Gout is a common crystal-induced arthritis, in which monosodium urate (MSU) crystals precipitate within joints and soft tissues and elicit an inflammatory response. The causes of elevated serum urate and the inflammatory pathways activated by MSU crystals have been well studied, but less is known about the processes leading to crystal formation and growth. Uric acid, the final product of purine metabolism, is a weak acid that circulates as the deprotonated urate anion under physiologic conditions, and combines with sodium ions to form MSU. MSU crystals are known to have a triclinic structure, in which stacked sheets of purine rings form the needle-shaped crystals that are observed microscopically. Exposed, charged crystal surfaces are thought to allow for interaction with phospholipid membranes and serum factors, playing a role in the crystal-mediated inflammatory response. While hyperuricemia is a clear risk factor for gout, local factors have been hypothesized to play a role in crystal formation, such as temperature, pH, mechanical stress, cartilage components, and other synovial and serum factors. Interestingly, several studies suggest that MSU crystals may drive the generation of crystal-specific antibodies that facilitate future MSU crystallization. Here, we review MSU crystal biology, including a discussion of crystal structure, effector function, and factors thought to play a role in crystal formation. We also briefly compare MSU biology to that of uric acid stones causing nephrolithasis, and consider the potential treatment implications of MSU crystal biology.

OBJECTIVE: Determine the characteristics of postintensive care syndrome in the cognitive, physical, and psychiatric domains in coronavirus disease 2019 ICU survivors. DESIGN: Single-center descriptive cohort study from April 21, to July 7, 2020. SETTING: Critical care recovery clinic at The Mount Sinai Hospital in New York City. PATIENTS: Adults who had critical illness due to coronavirus disease 2019 requiring an ICU stay of 7 days or more and who agreed to a telehealth follow-up in the critical care recovery clinic 1-month post hospital discharge. INTERVENTIONS: None. MEASURES AND MAIN RESULTS: Patient-reported outcome measures assessing physical and psychiatric domains were collected electronically, a cognitive test was performed by a clinician, and clinical data were obtained through electronic medical records. Outcome measures assessed postintensive care syndrome symptoms in the physical (Modified Rankin Scale, Dalhousie Clinical Frailty Scale, Neuro-Quality of Life Upper Extremity and Lower Extremity Function, Neuro-Quality of Life Fatigue), psychiatric (Insomnia Severity Scale; Patient Health Questionnaire-9; and Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition), and cognitive (Telephone Montreal Cognitive Assessment) domains. The 3-Level Version of Euro-QoL-5D was used to assess the physical and psychiatric domains. A diagnosis of postintensive care syndrome was made in cases with evidence of impairment in at least one postintensive care syndrome domain. We included 45 patients with a mean (sd) age of 54 (13) years, and 73% were male. Ninety-one percent of coronavirus disease 2019 ICU survivors fit diagnostic criteria for postintensive care syndrome. 86.7 % had impairments in the physical domain, 22 (48%) reported impairments in the psychiatric domain, and four (8%) had impairments on cognitive screening. We found that 58% had some degree of mobility impairment. In the psychiatric domain, 38% exhibited at least mild depression, and 18 % moderate to severe depression. Eighteen percent presented Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, scores suggestive of posttraumatic stress syndrome diagnosis. In the Telephone Montreal Cognitive Assessment, 9% had impaired cognition. CONCLUSIONS: Survivors of critical illness related to coronavirus disease 2019 are at high risk of developing postintensive care syndrome. These findings highlight the importance of planning for appropriate post-ICU care to diagnose and treat this population.

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Atypical EEG patterns not consistent with standard sleep staging criteria have been observed in medical intensive care unit (ICU) patients. Our aim was to examine the relationship between sleep architecture and sedation in critically ill mechanically ventilated patients pre‐ and post‐extubation. We performed a prospective observational repeated measures study where 50 mechanically ventilated patients with 31 paired analyses were examined at an academic medical centre. The sleep efficiency was 58.3 ± 25.4% for intubated patients and 45.6 ± 25.4% for extubated patients (p = .02). Intubated patients spent 76.33 ± 3.34% of time in non‐rapid eye movement (NREM) sleep compared to 64.66 ± 4.06% of time for extubated patients (p = .02). REM sleep constituted 1.36 ± 0.67% of total sleep time in intubated patients and 2.06 ± 1.09% in extubated patients (p = .58). Relative sleep atypia was higher in intubated patients compared to extubated patients (3.38 ± 0.87 versus 2.79 ± 0.42; p < .001). Eleven patients were sedated with propofol only, 18 patients with fentanyl only, 11 patients with fentanyl and propofol, and 10 patients had no sedation. The mean sleep times on “propofol”, “fentanyl”, “propofol and fentanyl,” and “no sedation” were 6.54 ± 0.64, 4.88 ± 0.75, 6.20 ± 0.75 and 4.02 ± 0.62 hr, respectively. The sigma/alpha values for patients on “propofol”, “fentanyl”, “propofol and fentanyl” and “no sedation” were 0.69 ± 0.04, 0.54 ± 0.01, 0.62 ± 0.02 and 0.57 ± 0.02, respectively. Sedated patients on mechanical ventilation had higher sleep efficiency and more atypia compared to the same patients following extubation. Propofol was associated with higher sleep duration and less disrupted sleep architecture compared to fentanyl, propofol and fentanyl, or no sedation.

Eosinophilic gastroenteritis is an uncommon condition characterized by focal or diffuse infiltration of eosinophils in the gastrointestinal tract in the absence of secondary causes. The pathogenesis of this condition is not well understood and its clinical presentation depends on the segment and layer of the gastrointestinal tract affected. The definition of eosinophilic gastroenteritis may be difficult, as the normal ranges of eosinophil numbers in normal and abnormal gastric and intestinal mucosa are not standardized. We present the case of a 59-year-old male who came to the hospital with hypovolemic shock and lethargy secondary to severe diarrhea. Laboratory analysis was significant for peripheral eosinophilia, and pathology from both the duodenum and colon showed marked eosinophilic infiltration.

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