Temporal Transitions of the Hyperinflammatory and Hypoinflammatory Phenotypes in Critical Illness.

Rationale: Systemic molecular phenotypes of critical illness are prognostically informative, yet their temporal kinetics and implications of changing phenotypes remain incompletely understood.

Objectives: To determine the temporal nature of the Hyperinflammatory and Hypoinflammatory phenotypes and assess the impact of transition between the phenotypes on mortality.

Methods: We used data from one prospective observational cohort (MARS) and two randomized controlled trials in ARDS (ALVEOLI) and sepsis (CLOVERS).

Measuring the cognitive effort associated with task switching in routine EHR-based tasks.

Objective: Clinical work involves performing overlapping, time-sensitive tasks that frequently require clinicians to switch their attention between multiple tasks. We developed a methodological approach using EHR-based audit logs to determine switch costs-the cognitive burden associated with task switching-and assessed its magnitude during routine EHR-based clinical tasks.

Method: Physician trainees (N = 75) participated in a longitudinal study where they provided access to their EHR-based audit logs.

Integrating machine learning predictions for perioperative risk management: Towards an empirical design of a flexible-standardized risk assessment tool.

Background: Surgical patients are complex, vulnerable, and prone to postoperative complications that can potentially be mitigated with quality perioperative risk assessment and management. Several institutions have incorporated machine learning (ML) into their patient care to improve awareness and support clinician decision-making along the perioperative spectrum. Recent research suggests that ML risk prediction can support perioperative patient risk monitoring and management across several situations, including the operating room (OR) to intensive care unit (ICU) handoffs.

In search of on-line locality effects in sentence comprehension.

Many comprehension theories assert that increasing the distance between elements participating in a linguistic relation (e.g., a verb and a noun phrase argument) increases the difficulty of establishing that relation during on-line comprehension.