Quantification of muscle recovery in post-ICU patients admitted for acute pancreatitis: a longitudinal single-center study.

OBJECTIVES: Critically ill patients with severe pancreatitis exhibit substantial muscle wasting, which limits in-hospital and post-hospital outcomes. Survivors of critical illness undergo extensive recovery processes. Previous studies have explored pancreatic function, quality of life, and costs post-hospitalization for AP patients, but none have comprehensively quantified muscle loss and recovery post-discharge. By applying an AI-based automated segmentation tool, we aimed to quantify muscle mass recovery in ICU patients after discharge. MATERIALS: Muscle segmentation was performed on 22 patients, with a minimum of three measurements taken during hospitalization and one clinically indicated examination after hospital discharge. Changes in psoas muscle area (PMA) between admission, discharge and follow up were calculated. T-Test was performed to identify significant differences between patients able and not able to recover their muscle mass. RESULTS: Monitoring PMA shows muscle loss during and gain after hospitalization: The mean PMA at the first scan before or at ICU admission (TP1) was 17.08 cm², at the last scan before discharge (TP2), mean PMA was 9.61 cm². The percentage change in PMA between TP1 and TP2 ranged from - 85.42% to -2.89%, with a mean change of -40.18%. The maximum muscle decay observed during the stay was - 50.61%. After a mean follow-up period of 438.73 days most patients (81%) were able to increase their muscle mass. Compared to muscle status at TP1, only 27% of patients exhibited full recovery, with the majority still presenting a deficit of 31.96%. CONCLUSION: Muscle recovery in ICU patients suffering from severe AP is highly variable, with only about one third of patients recovering to their initial physical status. Opportunistic screening of post-ICU patient recovery using clinically indicated imaging and AI-based segmentation tools enables precise quantification of patients' muscle status and can be employed to identify individuals who fail to recover and would benefit from secondary rehabilitation. Understanding the dynamics of muscle atrophy may improve prognosis and support personalized patient care.

Opportunistic screening for long-term muscle wasting in critically ill patients: insights from an acute pancreatitis cohort.

OBJECTIVES: To assess the feasibility of long-term muscle monitoring, we implemented an AI-guided segmentation approach on clinically indicated Computed Tomography (CT) examinations conducted throughout the hospitalization period of patients admitted to the intensive care unit (ICU) with acute pancreatitis (AP). In addition, we aimed to investigate the potential of muscle monitoring for early detection of patients at nutritional risk and those experiencing adverse outcomes. This cohort served as a model for potential integration into clinical practice. MATERIALS: Retrospective cohort study including 100 patients suffering from AP that underwent a minimum of three CT scans during hospitalization, totaling 749 assessments. Sequential segmentation of psoas muscle area (PMA) was performed and was relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan was calculated. Subgroup and outcome analyses were performed including ANOVA. Discriminatory power of muscle decay rates was evaluated using ROC analysis. RESULTS: Monitoring PMA decay revealed significant long-term losses of 48.20% throughout the hospitalization period, with an average daily decline of 0.98%. Loss rates diverged significantly between survival groups, with 1.34% PMA decay per day among non-survivors vs. 0.74% in survivors. Overweight patients exhibited significantly higher total PMA losses (52.53 vs. 42.91%; p = 0.02) and average PMA loss per day (of 1.13 vs. 0.80%; p = 0.039). The first and the maximum decay rate, in average available after 6.16 and 17.03 days after ICU admission, showed convincing discriminatory power for survival in ROC analysis (AUC 0.607 and 0.718). Both thresholds for maximum loss (at 3.23% decay per day) and for the initial loss rate (at 1.98% per day) proved to be significant predictors of mortality. CONCLUSIONS: The innovative AI-based PMA segmentation method proved robust and effortless, enabling the first comprehensive assessment of muscle wasting in a large cohort of intensive care pancreatitis patients. Findings revealed significant muscle wasting (48.20% on average), particularly notable in overweight individuals. Higher rates of initial and maximum muscle loss, detectable early, correlated strongly with survival. Integrating this tool into routine clinical practice will enable continuous muscle status tracking and early identification of those at risk for unfavorable outcomes.

