Immature granulocyte percentage for prediction of sepsis in severe burn patients: a machine leaning-based approach

Phenotypic Landscape of Immune Cells in Sepsis: Insights from High-Dimensional Mass Cytometry

Understanding the sepsis-induced immunological response can be facilitated by identifying phenotypic changes in immune cells at the single-cell level. Mass cytometry, a novel multiparametric single-cell analysis technique, offers considerable benefits in characterizing sepsis-induced phenotypic changes in peripheral blood mononuclear cells. Here, we analyzed peripheral blood mononuclear cells from 20 sepsis patients and 10 healthy donors using mass cytometry and employing 23 markers. Both manual gating and automated clustering approaches (PhenoGraph) were used for cell identification, complemented by uniform manifold approximation and projection (UMAP) for dimensionality reduction and visualization. Our study revealed that patients with sepsis exhibited a unique immune cell profile, marked by an increased presence of monocytes, B cells, and dendritic cells, alongside a reduction in natural killer (NK) cells and CD4/CD8 T cells. Notably, significant changes in the distributions of monocytes and B and CD4 T cells were observed. Clustering with PhenoGraph unveiled the subsets of each cell type and identified elevated CCR6 expression in sepsis patients' monocyte subset (PG#5), while further PhenoGraph clustering on manually gated T and B cells discovered sepsis-specific CD4 T cell subsets (CCR4low CD20low CD38low) and B cell subsets (HLA-DRlow CCR7low CCR6high), which could potentially serve as novel diagnostic markers for sepsis.

Immature Granulocyte Percentage as an Early Predictor of Necrosis in Volvulus

AIM

Volvulus is a disease characterized by the abnormal twisting of a gaseous distension of the loop of the intestine around itself. Colonic volvulus is the third common cause of colonic obstruction. The study aimed to determine whether the percentage of immature granulocytes is a marker of early necrosis in the volvulus.

METHODS

Demographic characteristics of the cases were collected in the study. In addition, age, gender, white blood cell count, immature granulocyte count, immature granulocyte percentage, platelet lymphocyte ratio, and neutrophil-lymphocyte ratio were compared between groups with and without necrosis in terms of treatment.

RESULTS

The effectiveness of immature granulocyte percentage (IG%) and IG markers were statistically significant in predicting necrosis. The AUC was the highest for IG (0.820, 95% CI: 0.586-1), followed by IG% (0.820, 95% CI: 0.617-1). The optimal cut-off value for the IG was 0.65, with a sensitivity of 76.2% and specificity of 85.7% (P = 0.013). The optimal cut-off value for the IG% was 0.065, with a sensitivity of 85.7% and specificity of 71.4% (0.018).

CONCLUSION

IG% and IG count were found to be useful for predicting necrosis in patients with volvulus.

Machine learning algorithms in sepsis

Sepsis remains a significant global health challenge due to its high mortality and morbidity, compounded by the difficulty of early detection given its variable clinical manifestations. The integration of machine learning (ML) into laboratory medicine for timely sepsis identification and outcome forecasting is an emerging field of interest. This comprehensive review assesses the current body of research on ML applications for sepsis within the realm of laboratory diagnostics, detailing both their strengths and shortcomings. An extensive literature search was performed by two independent investigators across PubMed and Scopus databases, employing the keywords "Sepsis," "Machine Learning," and "Laboratory" without publication date limitations, culminating in January 2023. Each selected study was meticulously evaluated for various aspects, including its design, intent (diagnostic or prognostic), clinical environment, demographics, sepsis criteria, data gathering period, and the scope and nature of features, in addition to the ML methodologies and their validation procedures. Out of 135 articles reviewed, 39 fulfilled the criteria for inclusion. Among these, the majority (30 studies) were focused on devising ML algorithms for diagnosis, fewer (8 studies) on prognosis, and one study addressed both aspects. The dissemination of these studies across an array of journals reflects the interdisciplinary engagement in the development of ML algorithms for sepsis. This analysis highlights the promising role of ML in the early diagnosis of sepsis while drawing attention to the need for uniformity in validating models and defining features, crucial steps for ensuring the reliability and practicality of ML in clinical setting.

Evaluation of immature granulocyte percentage and count in pediatric nephrotic syndrome

OBJECTIVE

The importance of immature granulocytes (IGs) in most infectious and inflammatory diseases has been highlighted. This study aimed to determine the clinical usability and importance of changes in the peripheral complete blood count profile, including IG percentage (IG%) and IG count (IG#), during the relapse and remission phases in pediatric nephrotic syndrome (NS) patients.

