Oculomic stratification of COVID-19 patients' intensive therapy unit admission status and mortality by retinal morphological findings.

To investigate if retinal thickness has predictive utility in COVID-19 outcomes by evaluating the statistical association between retinal thickness using OCT and of COVID-19-related mortality. Secondary outcomes included associations between retinal thickness and length of stay (LoS) in hospital. In this retrospective cohort study, OCT scans from 230 COVID-19 patients admitted to the Intensive Care Unit (ITU) were compared with age and gender-matched patients with pneumonia from before March 2020.

Causal Learning through Deliberate Undersampling.

Domain scientists interested in causal mechanisms are usually limited by the frequency at which they can collect the measurements of social, physical, or biological systems. A common and plausible assumption is that higher measurement frequencies are the only way to gain more informative data about the underlying dynamical causal structure. This assumption is a strong driver for designing new, faster instruments, but such instruments might not be feasible or even possible.

Psychological freedom, rationality, and the naive theory of reasoning.

To make sense of the social world, people reason about others' mental states, including whether and in what ways others can form new mental states. We propose that people's judgments concerning the dynamics of mental state change invoke a "naive theory of reasoning." On this theory, people conceptualize reasoning as a rational, semi-autonomous process that individuals can leverage, but not override, to form new rational mental states.

Causal inference in cognitive neuroscience.

Causal inference is a key step in many research endeavors in cognitive science and neuroscience, and particularly cognitive neuroscience. Statistical knowledge is sufficient for prediction and diagnosis, but causal knowledge is required for action and intervention. Most statistics courses and textbooks emphasize the difficulty of causal inference, focusing on the maxim that "correlation does not mean causation": there can be multiple causal possibilities, often many of them, consistent with given observed statistics.

Preoperative Identification of Patient-Dependent Blood Pressure Targets Associated With Low Risk of Intraoperative Hypotension During Noncardiac Surgery.

Background: Intraoperative hypotension (IOH) is strongly linked to organ system injuries and postoperative death. Blood pressure itself is a powerful predictor of IOH; however, it is unclear which pressures carry the lowest risk and may be leveraged to prevent subsequent hypotension. Our objective was to develop a model that predicts, before surgery and according to a patient's unique characteristics, which intraoperative mean arterial pressures (MAPs) between 65 and 100 mm Hg have a low risk of IOH, defined as an MAP <65 mm Hg, and may serve as testable hemodynamic targets to prevent IOH.