Search Results (3,866)

Background: Timely recognition of sepsis remains a critical clinical challenge, particularly in cancer patients, who are at higher risk due to immunosuppression. Monocyte distribution width (MDW) has emerged as a biomarker with potential utility in the early detection of sepsis. Methods: This retrospective study analyzed 1167 patients who presented to the emergency department of a cancer specialty hospital in Republic of Korea. Patients were classified according to Sepsis-2 and Sepsis-3 criteria, and the diagnostic performance of MDW was compared with conventional biomarkers, including C-reactive protein (CRP) and procalcitonin (PCT). Subgroup analyses were conducted based on malignancy status, leukopenia, and initial signs of infection. Additionally, turnaround times (TATs) were compared among the biomarkers. Results: MDW demonstrated diagnostic accuracy comparable to or exceeding that of CRP and PCT for identifying sepsis and infection across both Sepsis-2 and Sepsis-3 criteria. In the context of diagnosing sepsis using the Sepsis-3 criteria, MDW yielded the highest area under the curve (0.869), sensitivity (91.0%), and negative predictive value (98%). Notably, in cancer patients, MDW maintained strong diagnostic reliability. It also demonstrated high diagnostic capability in patients with leukopenia or presenting with initial signs of infection. Moreover, the TAT was significantly shorter for MDW (median 59 min) than for CRP (105 min) or PCT (111 min). Conclusions: MDW is a rapid and accessible biomarker with demonstrated value for early sepsis detection in emergency settings. Its balanced diagnostic profile and consistent performance across diverse patient subgroups support its integration into routine clinical workflows, especially as part of multimodal sepsis screening strategies. Full article

Oedema is a common clinical finding in critically ill neonates and may reflect systemic illness such as congestive heart failure, hepatic cirrhosis, nephrotic syndrome, sepsis, and acute kidney injury. Oedema is characterised by tissue swelling due to water accumulation in the interstitial space. Currently, the gold standard in clinical practice is visual assessment, which is subjective and limited in accuracy. Alternative methods, such as ultrasound and bioimpedance, have been explored; however, they are unsuitable in neonates and do not provide direct water quantification. Near-infrared spectroscopy (NIRS) is a non-invasive optical method that could measure water content through light interaction between near-infrared light and OH particles within the tissue. This study validated NIRS for oedema assessment using an ex vivo porcine skin model, where controlled oedema was induced by phosphate-buffered saline (PBS) injection. Continuous spectroscopic data were collected via optical fibres positioned perpendicularly and parallel to the tissue. Regression models were developed and evaluated using the spectral data, with partial least squares (PLS) regression outperforming ridge regression (RR) and support vector regression (SVR). Notably, spectra acquired in the parallel configuration yielded superior results (R² = 0.97, RMSE = 0.15). These findings support the potential of NIRS as a reliable, quantitative tool for neonatal oedema assessment. Full article

Pediatric sepsis is a major cause of morbidity and mortality worldwide, with outcomes dependent on timely recognition and rigorous management. As clinical management of pediatric sepsis depends on early recognition and initial therapeutic steps, targeted educational materials for healthcare workers in these early phases of care are warranted. Findings of this review highlight and compare the role of traditional educational methods (e.g., lectures) to alternative teaching methods (e.g., use of virtual reality) in educating healthcare workers about pediatric sepsis. Overall, there is a gradual shift from traditional, teacher-centered, transmissive teaching methods to more collaborative, reflective, and learner-centered approaches. These pedagogical approaches, despite some potential limitations, offer opportunities to use technological enhancements and Artificial Intelligence (AI) to enhance teaching and learning across various methods. Full article

