Prediction of Process Quality Performance Using Statistical Analysis and Long Short-Term Memory

In the manufacturing industry, the process capability index (Cpk) measures the level and capability required to improve the processes. However, the Cpk is not enough to represent the process capability and performance of the manufacturing processes. In other words, considering that the smart manufacturing environment can accommodate the big data collected from various facilities, we need to understand the state of the process by comprehensively considering diverse factors contained in the manufacturing. In this paper, a two-stage method is proposed to analyze the process quality performance (PQP) and predict future process quality. First, we propose the PQP as a new measure for representing process capability and performance, which is defined by a composite statistical process analysis of such factors as manufacturing cycle time analysis, process trajectory of abnormal detection, statistical process control analysis, and process capability control analysis. Second, PQP analysis results are used to predict and estimate the stability of the production process using a long short-term memory (LSTM) neural network, which is a deep learning algorithm-based method. The present work compares the LSTM prediction model with the random forest, autoregressive integrated moving average, and artificial neural network models to convincingly demonstrate the effectiveness of our proposed approach. Notably, the LSTM model achieved higher accuracy than the other models.

Pharmacoepidemiology in pregnancy: analysis protocol for an observational cohort study in the UK Clinical Practice Research Datalink

Large numbers of women take prescription and over-the-counter medications during pregnancy. However, there is very little definitive evidence about the potential effects of these drugs on the mothers and offspring. We will investigate the risks and benefits of continuing prescriptive drug use for chronic pre-existing maternal conditions such as diabetes, hypertension and thyroid related conditions throughout pregnancy. If left untreated, these conditions are established risk factors for adverse neonatal and maternal outcomes. However, some treatments for these conditions are associated with adverse neonatal outcomes. Our primary aims are twofold. Firstly, we aim to estimate the beneficial effect on the mother of continuing treatment during pregnancy. Second, we aim to determine whether there is an associated detrimental impact on the neonate of continuation of maternal treatment during pregnancy. To establish this evidence, we will investigate the relationship between maternal drug prescriptions and adverse and beneficial offspring outcomes to provide evidence to guide clinical decisions. We will conduct a hypothesis testing observational intergenerational cohort study using data from the UK Clinical Practice Research Datalink (CPRD). We will apply four statistical methods: multivariable adjusted regression, propensity score regression, instrumental variables analysis and negative control analysis. These methods should account for potential confounding when estimating the association between the drug exposure and maternal or neonatal outcome. In this protocol we describe the aims, motivation, study design, cohort and statistical analyses of our study to aid reproducibility and transparency within research.

Germline predisposition to pediatric Ewing sarcoma is uniquely characterized by inherited pathogenic variants in DNA damage repair genes

More knowledge is needed around the role and importance of specific genes in germline predisposition to Ewing sarcoma to inform biological investigation and clinical practice. In this study, we evaluated the enrichment of pathogenic germline variants in Ewing sarcoma relative to other pediatric sarcoma subtypes, as well as patterns of inheritance of these variants. We carried out an ancestry-matched case-control analysis to screen for enrichment of pathogenic germline variants in 141 established cancer predisposition genes in 1138 individuals with pediatric sarcoma diagnoses (222 Ewing sarcoma cases) relative to identically processed cancer-free controls. Findings in Ewing sarcoma were validated with an additional cohort of 425 individuals, and 301 Ewing sarcoma parent-proband trios were analyzed for inheritance patterns of identified pathogenic variants. A distinct pattern of pathogenic germline variants was seen in Ewing sarcoma relative to other sarcoma subtypes. FANCC was the only gene with an enrichment signal for heterozygous pathogenic variants in the discovery Ewing sarcoma cohort (OR 14.4, 95% CI 3.5 - 51.2, p = 0.002, FDR = 0.28). This enrichment in FANCC heterozygous pathogenic variants was seen again in the Ewing sarcoma validation cohort (OR 5.1, 95% CI 1.2 - 18.5, p = 0.03, single hypothesis), representing a broader importance of genes involved in DNA damage repair, which were also nominally enriched in Ewing sarcoma cases. Pathogenic variants in DNA damage repair genes were acquired through autosomal inheritance. Our study provides new insight into germline risk factors contributing to Ewing sarcoma pathogenesis.

Disparities in Outcomes Among Patients Diagnosed With Cancer in Proximity to an Emergency Department Visit

A suspected diagnosis of cancer in the emergency department (ED) may be associated with poor outcomes, related to health disparities, however data are limited. This study is a case-control analysis of the Indiana State Department of Health Cancer Registry, and the Indiana Network for Patient Care. First time cancer diagnoses appearing in the registry between January 2013 and December 2017 were included. Cases were patients who had an ED visit in the 6 months before their cancer diagnosis; controls had no recent ED visits. The primary outcome was mortality, comparing ED-associated mortality to non-ED-associated. 134,761 first-time cancer patients were identified, including 15,432 (11.5%) cases. The mean age was same at 65, more of the cases were Black than the controls (12.4% vs 7.4%, P<.0001) and more were low income (36.4%. vs 29.3%). The top 3 ED-associated cancer diagnoses were lung (18.4%), breast (8.9%), and colorectal cancers (8.9%), whereas the controls were breast (17%), lung (14.9%), and prostate cancers (10.1%). Cases observed an over three-fold higher mortality, with cumulative death rate of 32.9% for cases vs 9.0% for controls (P<.0001). Regression analysis predicting mortality, controlling for many confounders produced an odds ratio of 4.12 (95% CI 3.72-4.56 for cases). This study found that an ED visit within 6 months prior to the first time of ICD-coded cancer is associated with Black race, low income and an overall three-fold increased adjusted risk of death. The mortality rates for ED-associated cancers are uniformly worse for all cancer types. These data suggest that additional work is needed to reduce disparities among ED-associated cancer diagnoses.

