METHODS: Patient data was obtained retrospectively through the Ministry of Health, Malaysia, from 2011 to 2016. Patients with incomplete data were excluded. A total of 2044 clinical P. vivax malaria cases treated with primaquine were included. Data collected were patient, disease, and treatment characteristics. Two-thirds of the cases (n = 1362) were used to develop a clinical risk score, while the remaining third (n = 682) was used for validation.
RESULTS: Using multivariate analysis, age (p = 0.03), gametocyte sexual count (p = 0.04), indigenous transmission (p = 0.04), type of treatment (p = 0.12), and incomplete primaquine treatment (p = 0.14) were found to be predictors of recurrence after controlling for other confounding factors; these predictors were then used in developing the final model. The beta-coefficient values were used to develop a clinical scoring tool to predict possible recurrence. The total scores ranged between 0 and 8. A higher score indicated a higher risk for recurrence (odds ratio [OR]: 1.971; 95% confidence interval [CI]: 1.562-2.487; p ≤ 0.001). The area under the receiver operating characteristic (ROC) curve of the developed (n = 1362) and validated model (n = 682) was of good accuracy (ROC: 0.728, 95% CI: 0.670-0.785, p value area under the ROC curves showed no significant difference in predicting recurrence based on the constructed scoring mechanism (p = 0.399; Z-value: -0.8441; standard error: 0.045).
CONCLUSIONS: The developed model to predict recurrence was found to be of good accuracy and could be a useful tool in targeting patients at a higher risk for recurrence for closer monitoring during follow-up, after treatment with primaquine.
Methods: Six osteoporosis risk assessments tools (the Simple Calculated Osteoporosis Risk Estimation [SCORE], the Osteoporosis Risk Assessment Instrument, the Age Bulk One or Never Estrogen, the body weight, the Malaysian Osteoporosis Screening Tool, and the Osteoporosis Self-Assessment Tool for Asians) were used to screen postmenopausal women who had not been previously diagnosed with osteoporosis/osteopenia. These women also underwent a dual-energy X-ray absorptiometry (DXA) scan to confirm the absence or presence of osteoporosis.
Results: A total of 164/224 participants were recruited (response rate, 73.2%), of which only 150/164 (91.5%) completed their DXA scan. Sixteen participants (10.7%) were found to have osteoporosis, whilst 65/150 (43.3%) were found to have osteopenia. Using precision-recall curves, the recall of the tools ranged from 0.50 to 1.00, whilst precision ranged from 0.04 to 0.14. The area under the curve (AUC) ranged from 0.027 to 0.161. The SCORE had the best balance between recall (1.00), precision (0.04-0.12), and AUC (0.072-0.161).
Conclusions: We found that the SCORE had the best balance between recall, precision, and AUC among the 6 screening tools that were compared among Malaysian postmenopausal women.
METHODS: The derivation cohort included 90 Malaysian GBS patients with two sets of NCS performed early (1-20days) and late (3-8 weeks). Potential predictors of AIDP were considered in univariate and multivariate logistic regression models to develop a predictive model. The model was externally validated in 102 Japanese GBS patients.
RESULTS: Median motor conduction velocity (MCV), ulnar distal motor latency (DML) and abnormal ulnar/normal sural pattern were independently associated with AIDP at both timepoints (median MCV: p = 0.038, p = 0.014; ulnar DML: p = 0.002, p = 0.003; sural sparing: p = 0.033, p = 0.009). There was good discrimination of AIDP (area under the curve (AUC) 0.86-0.89) and this was valid in the validation cohort (AUC 0.74-0.94). Scores ranged from 0 to 6, and corresponded to AIDP probabilities of 15-98% at early NCS and 6-100% at late NCS.
CONCLUSION: The probabilities of AIDP could be reliably predicted based on median MCV, ulnar DML and ulnar/sural sparing pattern that were determined at early and late stages of GBS.
SIGNIFICANCE: A simple and valid model was developed which can accurately predict the probability of AIDP.
METHODS: Using the recently completed genome sequences from P. malariae, P. ovale and P. knowlesi, a set of 33 candidate cell surface and secreted blood-stage antigens was selected and expressed in a recombinant form using a mammalian expression system. These proteins were added to an existing panel of antigens from P. falciparum and P. vivax and the immunoreactivity of IgG, IgM and IgA immunoglobulins from individuals diagnosed with infections to each of the five different Plasmodium species was evaluated by ELISA. Logistic regression modelling was used to quantify the ability of the responses to determine prior exposure to the different Plasmodium species.