Background/Objectives: The management of asymptomatic bacteriuria (ASB) and candiduria (ASC) in kidney transplant recipients during the early post-transplant period is controversial. This study aimed to evaluate whether treating, versus not treating, ASB and ASC episodes in the first two months after kidney transplantation influences clinical outcomes and the emergence of multidrug-resistant (MDR) infections. Methods: We conducted a single-center retrospective cohort study enrolling patients with ASB or ASC occurring in the first two months after kidney transplantation between January 2019 and July 2024. Patients were classified into treated and untreated groups. The primary endpoint was 30-day mortality. Secondary endpoints included mortality at 90, 180 and 360 days; incidence of sepsis or septic shock; bacteremia/candidemia, hospitalization, graft loss; decline in renal function, urinary tract infections (UTIs), recurrent UTI and rate of MDR colonization/infection. Results: We enrolled 59 kidney transplant recipients and observed 147 episodes of ASB/ASC. Of the 147 episodes, 95 were untreated and 52 were treated. No significant differences were observed between treated and untreated patients in 30-day (2.1% vs. 3.8%) or 90-day mortality (2.1% vs. 1.9%), nor in any of the secondary clinical outcomes. However, patients who received treatment tended to have a higher rate of MDR colonization/infection (63% vs. 46%). MDR pathogen isolation was significantly associated with increased risks of septic shock (OR 4.639, p = 0.04), bacteremia/candidemia (OR 3.734, p = 0.01), hospitalization (OR 2.183, p = 0.03) and renal function deterioration (OR 3.93, p = 0.03). Conclusions: Antimicrobial treatment of ASB and ASC in the early post-transplant period would seem not to confer clinical benefit and may be associated with the risk of MDR colonization/infection. Full article

Sepsis poses a significant global health burden, with millions of cases and high mortality rates annually, largely due to challenges in early diagnosis and monitoring. Traditional methods, reliant on nonspecific clinical manifestations and limited biomarkers like C-reactive protein and procalcitonin, often fail to distinguish infection from non-infectious inflammation or capture disease heterogeneity. This review synthesizes recent progress in omics technologies—genomics, transcriptomics, proteomics, and metabolomics—for advancing sepsis management. Genomics, via metagenomic next-generation sequencing, enables rapid pathogen identification and genetic variant analysis for susceptibility and prognosis. Transcriptomics reveals molecular subtypes and immune dynamics through RNA sequencing and single-cell approaches. Proteomics and metabolomics uncover protein and metabolite profiles linked to immune imbalance, organ damage, and metabolic disorders. Multi-omics integration, enhanced by artificial intelligence and machine learning, facilitates biomarker discovery, patient stratification, and predictive modeling, bridging laboratory findings to bedside applications like rapid diagnostic tools and clinical decision support systems. Despite advancements, challenges including data heterogeneity, high costs, and ethical concerns persist. Future directions emphasize single-cell and spatial omics, AI-driven personalization, and ethical frameworks to transform sepsis care from reactive to proactive, ultimately improving outcomes. Full article

Background/Objectives: Klebsiella pneumoniae is a clinically important pathogen that causes respiratory tract infections, pneumonia, wound infections, urinary tract infections, and sepsis. It is on the World Health Organization (WHO) priority pathogen list as it causes antimicrobial-resistant infections. The aim of this study was to isolate bacteriophages against pan-resistant K. pneumoniae isolated from clinical wound infections. Results: One of the isolated phages, CTF-1, possesses a linear double-stranded DNA genome that is 40,841 base pairs (bp) long and contains 44 predicted genes. Functional assignments were made for 31 of the predicted gene products, which are associated with genome replication, phage packaging, structural proteins, and host lysis, leaving 13 annotated as hypothetical proteins. Based on sequencing analysis, phage CTF-1 is a new member of the genus Przondovirus within the order Autographivirales. Phage CTF-1 was effective against 22 of 25 (88%) pan-resistant K. pneumoniae isolates. The latent period and lytic cycle of the phage were approximately 40 min, with a burst size of about 92 PFU/mL. Conclusions: Our findings suggest that Klebsiella phage CTF-1 is an excellent candidate for phage therapy due to its high lytic activity against pan-resistant K. pneumoniae strains and lack of genes encoding antibiotic resistance, toxins, virulence factors, or integrases. Full article

