Wilson, Gregory A

Objectives: Persistent cognitive impairment after critical illness is an important healthcare problem forecasted to worsen in the near future. However, the epidemiology is insufficiently explored. We aimed to determine potentially modifiable risk factors during ICU hospitalization that play a significant role in developing persistent cognitive impairment. Design: An observational case-control study. Settings: Mayo Clinic ICUs between July 1, 2004, and November 20, 2015. Patients: We conducted a study nested in a large cohort of 98,227 adult critically ill patients. Using previously validated computable phenotypes for dementia and cognitive impairment, we determined the onset of cognitive impairment relative to ICU hospitalization and associated risk factors. The primary endpoint of the study was new and persistent cognitive impairment documented between 3 and 24 months after ICU discharge. Interventions: Unadjusted and adjusted analyses were performed to identify potentially modifiable risk factors during ICU hospitalization. Measurements and Main Results: Among 21,923 unique patients identified as cognitively impaired (22% of the entire ICU cohort), 2,428 (2.5%) developed incident new and persistent cognitive dysfunction after the index ICU admission. Compared with age- and sex-matched ICU controls (2,401 pairs), cases had higher chronic illness burden (Charlson Comorbidity Index, 6.2 vs 5.1; p < 0.01), and were more likely to have multiple ICU stays (22% vs 14%; p < 0.01). After adjustment for baseline differences, new and persistent cognitive dysfunction was associated with higher frequency of acute brain failure in the ICU, a higher exposure to severe hypotension, hypoxemia, hyperthermia, fluctuations in serum glucose, and treatment with quinolones or vancomycin. Association with sepsis observed in univariate analysis did not persist after adjustment. Conclusions: Cognitive dysfunction is highly prevalent in ICU patients. Incident new and persistent cognitive impairment is less common but important, potentially preventable problem after critical illness. Chronic comorbidities and number of ICU stays increase the risk of post-ICU cognitive dysfunction irrespective of age. Modifiable ICU exposures were identified as potential targets for future prevention trials.

BACKGROUNDIt is increasingly recognized that recipient risk factors play a prominent role in possible transfusion‐related acute lung injury (pTRALI) and transfusion‐associated circulatory overload (TACO). We hypothesized that both transfusion and recipient factors including natriuretic peptides could be used to distinguish TRALI from TACO and pTRALI.STUDY DESIGN AND METHODSWe performed a post hoc analysis of a case‐control study of pulmonary transfusion reactions conducted at the University of California at San Francisco and Mayo Clinic, Rochester. We evaluated clinical data and brain natriuretic peptides (BNP) levels drawn after transfusion in patients with TRALI (n = 21), pTRALI (n = 26), TACO (n = 22), and controls (n = 24). Logistic regression and receiver operating characteristics curve analyses were used to determine the accuracy of clinical and biomarker predictors in differentiating TRALI from TACO and pTRALI.RESULTSWe found that pTRALI and TACO were associated with older age, higher fluid balance, and elevated BNP levels relative to those of controls and TRALI. The following variables were useful in distinguishing cases of pTRALI and TACO from TRALI: age more than 70 years, BNP levels more than 1000 pg/mL, 24‐hour fluid balance of more than 3 L, and a lower number of transfused blood components. Using the above variables, our logistic model had a 91% negative predictive value in the differential diagnosis of TRALI.CONCLUSIONSModels incorporating readily available clinical and biomarker data can be used to differentiate transfusion‐related respiratory complications. Additional studies examining recipient risk factors and the likelihood of TRALI may be useful in decision making regarding donor white blood cell antibody testing.

BACKGROUND Pulmonary transfusion reactions are important complications of blood transfusion, yet differentiating these clinical syndromes is diagnostically challenging. We hypothesized that biologic markers of inflammation could be used in conjunction with clinical predictors to distinguish transfusion‐related acute lung injury (TRALI), transfusion‐associated circulatory overload (TACO), and possible TRALI. STUDY DESIGN AND METHODS In a nested case‐control study performed at the University of California at San Francisco and Mayo Clinic, Rochester, we evaluated clinical data and blood samples drawn before and after transfusion in patients with TRALI (n = 70), possible TRALI (n = 48), TACO (n = 29), and controls (n = 147). Cytokines measured included granulocyte‐macrophage–colony‐stimulating factor, interleukin (IL)‐6, IL‐8, IL‐10, and tumor necrosis factor‐α. Logistic regression and receiver operating characteristics curve analyses were used to determine the accuracy of clinical predictors and laboratory markers in differentiating TACO, TRALI, and possible TRALI. RESULTS Before and after transfusion, IL‐6 and IL‐8 were elevated in patients with TRALI and possible TRALI relative to controls, and IL‐10 was elevated in patients with TACO and possible TRALI relative to that of TRALI and controls. For all pulmonary transfusion reactions, the combination of clinical variables and cytokine measurements displayed optimal diagnostic performance, and the model comparing TACO and TRALI correctly classified 92% of cases relative to expert panel diagnoses. CONCLUSIONS Before transfusion, there is evidence of systemic inflammation in patients who develop TRALI and possible TRALI but not TACO. A predictive model incorporating readily available clinical and cytokine data effectively differentiated transfusion‐related respiratory complications such as TRALI and TACO.