Preoperative cephalhematoma size measured with computed tomography predicts intraoperative bleeding in pediatric patients undergoing cranioplasty

Background: Cranioplasty for the treatment of cephalhematomas in small infants with limited blood volume is challenging because of massive bleeding. This study aimed to elucidate the correlation between cephalhematoma size and intraoperative blood loss and identify criteria that can predict large intraoperative blood loss.Methods: We reviewed the medical records of 120 pediatric patients aged less than 24 months who underwent cranioplasty for treatment of a cephalhematoma. The cephalhematoma sizes in preoperative brain computed tomography (CT) were measured using ImageJ. Results: Pearson correlation showed that the cephalhematoma size in the pre-operative brain CT was weakly correlated with intraoperative blood loss (Pearson coefficient = 0.192, P = 0.037). In a multivariable logistic regression analysis, a cephalhematoma size greater than 113.5 cm3 was found to be a risk factor for large blood loss. The area under the curve in the receiver operating characteristic plot of the multivariable model was 0.714 (0.619–0.809).Conclusions: A cephalhematoma size cutoff value of 113.5 cm3, as measured in the preoperative CT imaging, can predict intraoperative blood loss exceeding 30% of the total body blood volume. The establishment of a transfusion strategy prior to surgery based on cephalhematoma size could be useful in pediatric cranioplasty.

COMP (Cartilage Oligomeric Matrix Protein) Neoepitope

Objective: COMP (cartilage oligomeric matrix protein) is abundantly expressed in the cardiovascular system, cartilage, and atherosclerotic plaques. We investigated if the total COMP (COMPtotal) and COMP neoepitope (COMPneo) with other cardiovascular markers and clinical parameters could identify symptomatic carotid stenosis. Approach and Results: Blood samples were collected from patients with symptomatic carotid stenosis (stenosis, n=50), patients with stroke without carotid stenosis but small plaques (plaque, n=50), and control subjects (n=50). COMPtotal and COMPneo were measured using an ELISA. Ninety-two cardiovascular disease markers were measured by the Olink CVD kit. The presence of native COMP and COMPneo was determined by immunohistochemistry. The concentration of COMPneo was higher and COMPtotal was lower in the stenosis group. When the concentration was compared between the stenosis and control groups, IL-1ra (interleukin-1 receptor antagonist protein), IL6 (interleukin-6), REN (Renin), MMP1 (matrix metalloproteinase-1), TRAIL-R2 (tumor necrosis factor-related apoptosis-inducing ligand receptor 2), ITGB1BP2 (integrin beta 1 binding protein 2), and COMPneo were predictive of stenosis. Conversely, KLK6 (kallikrein-6), COMPtotal, NEMO (nuclear factor-kappa-B essential modulator), SRC (Proto-oncogene tyrosine-protein kinase Src), SIRT2 (SIR2-like protein), CD40 (cluster of differentiation 40), TF (tissue factor), MP (myoglobin), and RAGE (receptor for advanced glycation end-products) were predictive of the control group. Model reproducibility was good with the receiver operating characteristic plot area under the curve being 0.86. When comparing the plaque group and stenosis group, COMPneo, GAL (galanin), and PTX3 (pentraxin-related protein PTX3) were predictive of stenosis. Model reproducibility was excellent (receiver operating characteristic plot area under the curve 0.92). COMPneo was detected in smooth muscle-, endothelial-, and foam-cells in carotid stenosis. Conclusions: Degradation of COMP may be associated with atherosclerosis progression and generation of a specific COMP fragment—COMPneo. This may represent a novel biomarker that together with COMPtotal and other risk-markers could be used to identify symptomatic carotid stenosis. Graphic Abstract: A graphic abstract is available for this article.

Identification of Metabolic Biomarkers in Relation to Methotrexate Response in Early Rheumatoid Arthritis

This study aimed to identify baseline metabolic biomarkers for response to methotrexate (MTX) therapy in rheumatoid arthritis (RA) using an untargeted method. In total, 82 baseline plasma samples (41 insufficient responders and 41 sufficient responders to MTX) were selected from the Treatment in the Rotterdam Early Arthritis Cohort (tREACH, trial number: ISRCTN26791028) based on patients’ EULAR response at 3 months. Metabolites were assessed using high-performance liquid chromatography-quadrupole time of flight mass spectrometry. Differences in metabolite concentrations between insufficient and sufficient responders were assessed using partial least square regression discriminant analysis (PLS-DA) and Welch’s t-test. The predictive performance of the most significant findings was assessed in a receiver operating characteristic plot with area under the curve (AUC), sensitivity and specificity. Finally, overrepresentation analysis was performed to assess if the best discriminating metabolites were enriched in specific metabolic events. Baseline concentrations of homocystine, taurine, adenosine triphosphate, guanosine diphosphate and uric acid were significantly lower in plasma of insufficient responders versus sufficient responders, while glycolytic intermediates 1,3-/2,3-diphosphoglyceric acid, glycerol-3-phosphate and phosphoenolpyruvate were significantly higher in insufficient responders. Homocystine, glycerol-3-phosphate and 1,3-/2,3-diphosphoglyceric acid were independent predictors and together showed a high AUC of 0.81 (95% CI: 0.72–0.91) for the prediction of insufficient response, with corresponding sensitivity of 0.78 and specificity of 0.76. The Warburg effect, glycolysis and amino acid metabolism were identified as underlying metabolic events playing a role in clinical response to MTX in early RA. New metabolites and potential underlying metabolic events correlating with MTX response in early RA were identified, which warrant validation in external cohorts.