Background: Inflammation is a common reason for dogs to present to veterinary clinics. Early diagnosis of systemic inflammation is important. Acute phase proteins, like C-reactive protein, are useful but not specific to infection. In human medicine, the intensive care infection score (ICIS) offers a faster, cost-effective alternative using advanced hematological parameters. While ICIS is not available for veterinary use, some components (e.g., neutrophil side fluorescent light) can be measured using analyzers like the Sysmex XN-1000V. Objectives: This study aimed to establish a control group of healthy dogs for the novel parameters neutrophil side fluorescent light (NE-SFL), neutrophil side scattered light (NE-SSC), and neutrophil forward scattered light (NE-FSC) and assess their utility in detecting inflammation in diseases such as sepsis, pyometra, steroid-responsive meningitis-arteritis (SRMA), and idiopathic epilepsy. Methods & Results: Value ranges were calculated based on 21 healthy dogs. Compared to controls, NE-SFL levels were significantly elevated in sepsis, pyometra, and SRMA, while NE-SSC was only elevated in sepsis and pyometra and NE-FSC only in sepsis. No increases were observed in idiopathic epilepsy. Manual gating of the white blood cell differential scattergram was necessary in samples showing high neutrophil toxicity and the presence of bands. Conclusion: NE-SFL and NE-SSC, obtainable from routine complete blood count, may serve as novel, accessible markers for inflammation in dogs. Further research is needed to validate their broader diagnostic use. Full article

Background: The intersection between oncology and intensive care has shifted from predominantly end-of-life care to a therapeutic bridge that can preserve anticancer trajectories in carefully selected patients. Yet, criteria separating benefit from futility remain fragmented. Objective: This paper seeks to map contemporary evidence (2015–2025) on outcomes after Intensive Care Unit (ICU) admission in adults with cancer and to identify clinical constellations in which ICU-level care still changes prognosis. Methods: PRISMA-ScR scoping review (PCC framework). PubMed search (2015–2025), dual screening, standardized extraction; narrative/thematic synthesis across six clusters (hematologic, solid tumors, sepsis/non-COVID-19 infection, COVID-19/viral pneumonia, novel/targeted-therapy toxicities, end-of-life/aggressive ICU) were used. No meta-analysis given heterogeneity. Results: Seventy-three studies (>170,000 ICU admissions) were included, mostly cohort designs across 27 countries. ICU mortality ranged 8–72% (weighted mean ≈ 41%); hospital ≈ 38%; 90-day ≈ 46%; 1-year ≈ 62%. About one third of ICU survivors resumed systemic therapy. Benefit concentrated in early admissions, single-organ failure, controlled/remission disease, postoperative/elective monitoring, and reversible treatment-related toxicities (e.g., ICI pneumonitis, CAR-T CRS/ICANS). Futility clustered around ≥3 organ supports, RRT > 7 days, refractory/progressive disease, and ECOG ≥ 3. Sepsis outcomes averaged 45–55% ICU mortality but improved with rapid recognition and source control; COVID-19 mortality was particularly high in hematologic malignancies early in the pandemic, with subsequent declines post-vaccination. Conclusions: In modern oncologic practice, ICU care changes prognosis when the acute physiological insult is reversible and cancer control remains plausible; conversely, high organ-support burden and refractory disease define practical futility thresholds. These signals support time-limited ICU trials, earlier ICU involvement for sepsis/irAEs, and embedded palliative care to align intensity with goals. Full article

