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Background: Impaired microcirculation is a cornerstone of sepsis development and leads to reduced tissue oxygenation, influenced by fluid and catecholamine administration during treatment. Hyperspectral imaging (HSI) is a non-invasive bedside technology for visualizing physicochemical tissue characteristics. Machine learning (ML) for skin HSI might offer an automated approach for bedside microcirculation assessment, providing an individualized tissue fingerprint of critically ill patients in intensive care. The study aimed to determine if machine learning could be utilized to automatically identify regions of interest (ROIs) in the hand, thereby distinguishing between healthy individuals and critically ill patients with sepsis using HSI., Methods: HSI raw data from 75 critically ill sepsis patients and from 30 healthy controls were recorded using TIVITA® Tissue System and analyzed using an automated ML approach. Additionally, patients were divided into two groups based on their SOFA scores for further subanalysis: less severely ill (SOFA ≤ 5) and severely ill (SOFA > 5). The analysis of the HSI raw data was fully-automated using MediaPipe for ROI detection (palm and fingertips) and feature extraction. HSI Features were statistically analyzed to highlight relevant wavelength combinations using Mann-Whitney-U test and Benjamini, Krieger, and Yekutieli (BKY) correction. In addition, Random Forest models were trained using bootstrapping, and feature importances were determined to gain insights regarding the wavelength importance for a model decision., Results: An automated pipeline for generating ROIs and HSI feature extraction was successfully established. HSI raw data analysis accurately distinguished healthy controls from sepsis patients. Wavelengths at the fingertips differed in the ranges of 575-695 nm and 840-1000 nm. For the palm, significant differences were observed in the range of 925-1000 nm. Feature importance plots indicated relevant information in the same wavelength ranges. Combining palm and fingertip analysis provided the highest reliability, with an AUC of 0.92 to distinguish between sepsis patients and healthy controls., Conclusion: Based on this proof of concept, the integration of automated and standardized ROIs along with automated skin HSI analyzes, was able to differentiate between healthy individuals and patients with sepsis. This approach offers a reliable and objective assessment of skin microcirculation, facilitating the rapid identification of critically ill patients., (© 2024. The Author(s).)

Hyperspectral imaging (HSI) is a non-invasive technology that provides information on biochemical tissue properties, including skin oxygenation and perfusion quality. Microcirculatory alterations are associated with organ dysfunction in septic COVID-19 patients. This prospective observational study investigated associations between skin HSI and organ dysfunction severity in critically ill COVID-19 patients. During the first seven days in the ICU, palmar HSI measurements were carried out with the TIVITA ® tissue system. We report data from 52 critically ill COVID-19 patients, of whom 40 required extracorporeal membrane oxygenation (ECMO). HSI parameters for superficial tissue oxygenation (StO 2 ) and oxygenation and perfusion quality (NPI) were persistently decreased. Hemoglobin tissue content (THI) increased, and tissue water content (TWI) was persistently elevated. Regression analysis showed strong indications for an association of NPI and weaker indications for associations of StO 2 , THI, and TWI with sequential organ failure assessment (SOFA) scoring. StO 2 and NPI demonstrated negative associations with vasopressor support and lactate levels as well as positive associations with arterial oxygen saturation. These results suggest that skin HSI provides clinically relevant information, opening new perspectives for microcirculatory monitoring in critical care.