Predicting Preeclampsia with Noninvasive Measures of Endothelial Dysfunction: A Pilot Study

Objective This study evaluates the assessment of endothelial function and its prediction for preeclampsia among women with high-risk factors. Study Design A prospective cohort study of 107 pregnant women at 20 weeks or greater gestation with risk factors for developing preeclampsia. Endothelial dysfunction was assessed using peripheral arterial tonometry by generating a reactive hyperemia index (RHI) score. An index score of <1.67 was defined as endothelial dysfunction. The primary outcome was preeclampsia. Logistic regression was used to predict preeclampsia from RHI scores, body mass index, gestational age at RHI evaluation, history of preeclampsia, history of pregestational diabetes mellitus, chronic hypertension, and fetal number. A receiver operating characteristic plot was constructed to predict preeclampsia from the RHI score. Results Among 107 women, 99 had interpretable RHI scores. Among those with an abnormal RHI (n = 61), 17 (28%) developed preeclampsia. Among women with a normal score (n = 38), six (16%) developed preeclampsia (p = 0.166). After logistic regression, there was no significant association. A receiver operating characteristic plot also revealed no association between RHI score and preeclampsia. Conclusion An abnormal RHI score using peripheral arterial tonometry indicating endothelial dysfunction was not predictive of developing preeclampsia in this cohort. Future studies are needed to further evaluate this relationship.

Comparison of Intensive Care Outcome Prediction Models Based on Admission Scores With those Based on 24-Hour Data

We compared the performance of six outcome prediction models - three based on 24-hour data and three based on admission-only data - in a metropolitan university-affiliated teaching hospital with a 10-bed intensive care unit. The Acute Physiology and Chronic Health Evaluation models, version II (APACHE II) and version III-J, and the Simplified Acute Physiology Score version II (SAPS II) are based on 24-hour data and were compared with the Mortality Prediction Model version II and the SAPS version III using international and Australian coefficients (SAPS IIIA). Data were collected prospectively according to the standard methodologies for each model. Calibration and discrimination for each model were assessed by the standardised mortality ratio, area under the receiver operating characteristic plot and Hosmer-Lemeshow contingency tables and chi-squared statistics (C10 and H10). Predetermined criteria were area under the receiver operating characteristic plot >0.8, standardised mortality ratio 95% confidence interval includes 1.0, and C10 and H10 P values >0.05. Between October 1, 2005 and December 31, 2007, 1843 consecutive admissions were screened and after the standard exclusions, 1741 were included in the analysis. The SAAPS II and SAPS IIIA models fulfilled and the APACHE II model failed all criteria. The other models satisfied the discrimination criterion but significantly over-predicted mortality risk and require recalibration. Outcome prediction models based on admission-only data compared favourably to those based on 24-hour data.

Thyrotropin Receptor Autoantibodies Are Independent Risk Factors for Graves’ Ophthalmopathy and Help to Predict Severity and Outcome of the Disease

Objective: The objective of this study was to examine whether TSH-receptor antibody [TSH binding inhibitory antibodies (TBII)] levels are associated with the severity of Graves’ ophthalmopathy (GO) over the entire course of the disease. Methods and Patients: A total of 159 patients with GO were followed for 12–24 months. One year after the first symptoms of GO, all patients were classified into mild or severe GO according to their clinical manifestations. TBII were measured every 3 months after onset of GO. Receiver operating characteristic plot analysis was performed to assess the power to discriminate both patient groups by TBII (specificity &gt;90%). Results: TBII levels and prevalence at each time point during follow-up were significantly higher in patients with a severe course of GO compared with patients with a mild course of GO. Prognostic statements on the course of the disease were possible for about half of the GO patients at all time points (except the first). If at first presentation and at consecutive time points TBII levels were less than 5.7, 2.6, 1.5, 1.5, 1.5, and 1.5 IU/liter, the patients had a 2.3- to 15.6-fold higher chance of a mild course. If 5–8 months after GO onset and at consecutive time points TBII levels were above 8.8, 5.1, 4.8, 2.8, and 2.8 IU/liter, the patients had a 8.7- to 31.1-fold higher risk of a severe course. This relationship of TBII to the severity was independent from age and smoking. Conclusion: Follow-up measurements of TBII allow, in half of the patients, assessment of the prognosis of GO and, therefore, could be of additional help for the disease management.

Evaluation of a First-Line Spectrophotometric Screening Test for Increased Urine Porphyrin Excretion

We compared a spectrophotometric screening test for urine porphyrin concentration with a high performance liquid chromatography (HPLC) method. The screening test gave lower values than those obtained by HPLC, but the overall correlation was good. Occasionally, spectrophotometry failed to detect porphyrins in the urine which were detected by HPLC. The type of porphyria had no influence on the efficacy of the screening method. Receiver operating characteristic plot analysis of the screening test led to a cut-off value of 110 nmol/24 h with a sensitivity of 96% and a specificity of 86%. We conclude that the spectrophotometric screening method is useful for detection of increased total urine porphyrin concentration.