitate computer-aided diagnosis.
Subject(s)
B7-H1 Antigen/analysis , Biomarkers, Tumor/analysis , Carcinoma, Non-Small-Cell Lung/diagnosis , Diagnosis, Computer-Assisted/methods , Lung Neoplasms/diagnosis , B7-H1 Antigen/antagonists & inhibitors , B7-H1 Antigen/genetics , Biomarkers, Tumor/antagonists & inhibitors , Biomarkers, Tumor/genetics , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/genetics , Carcinoma, Non-Small-Cell Lung/pathology , Deep Learning , Gene Expression Regulation, Neoplastic , Humans , Immune Checkpoint Inhibitors/pharmacology , Immune Checkpoint Inhibitors/therapeutic use , Immunohistochemistry , Lung/immunology , Lung/pathology , Lung Neoplasms/drug therapy , Lung Neoplasms/genetics , Lung Neoplasms/pathology , Patient Selection , Precision Medicine/methodsABSTRACT
With the great progress made recently in next generation sequencing (NGS) technology, sequencing accuracy and throughput have increased, while the cost for data has decreased. Various human leukocyte antigen (HLA) typing algorithms and assays have been developed and have begun to be used in clinical practice. In this study, we compared the HLA typing performance of three HLA assays and seven NGS-based HLA algorithms and assessed the impact of sequencing depth and length on HLA typing accuracy based on 24 benchmarked samples. The algorithms HISAT-genotype and HLA-HD showed the highest accuracy at both the first field and the second field resolution, followed by HLAscan. Our internal capture-based HLA assay showed comparable performance with whole exome sequencing (WES). We found that the minimal depth was 100X for HISAT-genotype and HLA-HD to obtain more than 90% accuracy at the third field level. The top three algorithms were quite robust to the change of read length. Thus, we recommend using HISAT-genotype and HLA-HD for NGS-based HLA genotyping because of their higher accuracy and robustness to read length. We propose that a minimal sequence depth for obtaining more than 90% HLA typing accuracy at the third field level is 100X. Besides, targeting capture-based NGS HLA typing may be more suitable than WES in clinical practice due to its lower sequencing cost and higher HLA sequencing depth.
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Algorithms , HLA Antigens/genetics , HLA Antigens/immunology , High-Throughput Nucleotide Sequencing/methods , Histocompatibility Testing/methods , Alleles , Computational Biology/methods , Genotype , High-Throughput Nucleotide Sequencing/standards , Histocompatibility Testing/standards , Humans , Reproducibility of Results , Sequence Analysis, DNA , SoftwareABSTRACT
OBJECTIVE: To generate real-world evidence for the epidemiology of gastroparesis in the UK, we evaluated the prevalence, incidence, patient characteristics and outcomes of gastroparesis in the Clinical Practice Research Datalink (CPRD) database. DESIGN: This was a retrospective, cross-sectional study. Prevalence and incidence of gastroparesis were evaluated in the CPRD database, with linkage to Hospital Episodes Statistics Admitted Patient Care and Office for National Statistics mortality data. Prevalence and incidence were age and sex standardised to mid-2017 UK population estimates. Descriptive analyses of demographics, aetiologies, pharmacological therapies and mortality were conducted. RESULTS: Standardised prevalence of gastroparesis, as documented in general practice records, was 13.8 (95% CI 12.6 to 15.1) per 100 000 persons in 2016, and standardised incidence of gastroparesis rose from 1.5 (95% CI 1.1 to 1.8) per 100 000 person-years in 2004 to 1.9 (95% CI 1.4 to 2.3) per 100 000 person-years in 2016. The most common disease aetiologies were idiopathic (39.4%) and diabetic gastroparesis (37.5%), with a similar distribution of type 1 and type 2 diabetes among the 90% who had type of diabetes documented. Patients with diabetic gastroparesis had a significantly higher risk of mortality than those with idiopathic gastroparesis after diagnosis (adjusted HR 1.9, 95% CI 1.2 to 3.0). Of those with gastroparesis, 31.6% were not offered any recognised pharmacological therapy after diagnosis. CONCLUSION: This is, to our knowledge, the first population-based study providing data on epidemiology and outcomes of gastroparesis in Europe. Further research is required to fully understand the factors influencing outcomes and survival of patients with gastroparesis.