RESULTS: Using sera from European travellers with diagnosed Plasmodium infections, antigens showing species-specific immunoreactivity were identified to select a panel of 22 proteins from five Plasmodium species for serological profiling. The immunoreactivity to the antigens in the panel of sera taken from travellers and individuals living in malaria-endemic regions with diagnosed infections showed moderate power to predict infections by each species, including P. ovale, P. malariae and P. knowlesi. Using a larger set of patient samples and logistic regression modelling it was shown that exposure to P. knowlesi could be accurately detected (AUC = 91%) using an antigen panel consisting of the P. knowlesi orthologues of MSP10, P12 and P38.
CONCLUSIONS: Using the recent availability of genome sequences to all human-infective Plasmodium spp. parasites and a method of expressing Plasmodium proteins in a secreted functional form, an antigen panel has been compiled that will be useful to determine exposure to these parasites.
METHODS: Data from a retrospective review of 13-year S.suis patient records in a tertiary hospital in Chiang Mai, Northern, Thailand was obtained. Univariate and multivariate logistic regressions were employed to develop a predictive model. The clinical risk score was constructed from the coefficients of significant predictors. Area under the receiver operator characteristic curve (AuROC) was identified to verify the model discriminative performance. Bootstrap technique with 1000-fold bootstrapping was used for internal validation.
KEY RESULTS: Among 133 patients, the incidence of hearing loss was 31.6% (n = 42). Significant predictors for S. suis hearing loss were meningitis, raw pork consumption, and vertigo. The predictive score ranged from 0-4 and correctly classified 81.95% patients as being at risk of S.suis hearing loss. The model showed good power of prediction (AuROC: 0.859; 95%CI 0.785-0.933) and calibration (AuROC: 0.860; 95%CI 0.716-0.953).
CONCLUSIONS: To our best knowledge, this is the first risk scoring system development for S.suis hearing loss. We identified meningitis, raw pork consumption and vertigo as the main risk factors of S.suis hearing loss. Future studies are needed to optimize the developed scoring system and investigate its external validity before recommendation for use in clinical practice.
METHODS: We measured 20 plasma markers i.e. IFN-γ, IL-10, granzyme-B, CX3CL1, IP-10, RANTES, CXCL8, CXCL6, VCAM, ICAM, VEGF, HGF, sCD25, IL-18, LBP, sCD14, sCD163, MIF, MCP-1 and MIP-1β in 141 dengue patients in over 230 specimens and correlate the levels of these plasma markers with the development of dengue without warning signs (DWS-), dengue with warning signs (DWS+) and severe dengue (SD).
RESULTS: Our results show that the elevation of plasma levels of IL-18 at both febrile and defervescence phase was significantly associated with DWS+ and SD; whilst increase of sCD14 and LBP at febrile phase were associated with severity of dengue disease. By using receiver operating characteristic (ROC) analysis, the IL-18, LBP and sCD14 were significantly predicted the development of more severe form of dengue disease (DWS+/SD) (AUC = 0.768, P
Methods: A cross-sectional study on 50 patients of age 50 and above with contrast-enhanced CT (CECT) and dual-energy X-ray absorptiometry (DXA) was conducted from November 2018 to November 2019. Single region of interest (ROI) was placed at the anterior trabecular part of L1 vertebra on CECT to obtain HU value. Correlation of CT HU value of L1 vertebra and DXA T-score, interrater reliability agreement between HU value of L1 vertebra and T-score in determining groups of with and without osteoporosis, ROC curve analysis for diagnostic accuracy and cut-off value of CT for detection of osteoporosis were identified.
Results: Significant correlation between HU value of L1 vertebra and L1 T-score (r = 0.683)/lowest skeletal T-score (r = 0.703) (P < 0.001). Substantial agreement between HU value of L1 vertebra and DXA in determining the groups with and without osteoporosis (k = 0.8; P < 0.001). The area under the receiver operating characteristic (AUROC) curve was 0.93 (95% CI: 0.86, 1.00) using HU value (P < 0.001). Cut-off value for osteoporosis was 149 HU.
Conclusion: HU value of lumbar vertebra is an effective alternative for the detection of osteoporosis with high diagnostic accuracy in hospitals without DXA facility.
