METHODS: Clinico-pathological data from a previously treated cohort of 590 newly presenting PMD patients were reviewed and clinical outcomes categorized as disease free, persistent PMD or MT. Multiple logistic regression was used to predict the probability of MT in the cohort using age, gender, lesion type, site and incision biopsy histopathological diagnoses. Internal validation and calibration of the model was performed using the bootstrap method (n = 1000), and bias-corrected indices of model performance were computed.
RESULTS: Potentially malignant disorders were predominantly leukoplakias (79%), presenting most frequently at floor of mouth and lateral tongue sites (51%); 99 patients (17%) developed oral squamous cell carcinoma during the study period. The nomogram performed well when MT predictions were compared with patient outcome data, demonstrating good bias-corrected discrimination and calibration (Dxy = 0.58; C = 0.790), with a sensitivity of 87% and specificity 63%, and a positive predictive value of 32% and negative predictive value 96%.
CONCLUSION: The "Newcastle Nomogram" has been developed to predict the probability of MT in PMD, based on an internally validated statistical model. Based upon readily available and patient-specific clinico-pathological data, it provides clinicians with a pragmatic diagrammatic aid for clinical decision-making during diagnosis and management of PMD.
METHOD: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features.
RESULTS: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively.
CONCLUSIONS: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients.
METHODS: Scientific literature was thoroughly searched to find 1) DKA treatment guidelines, 2) studies reporting hypokalemia in DKA, 3) and literature elaborating mechanisms involved in hypokalemia.
RESULTS: Acidosis affects SK and its regulators including insulin, catecholamines and aldosterone. Current conceptual framework is an argument to gauge the degree of hypokalemia before it strikes DKA patients utilizing SK level after adjusting it with pH. Suggested approach will reduce hypokalemia risk and its associated complications. The nomogram calculates pH-adjusted potassium and expected potassium loss. It also ranks hypokalemia associated risk, and proposes the potassium-replacement rate over given time period. The differences between current DKA treatment guidelines and proposed strategy are also discussed. Moreover, reasons and risk of hyperkalemia due to early initiation of potassium replacement and remedial actions are debated.
CONCLUSION: In light of proposed strategy, utilizing the nomogram ensures reduced incidence of hypokalemia in DKA resulting in improved clinical and patient outcomes. Pharmacoeconomic benefits can also be expected when avoiding hypokalemia ensures early discharge.
PURPOSE: The purpose of this study is twofold. First, it aimed to measure the renal length and calculate the renal volume of normal Thai children using 2-dimensional ultrasonography (2D-US) and study their correlations with somatic parameters. Second, it aimed to compare the age-specific renal size of normal Thai children with the published data of their Western and Chinese counterparts.
METHODS: A total of 321 children (150 boys, 171 girls; age, 6-15 years) with a normal renal profile were prospectively recruited. All subjects underwent 2D-US by an experienced pediatric radiologist and the renal length, width, and depth were measured. Renal volume was calculated using the ellipsoid formula as recommended. The data were compared between the left and right kidneys, the sexes, and various somatic parameters. The age-specific renal lengths were compared using a nomogram derived from a Western cohort that is currently referred by many Thailand hospitals, while the renal volumes were compared with the published data of a Chinese cohort.
RESULTS: No statistically significant difference (P<0.05) was found between sexes or the right and left kidneys. The renal sizes had strong correlations with height, weight, body surface area, and age but not with body mass index. The renal length of the Thai children was moderately correlated (r=0.59) with that of the Western cohort, while the age-specific renal volume was significantly smaller (P<0.05) than that of the Chinese children.
CONCLUSION: Therefore, we concluded that the age-specific renal length and volume obtained by 2D-US would vary between children in different regions and may not be suitably used as an international standard for diagnosis, although further studies may be needed to confirm our findings.
METHODS: A total of 109 (64 males and 45 females) aged 0-12 in Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) took part in this study. They underwent ultrasonography of both kidneys, and their demographic and anthropometric data were collected. The mean and standard deviations of the renal length and renal volume according to their age groups was calculated, and the final data was compared to the ones reported by Rosenbaum et al. (1984).
RESULT: Body weight and Body Surface Area (BSA) of the children reported the strongest correlation with renal size. Significant differences were found between local and the data from Rosenbaum et al (1984). A nomogram on paediatric renal size based on children in PPUKM was then created.
DISCUSSION: Ultrasonography is regarded as the standard method for determining renal size. Body weight and BSA were both strongly correlated with renal size. It was shown that the widely used nomograms derived from data obtained from Caucasian was not suitable to represent the population of Malaysian children.
METHODS: Six hundred and thirty-six adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from two independent Asian cohorts were enrolled in our study. Liver stiffness measurement (LSM) was assessed by vibration-controlled transient elastography (Fibroscan). Fibrotic NASH was defined as NASH with a NAFLD activity score (NAS) ≥ 4 and F ≥ 2 fibrosis.
RESULTS: Metabolic syndrome (MetS), platelet count and MACK-3 were independent predictors of fibrotic NASH. On the basis of their regression coefficients, we developed a novel nomogram showing a good discriminatory ability (area under receiver operating characteristic curve [AUROC]: 0.79, 95% confidence interval [CI 0.75-0.83]) and a high negative predictive value (NPV: 94.7%) to rule out fibrotic NASH. In the validation set, this nomogram had a higher AUROC (0.81, 95%CI 0.74-0.87) than that of MACK-3 (AUROC: 0.75, 95%CI 0.68-0.82; P
PATIENTS AND METHODS: Data of 2360 patients from APASL-ACLF Research Consortium (AARC) was analysed. Multivariate logistic regression model (PIRO score) was developed from a derivation cohort (n=1363) which was validated in another prospective multicentric cohort of acute on chronic liver failure patients (n=997).
RESULTS: Factors significant for P component were serum creatinine[(≥2 mg/dL)OR 4.52, 95% CI (3.67-5.30)], bilirubin [(<12 mg/dL,OR 1) vs (12-30 mg/dL,OR 1.45, 95% 1.1-2.63) vs (≥30 mg/dL,OR 2.6, 95% CI 1.3-5.2)], serum potassium [(<3 mmol/LOR-1) vs (3-4.9 mmol/L,OR 2.7, 95% CI 1.05-1.97) vs (≥5 mmol/L,OR 4.34, 95% CI 1.67-11.3)] and blood urea (OR 3.73, 95% CI 2.5-5.5); for I component nephrotoxic medications (OR-9.86, 95% CI 3.2-30.8); for R component,Systemic Inflammatory Response Syndrome,(OR-2.14, 95% CI 1.4-3.3); for O component, Circulatory failure (OR-3.5, 95% CI 2.2-5.5). The PIRO score predicted acute kidney injury with C-index of 0.95 and 0.96 in the derivation and validation cohort. The increasing PIRO score was also associated with mortality (P