Derivation and Validation of Generalized Sepsis-induced Acute Respiratory Failure Phenotypes Among Critically Ill Patients: A Retrospective Study.

Background: Septic patients who develop acute respiratory failure (ARF) requiring mechanical ventilation represent a heterogenous subgroup of critically ill patients with widely variable clinical characteristics. Identifying distinct phenotypes of these patients may reveal insights about the broader heterogeneity in the clinical course of sepsis. We aimed to derive novel phenotypes of sepsis-induced ARF using observational clinical data and investigate their generalizability across multi-ICU specialties, considering multi-organ dynamics. Methods: We performed a multi-center retrospective study of ICU patients with sepsis who required mechanical ventilation for ≥24 hours. Data from two different high-volume academic hospital systems were used as a derivation set with N=3,225 medical ICU (MICU) patients and a validation set with N=848 MICU patients. For the multi-ICU validation, we utilized retrospective data from two surgical ICUs at the same hospitals (N=1,577). Clinical data from 24 hours preceding intubation was used to derive distinct phenotypes using an explainable machine learning-based clustering model interpreted by clinical experts. Results: Four distinct ARF phenotypes were identified: A (severe multi-organ dysfunction (MOD) with a high likelihood of kidney injury and heart failure), B (severe hypoxemic respiratory failure [median P/F=123]), C (mild hypoxia [median P/F=240]), and D (severe MOD with a high likelihood of hepatic injury, coagulopathy, and lactic acidosis). Patients in each phenotype showed differences in clinical course and mortality rates despite similarities in demographics and admission co-morbidities. The phenotypes were reproduced in external validation utilizing an external MICU from second hospital and SICUs from both centers. Kaplan-Meier analysis showed significant difference in 28-day mortality across the phenotypes (p<0.01) and consistent across both centers. The phenotypes demonstrated differences in treatment effects associated with high positive end-expiratory pressure (PEEP) strategy. Conclusion: The phenotypes demonstrated unique patterns of organ injury and differences in clinical outcomes, which may help inform future research and clinical trial design for tailored management strategies.

The influence of microbial colonization on inflammatory versus pro-healing trajectories in combat extremity wounds.

A combination of improved body armor, medical transportation, and treatment has led to the increased survival of warfighters from combat extremity injuries predominantly caused by blasts in modern conflicts. Despite advances, a high rate of complications such as wound infections, wound failure, amputations, and a decreased quality of life exist. To study the molecular underpinnings of wound failure, wound tissue biopsies from combat extremity injuries had RNA extracted and sequenced. Wounds were classified by colonization (colonized vs. non-colonized) and outcome (healed vs. failed) status. Differences in gene expression were investigated between timepoints at a gene level, and longitudinally by multi-gene networks, inferred proportions of immune cells, and expression of healing-related functions. Differences between wound outcomes in colonized wounds were more apparent than in non-colonized wounds. Colonized/healed wounds appeared able to mount an adaptive immune response to infection and progress beyond the inflammatory stage of healing, while colonized/failed wounds did not. Although, both colonized and non-colonized failed wounds showed increasing inferred immune and inflammatory programs, non-colonized/failed wounds progressed beyond the inflammatory stage, suggesting different mechanisms of failure dependent on colonization status. Overall, these data reveal gene expression profile differences in healing wounds that may be utilized to improve clinical treatment paradigms.

ClotCatcher: a novel natural language model to accurately adjudicate venous thromboembolism from radiology reports.

