Early Blood Biomarkers to Improve Sepsis/Bacteremia Diagnostics in Pediatric Emergency Settings

The early diagnostic value of neutrophil to lymphocyte ratio and platelet to lymphocyte ratio in neonatal late-onset sepsis

Purpose

The purpose of this study is to investigate the early diagnostic value of the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and C-reactive protein (CRP) in neonatal late-onset sepsis (LOS), as well as to evaluate the combined diagnostic utility of these markers for the early detection of neonatal LOS.

Methods

The late-onset sepsis of newborns admitted to the neonatal intensive care unit of our hospital were retrospectively collected. 142 children with Late-Onset Sepsis (LOS) were selected as the LOS group, 50 neonates with systemic infection were selected as the systemic infection group, 50 neonates who underwent physical examination were selected as the non-systemic infection group. The differences of NLR, PLR, platelet-to-neutrophil ratio (PNR), and C-reactive protein (CRP), Procalcitonin among the three groups were compared.

Results

The levels of NLR and PLR in LOS group were significantly higher than those in systemic infection group and non-systemic infection group. The Receiver Operating Characteristic (ROC) curve result revealed that the area under ROC (AUC, Area Under Curve) of NLR for the diagnosis of LOS was 0.903. When the optimal cut-off value was 1.30, the sensitivity and specificity were 89.4% and 81.0%. The AUC of PLR for the diagnosis of LOS was 0.833. When the optimal truncation value was 57.86, the sensitivity and specificity were 92.3% and 68.0%. The AUC of CRP for the diagnosis of LOS was 0.876, and the sensitivity and specificity were 76.8% and 87.0% when the optimal cut-off value was 10.21 mg/dl. When NLR, PLR, and CRP were combined to diagnosis LOS, The AUC was 0.942, the sensitivity and specificity were 90.8% and 86.0%.

Conclusions

The levels of NLR and PLR in the LOS were higher, which have certain value in the early diagnosis of LOS, and combined with CRP can improve the diagnostic efficiency.

Exploring the clinical value of procalcitonin, c-reactive protein, white blood cell count, and neutrophil-to-lymphocyte ratio in the early diagnosis of bloodstream infections in children

BACKGROUD

In the diagnosis of bloodstream infections (BSI) in children, compared to the gold standard of blood culture, markers in the blood offer advantages such as rapid results and cost-effectiveness. Therefore, we investigated the clinical value of procalcitonin (PCT), C-reactive protein (CRP), white blood cell count (WBC), and neutrophil-to-lymphocyte ratio (NLR) in the early diagnosis of BSI in children.

METHODS

This study included a retrospective analysis of 309 suspected BSI cases and patients were categorized into 2 groups based on blood culture results: blood culture-positive group, and blood culture-negative group. The blood culture-positive group was further partitioned into 3 sub-groups based on the type of pathogen: Gram-positive (G +) bacteria, Gram-negative (G-) bacteria, and fungi. Changes in PCT, CRP, WBC, and NLR were evaluated, and pathogen infections among these aforementioned groups were further determined. Moreover, the study employed the receiver operating characteristic (ROC) curve to evaluate the diagnostic value of these indicators in identifying BSI in pediatric patients at an early stage.

RESULTS

Among the 98 strains of pathogens detected in blood culture, 58 (58.2%) strains were G- bacteria, 33 (33.7%) strains were G + bacteria, and 7 (7.1%) strains were fungi. The levels of PCT, CRP, WBC, and NLR were found to be significantly higher in the blood culture-positive group than the blood culture-negative group (p < 0.01). Upon comparing the levels of PCT and CRP in the three pathogen infections, it was found that the fungi group exhibited higher levels than the G- and G + bacteria groups (p < 0.01). The G- bacteria group exhibited higher levels of PCT, CRP, and WBC than the blood culture-negative group (p < 0.05). Similarly, the G + bacteria group exhibited higher levels of PCT, WBC, and NLR than the blood culture-negative group (p < 0.01). Besides, PCT presented the highest diagnostic efficiency among the single-item detections, with an AUC of 0.862 (95% CI: 0.819-0.906). The simultaneous detection of multiple parameters does not necessarily improve diagnostic performance but can enhance detection sensitivity.

CONCLUSIONS

PCT and CRP can provide important complementary information for the etiological diagnosis of BSI in children. Elevated levels of PCT and CRP were often associated with fungal or G- bacterial infections, with PCT showing particularly significant effects. Combined use of serum PCT, CRP, WBC, and NLR testing can improve the diagnostic sensitivity of pediatric BSI, reducing the risk of missed diagnoses, thereby enhancing the early diagnostic value of pediatric BSI.

Neutrophil-to-Lymphocyte Ratio (NLR) and Mean Platelet Volume (MPV) to Platelet Count Ratio in the Prognosis of Neonatal and Pediatric Sepsis

OBJECTIVES

To calculate and assess the role of neutrophil-to-lymphocyte ratio (NLR) and mean platelet volume (MPV)/ platelet count (PLT) ratios and their trends as prognostic indicators in neonates and children with sepsis.

METHODS

This prospective observational study was planned over a period of two years at a tertiary care teaching hospital. Two hundred seventy children with clinical suspicion of or diagnosed as sepsis were enrolled. Serial hemograms (day 1, 4, 7, 10) and trends of NLR and MPV/PLT ratios were reviewed.

RESULTS

NLR on day 10 of hospital stay had maximum sensitivity of 65% and specificity of 62%. Day 1 MPV was significantly higher in the mortality group. There was a significant correlation between lower Pediatric Sequential Organ Failure Assessment (p-SOFA) score and MPV in the survival group. MPV/PLT ratio on day 7 had maximum sensitivity of 85% and specificity of 74% in prediction of mortality. Serial decreasing trend of NLR (2.88-1.16) and MPV/PLT from day 1 to 10 (8.58-8.48) were associated with improved outcome (p < 0.001).

CONCLUSIONS

High NLR, MPV and MPV/PLT on admission are associated with increased mortality in neonatal and pediatric sepsis. Serial decreasing trends in NLR, MPV and MPV/PLT ratio are associated with improved prognosis.

Role of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in diagnosing neonatal sepsis

Clinical manifestations of neonatal sepsis are often unspecified. Therefore, sepsis biomarkers could be used to support diagnosis while waiting for blood culture results, such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR). The aim of this study was to evaluate the role of NLR and PLR as diagnostic markers in neonatal sepsis. A cross-sectional study was conducted at Haji Adam Malik General Hospital, Medan, Indonesia, from April to October 2019. This study included neonates aged less than 28 days, diagnosed with suspected sepsis, and had no previous history of antibiotics administration. Patients underwent clinical assessment, laboratory examination, and blood culture. Patients were grouped into sepsis and non-sepsis based on the blood culture results. The median hematological examination and the range of NLR and PLR in both the sepsis and non-sepsis groups were subjected to analysis using the Mann-Whitney U test to assess differences. NLR and PLR optimal cut-off values were determined using a receiver operator curve (ROC) with a confidence interval of 95%. A total of 137 neonates were enrolled, of which 49 were classified as sepsis and 89 as non-sepsis based on blood culture results. The optimal cutoff values for NLR and PLR were 2.75 and 11.73. Using those cutoff values, NLR and PLR could predict neonatal sepsis with sensitivities of 52.1% and 47.9%, specificities of 50.6% and 47.2%, area under the curve (AUC) of 0.46 and 0.47, with p=0.525 and p=0.662, respectively. Further investigation is warranted to refine the NLR and PLR utility and enhance diagnostic accuracy in clinical practices.

