Impact of malnutrition on postoperative delirium development after on pump coronary artery bypass grafting

Background & aims: Even though malnutrition is frequently observed in cardiac population outcome data after cardiac surgery in malnourished patients is very rare. No thorough research was done concerning the impact of malnutrition on neuropsychological outcomes after cardiac surgery. The aim of our study was to analyze the incidence of postoperative delirium development in malnourished patients undergoing on pump bypass grafting. Methods: We performed a cohort study of adults admitted to Vilnius University Hospital Santariskiu Clinics for elective coronary artery bypass grafting. The nutritional status of the patients was assessed by Nutritional Risk Screening 2002 (NRS-2002) questionnaire the day before surgery. Patients were considered as having no risk of malnutrition when NRS-2002 score was less than 3 and at risk of malnutrition when NRS-2002 score was ≥3. During ICU stay patients were screened for postoperative delirium development using the CAM-ICU method. and divided into two groups: delirium and non delirium. The statistical analysis was preformed to evaluate the differences between the two independent groups. The logistic regression model was used to evaluate the potential preoperative and intraoperative risk factors of postoperative delirium. Results: Ninety-nine patients were enrolled in the study. Preoperative risk of malnutrition was detected in 24 % (n = 24) of the patients. The incidence of early postoperative delirium in overall study population was 8.0 % (n = 8). The incidence of the patients at risk of malnutrition was significantly higher in the delirium group (5 (62.5 %) vs 19 (20.9 %), p <0.0191). In multivariate logistic regression analysis risk of malnutrition defined by NRS 2002 was an independent preoperative and intraoperative risk factor of postoperative delirium after coronary artery bypass grafting (OR: 6.316, 95 % CI: 1.384-28.819 p = 0.0173). Conclusions: Preoperative malnutrition is common in patients undergoing elective coronary artery bypass grafting. Nutrition deprivation is associated with early postoperative delirium after on pump coronary artery bypass grafting

Use of ringer’s lactate solution does not eliminate the risk of strong ion difference related metabolic acidosis following on pump cardiac surgery

Perioperative use of Normal Saline is linked to hyper- chloraemic or Strong Ion Difference (SID) related acido- sis. It has been suggested, that this can be avoided by the use of balanced crystalloid solutions including Ringer’s Lactate (RL). Significant changes in SID were noted pre- viously in cardiac surgery, however recent publication disproved the link between SID and hydrogen ion con- centratio

Ūminio inkstų funkcijos pažeidimo vertinimas širdies chirurgijoje: glomerulų filtracijos greičio ir liesosios kūno masės reikšmė

Background: eGFR (estimated glomerular filtration rate) formulas may be inaccurate in overweight cardiac surgery patients, overestimating the kidney reserve. The aim of this study was to modify the eGFR formulas and to determine whether the modified eGFR is a more accurate predictor of acute kidney injury (AKI). Materials and methods: The patients were assigned into 4 BMI groups as follows: normal weight (18.5–25 kg/m2), pre-obesity (25–30 kg/m2), class I obese (30–35 kg/m2), class II and III obese (≥35 kg/m2). Cockcroft–Gault (CG) eGFR formula was modified by using the fat-free mass (FFM) derived from bioelectrical impedance. ROC-AUC curves were analyzed to identify the accuracy of the eGFR formulas (CG, CG modified with FFM, Mayo Clinic Quadratic equation, CKD-EPI, MDRD) to predict the AKI in each group. Results: Although all of the used equations showed similar predictive power in the normal weight and overweight category, Mayo formula had the highest AUC in predicting the occurrence of AKI (ROC-AUC 0.717 and 0.624, p35 kg/m2). Conclusions: eGFR is a poor predictor of AKI, especially in the obese patients undergoing cardiac surgery. The only equation with a moderate predictive power for the class I obese patients was the CG formula modified with the fat-free mass

Determinants of Increased Effort of Breathing in Non-Intubated Critical COVID-19 Patients

Background and objectives: Acute respiratory distress syndrome (ARDS) is the most common complication occurring in COVID-19 patients admitted to the ICU. Given the increased respiratory work of these patients, it is necessary to evaluate their actual breathing efforts. The aim of this study is to report the incidence and determinants of increased effort of breathing (EOB) in critical COVID-19 patients. Materials and Methods: This was a retrospective study of COVID-19 patients admitted to the ICU during the year of 2020. Respiratory rate (RR) was chosen as an indicator of EOB. The cut-off value was set at more than 20 breaths per minute. ROC-AUC analysis was performed to identify the accuracy of the PaO2 and PaCO2 to determine increased EOB. Furthermore, multivariate regression analysis was performed to reveal the determinants of increased EOB. Results: 213 patients were included in the study. Mean RR in the population was 24.20 &plusmn; 6.28. 138 (64.8%) of the patients had increased EOB. The ROC-AUC analysis revealed the PaO2 (0.656 (CI 95%: 0.579&ndash;0.734, p &lt; 0.001) as more accurate predictor of EOB than PaCO2 (0.584 (CI 95%: 0.505&ndash;0.662, p = 0.043). In the final multivariate model, the SpO2 (exp(B) = 0.922, CI 95%: 0.874&ndash;0.97 p = 0.033), PaO2/FiO2 ratio (exp(B) = 0.996, CI 95%: 0.922&ndash;1.000, p = 0.003) and PaO2 (exp(B) = 0.989 CI 95%: 0.982&ndash;0.996 p = 0.003) prevailed as independent predictors of increased EOB. Conclusions: To conclude, PaO2 was revealed as a more accurate predictor of increased EOB than PaCO2. Further investigation revealed the independent determinants of EOB: blood oxygen saturation, PaO2 and PaO2/FiO2 ratio