INTRODUCTION: Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classification of diseases (ICD) codes which are inaccurate - leading to misclassification bias. Here, we developed ClotCatcher, a novel deep learning model that uses natural language processing to detect VTE from radiology reports. METHODS: Radiology reports to detect VTE were obtained from patients admitted to Emory University Hospital (EUH) and Grady Memorial Hospital (GMH). Data augmentation was performed using the Google PEGASUS paraphraser. This data was then used to fine-tune ClotCatcher, a novel deep learning model. ClotCatcher was validated on both the EUH dataset alone and GMH dataset alone. RESULTS: The dataset contained 1358 studies from EUH and 915 studies from GMH (n = 2273). The dataset contained 1506 ultrasound studies with 528 (35.1%) studies positive for VTE, and 767 CT studies with 91 (11.9%) positive for VTE. When validated on the EUH dataset, ClotCatcher performed best (AUC = 0.980) when trained on both EUH and GMH dataset without paraphrasing. When validated on the GMH dataset, ClotCatcher performed best (AUC = 0.995) when trained on both EUH and GMH dataset with paraphrasing. CONCLUSION: ClotCatcher, a novel deep learning model with data augmentation rapidly and accurately adjudicated the presence of VTE from radiology reports. Applying ClotCatcher to large databases would allow for rapid and accurate adjudication of incident VTE. This would reduce misclassification bias and form the foundation for future studies to estimate individual risk for patient to develop incident VTE.

Targeted metagenomic assessment reflects critical colonization in battlefield injuries.

IMPORTANCE: Microbial contamination in combat wounds can lead to opportunistic infections and adverse outcomes. However, current microbiological detection has a limited ability to capture microbial functional genes. This work describes the application of targeted metagenomic sequencing to profile wound bioburden and capture relevant wound-associated signatures for clinical utility. Ultimately, the ability to detect such signatures will help guide clinical decisions regarding wound care and management and aid in the prediction of wound outcomes.

Central role for neurally dysregulated IL-17A in dynamic networks of systemic and local inflammation in combat casualties.

Dynamic Network Analysis (DyNA) and Dynamic Hypergraphs (DyHyp) were used to define protein-level inflammatory networks at the local (wound effluent) and systemic circulation (serum) levels from 140 active-duty, injured service members (59 with TBI and 81 non-TBI). Interleukin (IL)-17A was the only biomarker elevated significantly in both serum and effluent in TBI vs. non-TBI casualties, and the mediator with the most DyNA connections in TBI wounds. DyNA combining serum and effluent data to define cross-compartment correlations suggested that IL-17A bridges local and systemic circulation at late time points. DyHyp suggested that systemic IL-17A upregulation in TBI patients was associated with tumor necrosis factor-α, while IL-17A downregulation in non-TBI patients was associated with interferon-γ. Correlation analysis suggested differential upregulation of pathogenic Th17 cells, non-pathogenic Th17 cells, and memory/effector T cells. This was associated with reduced procalcitonin in both effluent and serum of TBI patients, in support of an antibacterial effect of Th17 cells in TBI patients. Dysregulation of Th17 responses following TBI may drive cross-compartment inflammation following combat injury, counteracting wound infection at the cost of elevated systemic inflammation.

Metagenomic features of bioburden serve as outcome indicators in combat extremity wounds.

Battlefield injury management requires specialized care, and wound infection is a frequent complication. Challenges related to characterizing relevant pathogens further complicates treatment. Applying metagenomics to wounds offers a comprehensive path toward assessing microbial genomic fingerprints and could indicate prognostic variables for future decision support tools. Wound specimens from combat-injured U.S. service members, obtained during surgical debridements before delayed wound closure, were subjected to whole metagenome analysis and targeted enrichment of antimicrobial resistance genes. Results did not indicate a singular, common microbial metagenomic profile for wound failure, instead reflecting a complex microenvironment with varying bioburden diversity across outcomes. Genus-level Pseudomonas detection was associated with wound failure at all surgeries. A logistic regression model was fit to the presence and absence of antimicrobial resistance classes to assess associations with nosocomial pathogens. A. baumannii detection was associated with detection of genomic signatures for resistance to trimethoprim, aminoglycosides, bacitracin, and polymyxin. Machine learning classifiers were applied to identify wound and microbial variables associated with outcome. Feature importance rankings averaged across models indicated the variables with the largest effects on predicting wound outcome, including an increase in P. putida sequence reads. These results describe the microbial genomic determinants in combat wound bioburden and demonstrate metagenomic investigation as a comprehensive tool for providing information toward aiding treatment of combat-related injuries.

Clinical risk factors and inflammatory biomarkers of post-traumatic acute kidney injury in combat patients.