Predictive Value of Inflammatory Markers NLR, PLR, APRI, SII, and Liver Function Tests in Systemic Inflammatory Response Syndrome Detection in Full-Term Newborns

Systemic Inflammatory Response Syndrome (SIRS) is associated with significant morbidity and mortality in full-term newborns. This study aimed to evaluate the predictive value of the Neutrophil-to-Lymphocyte Ratio (NLR), Derived Neutrophil-to-Lymphocyte Ratio (dNLR), Platelet-to-Lymphocyte Ratio (PLR), Neutrophil, Lymphocyte, and Platelet Ratio (NLPR), AST-to-Platelet Ratio Index (APRI), and Systemic Immune-Inflammation Index (SII) in identifying the risk for SIRS development in full-term newborns. Conducted between January 2023 and January 2024, this observational cohort study compared full-term newborns diagnosed with SIRS with newborns without SIRS, measuring the inflammatory markers within the first day of life and three days post-birth. The study included 229 newborns, 81 with SIRS and 148 controls without SIRS. Statistically significant differences were observed in NLR (3.81 vs. 2.20, p < 0.0001), PLR (68.12 vs. 52.30, p < 0.0001), and liver enzymes (AST 40.96 U/L vs. 31.58 U/L, ALT 34.66 U/L vs. 22.46 U/L, both p < 0.0001) between the groups. The NLPR demonstrated substantial diagnostic value, with a sensitivity of 78.36% and specificity of 83.52% at 72 h (p < 0.0001). Regression analysis highlighted that the NLPR and SII were strongly predictive of SIRS, with the NLPR showing over three-times higher SIRS risk (HR 3.29, p < 0.0001) and SII indicating nearly 3.5 times the risk (HR 3.47, p < 0.0001). The NLPR, APRI, and SII showed similar prediction values to CRP levels measured on the first and third days of life (HR 3.16). Inflammatory markers like NLR, PLR, and systemic indices such as NLPR and SII, alongside liver function tests, are significant predictors of SIRS in full-term newborns. These findings support the integration of these markers into routine neonatal care, allowing for early identification and potentially improved management of newborns at risk for SIRS, thereby enhancing clinical outcomes.

Hematological Indices for Identifying Adverse Outcomes in Children Admitted to Pediatric ICUs

BACKGROUND

The pediatric ICU (PICU) is a specialized area where critically sick children are managed. The mortality rates in PICUs are higher in developing countries as compared to developed nations. Many of these deaths could be prevented if very sick children were identified soon after they arrived at the health facility. Hematological indices like platelet lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) have been frequently used in adults as indicators of mortality. However, their use in the pediatric population is limited due to a lack of validated reference intervals.

OBJECTIVE

The objective of the study is to assess the role of hematological indices in identifying adverse outcomes in terms of mortality in children admitted to the PICU.

MATERIALS AND METHODS

It is a prospective, observational study done at a tertiary care hospital. All children aged one year to 12 years admitted to the PICU were enrolled in the study. A sample for complete blood count was taken within one hour of admission to the PICU. Children who had received blood products in the last two months, those on chronic medications (>two weeks) that can affect bone marrow cellularity, and known cases of hematological disorders such as megaloblastic anemia, hematological malignancies, immune thrombocytopenia, and aplastic anemia were excluded from the study. PLR, NLR, and platelets to mean platelet volume ratio (PLT/MPV) were determined and compared among the survivors and non-survivors.

RESULTS

 Out of 275 enrolled patients, 119 (43.3%) patients expired during the study period. While PLR had high sensitivity and NLR had high specificity (85.71% and 92.31%, respectively) for predicting mortality, none of these parameters had a good area under the curve (AUC) in our study. PLT/MPV of ≥32 had a sensitivity of 39.5% and a specificity of 56.41% for predicting mortality.

CONCLUSIONS

Hematological parameters have been used across the world to predict ICU mortality. PLR and NLR are simple hematological biomarkers, easy to calculate, and cost-effective, and ratios are better than individual parameters. More studies and stratified samples are required to evaluate the role of hematological markers in identifying the risk of mortality in children admitted to PICUs.

Biomarkers for Serious Bacterial Infections in Febrile Children

Febrile infections in children are a common cause of presentation to the emergency department (ED). While viral infections are usually self-limiting, sometimes bacterial illnesses may lead to sepsis and severe complications. Inflammatory biomarkers such as C reactive protein (CRP) and procalcitonin are usually the first blood exams performed in the ED to differentiate bacterial and viral infections; nowadays, a better understanding of immunochemical pathways has led to the discovery of new and more specific biomarkers that could play a role in the emergency setting. The aim of this narrative review is to provide the most recent evidence on biomarkers and predictor models, combining them for serious bacterial infection (SBI) diagnosis in febrile children. Literature analysis shows that inflammatory response is a complex mechanism in which many biochemical and immunological factors contribute to the host response in SBI. CRP and procalcitonin still represent the most used biomarkers in the pediatric ED for the diagnosis of SBI. Their sensibility and sensitivity increase when combined, and for this reason, it is reasonable to take them both into consideration in the evaluation of febrile children. The potential of machine learning tools, which represent a real novelty in medical practice, in conjunction with routine clinical and biological information, may improve the accuracy of diagnosis and target therapeutic options in SBI. However, studies on this matter are not yet validated in younger populations, making their relevance in pediatric precision medicine still uncertain. More data from further research are needed to improve clinical practice and decision making using these new technologies.

PCT, IL-6, and IL-10 facilitate early diagnosis and pathogen classifications in bloodstream infection

BACKGROUND

In the diagnosis of bloodstream infection (BSI), various inflammatory markers such as C-reactive protein (CRP), procalcitonin (PCT), interleukins (IL), white blood cell count (WBC), neutrophil percentage (NE%), platelet count (PLT), and erythrocyte sedimentation rate (ESR) have been extensively utilized. However, their specific roles in distinguishing BSI from local bacterial infection (LBI) and in classifying BSI pathogens remain uncertain.

METHODS

A historical cohort study was conducted, involving the enrollment of 505 patients with BSI and 102 patients with LBI. To validate the reliability of the clinical data obtained from this cohort, mouse models of BSI were utilized.

RESULTS

Our findings revealed that patients with BSI had significantly higher levels of inflammatory markers, including CRP, PCT, IL-6, IL-10, WBC, NE%, and ESR, compared to those with LBI (p < 0.05). The receiver operating characteristic (ROC) curve analysis demonstrated that CRP, PCT, IL-6, IL-10, ESR and NE% exhibited excellent diagnostic efficacy for BSI. Additionally, we observed significant differences in CRP, PCT, IL-6, and IL-10 levels between patients with BSI caused by Gram-positive bacteria (GP-BSI) and Gram-negative bacteria (GN-BSI), but no significant variations were found among specific bacterial species. Furthermore, our study also found that CRP, PCT, and IL-10 have good discriminatory ability for vancomycin-resistant Enterococcus (VRE), but they show no significant diagnostic efficacy for other multidrug-resistant organisms (MDROs) such as carbapenem-resistant Enterobacteriaceae (CRE), carbapenem-resistant Pseudomonas aeruginosa (CRPA), and methicillin-resistant Staphylococcus aureus (MRSA). In our mouse model experiments, we observed a remarkable increase in PCT, IL-6, and IL-10 levels in mice with GN-BSI compared to those with GP-BSI.

