Diagnosis trajectories of prior multi-morbidity predict sepsis mortality

Sepsis affects millions of people every year, many of whom will die. In contrast to current survival prediction models for sepsis patients that primarily are based on data from within-admission clinical measurements (e.g. vital parameters and blood values), we aim for using the full disease history to predict sepsis mortality. We benefit from data in electronic medical records covering all hospital encounters in Denmark from 1996 to 2014. This data set included 6.6 million patients of whom almost 120,000 were diagnosed with the ICD-10 code: A41 ‘Other sepsis’. Interestingly, patients following recurrent trajectories of time-ordered co-morbidities had significantly increased sepsis mortality compared to those who did not follow a trajectory. We identified trajectories which significantly altered sepsis mortality, and found three major starting points in a combined temporal sepsis network: Alcohol abuse, Diabetes and Cardio-vascular diagnoses. Many cancers also increased sepsis mortality. Using the trajectory based stratification model we explain contradictory reports in relation to diabetes that recently have appeared in the literature. Finally, we compared the predictive power using 18.5 years of disease history to scoring based on within-admission clinical measurements emphasizing the value of long term data in novel patient scores that combine the two types of data

High plasma levels of C1-inhibitor are associated with lower risk of future venous thromboembolism

Background - C1-inhibitor (C1INH) is a broad-acting serine protease inhibitor with anticoagulant activity. The impact of C1INH plasma levels within the normal physiological range on risk of venous thromboembolism (VTE) is unknown. We assessed the association of plasma C1INH levels and VTE risk and evaluated the impact of C1INH on thrombin and plasmin generation in ex vivo assays. Methods - A nested case-control study with 405 patients with VTE and 829 age- and sex-matched controls was derived from the Tromsø Study. Odds ratios (ORs) with 95% confidence intervals (95% CI) for VTE were estimated across plasma C1INH quartiles. Genetic regulation of C1INH was explored using quantitative trait loci analysis of whole exome sequencing data. The effect of plasma C1INH levels on coagulation was evaluated ex vivo by calibrated automated thrombography. Results - Individuals with C1INH levels in the highest quartile had a lower risk of VTE (OR 0.68, 95% CI: 0.49-0.96) compared with those with C1INH in the lowest quartile. In subgroup analysis, the corresponding ORs were 0.60 (95% CI: 0.39-0.89) for deep vein thrombosis and 0.85 (95% CI: 0.52-1.38) for pulmonary embolism, respectively. No significant genetic determinants of plasma C1INH levels were identified. Addition of exogenous C1INH to normal human plasma reduced thrombin generation triggered by an activator of the intrinsic coagulation pathway, but not when triggered by an activator of the extrinsic coagulation pathway. Conclusions - High plasma levels of C1INH were associated with lower risk of VTE, and C1INH inhibited thrombin generation initiated by the intrinsic coagulation pathway ex vivo

Plasma lipopolysaccharide-binding protein is a biomarker for future venous thromboembolism: Results from discovery and validation studies

Background Effect-size underestimation impedes biomarker identification. Long follow-up time in prospective studies attenuates effect-size estimates for transient biomarkers, while disease category–specific biomarkers are affected by merging of categories. Venous thromboembolism (VTE) encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE). Objectives (i) To re-analyze untargeted proteomic data to identify biomarker candidates for future VTE that differ between DVT and PE and are attenuated by extended time between sampling and VTE. (ii) To perform targeted candidate validation. Patients/Methods A VTE case-control discovery study and a nested case-control validation study were derived from the general population surveyed in 1994–95. Plasma was obtained at study enrollment, and VTE events were registered until 2007. Untargeted proteomic data were re-analyzed for candidate discovery. Lipopolysaccharide-binding protein (LBP) was validated by enzyme-linked immunosorbent assay. Results Elevated LBP was discovered as a candidate DVT biomarker in women with less than 3 years between blood sampling and DVT. In the validation study, the odds ratio (OR) for DVT was 2.03 (95% confidence intervals [CI]: 1.53–2.74) per standard deviation (SD) increase in LBP for women with less than 3 years between blood sampling and DVT. Adjustment for age, body mass index, and C-reactive protein attenuated the OR to 1.79 (95% CI: 1.25–2.62) per SD. In the validation study, we observed an OR for VTE of 0.47 (95% CI: 0.28–0.77) for men in the 25th to 50th percentiles when compared to the lowest quartile. Conclusions We discovered and validated increased LBP as a predictive biomarker for DVT in women. We found an increased VTE risk for men in the lowest quartile of LBP