BACKGROUND: Post-traumatic acute kidney injury has occurred in every major military conflict since its initial description during World War II. To ensure the proper treatment of combat casualties, early detection is critical. This study therefore aimed to investigate combat-related post-traumatic acute kidney injury in recent military conflicts, used machine learning algorithms to identify clinical and biomarker variables associated with the development of post-traumatic acute kidney injury, and evaluated the effects of post-traumatic acute kidney injury on wound healing and nosocomial infection. METHODS: We conducted a retrospective clinical cohort review of 73 critically injured US military service members who sustained major combat-related extremity wounds and had collected injury characteristics, assayed serum and tissue biopsy samples for the expression of protein and messenger ribonucleic acid biomarkers. Bivariate analyses and random forest recursive feature elimination classification algorithms were used to identify associated injury characteristics and biomarker variables. RESULTS: The incidence of post-traumatic acute kidney injury was 20.5%. Of that, 86% recovered baseline renal function and only 2 (15%) of the acute kidney injury group required renal replacement therapy. Random forest recursive feature elimination algorithms were able to estimate post-traumatic acute kidney injury with the area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.91. Post-traumatic acute kidney injury was associated with injury severity score, serum epidermal growth factor, and tissue activin A type receptor 1, matrix metallopeptidase 10, and X-C motif chemokine ligand 1 expression. Patients with post-traumatic acute kidney injury exhibited poor wound healing and increased incidence of nosocomial infections. CONCLUSION: The occurrence of acute kidney injury in combat casualties may be estimated using injury characteristics and serum and tissue biomarkers. External validations of these models are necessary to generalize for all trauma patients.

Utilizing Precision Medicine to Estimate Timing for Surgical Closure of Traumatic Extremity Wounds.

BACKGROUND: Both the frequency and high complication rates associated with extremity wounds in recent military conflicts have highlighted the need for clinical decision support tools (CDST) to decrease time to wound closure and wound failure rates. METHODS: Machine learning was used to estimate both successful wound closure (based on penultimate debridement biomarker data) and the necessary number of surgical debridements (based on presentation biomarkers) in 73 service members treated according to military guidelines based on clinical data and the local/systemic level of 32 cytokines. Models were trained to estimate successful closure including an additional 8 of 80 civilian patients with similar injury patterns. Previous analysis has demonstrated the potential to reduce the number of operative debridements by 2, with resulting decreases in ICU and hospital LOS, while decreasing the rate of wound failure. RESULTS: Analysis showed similar cytokine responses when civilians followed a military-like treatment schedule with surgical debridements every 24 to 72 hours. A model estimating successful closure had AUC of 0.89. Model performance in civilians degraded when these had a debridement interval > 72 hours (73 of the 80 civilians). A separate model estimating the number of debridements required to achieve successful closure had a multiclass AUC of 0.81. CONCLUSION: CDSTs can be developed using biologically compatible civilian and military populations as cytokine response is highly influenced by surgical treatment. Our CDSTs may help identify who may require serial debridements versus early closure, and precisely when traumatic wounds should optimally be closed.

Precision Medicine Applications to Manage Multiply Injured Patients With Orthopaedic Trauma.

Precision medicine offers potential for improved outcomes by tailoring interventions based on patient-specific demographics and disease-specific data. Precision methods are relatively unexplored in trauma patients. New research is being looked at for precision methods to treat patients with large extremity wounds, nonunions, and fractures associated with polytrauma. Precision-based clinical decision tools are being validated to optimize timing for open wound definitive closure. Early patient-specific biomarkers to stratify nonunion risk within 1 week of fracture are being explored. Patient-specific data to stage timing of major fracture interventions in multiply injured patients are being interrogated.

Preclosure spectroscopic differences between healed and dehisced traumatic wounds.