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Gastroparesis/epidemiology , General Practice , Cross-Sectional Studies , Female , Gastrointestinal Agents/therapeutic use , Gastroparesis/drug therapy , Gastroparesis/etiology , Humans , Incidence , Male , Middle Aged , Prevalence , Retrospective Studies , United Kingdom/epidemiologyABSTRACT
Ecdysteroids, insect steroid hormones, play key roles in regulating insect development and reproduction. Hemipteran insects require ecdysteroids for egg production; however, ecdysteroid synthesis (ecdysteroidogenesis) details have not been elucidated. We identified all known genes encoding ecdysteroidogenic enzymes in Nilaparvata lugens and clarified their necessity during nymphal and ovarian development. We confirmed that N. lugens utilized 20-hydroxyecdysone as an active hormone. Assays using heterologous expression of enzymes in Drosophila S2 cells showed conserved functions of enzymes Neverland, CYP306A2, CYP314A1 and CYP315A1, but not CYP302A1. RNA interference and rescue analysis using 20-hydroxyecdysone demonstrated that most of the genes were necessary for nymphal development. The identified N. lugens enzymes showed conserved functions and pathways for ecdysteroidogenesis. Knockdown of ecdysteroidogenic enzyme genes in newly molted females caused failure of egg production: less vitellogenic and mature eggs in ovaries, fewer laid eggs and embryonic development deficiency of laid eggs. Considering the high expressions of ecdysteroidogenic enzyme genes in adults and ovaries, ecdysteroidogenesis in ovaries was critical for N. lugens ovarian development. Our study presents initial evidence that hemipteran insects require ecdysteroidogenesis for ovarian development.
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Ecdysteroids , Hemiptera/metabolism , Animals , Ecdysteroids/biosynthesis , Ecdysteroids/genetics , Ecdysteroids/metabolism , Ecdysterone/biosynthesis , Ecdysterone/genetics , Ecdysterone/metabolism , Female , Gene Expression Regulation, Developmental , Gene Knockdown Techniques , Genes, Insect , Hemiptera/embryology , Hemiptera/growth & development , Insect Proteins/metabolism , Molting/genetics , Nymph/growth & development , Nymph/metabolism , Ovary/growth & development , Ovary/metabolism , Oviposition/geneticsSubject(s)
Gastroparesis , Databases, Factual , Hospitalization , Humans , Prevalence , Retrospective Studies , United StatesABSTRACT
BACKGROUND: The latest estimate of the prevalence of inflammatory bowel disease (IBD) in the United States was based on 2009 data, which indicates a need for an up-to-date re-estimation. The objectives of this study were to investigate the prevalence of all forms of IBD including ulcerative colitis (UC), Crohn's disease (CD), and IBD unspecified (IBDU). METHODS: Pediatric (age 2-17) and adult (age ≥18) IBD patients were identified from 2 large claims databases. For each year between 2007 and 2016, prevalence was calculated per 100,000 population and standardized based on the 2016 national Census. A fixed-effects meta-analytical model was used for overall prevalence. RESULTS: The pediatric prevalence of IBD overall increased by 133%, from 33.0/100,000 in 2007 to 77.0/100,000 in 2016. Among children, CD was twice as prevalent as UC (45.9 vs 21.6). Prevalence was higher in boys than girls for all forms of IBD, in contrast to the adult population where the prevalence was higher in women than men. We also found that the 10-17 age subgroup was the major contributor to the rising pediatric IBD prevalence. For adults, the prevalence of IBD overall increased by 123%, from 214.9 in 2007 to 478.4 in 2016. The prevalence rates of UC and CD were similar (181.1 vs 197.7) in 2016. CONCLUSIONS: Inflammatory bowel disease continues to affect a substantial proportion of the US population. In 2016, 1 in 209 adults and 1 in 1299 children aged 2-17 were affected by IBD. Prevalence of IBD has been increasing compared with previously published 2009 data.
Subject(s)
Colitis, Ulcerative/epidemiology , Crohn Disease/epidemiology , Inflammatory Bowel Diseases/epidemiology , Adolescent , Adult , Age Factors , Aged , Aged, 80 and over , Child , Child, Preschool , Cross-Sectional Studies , Databases, Factual , Female , Forecasting , Humans , Male , Middle Aged , Prevalence , Retrospective Studies , United States/epidemiology , Young AdultABSTRACT
Application of selective algorithms to administrative health claims databases allows detection of specific patients and disease or treatment outcomes. This study identified and applied different algorithms to a single data set to compare the numbers of patients with different inflammatory bowel disease classifications identified by each algorithm. A literature review was performed to identify algorithms developed to define inflammatory bowel disease patients, including ulcerative colitis, Crohn's disease, and inflammatory bowel disease unspecified in routinely collected administrative claims databases. Based on the study population, validation methods, and results, selected algorithms were applied to the Optum Clinformatics® Data Mart database from June 2000 to March 2017. The patient cohorts identified by each algorithm were compared. Three different algorithms were identified from literature review and selected for comparison (A, B, and C). Each identified different numbers of patients with any form of inflammatory bowel disease (323 833; 246 953, and 171 537 patients, respectively). The proportions of patients with ulcerative colitis, Crohn's disease, and inflammatory bowel disease unspecified were 32.0% to 47.5%, 38.6% to 43.8%, and 8.7% to 26.6% of the total population with inflammatory bowel disease, respectively, depending on the algorithm applied. Only 5.1% of patients with inflammatory bowel disease unspecified were identified by all 3 algorithms. Algorithm C identified the smallest cohort for each disease category except inflammatory bowel disease unspecified. This study is the first to compare numbers of inflammatory bowel disease patients identified by different algorithms from a single database. The differences between results highlight the need for validation of algorithms to accurately identify inflammatory bowel disease patients.