 Modern biomedicine frequently contextualizes disease around isolated molecular or organ-specific mechanisms, but numerous chronic diseases, including Alzheimer’s disease, multiple sclerosis, depression, diabetes, and sepsis, share common trajectories of systemic destabilization. An increasing body of evidence indicates that health is not a property of single organs but the emergent property of interdependent feedback networks linking the microbiome, endocannabinoidome, neuroimmune system, and metabolic regulators. We propose the Endocannabinoid–Microbiota–Neuroimmune Super-System (EMN-S) as an evolutionarily conserved conceptual model that describes how these fields of influence reciprocally interact through feedback control. The microbial communities constituting the EMN-S encode environmental and dietary inputs, endocannabinoid signaling serves as an integrative regulator that synchronizes neural and immune activity, and neuroimmune circuits effectuate adaptive behaviors that alter microbiotal and lipid ecosystems. This review formalizes the EMN-S, contending that it is a unitary and cohesive model of physiological resilience, as well as offering a framework for precision feedback therapeutics. We describe how three mechanisms—encoder drift, integrator detuning, and executor overutilization—convert stabilizing negative feedback into runaway feedback cascades that underlie chronic, recurrent, and multisystemic disease. We then specify the EMN-S signature—integrated microbiome, lipidomic, and immune readouts—as an early indicator of resilience collapse and prospective preclinical state. Finally, we recapitulate the potential of AI-driven digital twins to illuminate feedback collapse, predict tipping points, and direct closed-loop intervention and treatments to restore dynamic equilibrium. By anchoring complexity in concrete and measurable feedback principles, the EMN-S shifts focus to investigate pathophysiology as opposed to reductionist lesion models of systemic derangements and embraces a systemic, empirically testable theory of stability.  Full article

Background/Objectives: Systemic hydrocortisone (HCS) in very low birth weight (VLBW) infants is commonly used to treat early hypotension or prevent bronchopulmonary dysplasia. This study evaluated the associations between postnatal HCS exposure and neurodevelopment in VLBW infants by comparing regional brain volume at term-equivalent age (TEA) with neurodevelopmental outcomes in early infancy. Methods: This retrospective cohort study included VLBW infants admitted to a neonatal intensive care unit (NICU) between 2013 and 2019. The cumulative HCS dose during hospitalization was recorded, and regional brain volumes were analyzed using magnetic resonance imaging at TEA. Neurodevelopmental outcomes were assessed at a corrected age for prematurity of 18–24 months. Results: Among 146 infants, 57 were classified in the high HCS group (>90 mg/kg) and 89 in the low HCS group (≤90 mg/kg HCS). Bronchopulmonary dysplasia, periventricular leukomalacia, and sepsis were more frequent in the high HCS group. Ninety-five infants underwent magnetic resonance imaging, which revealed reduced brain volumes in the high HCS group. At follow-up, cerebral palsy (35.9% vs. 9.1%, p = 0.003), neurodevelopmental impairment (54.0% vs. 23.6%, p = 0.002), and head circumference <10th percentile (64.3% vs. 19.5%, p < 0.001) were more common in the high HCS group. After adjustment, HCS > 90 mg/kg remained independently associated with cerebral palsy (adjusted odds ratio [aOR] 5.44, p = 0.016) and reduced head circumference (aOR 4.45, p = 0.016). Conclusions: High cumulative HC exposure correlated with reduced brain volume at TEA and adverse neurodevelopmental outcomes at 24 months of age. Careful monitoring of dose and treatment duration is essential to balance therapeutic benefits against potential risks. Full article

Introduction: In hemoglobinopathies, the amount of globin synthesis in hemoglobin (Hb) or its structure is altered. Clinical features are related to the rate and kind of structural aberrations. The heterozygous form of the Lepore syndrome resembles minor thalassemia both clinically and hematologically. On electrophoresis, abnormal Hb Lepore fractions are found at a rate of 5–15%, with a mildly higher percentage of HbF and lower HbA. In general, Hb Lepore heterozygotes are asymptomatic. Case presentation: A 32-year-old male was admitted to our hospital with complaints of pain and swelling in multiple large joints and high-grade fever for 11 days. His past history was unremarkable; one of his sisters had the β-thalassemia trait. On physical examination, he was moderately anemic, with mild hepatomegaly and normal spleen; both knees and ankles were tender and swollen. Laboratory showed mild microcytic hypochromic anemia with variables similar to the thalassemia trait and signs of inflammation with very high CRP, serum ferritin, and leukocytosis. Blood sugars were increased. Hb electrophoresis showed an abnormal pattern with mild elevation in HbS, normal Hb F, mild reduction in HbA, and high HbA2, compatible with heterozygosity for the Hb Lepore beta chain variant. He was initially diagnosed with diabetes (treated with insulin) and sepsis from unknown origin, but fever and joint pains did not respond to NSAIDs or antibiotics. He had very good response on high-dose methylprednisolone. Undifferentiated arthritis was diagnosed in the patient with Hb Lepore, and he was treated with oral prednisolone and sulfasalazine (SSZ). At follow up, the patient was doing well. He refused further investigations and did not allow testing on his family members. In summary: Hb Lepore is a rare hemoglobinopathy linked to thalassemia, which may manifest with musculoskeletal problems. Our patient with the Hb Lepore trait presented with undifferentiated polyarthritis and fever, but in our case, a causal relationship remains unclear. This is one of the first adult cases of Hb Lepore in Bangladesh and the first with arthritis of unknown origin. The prevalence of Hb Lepore in Bangladesh is unknown. Full article