Intermittent body composition analysis as monitoring tool for muscle wasting in critically ill COVID-19 patients.

OBJECTIVES: SARS-CoV-2 virus infection can lead to acute respiratory distress syndrome (ARDS), which can be complicated by severe muscle wasting. Until now, data on muscle loss of critically ill COVID-19 patients are limited, while computed tomography (CT) scans for clinical follow-up are available. We sought to investigate the parameters of muscle wasting in these patients by being the first to test the clinical application of body composition analysis (BCA) as an intermittent monitoring tool. MATERIALS: BCA was conducted on 54 patients, with a minimum of three measurements taken during hospitalization, totaling 239 assessments. Changes in psoas- (PMA) and total abdominal muscle area (TAMA) were assessed by linear mixed model analysis. PMA was calculated as relative muscle loss per day for the entire monitoring period, as well as for the interval between each consecutive scan. Cox regression was applied to analyze associations with survival. Receiver operating characteristic (ROC) analysis and Youden index were used to define a decay cut-off. RESULTS: Intermittent BCA revealed significantly higher long-term PMA loss rates of 2.62% (vs. 1.16%, p < 0.001) and maximum muscle decay of 5.48% (vs. 3.66%, p = 0.039) per day in non-survivors. The first available decay rate did not significantly differ between survival groups but showed significant associations with survival in Cox regression (p = 0.011). In ROC analysis, PMA loss averaged over the stay had the greatest discriminatory power (AUC = 0.777) for survival. A long-term PMA decline per day of 1.84% was defined as a threshold; muscle loss beyond this cut-off proved to be a significant BCA-derived predictor of mortality. CONCLUSION: Muscle wasting in critically ill COVID-19 patients is severe and correlates with survival. Intermittent BCA derived from clinically indicated CT scans proved to be a valuable monitoring tool, which allows identification of individuals at risk for adverse outcomes and has great potential to support critical care decision-making.

Efficacy and safety of argatroban in patients with acute respiratory distress syndrome and extracorporeal lung support.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) or pumpless extracorporeal lung assist (pECLA) requires effective anticoagulation. Knowledge on the use of argatroban in patients with acute respiratory distress syndrome (ARDS) undergoing ECMO or pECLA is limited. Therefore, this study assessed the feasibility, efficacy and safety of argatroban in critically ill ARDS patients undergoing extracorporeal lung support. METHODS: This retrospective analysis included ARDS patients on extracorporeal lung support who received argatroban between 2007 and 2014 in a single ARDS referral center. As controls, patients who received heparin were matched for age, sex, body mass index and severity of illness scores. Major and minor bleeding complications, thromboembolic events, administered number of erythrocyte concentrates, thrombocytes and fresh-frozen plasmas were assessed. The number of extracorporeal circuit systems and extracorporeal lung support cannulas needed due to clotting was recorded. Also assessed was the efficacy to reach the targeted activated partial thromboplastin time (aPTT) in the first consecutive 14 days of therapy, and the controllability of aPTT values is within a therapeutic range of 50-75 s. Fisher's exact test, Mann-Whitney U tests, Friedman tests and multivariate nonparametric analyses for longitudinal data (MANOVA; Brunner's analysis) were applied where appropriate. RESULTS: Of the 535 patients who met the inclusion criteria, 39 receiving argatroban and 39 matched patients receiving heparin (controls) were included. Baseline characteristics were similar between the two groups, including severity of illness and organ failure scores. There were no significant differences in major and minor bleeding complications. Rates of thromboembolic events were generally low and were similar between the two groups, as were the rates of transfusions required and device-associated complications. The controllability of both argatroban and heparin improved over time, with a significantly increasing probability to reach the targeted aPTT corridor over the first days (p < 0.001). Over time, there were significantly fewer aPTT values below the targeted aPTT goal in the argatroban group than in the heparin group (p < 0.05). Both argatroban and heparin reached therapeutic aPTT values for adequate application of extracorporeal lung support. CONCLUSIONS: Argatroban appears to be a feasible, effective and safe anticoagulant for critically ill ARDS patients undergoing extracorporeal lung support.

