Predicting quarantine failure rates.
Ontology highlight
ABSTRACT:
SUBMITTER: Day T
PROVIDER: S-EPMC3322804 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer's clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer's disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.
| S-EPMC7586089 | biostudies-literature
Project description:How the locus-specificity of epigenetic modifications is regulated remains an unanswered question. A contributing mechanism is that epigenetic enzymes are recruited to specific loci by DNA binding factors recognizing particular sequence motifs (referred to as epi-motifs). Using these motifs to predict biological outputs depending on local epigenetic state such as somatic mutation rates would confirm their functionality. Here, we used DNA motifs including known TF motifs and epi-motifs as a surrogate of epigenetic signals to predict somatic mutation rates in 13 cancers at an average 23kbp resolution. We implemented an interpretable neural network model, called contextual regression, to successfully learn the universal relationship between mutations and DNA motifs, and uncovered motifs that are most impactful on the regional mutation rates such as TP53 and epi-motifs associated with H3K9me3. Furthermore, we identified genomic regions with significantly higher mutation rates than the expected values in each individual tumor and demonstrated that such cancer-related regions can accurately predict cancer types. Interestingly, we found that the same mutation signatures often have different contributions to cancer-related and cancer-independent regions, and we also identified the motifs with the most contribution to each mutation signature.
| S-EPMC10569533 | biostudies-literature
Project description:Recent advances in understanding the capture of moving suspended particles in aquatic ecosystems have opened up new possibilities for predicting rates of suspension feeding, larval settlement, seagrass pollination and sediment removal. Drawing on results from both highly-resolved computational fluid dynamics (CFD) simulations and existing experimental data, we quantify the controlling influence of flow velocity, particle size and collector size on rates of contact between suspended particles and biological collectors over the parameter space characterising a diverse range of aquatic ecosystems. As distinct from assumptions in previous modeling studies, the functional relationships describing capture are highly variable. Contact rates can vary in opposing directions in response to changes in collector size, an organism's size, the size of particles being intercepted (related to diet in the case of suspension feeders), and the flow strength. Contact rates shift from decreasing to increasing with collector diameter when particles become relatively large and there is vortex shedding in the collector wake. And in some ranges of the ecologically relevant parameter space, contact rates do not increase strongly with velocity or particle size. The understanding of these complex dependencies allows us to reformulate some hypotheses of selection pressure on the physiology and ecology of aquatic organisms. We discuss the benefits and limitations of CFD tools in predicting rates of particle capture in aquatic ecosystems. Finally, across the complete parameter space relevant to real aquatic ecosystems, all quantitative estimates of particle capture from our model are provided here.
| S-EPMC8694431 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) surveillance is underutilized among patients with cirrhosis. Understanding which steps in the surveillance process are not being conducted is essential for designing effective interventions to improve surveillance rates. The aim of our study was to characterize reasons for failure in the HCC surveillance process among a cohort of cirrhotic patients with HCC. We conducted a retrospective cohort study of cirrhotic patients diagnosed with HCC at a large urban safety-net hospital between 2005 and 2011. Patients were characterized by receipt of HCC surveillance over a two-year period before HCC diagnosis. Among patients without HCC surveillance, we classified reasons for failure into four categories: failure to recognize liver disease, failure to recognize cirrhosis, failure to order surveillance, and failure to complete surveillance despite orders. Univariate and multivariate analyses were conducted to identify predictors of failures. We identified 178 patients with HCC, of whom 20% had undergone surveillance. There were multiple points of failure-20% had unrecognized liver disease, 19% had unrecognized cirrhosis, 38% lacked surveillance orders, and 3% failed to complete surveillance despite orders. Surveillance was more likely among patients seen by hepatologists [OR, 6.11; 95% confidence interval (CI), 2.5-14.8] and less likely in those with alcohol abuse (OR, 0.14; 95% CI, 0.03-0.65). Although a retrospective analysis in a safety-net hospital, our data suggest that only one in five patients received surveillance before HCC diagnosis. There are multiple points of failure in the surveillance process, with the most common being failure to order surveillance in patients with known cirrhosis. Future interventions must target multiple failure points in the surveillance process to be highly effective.
| S-EPMC3435471 | biostudies-literature
Project description:Although bedrock weathering strongly influences water quality and global carbon and nitrogen budgets, the weathering depths and rates within subsurface are not well understood nor predictable. Determination of both porewater chemistry and subsurface water flow are needed in order to develop more complete understanding and obtain weathering rates. In a long-term field study, we applied a multiphase approach along a mountainous watershed hillslope transect underlain by marine shale. Here we report three findings. First, the deepest extent of the water table determines the weathering front, and the range of annually water table oscillations determines the thickness of the weathering zone. Below the lowest water table, permanently water-saturated bedrock remains reducing, preventing deeper pyrite oxidation. Secondly, carbonate minerals and potentially rock organic matter share the same weathering front depth with pyrite, contrary to models where weathering fronts are stratified. Thirdly, the measurements-based weathering rates from subsurface shale are high, amounting to base cation exports of about 70 kmolc ha-1 y-1, yet consistent with weathering of marine shale. Finally, by integrating geochemical and hydrological data we present a new conceptual model that can be applied in other settings to predict weathering and water quality responses to climate change.
