Articles: cations.
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Delirium is an acute state of confusion associated with adverse postoperative outcomes. Delirium is diagnosed clinically using screening tools; most cases go undetected. Identifying a delirium biomarker would allow for accurate diagnosis, application of therapies, and insight into causal pathways. To agnostically discover novel biomarkers of delirium, we conducted a case-control sub-study using the VISION-Cardiac Surgery biobank. Our objective was to identify candidate biomarkers to investigate in future studies. ⋯ We identified 26 biomarkers significantly associated with delirium; all are novel except for IL-8. We did not identify an association between delirium and recognized neuro-inflammatory proteins and markers of brain injury, which supports using biomarkers to differentiate between delirium and other neurological conditions. While exploratory, our findings support using biomarkers to diagnose postoperative delirium and validate using agnostic screens to identify potential delirium biomarkers.
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A variety of minimal clinically important difference (MCID) estimates are available to distinguish subgroups with differing outcomes. When a true gold standard is absent, latent class growth curve analysis (LCGC) has been proposed as a suitable alternative for important change. Our purpose was to evaluate the performance of individual and baseline quartile-stratified MCIDs. ⋯ Classification errors in individual MCID estimates most likely result from ceiling effects. Minimal clinically important differences calculated for each baseline quartile are superior to individually calculated MCIDs and should be used when latent class methods are not available. Use of individual MCIDs likely contribute substantial error and are discouraged for clinical application.
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Accurate prognostication in comatose survivors of cardiac arrest is a challenging and high-stakes endeavor. We sought to determine whether internal EEG subparameters extracted by the Bispectral Index (BIS) monitor, a device commonly used to estimate depth-of-anesthesia intraoperatively, could be repurposed to predict recovery of consciousness after cardiac arrest. ⋯ In patients comatose after cardiac arrest, four EEG features calculated internally by the BIS Engine were repurposed by a compact neural network to achieve a prognostic accuracy superior to the current clinical qualitative gold-standard, with high sensitivity for recovery. These features hold promise for assessing patients after cardiac arrest.
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Disparities in postoperative nausea and vomiting (PONV) and its prophylaxis may exist based on race, ethnicity, and socioeconomic status (SES). Our objective was to evaluate whether patients from racial and ethnic minority groups and patients from lower SES backgrounds received less appropriate PONV prophylaxis and experienced higher rates of PONV and post-discharge nausea and vomiting (PDNV). ⋯ The study identified differences in appropriate PONV prophylaxis by race and ethnicity as well as community-level SES. There were no differences in PONV by our predictors, but higher odds of PDNV by race and ethnicity and payor. This study underscores the importance of data stratification in quality measures to identify disparities in perioperative care; it can lead to changes in perioperative anesthetic management. Further research should explore these associations in a broader cohort and address potential confounding sources.
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Historically in medicine and beyond, the understanding of and treatment of pain is based on finding tissue injury. The fact that for chronic pain, there often is no (longer) any traceable tissue injury, in combination with the fact that pain essentially is a private experience, poses a challenge for clinical communication. This paper therefore examines how pain is linguistically and interactionally constructed as invisible. ⋯ The discussion explores how on these three levels, notions of the abnormal or deviant body come into play, in which patients and health professionals complexly construct pain both as not normal (i.e. not a neutral or desirable state of being), while, at the same time, the lack of traceable tissue injury is constructed as medically normal for chronic pain. This also shows how patients and healthcare providers often orient to the stigma around chronic pain.