Introduction: Previous studies demonstrated that the implementation of the Kidney Disease Improving Global Outcomes (KDIGO) guideline-based bundle, consisting of different supportive measures in patients at high risk for acute kidney injury (AKI), might reduce rate and severity of AKI after surgery. However, the effects of the care bundle in broader population of patients undergoing surgery require confirmation., Methods and Analysis: The BigpAK-2 trial is an international, randomised, controlled, multicentre trial. The trial aims to enrol 1302 patients undergoing major surgery who are subsequently admitted to the intensive care or high dependency unit and are at high-risk for postoperative AKI as identified by urinary biomarkers (tissue inhibitor of metalloproteinases 2*insulin like growth factor binding protein 7 (TIMP-2)*IGFBP7)). Eligible patients will be randomised to receive either standard of care (control) or a KDIGO-based AKI care bundle (intervention). The primary endpoint is the incidence of moderate or severe AKI (stage 2 or 3) within 72 hours after surgery, according to the KDIGO 2012 criteria. Secondary endpoints include adherence to the KDIGO care bundle, occurrence and severity of any stage of AKI, change in biomarker values during 12 hours after initial measurement of (TIMP-2)*(IGFBP7), number of free days of mechanical ventilation and vasopressors, need for renal replacement therapy (RRT), duration of RRT, renal recovery, 30-day and 60-day mortality, intensive care unit length-of-stay and hospital length-of-stay and major adverse kidney events. An add-on study will investigate blood and urine samples from recruited patients for immunological functions and kidney damage., Ethics and Dissemination: The BigpAK-2 trial was approved by the Ethics Committee of the Medical Faculty of the University of Münster and subsequently by the corresponding Ethics Committee of the participating sites. A study amendment was approved subsequently. In the UK, the trial was adopted as an NIHR portfolio study. Results will be disseminated widely and published in peer-reviewed journals, presented at conferences and will guide patient care and further research., Trial Registration Number: NCT04647396., Competing Interests: Competing interests: MM has received lecture fees from Biomériux, Baxter and Fresenius Medical Care as well as an unrestricted research grant from Baxter. AZ has received lecture and consultancy fees from Biomériux, Baxter, AM Pharma, Novartis, Guard Therapeutics, Paion, Bayer and Fresenius Medical Care. In addition, AZ received unrestricted research grants from Baxter, Biomériux, Fresenius and the Deutsche Forschungsgemeinschaft (German Research Foundation). JK is a paid consultant to Biomériux and is employed by Spectral Medical. SR received lecture fees from bioMerieux, Baxter and BBraun, as well as an unrestricted research grant from Baxter. SdR has received an educational grant from bioMerieux. MO has received research funding from bioMerieux. JG has received honoraria from TESARO, QUIRIS Healthcare, Ecker+Ecker, Dr August Wolff, Roche, University Clinics Schleswig-Holstein and RWTH Aachen University. AS has received consultancy fees from bioMerieux. All other authors have no conflict of interests to declare., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

A biomarker for risk stratification and disease severity assessment in SARS-CoV-2 infections has not yet been established. Point of care testing (POCT) of butyrylcholinesterase (BChE) enables early detection of systemic inflammatory responses and correlates with disease severity in sepsis and burns. In acute care or resource-limited settings, POCT facilitates rapid clinical decision making, a particularly beneficial aspect in the management of pandemic situations. In this prospective observational study, POCT-measured BChE activity was assessed in 52 critically ill COVID-19 patients within 24 h of ICU admission and on the third and seventh day after ICU admission. Forty (77%) of these patients required venovenous extracorporeal membrane oxygenation (vvECMO). In critically ill COVID-19 patients, BChE activity is significantly decreased compared with healthy subjects, but also compared with other inflammatory conditions such as sepsis, burns, or trauma. POCT BChE activity reflects the severity of organ dysfunction and allows prediction of 28-day mortality in critically ill COVID-19 patients. Implementing early POCT BChE measurement could facilitate risk stratification and support admission and transfer decisions in resource-limited settings.