CONCLUSION

Our study has confirmed that PCT, IL-6, and IL-10 are efficient biomarkers for distinguishing between BSI and LBI. Furthermore, they can be utilized to classify BSI pathogens and differentiate between VRE and vancomycin-susceptible Enterococcus. These findings are extremely valuable for clinicians as they enable timely initiation of empiric antibiotic therapies and ultimately lead to improved clinical outcomes for patients with BSI.

Application of the FMEA Method in Improving the Quality Management of Emergency Complete Blood Count Testing

OBJECTIVE

Failure mode and effects analysis (FMEA) was used to identify factors that contribute to quality management deficiencies in laboratory testing of emergency complete blood count (CBC).

METHODS

Improvements included instrument updates, personnel training, and laboratory information system optimization. We used operational data from January 2021 (control group) and January 2022 (FMEA group) to compare the risk priority number (RPN) of FMEA, emergency CBC laboratory turnaround time (TAT), error report rate, and specimen failure rate.

RESULTS

After the implementation of FMEA, the average RPN dropped from 36.24 ± 9.68 to 9.45 ± 2.25, (t = 20.89, P < .05). Additionally, the median TAT for emergency CBCs decreased from 23 min to 11 min as did the interquartile distance (17-34 min to 8-16 min) (P < .05). The rate of emergency CBC error reports decreased from 1.39% to 0.71% (P < .05), and the specimen failure rate decreased from 0.95% to 0.32% (P < .05). Patient satisfaction also increased from 43% to 74% (P < .05), and the technician-performed morphology assessment pass rate increased from 16.7% to 100% (P < .05).

CONCLUSION

Improving the emergency CBC testing process with FMEA can shorten emergency CBC laboratory TAT and reduce specimen failure rates and reporting error rates. The FMEA can be used to improve quality management in emergency CBC laboratories.

The Neutrophil-to-Lymphocyte Ratio (NLR) Can Predict Sepsis's Presence and Severity in Malnourished Infants-A Single Center Experience

Sepsis represents one of the leading causes of death in newborns and infants, and prompt diagnosis is essential for achieving favorable outcomes. Regarding malnourished children with concurrent infection, most studies have focused, besides blood culture, on C-reactive protein and procalcitonin. Because malnutrition has a deleterious effect on cellular immune competence, the present study characterized the acute-phase response, including hematological indices, in response to sepsis. Among the examined laboratory biomarkers, procalcitonin and neutrophil-to-lymphocyte ratio were the most accurate discriminators between sepsis patients and those with bacterial infection. Moreover, these two parameters showed a gradual increase between sepsis, severe sepsis, and septic shock patients (p < 0.001). Subgroup analysis of the sepsis group revealed positive correlations of NLR with prolonged ICU stay (<0.001), acute organ dysfunction (0.038), mechanical ventilation (<0.001), and fatality (<0.001). In summary, our results suggest that the neutrophil-to-lymphocyte ratio can be used as an auxiliary diagnostic index in discriminating the presence and severity of bacterial sepsis in malnourished infants.

The role of neutrophil percentage to albumin ratio in predicting 1-year mortality in elderly patients with hip fracture and external validation

Objectives

This study aimed to investigate the association between the neutrophil percentage to albumin ratio (NPAR) on the day of admission and mortality 1 year after surgery in elderly patients with hip fractures.

Methods

Clinical characteristics and blood markers of inflammation were retrospectively collected from October 2016 to January 2022 in elderly patients with hip fractures at two different regional tertiary medical centers. It is divided into a training set and an external validation set. Multivariate Nomogram models such as NPAR were constructed using the least absolute shrinkage and selection operator (LASSO) regression results and multi-factor logistic regression analysis. In addition, multivariate Cox regression analysis and Kaplan-Meier survival curves were used to explore the relationship between NPAR values and mortality within 1 year in elderly patients with hip fractures. The predictive performance of the Nomogram was evaluated using the concordance index (C Index) and receiver operating characteristic curve (ROC) and validated by Bootstrap, Hosmer-Lemesow goodness of fit test, calibration curve, decision curve, and clinical impact curve analysis.

Results

The study included data from 1179 (mean age, 80.34 ± 8.06 years; 61.4[52.1%] male) patients from the Guangzhou Red Cross Hospital affiliated with Jinan University and 476 (mean age, 81.18 ± 8.33 years; 233 [48.9%] male) patients from the Xiaogan Central Hospital affiliated with Wuhan University of Science and Technology. The results showed that NPAR has good sensitivity and specificity in assessing patients' prognosis 1 year after surgery. Multivariate logistic regression models based on influencing factors such as NPAR have good discrimination and calibration ability (AUC=0.942, 95% CI:0.927-0.955; Hosmer-Lemeshow test: P >0.05). Kaplan-Meier survival curves for the training and validation sets showed that patients in the high NPAR group had a higher mortality rate at 1 year compared to the low NPAR group (P< 0.001). Multivariate Cox regression showed that high NPAR values were an independent risk factor for death within 1 year in elderly hip fracture patients (P< 0.001, HR =2.38,95%CI:1.84-3.08).

Conclusion

Our study showed that NPAR levels were significantly higher in patients who died within 1 year after surgery in both the training and validation sets. NPAR has good clinical value in assessing 1-year postoperative prognosis in elderly patients with hip fractures.

A machine learning model for distinguishing Kawasaki disease from sepsis

KD is an acute systemic vasculitis that most commonly affects children under 5 years old. Sepsis is a systemic inflammatory response syndrome caused by infection. The main clinical manifestations of both are fever, and laboratory tests include elevated WBC count, C-reactive protein, and procalcitonin. However, the two treatments are very different. Therefore, it is necessary to establish a dynamic nomogram based on clinical data to help clinicians make timely diagnoses and decision-making. In this study, we analyzed 299 KD patients and 309 sepsis patients. We collected patients' age, sex, height, weight, BMI, and 33 biological parameters of a routine blood test. After dividing the patients into a training set and validation set, the least absolute shrinkage and selection operator method, support vector machine and receiver operating characteristic curve were used to select significant factors and construct the nomogram. The performance of the nomogram was evaluated by discrimination and calibration. The decision curve analysis was used to assess the clinical usefulness of the nomogram. This nomogram shows that height, WBC, monocyte, eosinophil, lymphocyte to monocyte count ratio (LMR), PA, GGT and platelet are independent predictors of the KD diagnostic model. The c-index of the nomogram in the training set and validation is 0.926 and 0.878, which describes good discrimination. The nomogram is well calibrated. The decision curve analysis showed that the nomogram has better clinical application value and decision-making assistance ability. The nomogram has good performance of distinguishing KD from sepsis and is helpful for clinical pediatricians to make early clinical decisions.