BACKGROUND: The complexity and severity of traumatic wounds in military and civilian trauma demands improved wound assessment, before, during, and after treatment. Here, we explore the potential of 3 charge-coupled device (3CCD) imaging values to distinguish between traumatic wounds that heal following closure and those that fail. Previous studies demonstrate that normalized 3CCD imaging values exhibit a high correlation with oxygen saturation and allow for comparison of values between diverse clinical settings, including utilizing different equipment and lighting. METHODS: We screened 119 patients at Walter Reed National Military Medical Center and at Grady Memorial Hospital with at least one traumatic extremity wound of ≥ 75 cm2. We collected images of each wound during each débridement surgery for a total of 66 patients. An in-house written computer application selected a region of interest in the images, separated the pixel color values, calculated relative values, and normalized them. We followed patients until the enrolled wounds were surgically closed, quantifying the number of wounds that dehisced (defined as wound failure or infection requiring return to the operating room after closure) or healed. RESULTS: Wound failure occurred in 20% (19 of 96) of traumatic wounds. Normalized intensity values for patients with wounds that healed successfully were, on average, significantly different from values for patients with wounds that failed (p ≤ 0.05). Simple thresholding models and partial least squares discriminant analysis models performed poorly. However, a hierarchical cluster analysis model created with 17 variables including 3CCD data, wound surface area, and time from injury predicts wound failure with 76.9% sensitivity, 76.5% specificity, 76.6% accuracy, and a diagnostic odds ratio of 10.8 (95% confidence interval: 2.6-45.9). CONCLUSIONS: Imaging using 3CCD technology may provide a non-invasive and cost-effective method of aiding surgeons in deciding if wounds are ready for closure and could potentially decrease the number of required débridements and hospital days. The process may be automated to provide real-time feedback in the operating room and clinic. The low cost and small size of the cameras makes this technology attractive for austere and shipboard environments where space and weight are at a premium.

Nonsteroidal anti-inflammatory drugs may affect cytokine response and benefit healing of combat-related extremity wounds.

BACKGROUND: After adequate operative debridement and antimicrobial therapies, combat-related extremity wounds that either heal or fail are both associated with a distinct inflammatory response. Short-term use of nonsteroidal anti-inflammatory drugs in postoperative pain management may affect this response and, by consequence, the healing potential of these wounds. We investigated whether patients treated with nonsteroidal anti-inflammatory drugs had a distinct inflammatory response; different rates of critical colonization, defined as >105 colony forming units on quantitative bacteriology; and healing potential. METHODS: We retrospectively reviewed the records of 73 patients with combat-related extremity wounds. Patients were separated into 2 groups: those who received nonsteroidal anti-inflammatory drugs during the debridement period (nonsteroidal anti-inflammatory drugs group, N = 17) and those who did not (control group; N = 56). Serum and wound tissue samples collected during each operative debridement were measured for 32 known cytokines and tested for quantitative bacteriology, respectively. We compared cytokine concentrations between groups and then designed a logistic regression model to identify variables associated with successful wound healing, while controlling for known confounders. RESULTS: Despite similar demographics and wound characteristics, the nonsteroidal anti-inflammatory drugs group had significant lesser concentrations of inflammatory cytokines, interleukin-2, interleukin-6, interleukin-8, and monocyte chemoattractant protein-1. On multivariate analysis, nonsteroidal anti-inflammatory drug treatment emerged as a predictor of successful wound healing after controlling for known confounders such as wound size, tobacco use, Acute Physiology and Chronic Health Evaluation II score, and critical colonization. CONCLUSION: Treatment with nonsteroidal anti-inflammatory drugs for postoperative pain management after major combat-related extremity trauma is associated with lesser concentrations of inflammatory cytokines and may contribute to a more favorable inflammatory response leading to successful wound healing.

Serum Inflammatory Cytokine Markers of Invasive Fungal Infection in Previously Immunocompetent Battle Casualties.

