Project description:Processing of the dataset of synthetic phosphopeptides by Savitzki et al. (MCP, 2011) using multiple search engines. Establishment of the D-score: a search engine independent MD-score.
Project description:Evolutionary pressures have made foraging behaviours highly efficient in many species. Eye movements during search present a useful instance of foraging behaviour in humans. We tested the efficiency of eye movements during search using homogeneous and heterogeneous arrays of line segments. The search target is visible in the periphery on the homogeneous array, but requires central vision to be detected on the heterogeneous array. For a compound search array that is heterogeneous on one side and homogeneous on the other, eye movements should be directed only to the heterogeneous side. Instead, participants made many fixations on the homogeneous side. By comparing search of compound arrays to an estimate of search performance based on uniform arrays, we isolate two contributions to search inefficiency. First, participants make superfluous fixations, sacrificing speed for a perceived (but not actual) gain in response certainty. Second, participants fixate the homogeneous side even more frequently than predicted by inefficient search of uniform arrays, suggesting they also fail to direct fixations to locations that yield the most new information.
Project description:BackgroundIncreasing genetic variants associated with sepsis have been identified by candidate-gene and genome-wide association studies, but single variants conferred minimal alterations in risk prediction. Our aim is to evaluate whether a weighted genetic risk score (wGRS) that aggregates information from multiple variants could improve risk discrimination of traumatic sepsis.MethodsSixty-four genetic variants potential relating to sepsis were genotyped in Chinese trauma cohort. Genetic variants with mean decrease accuracy (MDA) > 1.0 by random forest algorithms were selected to construct the multilocus wGRS. The area under the curve (AUC) and net reclassification improvement (NRI) were adopted to evaluate the discriminatory and reclassification ability of weighted genetic risk score (wGRS).ResultsSeventeen variants were extracted to construct the wGRS in 883 trauma patients. The wGRS was significantly associated with sepsis after trauma (OR = 2.19, 95% CI = 1.53-3.15, P = 2.01 × 10-5) after being adjusted by age, sex, and ISS. Patients with higher wGRS have an increasing incidence of traumatic sepsis (P trend = 6.81 × 10-8), higher SOFA (P trend = 5.00 × 10-3), and APACHE II score (P trend = 1.00 × 10-3). The AUC of the risk prediction model incorporating wGRS into the clinical variables was 0.768 (95% CI = 0.739-0.796), with an increase of 3.40% (P = 8.00 × 10-4) vs. clinical factor-only model. Furthermore, the NRI increased 25.18% (95% CI = 17.84-32.51%) (P = 6.00 × 10-5).ConclusionOur finding indicated that genetic variants could enhance the predictive power of the risk model for sepsis and highlighted the application among trauma patients, suggesting that the sepsis risk assessment model will be a promising screening and prediction tool for the high-risk population.
Project description:Background: Many severity scores are widely used for clinical outcome prediction for critically ill patients in the intensive care unit (ICU). However, for patients identified by sepsis-3 criteria, none of these have been developed. This study aimed to develop and validate a risk stratification score for mortality prediction in sepsis-3 patients. Methods: In this retrospective cohort study, we employed the Medical Information Mart for Intensive Care III (MIMIC III) database for model development and the eICU database for external validation. We identified septic patients by sepsis-3 criteria on day 1 of ICU entry. The Least Absolute Shrinkage and Selection Operator (LASSO) technique was performed to select predictive variables. We also developed a sepsis mortality prediction model and associated risk stratification score. We then compared model discrimination and calibration with other traditional severity scores. Results: For model development, we enrolled a total of 5,443 patients fulfilling the sepsis-3 criteria. The 30-day mortality was 16.7%. With 5,658 septic patients in the validation set, there were 1,135 deaths (mortality 20.1%). The score had good discrimination in development and validation sets (area under curve: 0.789 and 0.765). In the validation set, the calibration slope was 0.862, and the Brier value was 0.140. In the development dataset, the score divided patients according to mortality risk of low (3.2%), moderate (12.4%), high (30.7%), and very high (68.1%). The corresponding mortality in the validation dataset was 2.8, 10.5, 21.1, and 51.2%. As shown by the decision curve analysis, the score always had a positive net benefit. Conclusion: We observed moderate discrimination and calibration for the score termed Sepsis Mortality Risk Score (SMRS), allowing stratification of patients according to mortality risk. However, we still require further modification and external validation.
Project description:Platelets are key mediators of atherothrombosis; yet, limited tools exist to identify individuals with a hyperreactive platelet phenotype. Here we derive and validate a Platelet Reactivity ExpreSsion Score (PRESS) integrating platelet aggregation responses and RNA sequencing in multiple cohorts. PRESS performs well in identifying a hyperreactive phenotype in patients with cardiovascular disease (AUC [cross-validation] 0.81, 95% CI 0.68 to 0.94), with similar discrimination in an independent cohort of healthy participants (AUC [validation] 0.77, 95% CI 0.75 to 0.79); accuracy 80%, sensitivity 71%, and specificity 86%. Next, we validate PRESS in multiple cohorts of patients with platelet RNASeq available. Following multivariable adjustment, PRESS was significantly higher in MI (β=1.8, p=0.02), and individuals with a score above the median more frequently develop a future cardiovascular event (adjusted HR 1.90, CI 1.07 to 3.36), p=0.027). Altogether, we provide strong evidence that PRESS is a robust prognostic marker, which could have an essential role in facilitating a personalized approach to cardiovascular risk management.