Platelet role in the prediction of MIS-C severity

Introduction

Multisystem inflammatory syndrome in children (MIS-C) has been reported as one of the cytokine storm syndromes associated with COVID-19. Despite the several proposed diagnostic criteria, MIS-C remains a diagnostic and clinical challenge. Recent studies have demonstrated that platelets (PLTs) play a crucial role in COVID-19 infection and its prognosis. This study aimed to investigate the clinical importance of PLT count and PLT indices in predicting MIS-C severity in children.

Patients and methods

We conducted a retrospective single-center study at our university hospital. A total of 43 patients diagnosed with MIS-C during a 2-year period (from October 2020 to October 2022) were included in the study. MIS-C severity was evaluated according to the composite severity score.

Results

Half of the patients were treated in the pediatric intensive care unit. No single clinical sign was associated with a severe condition, except for shock (p = 0.041). All the routine biomarkers, such as complete blood count (CBC) and C-reactive protein (CRP), used for MIS-C diagnosis were significant in predicting MIS-C severity. Single PLT parameters, such as mean PLT volume, plateletcrit, or PLT distribution width, did not differ between the severity groups. However, we found that a combination of PLT count and the previously mentioned PLT indices had the potential to predict MIS-C severity.

Conclusions

Our study emphasizes the importance of PLT in MIS-C pathogenesis and severity. It revealed that together with routine biomarkers (e.g., CBC and CRP), it could highly improve the prediction of MIS-C severity.

Monocyte, Lymphocyte and Neutrophil Ratios - Easy-to-Use Biomarkers for the Diagnosis of Pediatric Tuberculosis

BACKGROUND

The neutrophil-to-lymphocyte-ratio (NLR), neutrophil-to-monocyte-plus-lymphocyte-ratio (NMLR) and monocyte-to-lymphocyte-ratio (MLR) may have diagnostic potential for tuberculosis (TB).

METHODS

Data of two prospective multicenter studies in Switzerland were used, which included children <18 years with TB exposure, infection or disease or with febrile non-TB lower-respiratory-tract infection (nTB-LRTI).

RESULTS

Of the 389 children included 25 (6.4%) had TB disease, 12 (3.1%) TB infection, 28 (7.2%) were healthy TB exposed and 324 (83.3%) nTB-LRTI. Median (IQR) NLR was highest with 2.0 (1.2, 2.2) in children with TB disease compared to TB exposed [0.8 (0.6, 1.3); P = 0.002] and nTB-LRTI [0.3 (0.1, 1.0); P < 0.001]. Median (IQR) NMLR was highest with 1.4 (1.2, 1.7) in children with TB disease compared to healthy exposed [0.7 (0.6, 1.1); P = 0.003] and children with nTB-LRTI [0.2 (0.1, 0.6); P < 0.001). Receiver operating characteristic curves to detect TB disease compared to nTB-LRTI for NLR and NMLR had an area under the curve of 0.82 and 0.86, the sensitivity of 88% and 88%, and specificity of 71% and 76%, respectively.

CONCLUSION

NLR and NMLR are promising, easy-to-obtain diagnostic biomarkers to differentiate children with TB disease from other lower respiratory tract infections. These results require validation in a larger study and in settings with high and low TB endemicity.

Platelet index on admission as a predictor of bacteremia in acute cholangitis: a 7-year retrospective observational study

Bacteremia frequently occurs in patients with acute cholangitis, which could increase the risk of mortality. This single-center retrospective observational study was conducted from July 2013 to July 2020 to evaluate the predictive value of platelet index for bacteremia at admission for acute cholecystitis. A total of 285 patients with acute cholangitis were divided into bacteremia group and non-bacteremia group. The incidence of bacteremia in acute cholangitis was 48.42%. The bacteremia group had more grade III patients, higher 30d mortality rate [17(12.32%) vs 8(5.44%), p = .040] and higher incidence of thrombocytopenia [76(55.07%) vs 35(23.81%), p < .001]. Platelet counts and plateletcrit were significantly lower in the bacteremia group [84.5(60, 180) vs 162(102,225) ×10⁹/L and 0.10(0.07, 0.21)% vs 0.18(0.12, 0.25) %, both p < .001]. ROC analysis indicated a high predictive value of platelet count and plateletcrit for bacteremia in patients with acute cholangitis and the area under the ROC curve (AUC) were 0.649 and 0.655, respectively. These results support the value of platelet count and plateletcrit in early prediction of bacteremia at admission for acute cholangitis.

Predictive value of combining maternal peripheral blood count indicators for early-onset sepsis in preterm infants: A retrospective cohort study

To assess the early predictive value of maternal parameters for early-onset sepsis (EOS) in preterm infants, especially including the maternal neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and mean platelet volume (MPV). The retrospective cohort study examined a total of 231 preterm infants (69 with EOS) from May 2017 to October 2021 of the Fourth Hospital of Hebei Medical University, randomly divided (7:3) into the training set group (n = 162) and validation set group (n = 69). Thirteen clinical variables (including MPV, NLR, and PLR) were included as the research objects. By logistic regression, the factors significantly associated with EOS were distinguished. Additionally, a nomogram was constructed based on the independent risk factors, the validation of which relied on the concordance index, calibration curves, receiver operating characteristic curves, and decision curve analyses. Multivariate logistic regression proved that NLR (OR = 1.67, 95% CI = 1.18-2.36, P = .004), PLR (OR = 1.03, 95% CI = 1.01-1.04, P = .001), and MPV (OR = 1.75, 95% CI = 1.15-2.66, P = .009) were independent risk factors for EOS. The AUC of the nomogram for the training set group was 0.872 (0.814, 0.931) and 0.889 (0.843, 0.935) in the validation set group. The P values of Hosmer-Lemeshow test for the training set and validation set groups were .903 and .752, respectively. The decision curve analyses outcome indicated good clinical practicability. The C-index for the training set and validation set groups were 0.872 and 0.889, respectively. The maternal NLR, PLR, and MPV levels had good predictive value for EOS in premature infants. The nomogram in our study could help clinicians predict the occurrence of EOS.

Monocyte Distribution Width in Children With Systemic Inflammatory Response: Retrospective Cohort Examining Association With Early Sepsis

OBJECTIVES

To investigate the association between increased monocyte distribution width (MDW) and pediatric sepsis in the emergency department (ED).

DESIGN

Retrospective cohort study.

SETTING

A single academic hospital study.

PATIENTS

Patients from birth to the age of 18 years who presented at the ED of an academic hospital with systemic inflammatory response syndrome (SIRS) were consecutively enrolled. Sepsis was diagnosed using the International Pediatric Surviving Sepsis Campaign criteria.

INTERVENTIONS

Antibiotic treatment was administrated once infection was suspected.