MATERIALS AND METHODS: Atrial arrhythmogenesis was investigated in Langendorff-perfused young (3-4 month) and aged (>12 month), wild type (WT) and peroxisome proliferator activated receptor-γ coactivator-1β deficient (Pgc-1β-/-) murine hearts modeling age-dependent chronic mitochondrial dysfunction during regular pacing and programmed electrical stimulation (PES).
RESULTS AND DISCUSSION: The Pgc-1β-/- genotype was associated with a pro-arrhythmic phenotype progressing with age. Young and aged Pgc-1β-/- hearts showed compromised maximum action potential (AP) depolarization rates, (dV/dt)max, prolonged AP latencies reflecting slowed action potential (AP) conduction, similar effective refractory periods and baseline action potential durations (APD90) but shortened APD90 in APs in response to extrasystolic stimuli at short stimulation intervals. Electrical properties of APs triggering arrhythmia were similar in WT and Pgc-1β-/- hearts. Pgc-1β-/- hearts showed accelerated age-dependent fibrotic change relative to WT, with young Pgc-1β-/- hearts displaying similar fibrotic change as aged WT, and aged Pgc-1β-/- hearts the greatest fibrotic change. Mitochondrial deficits thus result in an arrhythmic substrate, through slowed AP conduction and altered repolarisation characteristics, arising from alterations in electrophysiological properties and accelerated structural change.
METHOD: In this work, resting-state EEG-derived features were utilized as input data to the proposed feature selection and classification method. The aim was to perform automatic classification of AUD patients and healthy controls. The validation of the proposed method involved real-EEG data acquired from 30 AUD patients and 30 age-matched healthy controls. The resting-state EEG-derived features such as synchronization likelihood (SL) were computed involving 19 scalp locations resulted into 513 features. Furthermore, the features were rank-ordered to select the most discriminant features involving a rank-based feature selection method according to a criterion, i.e., receiver operating characteristics (ROC). Consequently, a reduced set of most discriminant features was identified and utilized further during classification of AUD patients and healthy controls. In this study, three different classification models such as Support Vector Machine (SVM), Naïve Bayesian (NB), and Logistic Regression (LR) were used.
RESULTS: The study resulted into SVM classification accuracy=98%, sensitivity=99.9%, specificity=95%, and f-measure=0.97; LR classification accuracy=91.7%, sensitivity=86.66%, specificity=96.6%, and f-measure=0.90; NB classification accuracy=93.6%, sensitivity=100%, specificity=87.9%, and f-measure=0.95.
CONCLUSION: The SL features could be utilized as objective markers to screen the AUD patients and healthy controls.
Methods: We evaluated commonly used surrogate and imputed baseline creatinine values against a "reference" creatinine measured during follow-up in an adult clinical trial cohort. Known AKI incidence (Kidney Disease: Improving Global Outcomes [KDIGO] criteria) was compared with AKI incidence classified by (1) back-calculation using the Modification of Diet in Renal Disease (MDRD) equation with and without a Chinese ethnicity correction coefficient; (2) back-calculation using the Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) equation; (3) assigning glomerular filtration rate (GFR) from age and sex-standardized reference tables; and (4) lowest measured creatinine during admission. Back-calculated distributions were performed using GFRs of 75 and 100 ml/min.
Results: All equations using an assumed GFR of 75 ml/min underestimated AKI incidence by more than 50%. Back-calculation with CKD-EPI and GFR of 100 ml/min most accurately predicted AKI but misclassified all AKI stages and had low levels of agreement with true AKI diagnoses. Back-calculation using MDRD and assumed GFR of 100 ml/min, age and sex-reference GFR values adjusted for good health, and lowest creatinine during admission performed similarly, best predicting AKI incidence (area under the receiver operating characteristic curves [AUC ROCs] of 0.85, 0.87, and 0.85, respectively). MDRD back-calculation using a cohort mean GFR showed low total error (22%) and an AUC ROC of 0.85.
Conclusion: Current methods for estimating baseline creatinine are large sources of potential error in acute infection studies. Preferred alternatives include MDRD equation back-calculation with a population mean GFR, age- and sex-specific GFR values corrected for "good health," or lowest measured creatinine. Studies using surrogate baseline creatinine values should report specific methodology.
Materials and methods: QOS collagen nanofibers were electrospun by incorporating various concentrations of QOS (0.1%-10% w/w) and were cross-linked in situ after exposure to ammonium carbonate. The QOS cross-linked scaffolds were characterized and their biological properties were evaluated in terms of their biocompatibility, cellular adhesion and metabolic activity for primary human dermal fibroblasts and human fetal osteoblasts.