Estimating the impact of donor programs on child mortality in low- and middle-income countries: a synthetic control analysis of child health programs funded by the United States Agency for International Development

Background Significant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the USA and the UK. Direct attribution of impact to large-scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. Methods This study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. Results In the study period (2000–16), countries with above average USAID funding had an under-five mortality rate lower than the synthetic control by an average of 29 deaths per 1000 live births (year-to-year range of − 2 to − 38). This finding was consistent with several sensitivity analyses. Conclusions The synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

Association between glycemic control and risk of venous thromboembolism in diabetic patients: a nested case–control study

Background Previous studies suggested an elevated risk of venous thromboembolism (VTE) among patients with type 2 diabetes mellitus (T2DM), with a possible sex difference. The impact of glycemic control on the risk of VTE is unclear. Our objective was to analyze the association between glycemic control and the risk of unprovoked (idiopathic) VTE in men and women with T2DM. Methods We conducted a nested case–control analysis (1:4 matching) within a cohort of patients with incident T2DM between 1995 and 2019 using data from the CPRD GOLD. We excluded patients with known risk factors for VTE prior to onset of DM. Cases were T2DM patients with an unprovoked treated VTE. The exposure of interest was glycemic control measured as HbA1c levels. We conducted conditional logistic regression analyses adjusted for several confounders. Results We identified 2′653 VTE cases and 10′612 controls (53.1% females). We found no association between the HbA1c level and the risk of VTE in our analyses. However, when the most recent HbA1c value was recorded within 90 days before the index date, women with HbA1c levels > 7.0% had a 36–55% increased relative risk of VTE when compared to women with HbA1c > 6.5–7.0%. Conclusions Our study raises the possibility that female T2DM patients with HbA1c levels > 7% may have a slightly higher risk for unprovoked VTE compared to women with HbA1c levels > 6.5–7.0%. This increase may not be causal and may reflect differences in life style or other characteristics. We observed no effect of glycemic control on the risk of VTE in men.

Streptococcus agalactiae infective endocarditis in Canada: a multicenter retrospective nested case control analysis

Background Infective endocarditis (IE) caused by Streptococcus agalactiae (GBS) is increasingly reported and associated with an aggressive course and high mortality rate. Existing literature on GBS IE is limited to case series; we compared the characteristics of patients with GBS IE to patients with GBS bacteremia without IE to identify risk factors for development of IE. Methods A nested case–control study in a cohort of adult patients with GBS bacteremia over a 18-year period was conducted across seven centres in three Canadian cities. A chart review identified patients with possible or definite IE (per Modified Duke Criteria) and patients with IE were matched to those without endocarditis in a 1:3 fashion. Multivariate analyses were completed using logistic regression. Results Of 520 patients with GBS bacteremia, 28 cases of possible or definite IE were identified (5.4%). 68% (19/28) met criteria for definite IE, surgery was performed in 29% (8/28), and the overall in-hospital mortality rate was 29% (8/28). Multivariate analysis demonstrated that IE was associated with injection drug use (OR = 19.6, 95% CI = 3.39–111.11, p = 0.001), prosthetic valve (OR = 11.5, 95% CI = 1.73–76.92, p = 0.011) and lack of identified source of bacteremia (OR = 3.81, 95% CI = 1.24–11.65, p = 0.019). Conclusions GBS bacteremia, especially amongst people who inject drugs, those with prosthetic valves, and those with no apparent source of infection, should increase clinical suspicion for IE.

Control Analysis with Modified LQR Method of Anti-Tank Missile with Vectorization of the Rocket Engine Thrust

This article approaches the issue of the optimal control of a hypothetical anti-tank guided missile (ATGM) with an innovative rocket engine thrust vectorization system. This is a highly non-linear dynamic system; therefore, the linearization of such a mathematical model requires numerous simplifications. For this reason, the application of a classic linear-quadratic regulator (LQR) for controlling such a flying object introduces significant errors, and such a model would diverge significantly from the actual object. This research paper proposes a modified linear-quadratic regulator, which analyzes state and control matrices in flight. The state matrix is replaced by a Jacobian determinant. The ATGM autopilot, through the LQR method, determines the signals that control the control surface deflection angles and the thrust vector via calculated Jacobians. This article supplements and develops the topics addressed in the authors’ previous work. Its added value includes the introduction of control in the flight direction channel and the decimation of the integration step, aimed at speeding up the computational processes of the second control loop, which is the LQR based on a linearized model.