Project description:BackgroundPatients suffering from major trauma often experience complications such as sepsis. The early recognition of patients at high risk of sepsis after trauma is critical for precision therapy. We aimed to derive and validate a novel predictive score for sepsis risk using electronic medical record (EMR) data following trauma.Materials and methodsClinical and laboratory variables of 684 trauma patients within 24 h after admission were collected, including 411 patients in the training cohort and 273 in the validation cohort. The least absolute shrinkage and selection operator (LASSO) technique was adopted to identify variables contributing to the early prediction of traumatic sepsis. Then, we constructed a traumatic sepsis score (TSS) using a logistic regression model based on the variables selected in the LASSO analysis. Moreover, we evaluated the discrimination and calibration of the TSS using the area under the curve (AUC) and the Hosmer-Lemeshow (H-L) goodness-of-fit test.ResultsBased on the LASSO, seven variables (injury severity score, Glasgow Coma Scale, temperature, heart rate, albumin, international normalized ratio, and C-reaction protein) were selected for construction of the TSS. Our results indicated that the incidence of sepsis after trauma increased with an increasing TSS (P trend = 7.44 × 10-21 for the training cohort and P trend = 1.16 × 10-13 for the validation cohort). The areas under the receiver operating characteristic (ROC) curve of TSS were 0.799 (0.757-0.837) and 0.790 (0.736-0.836) for the training and validation datasets, respectively. The discriminatory power of our model was superior to that of a single variable and the sequential organ failure assessment (SOFA) score (P < 0.001). Moreover, the TSS was well calibrated (P > 0.05).ConclusionsWe developed and validated a novel TSS with good discriminatory power and calibration for the prediction of sepsis risk in trauma patients based on the EMR data.
Project description:BackgroundExisting scoring systems have limitations in predicting the in-hospital mortality of adult sepsis patients. We aimed to develop and validate a novel risk score for predicting the in-hospital mortality of adult sepsis patients.MethodsThe clinical data of 1,335 adult sepsis inpatients were retrospectively analyzed. Enrolled patients were randomly divided into a modeling group and a validation group at a 3:2 ratio. The modeling group (n=801) was used to develop the risk score by univariate and multivariate logistic regression analyses. The score's performance was validated in the validation group (n=534). We classified patients into four risk levels according to the novel risk score.ResultsAge, central vein catheterization, mechanical ventilation, vasopressin, Charlson comorbidity index (CCI), respiratory rate (RR), heart rate (HR), Glasgow coma scale (GCS) score, platelet (PLT), hematocrit (HCT), aspartate aminotransferase (AST), and activated partial thrombin time (APTT) were independent risk factors for in-hospital death in adult sepsis patients. Continuous variables were converted into classified variables to develop the risk score, with a total score of 39 points. Adult sepsis patients with low, lower medium, higher medium, and high risk levels had in-hospital mortality rates of 9.8%, 24.7%, 55.8%, and 83.5%, respectively.ConclusionsCompared with the Acute Physiology and Chronic Health Evaluation II scoring system (APACHE II) and the Modified Early Warning Score (MEWS), the novel risk score showed good predictive performance for in-hospital mortality in adult sepsis patients.
Project description:BACKGROUND:Bioprosthetic heart valves undergo structural degeneration and calcification. Similarities exist in the histopathologic features of explanted bioprosthetic valves and rejected pig tissues and organs after xenotransplantation into nonhuman primates. The development of more durable bioprosthetic valves, namely from genetically modified pigs, could negate the need for the insertion of mechanical prostheses in children and young adults with the requirement for life-long anticoagulation and might avoid the need for reoperation in elderly patients. METHODS:We reviewed the literature (MedlinePlus, PubMed, Google Scholar) through September 1, 2018, under four key terms: (1) bioprosthetic heart valves, (2) xenograft antigens, (3) immunologic responses to bioprosthetic valves, and (4) genetic modification of xenografts. RESULTS:Advances in tissue and organ xenotransplantation have elucidated important immunologic barriers that provide innovative approaches to prevent structural degeneration of bioprosthetic heart valves. The current evidence suggests that bioprosthetic valves derived from genetically modified pigs lacking xenogeneic antigens (namely Gal, Neu5Gc, and Sda), termed triple-knockout pigs, would function considerably longer than current wild-type (genetically unmodified) porcine valves in human recipients. CONCLUSIONS:Preclinical and clinical studies to determine the safety and efficacy of triple-knockout porcine bioprosthetic valves will likely establish that they are more resistant to human immune responses and thus less susceptible to structural degeneration.