(1) Background: The assessment of neonatal health and prognosis is one of the most critical areas in pediatric medicine. Intrauterine inflammation and the fetal inflammatory response syndrome (FIRS) are increasingly recognized as major determinants of neonatal morbidity. Interleukin-6 (IL-6), measured in the umbilical cord (UC) blood, has emerged as a promising biomarker, reflecting both intrauterine conditions and early neonatal risk. This narrative review aims to synthesize current evidence on the predictive value of umbilical cord blood IL-6 for neonatal outcome, including sepsis, respiratory distress, hypoxic–ischemic encephalopathy (HIE) and mortality. (2) Methods: A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science. Studies reporting umbilical cord IL-6 levels in relation to neonatal outcomes were analyzed and summarized narratively. (3) Results: Evidence consistently indicates that elevated umbilical cord IL-6 is associated with early-onset neonatal sepsis (EONS) and respiratory complications, and provides prognostic insight into neurological outcomes, even though results are influenced by gestational age (GA), mode of delivery, and the presence of chorioamnionitis. (4) Conclusions: UC IL-6 represents a valuable early biomarker for neonatal risk stratification and supports clinical decision-making. Future research should prioritize assay standardization, reference interval development, and prospective multicenter studies to validate its integration into routine neonatal care. Full article

This review reappraises the anti-inflammatory potential of the contact activation system (CAS) in intensive care through an evolutionary lens. The authors propose that coagulation factor XII (FXII) and related components evolved in terrestrial animals as a “foreign-surface sensing–immunothrombosis” module, helping to explain the minimal bleeding phenotype of FXII deficiency and the secondary loss of F12 in marine mammals. CAS shares components with the kallikrein–kinin system (KKS): alpha-coagulation factor XIIa (α-FXIIa) drives coagulation factor XI (FXI) activation to amplify coagulation, whereas betacoagulation factor XIIa (β-FXIIa) activates the KKS to generate bradykinin, promoting vasodilation and vascular leak. Beyond proteolysis, zymogen FXII signals via urokinase-type plasminogen activator receptor (uPAR) to induce neutrophil extracellular trap formation (NETosis), thereby amplifying immunothrombosis. Clinically, the relevance spans sepsis and extracorporeal organ support: pathogens can hijack CAS/KKS to facilitate invasion, and artificial surfaces such as extracorporeal membrane oxygenation (ECMO) circuits chronically trigger contact activation. In animal models, selective inhibition of FXII/FXI prolongs circuit life and attenuates pulmonary edema and inflammation without materially increasing bleeding. The review also catalogs “non-coagulation” roles of CAS members: Activated coagulation factor XI (FXIa) modulates endothelial permeability and smooth-muscle migration, and the FXII heavy chain exhibits direct antimicrobial activity—underscoring CAS as a nexus for coagulation, inflammation, and host defense. Overall, CAS inhibitors may couple “safe anticoagulation” with “cascade-level anti-inflammation,” offering a testable translational path for organ protection in the ICU alongside infection control and informing combined, precision strategies for anticoagulation and anti-inflammatory therapy. Full article