Background: Accurate pre-operative evaluation of cardiovascular risk is vital to identify patients at risk for major adverse cardiovascular and cerebrovascular events (MACCE) after noncardiac surgery. Elevated presepsin (sCD14-ST) is associated with peri-operative MACCE in coronary artery disease (CAD) patients after noncardiac surgery., Objectives: Validating the prognostic utility of presepsin for MACCE after noncardiac surgery., Design: Prospective patient enrolment and blood sampling, followed by post hoc evaluation of pre-operative presepsin for prediction of MACCE., Setting: Single university centre., Patients: A total of 222 CAD patients undergoing elective, inpatient noncardiac surgery., Intervention: Pre-operative presepsin measurement., Main Outcome Measures: MACCE (cardiovascular death, myocardial infarction, myocardial ischaemia and stroke) at 30 days postsurgery., Results: MACCE was diagnosed in 23 (10%) patients. MACCE patients presented with increased pre-operative presepsin (median [IQR]; 212 [163 to 358] vs. 156 [102 to 273] pgml, P = 0.023). Presepsin exceeding the previously derived threshold of 184 pg ml was associated with increased 30-day MACCE rate. After adjustment for confounders, presepsin more than 184 pg ml [OR = 2.8 (95% confidence interval 1.1 to 7.3), P = 0.03] remained an independent predictor of peri-operative MACCE. Predictive accuracy of presepsin was moderate [area under the curve (AUC) = 0.65 (0.54 to 0.75), P = 0.023]. While the basic risk model of revised cardiac risk index, high-sensitive cardiac troponin T and N-terminal fragment of pro-brain natriuretic peptide resulted in an AUC = 0.62 (0.48 to 0.75), P = 0.072, addition of presepsin to the model led to an AUC = 0.67 (0.56 to 0.78), P = 0.009 and (ΔAUC = 0.05, P = 0.438). Additive risk predictive value of presepsin was demonstrated by integrated discrimination improvement analysis (integrated discrimination improvement = 0.023, P = 0.022). Net reclassification improvement revealed that the additional strength of presepsin was attributed to the reclassification of no-MACCE patients into a lower risk group., Conclusion: Increased pre-operative presepsin independently predicted 30-day MACCE in CAD patients undergoing major noncardiac surgery. Complementing cardiovascular risk prediction by inflammatory biomarkers, such as presepsin, offers potential to improve peri-operative care. However, as prediction accuracy of presepsin was only moderate, further validation studies are needed., Trial Registration: Clinicaltrials.gov: NCT03105427.

Immune cells drive atherosclerotic lesion progression and plaque destabilization. Coronary heart disease patients undergoing noncardiac surgery are at risk for perioperative major adverse cardiac and cerebrovascular events (MACCE). It is unclear whether differential leukocyte subpopulations contribute to perioperative MACCE and thereby could aid identification of patients prone to perioperative cardiovascular events. First, we performed a hypothesis-generating post hoc analysis of the LeukoCAPE-1 study (n = 38). We analyzed preoperative counts of 6 leukocyte subpopulations in coronary heart disease patients for association with MACCE (composite of cardiac death, myocardial infarction, myocardial ischemia, myocardial injury after noncardiac surgery, thromboembolic stroke) within 30 d after surgery. Regulatory T cells (Tregs) were the only leukocyte subgroup associated with MACCE. We found reduced Tregs in patients experiencing MACCE versus no-MACCE (0.02 [0.01; 0.03] vs. 0.04 [0.03; 0.05] Tregs nl -1 , P = 0.002). Using Youden index, we derived the optimal threshold value for association with MACCE to be 0.027 Tregs nl -1 . Subsequently, we recruited 233 coronary heart disease patients for the prospective, observational LeukoCAPE-2 study and independently validated this Treg cutoff for prediction of MACCE within 30 d after noncardiac surgery. After multivariate logistic regression, Tregs < 0.027 cells nl -1 remained an independent predictor for MACCE (OR = 2.54 [1.22; 5.23], P = 0.012). Tregs improved risk discrimination of the revised cardiac risk index based on ΔAUC (area under the curve; ΔAUC = 0.09, P = 0.02), NRI (0.26), and IDI (0.06). Preoperative Treg levels below 0.027 cells nl -1 predicted perioperative MACCE and can be measured to increase accuracy of established preoperative cardiac risk stratification in coronary heart disease patients undergoing noncardiac surgery., (© 2019 The Authors. Journal of Leukocyte Biology published by Wiley Periodicals, Inc. on behalf of Society for Leukocyte Biology.)