METHODS

This retrospective observational study was performed at a tertiary care hospital between February 2020 and August 2022. Demographic characteristics and laboratory parameters were recorded. The IG count and IG% were measured using an automated hematological analyzer.

RESULTS

IG% and IG# were both higher during the relapse phase of NS than during the remission phase (0.29% ± 0.14%, versus 0.23% ± 0.14%, p = 0.037 and 0.027 ± 0.015 × 103/µL, versus 0.018 ± 0.014 × 103/µL, p = 0.005, respectively). The neutrophil to lymphocyte ratio (NLR), platelet (PLT), white blood cell (WBC), and neutrophil counts had a strong positive correlation with IG# (r = 0.397, p < 0.001; r = 0.352, p < 0.001; r = 0.622, p < 0.001; r = 0.660, p < 0.001, respectively). The NLR, PLT, WBC, and neutrophil counts had a strong positive correlation with IG% (r = 0.348, p < 0.001; r = 0.187, p = 0.039; r = 0.303, p = 0.001; r = 0.426, p < 0.001, respectively). Receiver operating characteristic curve analysis showed that IG# had the best AUC value of 0.69 (95% CI: 0.58-0.77; p = 0.001) for the relapse phase of NS with a cutoff value of 0.025 × 103/µL (sensitivity: 81.0%, specificity: 78.1%).

CONCLUSIONS

It is probable that a high level of immature granulocyte count has a positive correlation for NS relapse in pediatric patients. The IG % and IG# can be used together as biomarkers of inflammation in pediatric NS relapse.

Surviving Sepsis After Burn Campaign

INTRODUCTION

The Surviving Sepsis Campaign was developed to improve outcomes for all patients with sepsis. Despite sepsis being the primary cause of death after thermal injury, burns have always been excluded from the Surviving Sepsis efforts. To improve sepsis outcomes in burn patients, an international group of burn experts developed the Surviving Sepsis After Burn Campaign (SSABC) as a testable guideline to improve burn sepsis outcomes.

METHODS

The International Society for Burn Injuries (ISBI) reached out to regional or national burn organizations to recommend members to participate in the program. Two members of the ISBI developed specific "patient/population, intervention, comparison and outcome" (PICO) questions that paralleled the 2021 Surviving Sepsis Campaign [1]. SSABC participants were asked to search the current literature and rate its quality for each topic. At the Congress of the ISBI, in Guadalajara, Mexico, August 28, 2022, a majority of the participants met to create "statements" based on the literature. The "summary statements" were then sent to all members for comment with the hope of developing an 80% consensus. After four reviews, a consensus statement for each topic was created or "no consensus" was reported.

RESULTS

The committee developed sixty statements within fourteen topics that provide guidance for the early treatment of sepsis in burn patients. These statements should be used to improve the care of sepsis in burn patients. The statements should not be considered as "static" comments but should rather be used as guidelines for future testing of the best treatments for sepsis in burn patients. They should be updated on a regular basis.

CONCLUSION

Members of the burn community from the around the world have developed the Surviving Sepsis After Burn Campaign guidelines with the goal of improving the outcome of sepsis in burn patients.

Positive Role of Delta Neutrophil Index (DNI) as a Prodiagnostic Marker in Cecal Ligation and Puncture (CLP)-Induced Sepsis Murine Model

Sepsis is an emergent infectious disease and a leading cause of death despite immediate intervention. While Delta neutrophil index (DNI) and myeloperoxidase (MPO) are known as a prodiagnostic marker of sepsis, the preclinical evidence of the best marker of sepsis is unclear. For this, using a well-designed cecal ligation and puncture (CLP)-induced sepsis mouse model, we comparatively measured the level and cost-effectiveness of sepsis biomarkers such as DNI, myeloperoxidase (MPO), procalcitonin (PCT), and tumor necrosis factor-alpha (TNF-α). First, we found that the optimal time point for early detection is at 6 h, 24 h post-CLP. Strikingly, the peak level and fold change of DNI was revealed at 24 h, further showing the best fold change as compared with other biomarker levels. Given the fold change at 6, 24 h, PCT was next to DNI. Third, a cost-effectiveness survey showed that DNI was the best, with PCT next. Further, DNI level was moderate positively associated with PCT (ρ = 0.697, p = 0.012) and TNF-α (ρ = 0.599, p = 0.040). Collectively, these data indicate that DNI in CLP-induced sepsis mice is as effective as the existent inflammatory biomarkers such as MPO, PCT and TNF-α to predict the prognosis of sepsis. This might have clinically important implications that DNI is cost effective, thus quickly and rationally applying to diverse types of imminent sepsis regardless of species. This might be the first report on the validity of DNI in preclinical CLP-induced murine sepsis.