Background/Objectives: Artificial intelligence (AI) is increasingly applied across the perioperative continuum, with potential benefits in efficiency, personalization, and patient safety. Unfortunately, most such tools are developed in isolation, limiting their clinical utility. Multi-Agent Systems for Healthcare (MASH), in which autonomous AI agents coordinate tasks across multiple domains, may provide the necessary framework for integrated perioperative care. This critical review synthesizes current AI applications in anesthesiology and considers their integration within a MASH architecture. This is the first review to advance MASH as a conceptual and practical framework for anesthesiology, uniquely contributing to the AI discourse by proposing its potential to unify isolated innovations into adaptive and collaborative systems. Methods: A critical review was conducted using PubMed and Google Search to identify peer-reviewed studies published between 2015 and 2025. The search strategy combined controlled vocabulary and free-text terms for AI, anesthesiology, perioperative care, critical care, and pain management. Results were filtered for randomized controlled trials and clinical trials. Data were extracted and organized by perioperative phase. Results: The 16 studies (6 from database search, 10 from prior work) included in this review demonstrated AI applications across the perioperative timeline. Preoperatively, predictive models such as POTTER improved surgical risk stratification. Intraoperative trials evaluated systems like SmartPilot and Navigator, enhancing anesthetic dosing and physiologic stability. In critical care, algorithms including NAVOY Sepsis and VentAI supported early detection of sepsis and optimized ventilatory management. In pain medicine, AI assisted with opioid risk assessment and individualized pain-control regimens. While these trials demonstrated clinical utility, most applications remain domain-specific and unconnected from one another. Conclusions: AI has broad potential to improve perioperative care, but its impact depends on coordinated deployment. MASH offers a unifying framework to integrate diverse agents into adaptive networks, enabling more personalized anesthetic care that is safer and more efficient. Full article

Background: Patient monitors assist caregivers in identifying deterioration earlier by using threshold alarms. Not all of the threshold alarms necessitate immediate action, but some are a result of the triggering of a physiological event. We aim to use pattern recognition techniques to identify threshold alarm signal patterns before the onset of critical illness, thereby enabling the faster and more effective detection of clinical deterioration and supporting better clinical decision-making. Method: Secondary data from 774 pediatric patients were extracted from the IMPALA Project conducted in the High Dependency Unit (HDU) at Queen Elizabeth and Zomba Central Hospitals in Malawi. The threshold alarm data were generated from the vital signs using WHO age cut-offs and GOAL3 age cut-offs. Time-segmented alarm analysis was conducted to examine the distribution of threshold alarms around each vital sign 8 h before the onset of critical illness events. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was used to generate threshold alarm signal patterns for each signal per individual before the onset of a critical illness event. We used three machine learning approaches, random forest, support vector machine, and decision tree, to learn threshold alarm patterns in signals preceding critical illness events. Results: The total threshold alarm summed up to (3,910,083) in total for WHO and (2,041,740) for GOAL3. Temporal distributions of ECGRR, ECGHR and oxygen saturation rate (SPO2) threshold alarms were observed, revealing patterns before the onset of the critical illness events. A pattern of most threshold alarms was distributed around (40–60) for ECGRR upper threshold alarms and (0–20) for ECGRR lower threshold alarms, (80–85) for ECGHR lower threshold alarms and (140–160) for ECGHR upper threshold alarms, and (85–90) for SPO2 for death (CPR and PICU), around WHO threshold alarms. For sepsis, most of these threshold alarms were distributed around (40–50) of ECGRR upper threshold alarms and (0–20) for ECGRR lower threshold alarms, (150–180) for ECGHR upper threshold alarms, and (85) for SPO2 for WHO threshold alarms, and most of the threshold alarms had a duration of less than 30 s. The results indicate that the random forest classifier performed better in learning the threshold patterns, with an accuracy of 93% and an area under the curve of 92, compared to using the support vector machine learning model and decision tree, which had an accuracy from a classification report of 85% and 94%, with low death and sepsis precision, recall, and F1-Score. Conclusions: The analysis of threshold alarm data before critical illness events has provided valuable insights into threshold alarm patterns associated with death and sepsis. The data revealed distinct patterns in ECGRR, ECGHR, and SPO2 signals, and most of the threshold alarms were in the lower duration. The random forest classifier effectively distinguished these learned patterns around death and sepsis events compared to other algorithms. Further studies are required on the use of algorithms on all vital sign signal features in clinical settings. Full article