| S-EPMC6868182 | biostudies-literature
Project description:Mosquito-borne pathogens continue to be a significant burden within human populations, with Aedes aegypti continuing to spread dengue, chikungunya, and Zika virus throughout the world. Using data from a previously conducted study, a linear regression model was constructed to predict the aquatic development rates based on the average temperature, temperature fluctuation range, and larval density. Additional experiments were conducted with different parameters of average temperature and larval density to validate the model. Using a paired t-test, the model predictions were compared to experimental data and showed that the prediction models were not significantly different for average pupation rate, adult emergence rate, and juvenile mortality rate. The models developed will be useful for modeling and estimating the upper limit of the number of Aedes aegypti in the environment under different temperature, diurnal temperature variations, and larval densities.
| S-EPMC6528993 | biostudies-literature
Project description:Noninvasive ventilation (NIV) is useful when managing critically ill patients. However, it is not easy to apply to elderly patients, particularly those with pneumonia, due to the possibility of NIV failure and the increased mortality caused by delayed intubation. In this prospective observational study, we explored whether NIV was appropriate for elderly patients with pneumonia, defined factors that independently predicted NIV failure, and built an optimal model for prediction of such failure. We evaluated 78 patients with a median age of 77 years. A low PaCO2 level, a high heart rate, and the presence of pneumonia were statistically significant independent predictors of NIV failure. The predictive power for NIV failure of Model III (pneumonia, PaCO2 level, and heart rate) was better than that of Model I (pneumonia alone). Considering the improvement in parameters, patients with successful NIV exhibited significantly improved heart rates, arterial pH and PaCO2 levels, and patients with NIV failure exhibited a significantly improved PaCO2 level only. In conclusion, NIV is reasonable to apply to elderly patients with pneumonia, but should be done with caution. For the early identification of NIV failure, the heart rate and arterial blood gas parameters should be monitored within 2 h after NIV commencement.
| S-EPMC7408979 | biostudies-literature
Project description:Contraceptive failure is a major contributor to unintended pregnancy worldwide. DHS retrospective calendars, which are the most widely used data source for estimating contraceptive failure in low-income countries, vary in quality across countries and surveys. We identified surveys with the most reliable calendar data and analyzed 105,322 episodes of contraceptive use from 15 DHSs conducted between 1992 and 2014. We estimate contraceptive method-specific 12-month failure rates. We also examined how failure rates vary by age, education, socioeconomic status, contraceptive intention, residence, and marital status using multilevel piecewise exponential hazard models. Our failure rate estimates are significantly lower than results from the United States and slightly higher than previous studies that included more DHS surveys, including some with lower-quality data. We estimate age-specific global contraceptive failure rates and find strong, consistent age patterns with the youngest users experiencing failure rates up to ten times higher than older women for certain methods. Failure also varies by socioeconomic status, with the poorest, and youngest, women at highest risk of experiencing unintended pregnancy due to failure.
| S-EPMC6594038 | biostudies-literature
Project description:Disease management programs that target patients with the highest risk of subsequent costs may help payers and providers control health care costs, but identifying these patients prospectively is challenging. We hypothesized that medical history and clinical data from a heart failure registry could be used to prospectively identify patients with heart failure most likely to incur high costs. We linked Medicare inpatient claims to clinical registry data for patients with heart failure and calculated total Medicare costs during the year after the index heart failure hospitalization. We defined patients as having high costs if they were in the upper 5% (>$76,500) of the distribution. We used logistic regression models to identify patient and clinical characteristics associated with high costs. Costs for 40,317 patients in the study varied widely. Patients in the upper 5% of the cost distribution incurred mean costs of $117,193 ± 55,550 during 1 year of follow-up compared to $17,086 ± 17,792 for the lower-cost group. Demographic and clinical characteristics associated with high costs included younger age and black race; history of anemia, chronic obstructive pulmonary disease, ischemic heart disease, diabetes mellitus, or peripheral vascular disease; serum creatinine level; and systolic blood pressure at admission. Mean 1-year Medicare costs for patients whom the model predicted would exceed the high-cost threshold were >2 times the costs for patients below the threshold. In conclusion, a model based on variables from clinical registries can identify a group of patients with heart failure who on average will incur higher costs in the first year after hospitalization.
| S-EPMC3288564 | biostudies-literature
Project description:We have developed statistical models for estimating the failure rate of polymerase chain reaction (PCR) primers using 236 primer sequence-related factors. The model involved 1314 primer pairs and is based on more than 80 000 PCR experiments. We found that the most important factor in determining PCR failure is the number of predicted primer-binding sites in the genomic DNA. We also compared different ways of defining primer-binding sites (fixed length word versus thermodynamic model; exact match versus matches including 1-2 mismatches). We found that the most efficient prediction of PCR failure rates can be achieved using a combination of four factors (number of primer-binding sites counted in different ways plus GC% of the primer) combined into single statistical model GM1. According to our estimations from experimental data, the GM1 model can reduce the average failure rate of PCR primers nearly 3-fold (from 17% to 6%). The GM1 model can easily be implemented in software to premask genome sequences for potentially failing PCR primers, thus improving large-scale PCR-primer design.
| S-EPMC2441781 | biostudies-literature