MEASUREMENTS AND MAIN RESULTS

Routine complete blood cell count, neutrophil-to-lymphocyte ratio (NLR), and MDW, a new inflammatory biomarker, were evaluated in the ED. Logistic regression models were used to explore associations with early pediatric sepsis. We included 201 patients with sepsis and 1,050 without sepsis. In the multivariable model, MDW greater than 23 U (odds ratio [OR], 4.97; 95% CI, 3.42-7.22; p < 0.0001), NLR greater than 6 (OR, 2.06; 95% CI, 1.43-2.94; p = 0.0001), WBC greater than 11,000 cells/µL (OR, 6.52; 95% CI, 4.45-9.53; p < 0.0001), and the SIRS score (OR, 3.42; 95% CI, 2.57-4.55; p < 0.0001) were associated with pediatric sepsis. In subgroup analysis, MDW greater than 23 U remained significantly associated with sepsis for children 6-12 years old (OR, 6.76; 95% CI, 2.60-17.57; p = 0.0001) and 13-18 years (OR, 17.49; 95% CI, 7.69-39.76; p = 0.0001) with an area under the receiver operating curve of 0.8-0.9.

CONCLUSIONS

MDW greater than 23 U at presentation is associated with the early diagnosis of sepsis in children greater than or equal to 6 years old. This parameter should be considered as a stratification variable in studies of pediatric sepsis.

Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU

OBJECTIVES

Unrecognized clinical deterioration during illness requiring hospitalization is associated with high risk of mortality and long-term morbidity among children. Our objective was to develop and externally validate machine learning algorithms using electronic health records for identifying ICU transfer within 12 hours indicative of a child's condition.

DESIGN

Observational cohort study.

SETTING

Two urban, tertiary-care, academic hospitals (sites 1 and 2).

PATIENTS

Pediatric inpatients (age <18 yr).

INTERVENTIONS

None.

MEASUREMENT AND MAIN RESULTS

Our primary outcome was direct ward to ICU transfer. Using age, vital signs, and laboratory results, we derived logistic regression with regularization, restricted cubic spline regression, random forest, and gradient boosted machine learning models. Among 50,830 admissions at site 1 and 88,970 admissions at site 2, 1,993 (3.92%) and 2,317 (2.60%) experienced the primary outcome, respectively. Site 1 data were split longitudinally into derivation (2009-2017) and validation (2018-2019), whereas site 2 constituted the external test cohort. Across both sites, the gradient boosted machine was the most accurate model and outperformed a modified version of the Bedside Pediatric Early Warning Score that only used physiologic variables in terms of discrimination ( C -statistic site 1: 0.84 vs 0.71, p < 0.001; site 2: 0.80 vs 0.74, p < 0.001), sensitivity, specificity, and number needed to alert.

CONCLUSIONS

We developed and externally validated a novel machine learning model that identifies ICU transfers in hospitalized children more accurately than current tools. Our model enables early detection of children at risk for deterioration, thereby creating opportunities for intervention and improvement in outcomes.

Soluble PD-L1 in blood correlates positively with neutrophil and negatively with lymphocyte mRNA markers and implies adverse sepsis outcome

Sepsis causes a myriad of immunological reactions that result in life-threatening alterations in the human body. Immunosuppression in sepsis is partly attributed to the programmed death receptor (PD-1) and its associated ligand (PD-L1) via the regulation of lymphocytes and neutrophils. Although the soluble forms of these proteins (i.e., sPD-1 and sPD-L1, respectively) are recognized as possible sepsis biomarkers, their functional implications are yet to be elucidated. Our research assessed the correlation between sPD-1 and sPD-L1 and blood mRNA markers and sepsis outcome. Blood samples of septic patients of urogenital origin versus control patients (both groups: n = 18) were analyzed. Blood serum sPD-1 and sPD-L1 levels were determined using the enzyme-linked immunosorbent assay (ELISA). The whole blood mRNA concentrations of PD-1, PD-L1, neutrophil markers (CEACAM8 and MPO), and T-lymphocyte markers (TCRβ, CD4 and CD8) were determined via reverse transcriptase quantitative PCR (RT-qPCR). sPD-L1 levels were significantly increased in septic patients when compared to the controls, whereas sPD-1 levels were unaltered. Patients with high sPD-L1 levels, as dichotomized to the median, had a significantly shorter survival rate than those with low sPD-L1 levels. The sensitivity/specificity characteristics of sPD-L1 proved significant for sepsis detection. Furthermore, sPD-L1 correlated with the mRNA concentrations of PD-L1, CEACAM, and MPO, as well as major inflammatory markers (C-reactive protein and procalcitonin). However, sPD-L1 negatively correlated with TCRβ, CD4, and CD8 mRNAs. sPD-L1 was found to be significantly increased in septic patients. Notably, sPD-L1 correlated with PD-L1 mRNA and neutrophil markers and was indicative of adverse outcomes.

A Novel Algorithm With Paired Predictive Indexes to Stratify the Risk Levels of Neonates With Invasive Bacterial Infections: A Multicenter Cohort Study

BACKGROUND

Our aim was to develop a predictive model comprising clinical and laboratory parameters for early identification of full-term neonates with different risks of invasive bacterial infections (IBIs).

METHODS

We conducted a retrospective study including 1053 neonates presenting in 9 tertiary hospitals in China from January 2010 to August 2019. An algorithm with paired predictive indexes (PPIs) for risk stratification of neonatal IBIs was developed. Predictive performance was validated using k-fold cross-validation.

RESULTS

Overall, 166 neonates were diagnosed with IBIs (15.8%). White blood cell count, C-reactive protein level, procalcitonin level, neutrophil percentage, age at admission, neurologic signs, and ill-appearances showed independent associations with IBIs from stepwise regression analysis and combined into 23 PPIs. Using 10-fold cross-validation, a combination of 7 PPIs with the highest predictive performance was picked out to construct an algorithm. Finally, 58.1% (612/1053) patients were classified as low-risk cases. The sensitivity and negative predictive value of the algorithm were 95.3% (95% confidence interval: 91.7-98.3) and 98.7% (95% confidence interval: 97.8-99.6), respectively. An online calculator based on this algorithm was developed for clinical use.

CONCLUSIONS

The new algorithm constructed for this study was a valuable tool to screen neonates with suspected infection. It stratified risk levels of IBIs and had an excellent predictive performance.

The Value of Neutrophil-To-Lymphocyte Ratio for Evaluating Blood Stream Infection Caused by Carbapenem-Resistant Klebsiella pneumoniae: A Retrospective Cohort Study

Background

The neutrophil-to-lymphocyte ratio (NLR) is a useful marker of inflammation. However, the prognostic function of the NLR in patients with carbapenem-resistant Klebsiella pneumoniae (CRKP) blood stream infection (BSI) remains largely unknown. The aim of this study was to explore the potential relationship between the NLR and mortality in these patients.

Methods

We performed a retrospective cohort study based on data retrieved from the computerized patient record system in a tertiary hospital from 1 January 2017 to 31 October, 2020. A total of 134 inpatients with CRKP BSI were enrolled in this study, including 54 fatal cases and 80 survival cases, 28 days after the onset of CRKP BSI. A logistic analysis was performed to assess the association between the NLR on the 4th day and 28-day mortality. Multivariate analyses were used to control for the confounders.

