A system theory based digital model for predicting the cumulative fluid balance course in intensive care patients.

Background: Surgical interventions can cause severe fluid imbalances in patients undergoing cardiac surgery, affecting length of hospital stay and survival. Therefore, appropriate management of daily fluid goals is a key element of postoperative intensive care in these patients. Because fluid balance is influenced by a complex interplay of patient-, surgery- and intensive care unit (ICU)-specific factors, fluid prediction is difficult and often inaccurate. Methods: A novel system theory based digital model for cumulative fluid balance (CFB) prediction is presented using recorded patient fluid data as the sole parameter source by applying the concept of a transfer function. Using a retrospective dataset of n = 618 cardiac intensive care patients, patient-individual models were created and evaluated. RMSE analyses and error calculations were performed for reasonable combinations of model estimation periods and clinically relevant prediction horizons for CFB. Results: Our models have shown that a clinically relevant time horizon for CFB prediction with the combination of 48 h estimation time and 8-16 h prediction time achieves high accuracy. With an 8-h prediction time, nearly 50% of CFB predictions are within ±0.5 L, and 77% are still within the clinically acceptable range of ±1.0 L. Conclusion: Our study has provided a promising proof of principle and may form the basis for further efforts in the development of computational models for fluid prediction that do not require large datasets for training and validation, as is the case with machine learning or AI-based models. The adaptive transfer function approach allows estimation of CFB course on a dynamically changing patient fluid balance system by simulating the response to the current fluid management regime, providing a useful digital tool for clinicians in daily intensive care.

A sliding-window based algorithm to determine the presence of chest compressions from acceleration data.

This publication presents in detail five exemplary cases and the algorithm used in the article (Orlob et al. 2022). Defibrillator records for the five exemplary cases were obtained from the German Resuscitation Registry. They consist of accelerometry, electrocardiogram and capnography time series as well as defibrillation times, energies and impedance when recorded. For these cases, experienced physicians annotated time points of cardiac arrest and return of spontaneous circulation or termination of resuscitation attempts, as well as the beginning and ending of every single chest compression period in consensus, as described in Orlob et al. (2022). Furthermore, an algorithm was developed which reliably detects chest compression periods automatically without the time-consuming process of manual annotation. This algorithm allows for an usage in automatic resuscitation quality assessment, machine learning approaches, and handling of big amounts of data (Orlob et al. 2022).

Chest compression fraction calculation: A new, automated, robust method to identify periods of chest compressions from defibrillator data - Tested in Zoll X Series.

AIM: To introduce and evaluate a new, open-source algorithm to detect chest compression periods automatically by the rhythmic, high amplitude signals from an accelerometer, without processing single chest compression events, and to consecutively calculate the chest compression fraction (CCF). METHODS: A consecutive sample of defibrillator records from the German Resuscitation Registry was obtained and manually annotated in consensus as ground truth. Chest compression periods were determined by different automatic approaches, including the new algorithm. The diagnostic performance of these approaches was assessed. Further, using the different approaches in conjunction with different granularities of manual annotation, several CCF versions were calculated and compared by intraclass correlation coefficient (ICC). RESULTS: 131 defibrillator recordings with a total duration of 5755 minutes were analysed. The new algorithm had a sensitivity of 99.39 (95% CI 99.38, 99.41)% and specificity of 99.17 (95% CI 99.15; 99.18)% to detect chest compressions at any given timepoint. The ICC compared to ground truth was 0.998 for the new algorithm and 0.999 for manual annotation, while the ICC of the proposed algorithm compared to the proprietary software was 0.978. The time required for manual annotation to calculate CCF was reduced by 70.48 (22.55, [94.35, 14.45])%. CONCLUSION: The proposed algorithm reliably detects chest compressions in defibrillator recordings. It can markedly reduce the workload for manual annotation, which may facilitate uniform reporting of measured quality of cardiopulmonary resuscitation. The algorithm is made freely available and may be used in big data analysis and machine learning approaches.

Convalescent plasma therapy and mortality in COVID-19 patients admitted to the ICU: a prospective observational study.

BACKGROUND: This study aimed to quantify the potential survival benefit of convalescent plasma therapy (CVP) in critically ill patients with acute respiratory failure related to coronavirus disease-2019 (COVID-19). METHODS: This is a single-center prospective observational cohort study in COVID-19 patients with acute respiratory failure. Immediately after intensive care unit (ICU) admission patients were allocated to CVP treatment following pre-specified criteria to rapidly identify those patients potentially susceptible for this treatment. A propensity score adjustment [inverse probability of treatment weighted (IPTW) analysis] was implemented to account rigorously for imbalances in prognostic variables between the treatment groups. RESULTS: We included 120 patients of whom 48 received CVP. Thirty percent were female with a median age of 66 years [25th-75th percentile 54-75]. Eighty-eight percent of patients presented with severe acute respiratory failure as displayed by a median paO2/FiO2 ratio (Horowitz Index) of 92 [77-150]. All patients required any kind of ventilatory support with more than half of them (52%) receiving invasive ventilation. Thirty-day ICU overall survival (OS) was 69% in the CVP group and 54% in the non-CVP group (log-rank p = 0.049), respectively. After weighing the time-to-event data for the IPTW, the favorable association between CVP and OS became even stronger (log-rank p = 0.035). Moreover, an exploratory analysis showed an overall survival benefit of CVP therapy for patients with non-invasive ventilation (Hazard ratio 0.12 95% CI 0.03-0.57, p = 0.007) CONCLUSION: Administration of CVP in patients with acute respiratory failure related to COVID-19 is associated with improved ICU survival rates.