Role of fat-free mass index on amino acid loss during CRRT in critically Ill patients

Background and objectives: Amino acid (AA) loss is a prevalent unwanted effect of continuous renal replacement therapy (CRRT) in critical care patients, determined both by the machine set-up and individual characteristics. The aim of this study was to evaluate the bioelectrical impedance analysis-derived fat-free mass index (FFMI) effect on amino acid loss. Materials and methods: This was a prospective, observational, single sample study of critical care patients upon initiation of CRRT. AA loss during a 24 h period was estimated. Conventional determinants of AA loss (type and dose of CRRT, concentration of AA) and FFMI were entered into the multivariate regression analysis to determine the individual predictive value. Results: Fifty-two patients were included in the study. The average age was 66.06 ± 13.60 years; most patients had a high mortality risk with APAHCE II values of 22.92 ± 8.15 and SOFA values of 12.11 ± 3.60. Mean AA loss in 24 h was 14.73 ± 9.83 g. There was a significant correlation between the lost AA and FFMI (R = 0.445, B = 0.445 CI95%: 0.541–1.793 p = 0.02). Multivariate regression analysis revealed the independent predictors of lost AA to be the systemic concentration of AA (B = 6.99 95% CI:4.96–9.04 p = 0.001), dose of CRRT (B = 0.48 95% CI:0.27–0.70 p < 0.001) and FFMI (B = 0.91 95% CI:0.42–1.41 p < 0.001). The type of CRRT was eliminated in the final model due to co-linearity with the dose of CRRT. Conclusions: A substantial amount of AA is lost during CRRT. The amount lost is increased by the conventional factors as well as by higher FFMI. Insights from our study highlight the FFMI as a novel research object during CRRT, both when prescribing the dosage and evaluating the nutritional support needed

Comparison of mortality risk evaluation tools efficacy in critically ill COVID-19 patients

Background: As the COVID-19 pandemic continues, the number of patients admitted to the intensive care unit (ICU) is still increasing. The aim of our article is to estimate which of the conventional ICU mortality risk scores is the most accurate at predicting mortality in COVID-19 patients and to determine how these scores can be used in combination with the 4C Mortality Score. Methods: This was a retrospective study of critically ill COVID-19 patients treated in tertiary reference COVID-19 hospitals during the year 2020. The 4C Mortality Score was calculated upon admission to the hospital. The Simplified Acute Physiology Score (SAPS) II, Acute Physiology and Chronic Health Evaluation (APACHE) II, and Sequential Organ Failure Assessment (SOFA) scores were calculated upon admission to the ICU. Patients were divided into two groups: ICU survivors and ICU non-survivors. Results: A total of 249 patients were included in the study, of which 63.1% were male. The average age of all patients was 61.32 ± 13.3 years. The all-cause ICU mortality ratio was 41.4% (n = 103). To determine the accuracy of the ICU mortality risk scores a ROC-AUC analysis was performed. The most accurate scale was the APACHE II, with an AUC value of 0.772 (95% CI 0.714–0.830; p < 0.001). All of the ICU risk scores and 4C Mortality Score were significant mortality predictors in the univariate regression analysis. The multivariate regression analysis was completed to elucidate which of the scores can be used in combination with the independent predictive value. In the final model, the APACHE II and 4C Mortality Score prevailed. For each point increase in the APACHE II, mortality risk increased by 1.155 (OR 1.155, 95% CI 1.085–1.229; p < 0.001), and for each point increase in the 4C Mortality Score, mortality risk increased by 1.191 (OR 1.191, 95% CI 1.086–1.306; p < 0.001), demonstrating the best overall calibration of the model. Conclusions: The study demonstrated that the APACHE II had the best discrimination of mortality in ICU patients. Both the APACHE II and 4C Mortality Score independently predict mortality risk and can be used concomitantly

Kinetics of SuPAR hemoadsorption in critical COVID-19 patients on renal replacement therapy

BACKGROUND: SARS-CoV-2 viral infection is associated with a rapid and vigorous systemic inflammatory response syndrome. Soluble urokinase-type plasminogen activator receptor (suPAR) is a novel biomarker, both indicative of inflammation and propagating it. Hemoadsorption has been proposed as a potential therapy in COVID-19 patients, therefore the aim of this study is to determine suPAR kinetics during hemoadsoprtion. METHODS: This was a prospective observational study of critical COVID-19 patients, enrolled when hemoperfusion therapy was initiated. Hemoadsorber was integrated into the continuous renal replacement therapy circuit. The first series of suPAR measurements was performed 10 minutes after the start of the session, sampling both incoming and outgoing lines of the adsorber. A second series of the measurements was performed beforefinishing the session with the same adsorber. Statistical significance level was set < 0.05. RESULTS: This study included 18 patients. In the beginning of the session the fraction of suPAR cleared across the adsorber was 29.5% [16-41], and in the end of the session it decreased to 7.2% [4-22], 4 times lower, p = 0.003. The median length of session was 21 hours, with minimal duration of 16 hours and maximal duration of 24 hours. The median suPAR before the procedure was 8.71 [7.18-10.78] and after the session was 7.35 [6.53-11.28] ng/ml. There was no statistically significant difference in suPAR concentrations before and after the session (p = 0.831). CONCLUSIONS: This study concluded that in the beginning of the hemoadsorption procedure significant amount of suPAR is removed from the circulation. However, in the end of the procedure there is a substantial drop in adsorbed capacity. Furthermore, despite a substantial amount of suPAR cleared there is no significant difference in systemic suPAR concentrations before and after the hemoadsorption procedure