Results

The overall 28-day mortality rate of patients with a CRKP BSI episode was 40.3% (54/134). We conducted a multivariate analysis of the data of 134 patients and found that the NLR on the 4th day [odds ratio (OR) 1.148, 95% confidence interval (CI) 1.076–1.225, p < 0.001] and antibiotic exposure before BSI onset (OR 3.847, 95% CI 1.322–11.196, p = 0.013) were independent risk factors for 28-day mortality of patients with CRKP BSI, while appropriate initial therapy (AIT, OR 0.073, 95% CI 0.017–0.307, p < 0.001) was an independent protective factor. Among patients treated with AITs, the Cox proportional hazards regression analysis revealed a significant difference in prognosis (p = 0.006) between the ceftazidime/avibactam contained (CAZ) group and non CAZ-AVI groups. After dividing the non CAZ-AVI group into the tigecycline (TGC), colistin (COL), and TGC + COL groups, there were no differences between the CAZ-AVI group and the TGC group (p = 0.093), but CAZ-AVI group showed lower 28-day mortality than COL (p = 0.002) and TGC + COL (p = 0.002) groups. Meanwhile, there was no difference in NLR on the 1st day (p = 0.958) of patients in different groups but significant difference in NLR on the 4th day (p = 0.047).

Conclusions

The NLR on the 4th day is a readily available and independent prognostic biomarker for patients with CRKP BSI. This marker may have the potential for use in evaluating the efficacy of different anti-infection therapy strategies at an early stage.

Early Warning and Clinical Epidemiological Characteristics of Lung Injury in the Treatment of Infectious Staphylococcus aureus Sepsis by Vancomycin Based on Adaptive Niche Genetic Algorithm and Pulmonary Ultrasound Images

Adaptive niche genetic algorithm (ANGA) and lung ultrasound were combined, the death warning mathematical model was established for patients with sepsis-lung injury, and the epidemiological characteristics were analyzed to explore the efficacy of Vancomycin in the treatment of sepsis-lung injury. First, 88 sepsis patients with lung injury were selected as the research objects. General clinical data and pulmonary ultrasound results were collected. On this basis, epidemiological analysis was carried out, and the death warning model of patients with sepsis-lung injury was established based on ANGA algorithm. Then, the total cure rate, Staphylococcus aureus (SA) clearance rate, methicillin-resistant SA (MRSA) clearance rate, and the incidence of adverse reactions after intravenous infusion of Vancomycin were analyzed. The results showed that the ANGA mathematical model combined with the random forest (RF) classifier proposed had better classification effect and robustness relative to the traditional principal component analysis and NGA. The early warning accuracy of the proposed ANGA + RF mathematical model was higher than 95% in contrast to that of the APACHE-II score and the SOFA score. Compared with patients in the severe group, the MRSA infection rate and the levels of procalcitonin (PCT), C-reactive protein (CRP), and activated partial thromboplastin time (APTT) of SA sepsis-lung injury patients were greatly reduced, while thrombin time (TT) and D-D dimer in the death group were considerably increased (p < 0.05), and the PLT level was greatly reduced (p < 0.05). In addition, the total cure rate, SA clearance rate, and MRSA clearance rate of Vancomycin-treated SA sepsis-lung injury patients were significantly increased (p < 0.05) compared with patients in the conventional treatment control group. However, the probability of adverse reactions was increased notably (p < 0.05). ANGA combined with RF classifier can improve the accuracy of death warning in patients with sepsis-lung injury. Vancomycin can effectively eliminate MRSA infection rate in patients with sepsis-lung injury and improve the treatment effect of patients.

Efficiency of Monocyte/High-Density Lipoprotein Cholesterol Ratio Combined With Neutrophil/Lymphocyte Ratio in Predicting 28-Day Mortality in Patients With Sepsis

Background: Sepsis can cause unpredictable harm, and early identification of risk for mortality may be conducive to clinical diagnosis. The present study proposes to assess the efficacy of the monocyte/high-density lipoprotein cholesterol ratio (MHR) combined with the neutrophil/lymphocyte ratio (NLR) on the day of admission in predictive efficacy in the 28-day mortality risk in critical patients with sepsis.

Material and Methods: We administered observational and retrospective cohort research from a single center. The correlation of the clinical variables, together with the system severity scores of APACHE II and SOFA, are displayed by correlation analysis, and a Cox regression model could be performed to screen the independent risk factors and estimate the capacity of multiple markers in predicting 28-day mortality. The receiver operating characteristic (ROC) curve served as an applied method to output cutoff values for the diagnosis and prognostic risk, and the area under the ROC curve and net reclassification improvement index (NRI), as well as integrated discrimination improvement index (IDI) were employed to assess the feasibility of multiple parameters for predictive value in 28-day mortality of septic patients.

Results: The study enrolled 274 eligible patients with sepsis. The correlation analysis indicated NLR and MHR were related to the sepsis severity. A multivariate Cox regression analysis indicated that NLR together with MHR displayed a close relation to death rate after adjusting for other potential confounders (NLR, HR = 1.404 [95% CI 1.170–1.684], P < 0.001; MHR, HR = 1.217 [95% CI 1.112–1.331], P < 0.001). The AUC of NLR, MHR, NLR_MHR was 0.827, 0.876, and 0.934, respectively. The addition on the biomarker NLR_MHR to the prediction model improved IDI by 18.5% and NRI by 37.8%.

Conclusions: Our findings suggest that NLR and MHR trend to an elevated level in non-surviving patients with sepsis. Evaluation of NLR_MHR, an independent risk factor for increased mortality, might improve the predictive efficacy for 28-day mortality risk in septic patients.

Evaluation of CBC Parameters in Relation to PCR Test Results in Diagnosing Pediatric COVID-19 Disease

Objective This study aimed to investigate whether complete blood count parameters have predictive properties in diagnosing coronavirus disease 2019 (COVID-19) in regard to positive polymerase chain reaction (PCR) test in children with a prediagnosis of COVID-19, and whether these parameters are related to the severity of clinical findings in children with COVID-19.

Methods This retrospective cross-sectional study included children who were hospitalized with a possible diagnosis of COVID-19 and had undergone PCR testing in the COVID-19 children's clinic. Probable case definition was made according to the COVID-19 diagnostic and therapeutic guidelines of the Ministry of Health of the Republic of Turkey.

Results A total of 133 patients were included in the study, of which 46 (34.6%) were negative for the PCR test and 87 (65.4%) were positive for the PCR test. white blood cell (WBC), neutrophil, lymphocyte, and platelet levels were significantly lower in the PCR positive group than in the PCR negative group. The platelet to mean platelet volume ratio (PLT/MPV) was significantly lower in the PCR positive group than the PCR negative group, whereas the platelet distribution width (PDW) of the PCR positive patient group was significantly higher than the PCR negative group. For the multivariable model with PDW and neutrophil to lymphocyte ratio/age factors included, F1 score was 0.864, area under the receiver operating characteristics was 0.804, and area under the precision-recall curve was 0.873. The decision tree had a 72.9% cross-validation accuracy value.

Conclusion WBC, neutrophils, lymphocytes, platelets, PLT/MPV, and PDW parameters could be used in conjunction with clinical symptoms and findings to predict the PCR test result.

