α1-Acid glycoprotein for the early diagnosis of neonatal sepsis

Establishment of a differential diagnosis method and an online prediction platform for AOSD and sepsis based on gradient boosting decision trees algorithm

OBJECTIVE

The differential diagnosis between adult-onset Still's disease (AOSD) and sepsis has always been a challenge. In this study, a machine learning model for differential diagnosis of AOSD and sepsis was developed and an online platform was developed to facilitate the clinical application of the model.

METHODS

All data were collected from 42 AOSD patients and 50 sepsis patients admitted to Affiliated Hospital of Xuzhou Medical University from December 2018 to December 2021. In addition, 5 AOSD patients and 10 sepsis patients diagnosed in our hospital after March 2022 were collected for external validation. All models were built using the scikit-learn library (version 1.0.2) in Python (version 3.9.7), and feature selection was performed using the SHAP (Shapley Additive exPlanation) package developed in Python.

RESULTS

The results showed that the gradient boosting decision tree(GBDT) optimization model based on arthralgia, ferritin × lymphocyte count, white blood cell count, ferritin × platelet count, and α1-acid glycoprotein/creatine kinase could well identify AOSD and sepsis. The training set interaction test (AUC: 0.9916, ACC: 0.9457, Sens: 0.9556, Spec: 0.9578) and the external validation also achieved satisfactory results (AUC: 0.9800, ACC: 0.9333, Sens: 0.8000, Spec: 1.000). We named this discrimination method AIADSS (AI-assisted discrimination of Still's disease and Sepsis) and created an online service platform for practical operation, the website is http://cppdd.cn/STILL1/ .

CONCLUSION

We created a method for the identification of AOSD and sepsis based on machine learning. This method can provide a reference for clinicians to formulate the next diagnosis and treatment plan.

Ways to Improve Insights into Clindamycin Pharmacology and Pharmacokinetics Tailored to Practice

Given the increase in bacterial resistance and the decrease in the development of new antibiotics, the appropriate use of old antimicrobials has become even more compulsory. Clindamycin is a lincosamide antibiotic approved for adults and children as a drug of choice for systemic treatment of staphylococcal, streptococcal, and gram-positive anaerobic bacterial infections. Because of its profile and high bioavailability, it is commonly used as part of an oral multimodal alternative for prolonged parenteral antibiotic regimens, e.g., to treat bone and joint or prosthesis-related infections. Clindamycin is also frequently used for (surgical) prophylaxis in the event of beta-lactam allergy. Special populations (pediatrics, pregnant women) have altered cytochrome P450 (CYP)3A4 activity. As clindamycin is metabolized by the CYP3A4/5 enzymes to bioactive N-demethyl and sulfoxide metabolites, knowledge of the potential relevance of the drug’s metabolites and disposition in special populations is of interest. Furthermore, drug–drug interactions derived from CYP3A4 inducers and inhibitors, and the data on the impact of the disease state on the CYP system, are still limited. This narrative review provides a detailed survey of the currently available literature on pharmacology and pharmacokinetics and identifies knowledge gaps (special patient population, drug–drug, and drug–disease interactions) to describe a research strategy for precision medicine.

Effect of nanocellulose polymorphism on electrochemical analytical performance in hybrid nanocomposites with non-oxidized single-walled carbon nanotubes

Two cellulose nanocrystals/single-walled carbon nanotube (CNC/SW) hybrids, using two cellulose polymorphs, were evaluated as electrochemical transducers: CNC type I (CNC-I/SW) and CNC type II (CNC-II/SW). They were synthesized and fully characterized, and their analytical performance as electrochemical sensors was carefully studied. In comparison with SWCNT-based and screen-printed carbon electrodes, CNC/SW sensors showed superior electroanalytical performance in terms of sensitivity and selectivity, not only in the detection of small metabolites (uric acid, dopamine, and tyrosine) but also in the detection of complex glycoproteins (alpha-1-acid glycoprotein (AGP)). More importantly, CNC-II/SW exhibited 20 times higher sensitivity than CNC-I/SW for AGP determination, yielding a LOD of 7 mg L^-1.These results demonstrate the critical role played by nanocellulose polymorphism in the electrochemical performance of CNC/SW hybrid materials, opening new directions in the electrochemical sensing of these complex molecules. In general, these high-active-surface hybrids smartly exploited the preserved non-oxidized SW conductivity with the high aqueous dispersibility of the CNC, avoiding the use of organic solvents or the incorporation of toxic surfactants during their processing, making the CNC/SW hybrids promising nanomaterials for electrochemical detection following greener approaches.

Investigation of salivary C-reactive protein and interleukin-18 for the diagnosis of neonatal sepsis

BACKGROUND

Neonatal sepsis is a leading cause of death in neonates worldwide. The investigation of biomarkers for the early diagnosis of neonatal sepsis is in progress with controversial outcomes. The current report aims to evaluate the values of salivary C-reactive protein (CRP) and interleukin-18 (IL-18) for the diagnosis of neonatal sepsis.