BACKGROUND: Invasive fungal infection (IFI) is described increasingly in individuals experiencing high-energy military trauma. Hallmarks of successful treatment involve aggressive surgical debridement and early initiation of systemic antimicrobial therapy. Currently, intravenous anti-fungal therapy commences based on appearance of wounds and patient's clinical course. Whereas some clinical protocols exist to predict which critically injured patients should receive anti-fungal therapies, there are no established serum markers associated with IFI. Our hypothesis is that serum inflammatory cytokines exist that can assist in identifying individuals at risk for IFI. METHODS: This is a retrospective case control study at a single institution. Nine patients with IFI (Saksenaea vasiformis, Fusarium sp., Graphium sp., Scedosporium sp., Aspergillus sp., Mucor sp., and Alternaria sp.) after battlefield trauma were matched to nine individuals with similar injury patterns whose laboratory results were negative for IFI. The combination of serum inflammatory cytokines from the first and second debridements was examined with multiplex platform proteomic analysis. We defined statistical significance as a two-tailed α<0.05 after adjusting for multiple comparisons using the false discovery rate method. This model was refined further with correlation-based filter selection and the area under the curve of the receiver operating characteristics (AUROC) was tested. RESULTS: Both groups had similar Injury Severity Scores (ISS) (mean±standard deviation [SD]) (26.8±15.5 vs. 29.2±16.8, p=0.766). Elevated RANTES (regulated on activation, normal T cell expressed and secreted) alone (10,492.8±4,450.1 vs. 5,333.3±4,162.2, p=0.006) correlated with IFI. Also, the combination of persistent elevations in RANTES, interleukin (IL)-2R, and IL-15 was a robust model for predicting IFI with the AUROC being 0.9. CONCLUSIONS: Elevation in serum cytokines, particularly RANTES, correlated with IFI in this small group of patients. This demonstrates the potential of future rapid serum testing for early initiation and guidance of anti-fungal therapies.

Bilateral lower-extremity amputation wounds are associated with distinct local and systemic cytokine response.

BACKGROUND: Approximately 25% of U.S. military members sustaining extremity amputations in recent military conflicts have bilateral lower-extremity amputations (BLA). We investigated among combat-related extremity wounds whether BLA exhibit different bacterial burden, inflammatory response, and local complications. METHODS: A total of 75 patients with combat-related extremity wounds (19 BLA) were evaluated for age, tobacco use, body mass index, Injury Severity Score, Acute Physiology and Chronic Health Evaluation II, and delayed primary closure time. Blood, wound exudates, and muscle biopsies were obtained and analyzed for cytokine and quantitative bacteriology, excluding patients using nonsteroidal anti-inflammatory medications and corticosteroids, due to potential effects on their inflammatory profile. RESULTS: BLA was not associated with differences in age, tobacco use, body mass index, and delayed primary closure time, but these patients had increased Injury Severity Score, Acute Physiology and Chronic Health Evaluation II, and rates of critical colonization. Proinflammatory cytokines including tumor necrosis factor-α (exudate), interleukin (IL)-1 (exudate) and IL-6 (serum) were increased in BLA patients. They also had serum and exudate increased IL-8 and decreased IL-13 and granulocyte-macrophage colony-stimulating factor. Both wound dehiscence (WD) and heterotopic ossification (HO) were more common in BLA patients. CONCLUSION: BLA patients were more likely to exhibit critical bacterial colonization, a distinct inflammatory response, and develop WD and HO. Modulating this response represents an attractive target in an effort to prevent complications such as WD and HO.

Pregnancy-specific glycoprotein 1 induces endothelial tubulogenesis through interaction with cell surface proteoglycans.

Pregnancy-specific ß1 glycoproteins (PSGs) are the most abundant fetal proteins in the maternal bloodstream in late pregnancy. They are secreted by the syncytiotrophoblast and are detected around day 14 postfertilization. There are 11 human PSG genes, which encode a family of proteins exhibiting significant conservation at the amino acid level. We and others have proposed that PSGs have an immune modulatory function. In addition, we recently postulated that they are proangiogenic due to their ability to induce the secretion of VEGF-A and the formation of tubes by endothelial cells. The cellular receptor(s) for human PSGs remain unknown. Therefore, we conducted these studies to identify the receptor for PSG1, the highest expressed member of the family. We show that removal of cell surface glycosaminoglycans (GAGs) by enzymatic or chemical treatment of cells or competition with heparin completely inhibited binding of PSG1. In addition, PSG1 did not bind to cells lacking heparan or chondroitin sulfate on their surface, and binding was restored upon transfection with all four syndecans and glypican-1. Importantly, the presence of GAGs on the surface of endothelial cells was required for the ability of PSG1 to induce tube formation. This finding indicates that the PSG1-GAG interaction mediates at least some of the PSG1 proposed functions.