Monocyte Distribution Width, Neutrophil-to-Lymphocyte Ratio, and Platelet-to-Lymphocyte Ratio Improves Early Prediction for Sepsis at the Emergency

(1) Background: Sepsis is a life-threatening condition, and most patients with sepsis first present to the emergency department (ED) where early identification of sepsis is challenging due to the unavailability of an effective diagnostic model. (2) Methods: In this retrospective study, patients aged ≥20 years who presented to the ED of an academic hospital with systemic inflammatory response syndrome (SIRS) were included. The SIRS, sequential organ failure assessment (SOFA), and quick SOFA (qSOFA) scores were obtained for all patients. Routine complete blood cell testing in conjugation with the examination of new inflammatory biomarkers, namely monocyte distribution width (MDW), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), was performed at the ED. Propensity score matching was performed between patients with and without sepsis. Logistic regression was used for constructing models for early sepsis prediction. (3) Results: We included 296 patients with sepsis and 1184 without sepsis. A SIRS score of >2, a SOFA score of >2, and a qSOFA score of >1 showed low sensitivity, moderate specificity, and limited diagnostic accuracy for predicting early sepsis infection (c-statistics of 0.660, 0.576, and 0.536, respectively). MDW > 20, PLR > 9, and PLR > 210 showed higher sensitivity and moderate specificity. When we combined these biomarkers and scoring systems, we observed a significant improvement in diagnostic performance (c-statistics of 0.796 for a SIRS score of >2, 0.761 for a SOFA score of >2, and 0.757 for a qSOFA score of >1); (4) Conclusions: The new biomarkers MDW, NLR, and PLR can be used for the early detection of sepsis in the current sepsis scoring systems.

Effects of Neutrophil-to-Lymphocyte Ratio Combined With Interleukin-6 in Predicting 28-Day Mortality in Patients With Sepsis

Background

The current study aimed to evaluate the relationship between the neutrophil-to-lymphocyte ratio (NLR) combined with interleukin (IL)-6 on admission day and the 28-day mortality of septic patients.

Material and Methods

We conducted an observational retrospective study. Patients with presumed sepsis were included. We observed the correlation of studied biomarkers (NLR, IL-6, PCT, and CRP) and the severity scores (APACHE II and SOFA scores) by plotting scatter plots. The relationships of the studied biomarkers and 28-day mortality were evaluated by using Cox regression model, receiver-operating characteristic (ROC) curve, and reclassification analysis.

Results

A total of 264 patients diagnosed with sepsis were enrolled. It was revealed that IL-6 had the strongest correlation with both APACHE II and SOFA scores, followed by the NLR and PCT, and there was no obvious correlation between CRP and the illness severity. NLR and IL-6 were independent predictors of the 28-day mortality in septic patients in the Cox regression model [NLR, odds ratio 1.281 (95% CI 1.159-1.414), P < 0.001; IL-6, odds ratio 1.017 (95% CI 1.005-1.028), P=0.004]. The area under the ROC curve (AUC) of NLR, IL-6 and NLR plus IL-6 (NLR_IL-6) was 0.776, 0.849, and 0.904, respectively.

Conclusion

Our study showed that the levels of NLR and IL-6 were significantly higher in the deceased patients with sepsis. NLR and IL-6 appeared to be independent predictors of 28-day mortality in septic patients. Moreover, NLR combined with IL-6 could dramatically enhance the prediction value of 28-day mortality.

Distinguishing bacterial versus non-bacterial causes of febrile illness - A systematic review of host biomarkers

BACKGROUND

Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development.

OBJECTIVES

To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI.

DATA SOURCES

The PubMed database was systematically searched for relevant studies published between 2015 and 2019.

STUDY ELIGIBILITY CRITERIA

Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included.

PARTICIPANTS

Studies involving human participants and/or human samples were included.

METHODS

We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A risk of bias assessment was performed, based on a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Score 2).

RESULTS

We identified 1107 publications. Following screening, 55 publications were included, with 265 biomarker entries. Entries mostly comprised protein biomarkers (58.9%), followed by haematological, RNA, and metabolite biomarkers (15.5%, 8.7%, 12.5%). Sensitivity/specificity was reported for 45.7% of biomarker entries. We assessed a high overall risk of bias for most entries (75.8%). In studies with low/medium risk of bias, four biomarker entries tested in blood samples had sensitivity/specificity of more than 0.90/0.80. Only 12 additional biomarker entries were identified with sensitivity/specificity of more than 0.65/0.65.

CONCLUSIONS

Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings.

Biochemical and molecular study on serum miRNA-16a and miRNA- 451 as neonatal sepsis biomarkers

Background

Sepsis is the serious cause of fatality in the unit of medical-intensive care (ICU). Non-coding RNA transcripts are microRNA that control gene expression by repressing translation or degrading mRNA. There are several reports discussing the concept of using miRNAs as sepsis a biomarkers by profiling miRNA dysregulation in sepsis patients' blood samples.

Objectives

The research was aimed at exploring the clinical utility of miRNA-16a and miRNA- 451 for diagnosis of neonatal sepsis.

Subjects

and methods: This research was conducted on 50 full term neonates, 25 neonates with suspected or proven sepsis and 25 clinically healthy sex and age matched neonates with no evidence of sepsis. All newborns have been exposed to clinical review, history taking and laboratory investigations including total & differential count of blood cells, C-reactive protein, blood culture. Serum miRNA-16a and miRNA-451 levels have been assessed using Real Time polymerase chain reaction (Real Time PCR) technique.

Results

Neonates with sepsis had considerably higher levels of miRNA-16a and miRNA- 451 than the healthy neonates (p ≤ 0.001). Receiver operating curve (ROC) showed that serum miRNA-16a was superior to miRNA-451 for diagnosis of sepsis with neonatal origin; it had sensitivity and specificity of 88% and 98% versus 64% and 61% respectively. Cut off point for miRNA-16a to diagnose neonatal sepsis was above or equal 3.16. Also, cut off point for miRNA-451 was above or equal 1.26. miRNA-16 a and miRNA 451 expression was significantly correlated with respiratory rate, WBCs, and CRP.

Conclusion

Both miRNA −16a and miRNA-451 are detected in higher levels in newborn with sepsis compared to controls. MiRNA- 16a could be considered as promising biomarkers for diagnosis of neonatal sepsis.

•

Septic neonates had substantially higher levels of level of miRNA-16a.

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miRNA-16a had greater sensitivity and specificity than miRNA-451.

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miRNA-16a was superior to miRNA-451 concerning neonatal sepsis diagnosis.

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miRNA-16a could be diagnostic biomarker for neonatal sepsis.

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miRNA-16a and miRNA-451 might serve as prognostic markers for neonatal sepsis.

