Objectives: To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. Design: Prospective observational study. Setting: Nine Canadian ICUs. Subjects: Three-hundred fifty-six septic patients. Interventions: None. Measurements and Main Results: Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the “day 1” and “change” variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86–0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. Conclusions: Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient’s overall daily mortality risk.

Background: A limitation of diagnostic scoring systems for disseminated intravascular coagulation (DIC) is that once DIC is identified, it may be in a state of irreversible deterioration. Objectives: To identify hemostatic markers that can identify the pre-DIC state. Methods: This was a multi-center observational study of 357 septic patients. The incidence of DIC was determined using the International Society on Thrombosis and Haemostasis (ISTH) DIC Score. Markers of interest include components of the DIC score: protein C (PC), antithrombin (AT), and citrullinated histones (H3Cit), which is a marker of NETosis. Results: Out of 357 sepsis patients, 236 patients did not develop DIC (without-DIC), 79 patients had DIC on Day 1 (overt-DIC), and 42 patients developed DIC after Day 1 (pre-DIC). Compared to without-DIC patients, pre-DIC patients had decreased platelet count, increased international normalized ratio (INR), decreased PC and AT, and increased H3Cit. In contrast, D-dimer and fibrinogen levels did not differ between pre-DIC and without-DIC patients. Using receiver operating characteristics (ROC) analysis, we found that platelet count and INR in combination with PC and AT could discriminate pre-DIC from without-DIC. The area under the curve in the ROC analysis was 0.83 (95% confidence interval, 0.76 to 0.89). Conclusion: Our study suggests that platelets and INR in combination with PC and AT can identify the pre-DIC state in septic patients. In contrast, D-dimer increased and fibrinogen decreased in the late (ie, overt) stages of DIC. Our data also suggest that NETosis contributes to the onset of DIC in sepsis.

Introduction: Health care professionals rely on annual general meetings (AGMs) to obtain up-to-date information and practice guidelines relevant to their specialty. The majority of such information at meetings is presented through abstract sessions. However, the quality of the evidence presented during such abstract sessions is unclear. Standardized measures were applied to assess the quality of evidence of abstracts presented at the Canadian Society of Nephrology AGM over a 5-year period. Methods: Two authors independently reviewed all CSN AGM abstracts presented from 2012 to 2016. Using a schema published in 2011 by the Oxford Centre for Evidence-Based Medicine (OCEBM), each abstract was subsequently ranked based on the quality of evidence. Schema categories ranged from level I, representing the highest evidence quality, to level V, representing the lowest. The number of authors and the authors' institution affiliations were also collected from the abstracts, where available, or if affiliations were unclear, an internet search of the author was performed. Results: Six hundred forty-two articles were screened. In total, 70% (n = 450) met the inclusion criteria. When assessed, 15% of articles were level I (highest quality), 17% level II, 53% level III, 12% level IV, and 3% level V (lowest quality). A Jonckheere–Terpstra test demonstrated a significant trend of increasing quality of evidence (P < .05) and collaboration (P < .005) over the 5-year study period. There was a significant correlation between level of evidence and collaboration across years reviewed in the study, rs(98) = −0.226, P < .001. Discussion: The results indicate a consistent increase in quality of evidence and collaborative submissions over time. To the authors' knowledge, this is the first assessment and analysis of AGM presentation quality within internal medicine and its subspecialties. Documenting and monitoring changes in the quality of evidence with a standardized framework may offer valuable insight pertaining to the medical field and the research community.