MATERIALS AND METHODS

In this cross-sectional study, 89 neonates, including 49 neonatal septic case and 40 healthy group admitted at the neonatal intensive care unit, were evaluated. The salivary samples of IL-18 and CRP were measured before the antibiotic therapy initiation, as soon as blood samplings. Sepsis diagnosis was confirmed by the positive blood culture. The diagnostic values of the biomarkers were determined using the receiver operating characteristic curve (ROC curve) analysis. Besides, the sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV) positive likelihood ratio (LR+), negative likelihood ratio (LR-), and diagnostic accuracy were measured.

RESULTS

Salivary CRP level was remarkably higher in septic case than healthy group (5.2 ± 4.61 vs. 3.5 ± 1.7; P = 0.02), while salivary IL-18 was not different between the groups (0.1 ± 0.29 vs. 0.04 ± 0.19; P = 0.25). The ROC curve for IL-18 showed insignificant values (P = 0.37). The ROC curve of salivary CRP showed area under the curve of 0.63 (95% confidence interval: 0.51-0.74; P = 0.03) with the sensitivity, specificity, PPV, NPV, LR+, LR - and diagnostic accuracy of 44.9% (31.8-58.7), 80% (65.2-89.5), 73.3% (55.5-85.82), 54.2% (41.6-66.3), 60.6% (50.29-70.18), 2.24 (1.57-3.2), and 0.68 (0.63-0.75) at the cutoff of 4.55 ng/L, respectively.

CONCLUSION

Based on the findings of the current study, salivary CRP can be considered a biomarker for the early diagnosis of neonatal sepsis, while no statistical values for salivary IL-18 were detected. Due to the significance of neonatal sepsis, further evaluations are strongly recommended.

Evidence of both foetal inflammation and hypoxia-ischaemia is associated with meconium aspiration syndrome

Foetal hypoxia–ischaemia is a key trigger of meconium aspiration syndrome (MAS). However, many neonates develop MAS without evidence of hypoxia–ischaemia, suggesting the presence of covert but important risk variables. We evaluated the association of MAS with clinical variables, placental histopathologic findings, and inflammatory biomarkers at birth. Of 1336 symptomatic and asymptomatic term singleton neonates with meconium-stained amniotic fluid, 88 neonates (6.6%) developed MAS. Univariate analysis showed that MAS development was associated with low 1- and 5-min Apgar scores, low cord blood pH, funisitis, higher α₁-acid glycoprotein levels, and higher haptoglobin levels (all p < 0.001 except for p = 0.001 for haptoglobin). Associations of MAS with caesarean delivery (p = 0.004), premature rupture of the membranes (p = 0.006), chorioamnionitis (p = 0.007), and higher C-reactive protein levels (p = 0.008) were lost when adjusted for multiple comparisons. The final multivariate model to explain MAS development comprised lower cord blood pH (odds ratio [OR] 0.58; 95% confidence interval [CI] 0.47–0.73; p < 0.001), funisitis (OR 2.45; 95% Cl 1.41–4.26; p = 0.002), and higher α₁-acid glycoprotein levels (OR 1.02; 95% Cl 1.01–1.03; p = 0.001). Our data from a large cohort of neonates suggested that intrauterine inflammation is one of the key independent variables of MAS development, together with foetal hypoxia–ischaemia.

Biomarkers for diagnosis of neonatal sepsis: a literature review

Sepsis is an important cause of mortality and morbidity in neonatal populations. There has been constant search of an ideal sepsis biomarker that have high sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), so that both the diagnosis and exclusion of neonatal sepsis can be made at the earliest possible and appropriate antibiotics can be started to neonate. Ideal sepsis biomarker will help in guiding us when not to start antibiotics in case of suspect sepsis and total duration of antibiotics course in case of proven sepsis. There are numerous sepsis biomarkers that have been evaluated for early detection of neonatal sepsis but till date there is no single ideal biomarker that fulfills all essential criteria's for being an ideal biomarker. The most commonly used biomarkers are C-reactive protein (CRP) and procalcitonin (PCT), but both have shown varied sensitivity, specificity, PPV and NPV in different studies. We conducted literature search for various neonatal sepsis biomarkers and this review article will cover briefly all the markers with current available evidence.

Early diagnosis of sepsis using serum biomarkers

Sepsis, an innate immunological response of systemic inflammation to infection, is a growing problem worldwide with a relatively high mortality rate. Immediate treatment is required, necessitating quick, early and accurate diagnosis. Rapid molecular-based tests have been developed to address this need, but still suffer some disadvantages. The most commonly studied biomarkers of sepsis are reviewed for their current uses and diagnostic accuracies, including C-reactive protein, procalcitonin, serum amyloid A, mannan and IFN-γ-inducible protein 10, as well as other potentially useful biomarkers. A singular ideal biomarker has not yet been identified; an alternative approach is to shift research focus to determine the diagnostic relevancy of multiple biomarkers when used in concert. Challenges facing biomarker research, including lack of methodology standardization and assays with better detection limits, are discussed. The ongoing efforts in the development of a multiplex point-of-care testing kit, enabling quick and reliable detection of serum biomarkers, may have great potential for early diagnosis of sepsis.