The Utility of the Neutrophil-Lymphocyte Ratio as an Early Diagnostic Marker in Neonatal Sepsis

Aim To find the diagnostic utility of the neutrophil to lymphocyte ratio (NLR) in the early diagnosis of neonatal sepsis. Methodology The case records of all blood culture-positive septic neonates admitted from January 2018 to December 2018 were reviewed. Total leucocyte count, absolute neutrophil count, absolute lymphocyte counts, NLR, and C-reactive protein (CRP) of septic neonates were compared with gestational age-matched nonseptic neonates by an unpaired t-test. The diagnostic performance of NLR and CRP was analyzed by receiver operating characteristic (ROC) analysis. Result A total of 41 blood culture-positive neonates and 52 nonseptic neonates were enrolled in this study. There was no significant difference in the total leucocyte count and absolute neutrophil counts of septic and nonseptic neonates. The mean absolute lymphocyte count of septic neonates (2795±1424/cumm) was significantly lower than that of nonseptic neonates (4449±1794/cumm; p=<0.001). The mean NLR of septic neonates (3.88±1.78) was significantly higher as compared to nonseptic (2.3404 ±1.98) neonates (p=0.045). For the diagnosis of sepsis, NLR at cutoff >1.7 had a sensitivity and specificity of 68.3% and 46.2%, respectively; CRP at cutoff >6 mg/dl had sensitivity and specificity of 78.05% and 92.31%, respectively. In the ROC analysis, the area under the curve (AUC) for CRP and NLR for the diagnosis of neonatal sepsis was 0.918 (p=<0.001) and 0.623 (p=0.042), respectively. Conclusion Blood culture-positive septic neonates had significantly higher NLR as compared to nonseptic neonates. However, when compared to CRP, NLR was not found to be a better predictor of sepsis in our study.

Reliability of Capillary Complete Blood Count in Children With Acute Gastroenteritis

Background: To assess the reliability of complete blood count (CBC) in the capillary blood of children with acute gastroenteritis (AGE), with a focus on leukocytes. Methods: This was a retrospective cross-sectional study. Complete blood count was compared between the capillary and venous blood in children admitted to a pediatric gastroenterology department with primary diagnosis of AGE (ICD-10 A09, A08.0, A08.2). Capillary blood was obtained in the emergency room and venous blood was sampled in the ward shortly thereafter during peripheral intravenous line placement. Results: One hundred and forty children were included. The mean (±SD) age and weight of patients were 3.0 ± 2.9 years and 16 ± 9 kg; 26% had leukocytosis. The mean difference between obtaining results of capillary and venous blood tests was 2 ± 1 h. Area under the receiver operating characteristic curve (AUC) for the identification of leukocytosis using the capillary blood was 0.98 (95% CI 0.96-1.0). The sensitivity and specificity were 86 and 98%, respectively (accuracy 95%). The positive and negative predictive values were 94 and 95%, respectively. The intraclass correlation coefficient revealed high concordance between capillary and venous CBC measurements (leukocyte count 0.94, hemoglobin 0.88, erythrocyte count 0.77, hematocrit 0.79, platelet count 0.90). Matched pairs comparisons revealed marginally higher erythrocytes (difference of medians: 0.2 T/L), hemoglobin (0.3 g/dL), hematocrit (1.0%), and platelets (9 G/L) in the capillary blood. Conclusion: Capillary CBC is useful in detecting leukocytosis in children with AGE.

Predicting bacteraemia in maternity patients using full blood count parameters: A supervised machine learning algorithm approach

INTRODUCTION

Bacteraemia in pregnancy and the post-partum period can lead to maternal and newborn morbidly. The purpose of this study was to use machine learning tools to identify if bacteraemia in pregnant or post-partum women could be predicted by full blood count (FBC) parameters other than the white cell count.

METHODS

The study was performed on 129 women with a positive blood culture (BC) for a clinically significant organism, who had a FBC taken at the same time. They were matched with controls who had a negative BC taken at the same time as a FBC. The data were split in to a training (70%) and test (30%) data set. Machine learning techniques such as recursive partitioning and classification and regression trees were used.

RESULTS

A neutrophil/lymphocyte ratio (NLR) of >20 was found to be the most clinically relevant and interpretable construct of the FBC result to predict bacteraemia. The diagnostic accuracy of NLR >20 to predict bacteraemia was then examined. Thirty-six of the 129 bacteraemia patients had a NLR >20, while only 223 of the 3830 controls had a NLR >20. This gave a sensitivity of 27.9% (95% CI 20.3-36.4), specificity of 94.1% (93.3-94.8), positive predictive value of 13.9% (10.6-17.9) and a negative predictive value (NPV) of 97.4% (97.2-97.7) when the prevalence of bacteraemia was 3%.

CONCLUSION

The NLR should be considered for use in routine clinical practice when assessing the FBC result in patients with suspected bacteraemia during pregnancy or in the post-partum period.

The Combination of Hemogram Indexes to Predict Exacerbation in Stable Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is characterized by pulmonary and systemic inflammatory processes, and exacerbation of COPD represents a critical moment in the progression of COPD. Several biomarkers of inflammation have been proposed to have a predictive function in acute exacerbation. However, their use is still limited in routine clinical practice. The purpose of our study is to explore the prognostic efficacy of novel inflammatory hemogram indexes in the exacerbation among stable COPD patients. Method: A total of 275 stable COPD patients from the Shanghai COPD Investigation Comorbidity Program were analyzed in our study. Blood examinations, especially ratio indexes like platelet-lymphocyte ratio (PLR), platelet × neutrophil/lymphocyte ratio [systemic immune-inflammation index (SII)], and monocyte × neutrophil/lymphocyte ratio [systemic inflammation response index (SIRI)], lung function test, CT scans, and questionnaires were performed at baseline and routine follow-ups. Clinical characteristics and information of exacerbations were collected every 6 months. The relationship between hemogram indexes and diverse degrees of exacerbation was assessed by logistic regression. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the ability of hemogram indexes to predict exacerbation of COPD. Furthermore, the discrimination and accuracy of combined indexes were measured by ROC and calibration curve. Result: There was a significant positive correlation between PLR levels and total exacerbation of COPD patients in a stable stage in a year. Also, the predictive ability of PLR exceeded any other ratio indexes, with an AUC of 0.66. SII and SIRI ranked second only to PLR, with an AUC of 0.64. When combining PLR with other indexes (sex, COPD year, and St. George's Respiratory Questionnaire scores), they were considered as the most suitable panel of index to predict total exacerbation. Based on the result of the ROC curve and calibration curve, the combination shows optimal discrimination and accuracy to predict exacerbation events in COPD patients. Conclusion: The hemogram indexes PLR, SII, and SIRI were associated with COPD exacerbation. Moreover, the prediction capacity of exacerbation was significantly elevated after combining inflammatory hemogram index PLR with other indexes, which will make it a promisingly simple and effective marker to predict exacerbation in patients with stable COPD.

Biomarkers for Point-of-Care Diagnosis of Sepsis

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. In 2017, almost 50 million cases of sepsis were recorded worldwide and 11 million sepsis-related deaths were reported. Therefore, sepsis is the focus of intense research to better understand the complexities of sepsis response, particularly the twin underlying concepts of an initial hyper-immune response and a counter-immunological state of immunosuppression triggered by an invading pathogen. Diagnosis of sepsis remains a significant challenge. Prompt diagnosis is essential so that treatment can be instigated as early as possible to ensure the best outcome, as delay in treatment is associated with higher mortality. In order to address this diagnostic problem, use of a panel of biomarkers has been proposed as, due to the complexity of the sepsis response, no single marker is sufficient. This review provides background on the current understanding of sepsis in terms of its epidemiology, the evolution of the definition of sepsis, pathobiology and diagnosis and management. Candidate biomarkers of interest and how current and developing point-of-care testing approaches could be used to measure such biomarkers is discussed.