High Rate of Gastrointestinal Bleeding in Patients with Secondary Sclerosing Cholangitis in Critically Ill Patients (SC-CIP).

Secondary sclerosing cholangitis in critically ill patients (SC-CIP) is a rare cholestatic liver disease triggered by long-term intensive care treatment. The aim of this study was to evaluate the frequency and characteristics of gastrointestinal bleeding in SC-CIP. Patients with diagnosed SC-CIP were retrospectively identified and compared to a control group of patients with cardiac surgery and intensive care treatment but without the development of SC-CIP. Fifty-three patients with SC-CIP and 19 controls were included in the study. The frequency of gastrointestinal bleeding was 30% in SC-CIP (16 patients) and 5% in the control group (1 patient) (p = 0.03). Bleeding occured in the mean 13 months after admission to an intensive care unit in SC-CIP, three patients (19%) suffered bleeding during intensive care treatment. Three SC-CIP patients (19%) had cirrhosis at the time of bleeding, five (31%) had splenomegaly, and four (25%) received oral anticoagulation. In SC-CIP, 13 bleedings were identified in the upper gastrointestinal tract, two in the lower, and one remained unknown. The most common reasons for bleeding were gastroduodenal ulcers. In total, 80% of patients needed blood units, and one death due to bleeding occurred in SC-CIP. In conclusion, gastrointestinal bleeding is a frequent complication in patients with SC-CIP. Whether the liver disease itself or cofactors cause the susceptibility for bleeding remains unclear.

Vitamin D assessment in perioperative medicine and critical care : A prospective observational pilot study.

BACKGROUND: There is controversy about the impact of acute illness on vitamin D levels. This study was carried out to assess the influence of perioperative fluid loading on 25-hydroxy-vitamin D [25(OH)D] levels. The study evaluated the clinical utility of a commonly available chemiluminescence assay (ECLIA, IDS-iSYS) and liquid chromatography/mass spectrometry (LC-MS/MS) in the diagnosis of vitamin D deficiency in this setting. METHODS: In this prospective observational pilot study in adult patients undergoing cardiovascular surgery on cardiopulmonary bypass (CPB), blood samples drawn at preoperative baseline (t1), after weaning from CPB (t2), on intensive care unit (ICU) admission (t3) and on the first (t4) and second (t5) postoperative days were analyzed. RESULTS: A total of 26 patients (130 samples) were included in this study. Fluid loading by CPB led to a median reduction of 25(OH)D by -22.6% (range -54.5% to -19.5%) between t1 and t2. Cohen's kappa (κ) for method agreement for vitamin D deficiency (tested cut-off values 20 ng/ml and 12 ng/ml), was κ = 0.291 (p < 0.001) and κ = 0.469 (p < 0.001), respectively. The mean difference between measurements by ECLIA and LC-MS/MS was 4.8 ng/ml (±5.7), Pearson's r for correlation was 0.73 (p < 0.001). The biologically inactive C3-epimer did not contribute to 25(OH)D levels assessed by LC-MS/MS. CONCLUSION: The 25(OH)D measurements by chemiluminescence assays can noticeably deviate from those measured by LC-MS/MS, which can be considered the unequivocal gold standard. These assays may still be acceptably reliable in the screening for vitamin D deficiency, especially in the setting of low vitamin D levels. Stricter definitions, e.g. serum 25(OH)D levels lower than 12 ng/ml, may be used to diagnose deficiency with low false positive rate. TRIAL REGISTRATION: DRKS00009216, German Clinical Trials Registry ( www.drks.de ).

Effects of enteral nutrition on gastrointestinal function in patients who are critically ill.

Nutritional management is a cornerstone of therapy for patients who are critically ill. Data show that enteral nutrition is better than parenteral nutrition with regard to the morbidity of critcally ill patients, especially for infectious complications. These findings suggest that feeding patients enterally has other beneficial effects besides delivering nutrients. In the absence of enteral nutrition, the mucosal architecture changes distinctly, leading to an impairment in function of the gastrointestinal barrier. This impairment facilitates the migration of bacteria from the intestinal lumen into the submucosal tissue and triggers epithelial inflammation. Consequently, proinflammatory and anti-inflammatory factors are imbalanced, leading to further degradation of gastrointestinal mucosal resistance. The enteral stimulus is also important to maintain physiological interaction of commensal bacteria with enteric immune cells. The absence of enteral nutrition induces deregulation of receptors that modulate the immunological response to commensal bacteria and pathogens-an important factor that initiates intestinal inflammation. Additionally, without enteral nutrients, the gastrointestinal mucosa atrophies because epithelial cells absorb nutrients directly from the gastrointestinal tract to meet their nutritional requirements. All these negative effects of absent enteral nutrition can be explained by a distinct change in cellular signalling pathways. Studies show that the physiological stimulus of enteral nutrition is crucial to maintain gastrointestinal functions such as barrier, immunological, and resorptive function. Enteral nutrients are important to maintain intact gastrointestinal motility since the nutrients stimulate the secretion of motility-regulating gastrointestinal hormones.