Background: To evaluate diagnostic and long-term prognostic values of hFABP compared to NT-proBNP and troponin I (TnI) in patients presenting to the emergency department (ED) suspected of acute heart failure (AHF)., Methods: 401 patients with acute dyspnea or peripheral edema, 122 suffering from AHF, were prospectively enrolled and followed up to 5 years. hFABP combined with NT-proBNP versus NT-proBNP alone was tested for AHF diagnosis. Prognostic value of hFABP versus TnI was evaluated in models predicting all-cause mortality (ACM) and AHF related rehospitalization (AHF-RH) at 1 and 5 years, including 11 conventional risk factors plus NT-proBNP., Results: Additional hFABP measurements improved diagnostic specificity and positive predictive value (PPV) of sole NT-proBNP testing at the cutoff <300 ng/l to "rule out" AHF. Highest hFABP levels (4th quartile) were associated with increased ACM (hazard ratios (HR): 2.1-2.5; p = 0.04) and AHF-RH risk at 5 years (HR 2.8-8.3, p = 0.001). ACM was better characterized in prognostic models including TnI, whereas AHF-RH was better characterized in prognostic models including hFABP. Cox analyses revealed a 2 % increase of ACM risk and 3-7 % increase of AHF-RH risk at 5 years by each unit increase of hFABP of 10 ng/ml., Conclusions: Combining hFABP plus NT-proBNP (<300 ng/l) only improves diagnostic specificity and PPV to rule out AHF. hFABP may improve prognosis for long-term AHF-RH, whereas TnI may improve prognosis for ACM., Trial Registration: ClinicalTrials.gov identifier: NCT00143793 .

Background: To evaluate the diagnostic and prognostic value of sensitive troponin I (TnI) in patients with acute dyspnea and/or peripheral edema suspected of having acute heart failure (AHF)., Methods: This single centre prospective clinical study evaluates 372 patients presenting with acute dyspnea and/or peripheral edema to the emergency department (ED). Measurements of TnI and NT-proBNP were performed at the initial presentation in the ED. All patients were followed up to 5 years. The diagnostic value of TnI compared to NT-proBNP for AHF diagnosis as well as long-term prognostic values for all cause mortality and AHF related rehospitalization were evaluated., Results: TnI plus NT-proBNP improved the diagnosis of AHF (improvement of accuracy (75%, 95% CI 71% - 79%), specificity (68%, 95% CI 62% - 74%), PPV (54%, 95% CI 47% - 62%), and NRI +0.15) compared to NT-proBNP alone (p = 0.0001). TnI levels showed independent prognostic value for all-cause mortality and AHF related rehospitalization after 1 and 5 years (range of AUCs 0.64 - 0.72; p = 0.03 or lower). Highest TnI levels of the 4th quartile revealed an up to 5.5 times higher risk of death within 1 and 5 years (range of HRs: 2.5 - 5.5; p = 0.0001). TnI added significantly to multivariable Cox prediction models even after adjusting for NT-proBNP, particularly in AHF patients (range of HRs: 2.1 - 2.7; p ≤ 0.05)., Conclusions: TnI improves AHF diagnosis when combined with NT-proBNP. TnI identifies patients with high 1- and 5-year all-cause mortality and AHF-related rehospitalization risk and adds prognostic value to NT-proBNP.

Aims: To evaluate the diagnostic and prognostic value of osteopontin in patients with acute dyspnoea and/or peripheral oedema suspected of having acute congestive heart failure (aCHF)., Methods and Results: A total of 401 patients presenting with acute dyspnoea and/or peripheral oedema to the emergency department were prospectively enrolled and followed up for up to 5 years. Blood samples for biomarker measurements were collected on admission to the emergency department. Osteopontin combined with NT-proBNP vs. NT-proBNP alone for diagnosis of aCHF was tested. Additionally, osteopontin vs. NT-proBNP for prognostic outcomes (i.e. all-cause mortality, aCHF-related rehospitalization, and both in combination) was tested. The diagnostic and prognostic capacity of osteopontin was tested by C-statistics, reclassification indices, and multivariable Cox prediction models. Osteopontin plus NT-proBNP improved the diagnostic capacity for aCHF diagnosis [accuracy 76%, 95% confidence interval (CI) 72-80%; specificity 74%, 95% CI 69-79%, net reclassification improvement (NRI) +0.10] compared with NT-proBNP alone in the emergency department (P = 0.0001). Osteopontin independently predicted all-cause mortality and aCHF-related rehospitalization after 1 and 5 years. Compared with NT-proBNP, osteopontin was of superior prognostic value, specifically in aCHF patients and for the prognostic outcome of aCHF-related rehospitalization., Conclusion: Osteopontin improves aCHF diagnosis when combined with NT-proBNP. Osteopontin identifies aCHF patients with high 1- and 5-year mortality and rehospitalization risk, and adds prognostic value to NT-proBNP. Trial registration NCT00143793.