Results and discussion: The study revealed that 1) QOS cross-linking increased the flexibility of otherwise rigid collagen nanofibers and improved the thermal stability; 2) QOS cross-linked mats displayed potent antibacterial activity and 3) the biocompatibility of the composite mats depended on the amount of QOS present in dope solution - at low QOS concentrations (0.1% w/w), the mats promoted mammalian cell proliferation and growth, whereas at higher QOS concentrations, cytotoxic effect was observed.
Conclusion: This study demonstrates that QOS cross-linked mats possess anti-infective properties and confer niches for cellular growth and proliferation, thus offering a useful approach, which is important for hard and soft tissue engineering and regenerative medicine.
METHODS: We did an individual patient data meta-analysis, in which we searched PubMed and Web of Science for studies published from database inception until April 30, 2019. Studies reporting original biopsy-controlled data of CAP for non-invasive grading of steatosis were eligible. Probe recommendation was based on automated selection, manual assessment of skin-to-liver-capsule distance, and a body-mass index (BMI) criterion. Receiver operating characteristic methods and mixed models were used to assess diagnostic properties and covariates. Patients with non-alcoholic fatty liver disease (NAFLD) were analysed separately because they are the predominant patient group when using the XL probe. This study is registered with PROSPERO, CRD42018099284.
FINDINGS: 16 studies reported histology-controlled CAP including the XL probe, and individual data from 13 papers and 2346 patients were included. Patients with a mean age of 46·5 years (SD 14·5) were recruited from 20 centres in nine countries. 2283 patients had data for BMI; 673 (29%) were normal weight (BMI <25 kg/m2), 530 (23%) were overweight (BMI ≥25 to <30 kg/m2), and 1080 (47%) were obese (BMI ≥30 kg/m2). 1277 (54%) patients had NAFLD, 474 (20%) had viral hepatitis, 285 (12%) had alcohol-associated liver disease, and 310 (13%) had other liver disease aetiologies. The XL probe was recommended in 1050 patients, 930 (89%) of whom had NAFLD; among the patients with NAFLD, the areas under the curve were 0·819 (95% CI 0·769-0·869) for S0 versus S1 to S3 and 0·754 (0·720-0·787) for S0 to S1 versus S2 to S3. CAP values were independently affected by aetiology, diabetes, BMI, aspartate aminotransferase, and sex. Optimal cutoffs differed substantially across aetiologies. Risk of bias according to QUADAS-2 was low.
INTERPRETATION: CAP cutoffs varied according to cause, and can effectively recognise significant steatosis in patients with viral hepatitis. CAP cannot grade steatosis in patients with NAFLD adequately, but its value in a NAFLD screening setting needs to be studied, ideally with methods beyond the traditional histological reference standard.
FUNDING: The German Federal Ministry of Education and Research and Echosens.
METHODS: A total of 28 critically ill patients were included in this study. All data were collected from medical, microbiology and pharmacokinetic records. The clinical response was evaluated on the basis of clinical and microbiological parameters. The 24-h area under the curve (AUC0-24) was estimated from a single trough level using established equations.
RESULTS: Out of the 28 patients, 46% were classified as responders to vancomycin treatment. The trough vancomycin concentration did not differ between the responders and non-responders (15.02 ± 6.16 and 14.83 ± 4.80 μg mL-1; P = 0.929). High vancomycin minimum inhibitory concentration (MIC) was observed among the non-responders (P = 0.007). The ratio between vancomycin trough concentration and vancomycin MIC was significantly lower in the non-responder group (8.76 ± 3.43 vs. 12.29 ± 4.85 μg mL-1; P = 0.034). The mean ratio of estimated AUC0-24 and vancomycin MIC was 313.78 ± 117.17 μg h mL-1 in the non-responder group and 464.44 ± 139.06 μg h mL-1 in the responder group (P = 0.004). AUC0-24/MIC of ≥ 400 μg h mL-1 was documented for 77% of the responders and 27% of the non-responders (c2 = 7.03; P = 0.008).
CONCLUSIONS: Ratio of trough concentration/MIC and AUC0-24/MIC of vancomycin are better predictors for MRSA treatment outcomes than trough vancomycin concentration or AUC0-24 alone. The single trough-based estimated AUC may be sufficient for the monitoring of treatment response with vancomycin.