Human pregnancy specific beta-1-glycoprotein 1 (PSG1) has a potential role in placental vascular morphogenesis.

Previous studies suggest that human pregnancy specific beta-1-glycoproteins (PSGs) play immunomodulatory roles during pregnancy; however, other possible functions of PSGs have yet to be explored. We have observed that PSGs induce transforming growth factor beta 1 (TGFB1), which among its other diverse functions inhibits T-cell function and has proangiogenic properties. The present study investigates a potential role for PSG1, the most abundant PSG in maternal serum, as a possible inducer of proangiogenic growth factors known to play an important role in establishment of the vasculature at the maternal-fetal interface. To this end, we measured TGFB1, vascular endothelial growth factors (VEGFs) A and C, and placental growth factor (PGF) protein levels in several cell types after PSG1 treatment. In addition, tube formation and wound healing assays were performed to investigate a possible direct interaction between PSG1 and endothelial cells. PSG1 induced up-regulation of both TGFB1 and VEGFA in human monocytes, macrophages, and two human extravillous trophoblast cell lines. We did not observe induction of VEGFC or PGF by PSG1 in any of the cells tested. PSG1 treatment resulted in endothelial tube formation in the presence and absence of VEGFA. Site-directed mutagenesis was performed to map the essential regions within the N-domain of PSG1 required for functional activity. We found that the aspartic acid at position 95, previously believed to be required for binding of PSGs to cells, is not required for PSG1 activity but that the amino acids implicated in the formation of a salt bridge within the N-domain are essential for PSG1 function.

Phospholipase d promotes lipid microdomain-associated signaling events in mast cells.

Initial IgE-dependent signaling events are associated with detergent-resistant membrane microdomains. Following Ag stimulation, the IgE-receptor (Fc(epsilon)RI ) accumulates within these domains. This facilitates the phosphorylation of Fc(epsilon)RI subunits by the Src kinase, Lyn, and the interaction with adaptor proteins, such as the linker for activation of T cells. Among the phospholipases (PL) subsequently activated, PLD is of interest because of its presence in lipid microdomains and the possibility that its product, phosphatidic acid, may regulate signal transduction and membrane trafficking. We find that in Ag-stimulated RBL-2H3 mast cells, the association of Fc(epsilon)RI with detergent-resistant membrane fractions is inhibited by 1-butanol, which subverts production of phosphatidic acid to the biologically inert phosphatidylbutanol. Furthermore, the knockdown of PLD2, and to a lesser extent PLD1 with small inhibitory RNAs, also suppressed the accumulation of Fc(epsilon)RI and Lyn in these fractions as well as the phosphorylation of Src kinases, Fc(epsilon)RI , linker for activation of T cells, and degranulation. These effects were accompanied by changes in distribution of the lipid microdomain component, ganglioside 1, in the plasma membrane as determined by binding of fluorescent-tagged cholera toxin B subunit and confocal microscopy in live cells. Collectively, these findings suggest that PLD activity plays an important role in promoting IgE-dependent signaling events within lipid microdomains in mast cells.

FcepsilonR1 and toll-like receptors mediate synergistic signals to markedly augment production of inflammatory cytokines in murine mast cells.

Mast cells mediate both IgE-dependent allergic reactions and protective responses against acute infections, possibly through the activation of Toll-like receptors (TLRs). We find that antigen interacts synergistically with TLR2 and TLR4 ligands to markedly enhance production of cytokines in murine mast cell lines. However, the TLR ligands neither stimulated degranulation and release of arachidonic acid nor influenced such responses to antigen, probably because these ligands failed to generate a necessary calcium signal. The enhanced cytokine production could be attributed to synergistic activation of mitogen-activated protein kinases in addition to the engagement of a more effective repertoire of transcription factors for cytokine gene transcription. The synergistic interactions of TLR ligands and antigen might have relevance to the exacerbation of IgE-mediated allergic diseases by infectious agents.