Predictors of survival in critically ill patients with acute respiratory distress syndrome (ARDS): an observational study.

BACKGROUND: Currently there is no ARDS definition or classification system that allows optimal prediction of mortality in ARDS patients. This study aimed to examine the predictive values of the AECC and Berlin definitions, as well as clinical and respiratory parameters obtained at onset of ARDS and in the course of the first seven consecutive days. METHODS: The observational study was conducted at a 14-bed intensive care unit specialized on treatment of ARDS. Predictive validity of the AECC and Berlin definitions as well as PaO2/FiO2 and FiO2/PaO2*Pmean (oxygenation index) on mortality of ARDS patients was assessed and statistically compared. RESULTS: Four hundred forty two critically-ill patients admitted for ARDS were analysed. Multivariate Cox regression indicated that the oxygenation index was the most accurate parameter for mortality prediction. The third day after ARDS criteria were met at our hospital was found to represent the best compromise between earliness and accuracy of prognosis of mortality regarding the time of assessment. An oxygenation index of 15 or greater was associated with higher mortality, longer length of stay in ICU and hospital and longer duration of mechanical ventilation. In addition, non-survivors had a significantly longer length of stay and duration of mechanical ventilation in referring hospitals before admitted to the national reference centre than survivors. CONCLUSIONS: The oxygenation index is suggested to be the most suitable parameter to predict mortality in ARDS, preferably assessed on day 3 after admission to a specialized centre. Patients might benefit when transferred to specialized ICU centres as soon as possible for further treatment.

Social support during intensive care unit stay might improve mental impairment and consequently health-related quality of life in survivors of severe acute respiratory distress syndrome.

INTRODUCTION: We investigated health-related quality of life (HRQoL) and persistent symptoms of post-traumatic stress disorder (PTSD) in long-term survivors of acute respiratory distress syndrome (ARDS). We wished to evaluate the influence of PTSD on HRQoL and to investigate the influence of perceived social support during intensive care unit (ICU) treatment on both PTSD symptoms and HRQoL. METHODS: In ARDS patients we prospectively measured HRQoL (Medical Outcomes Study 36-Item Short Form; SF-36), symptoms of PTSD (Post-Traumatic Stress Syndrome 10-Questions Inventory; PTSS-10), perceived social support (Questionnaire for Social Support; F-Sozu) and symptoms of psychopathology (Symptom Checklist-90-R); and collected sociodemographic data including current employment status. Sixty-five (50.4%) out of 129 enrolled survivors responded, on average 57 +/- 32 months after discharge from ICU. Measuring symptoms of PTSD the PTSS-10 was used to divide the ARDS patients into two subgroups ('high-scoring patients', indicating patients with an increased risk for developing PTSD, and 'low-scoring patients'). RESULTS: HRQoL was significantly reduced in all dimensions in comparison with age- and gender-adjusted healthy controls. Eighteen patients (29%) were identified as being at increased risk for PTSD. PTSD risk was significantly linked with anxiety during their ICU stay. In this group of patients there was a trend towards permanent or temporary disability, independent of the period between discharge from ICU and study entry. Perceived social support was associated with a reduction in PTSD symptoms (Pearson correlation; p < 0.05). Post-hoc test revealed a significant difference between 'high-scoring patients' and 'low-scoring patients' with respect to mental health, although they did not differ in physical dimensions. CONCLUSION: HRQoL was reduced in long-term survivors, and was linked with an increased risk of chronic PTSD with ensuing psychological morbidity. This was independent of physical condition and was associated with traumatic memories of anxiety during their ICU stay. Social support might improve mental health and consequently long-term outcome including employment status.