Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes

OBJECTIVE Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD) calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers and investigates its performance according to the age and pharmacological treatment. <p>RESEARCH DESIGN AND METHODS This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) employed three risk scores: a GRS, a validated clinical score and their combined score. Hazard ratios (HR) were calculated with Cox regression and model performances compared with Harrel’s C-index. </p> <p>RESULTS A HR of 6.7 for CAD was observed between the highest and the lowest 5^th percentile of the GRS (<i>P</i>=1.8×10^-6). The performance of GRS (C-index [C] 0.562) was similar to HbA_1c (C=0.563, <i>p</i>-value for difference 0.96), HDL (C=0.571, <i>P</i>=0.6) and total cholesterol (C=0.594, <i>P</i>=0.1). The GRS was not correlated with the clinical score (<i>r</i>=-0.013, <i>P</i>=0.5). The combined score outperformed the clinical score (C=0.813 vs C=0.820, <i>P</i>=0.003). The GRS performed better in individuals below the median age (38.6 years) compared to those above (C=0.637 vs C=0.546). </p> <p>CONCLUSIONS A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD with a predictive power comparable to that of HbA_1c, HDL and total cholesterol and, when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD. </p>

Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes

OBJECTIVE Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD) calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers and investigates its performance according to the age and pharmacological treatment. <p>RESEARCH DESIGN AND METHODS This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) employed three risk scores: a GRS, a validated clinical score and their combined score. Hazard ratios (HR) were calculated with Cox regression and model performances compared with Harrel’s C-index. </p> <p>RESULTS A HR of 6.7 for CAD was observed between the highest and the lowest 5^th percentile of the GRS (<i>P</i>=1.8×10^-6). The performance of GRS (C-index [C] 0.562) was similar to HbA_1c (C=0.563, <i>p</i>-value for difference 0.96), HDL (C=0.571, <i>P</i>=0.6) and total cholesterol (C=0.594, <i>P</i>=0.1). The GRS was not correlated with the clinical score (<i>r</i>=-0.013, <i>P</i>=0.5). The combined score outperformed the clinical score (C=0.813 vs C=0.820, <i>P</i>=0.003). The GRS performed better in individuals below the median age (38.6 years) compared to those above (C=0.637 vs C=0.546). </p> <p>CONCLUSIONS A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD with a predictive power comparable to that of HbA_1c, HDL and total cholesterol and, when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD. </p>

Genetic Risk Score Enhances Coronary Artery Disease Risk Prediction in Individuals With Type 1 Diabetes

OBJECTIVE Individuals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD), calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment. RESEARCH DESIGN AND METHODS This study in 3,295 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) used three risk scores: a GRS, a validated clinical score, and their combined score. Hazard ratios (HR) were calculated with Cox regression, and model performances were compared with the Harrell C-index (C-index). RESULTS A HR of 6.7 for CAD was observed between the highest and the lowest 5th percentile of the GRS (P = 1.8 × 10−6). The performance of GRS (C-index = 0.562) was similar to HbA1c (C-index = 0.563, P = 0.96 for difference), HDL (C-index = 0.571, P = 0.6), and total cholesterol (C-index = 0.594, P = 0.1). The GRS was not correlated with the clinical score (r = −0.013, P = 0.5). The combined score outperformed the clinical score (C-index = 0.813 vs. C-index = 0.820, P = 0.003). The GRS performed better in individuals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546). CONCLUSIONS A GRS identified individuals at high risk of CAD and worked better in younger individuals. GRS was also an independent risk factor for CAD, with a predictive power comparable to that of HbA1c and HDL and total cholesterol, and when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD.

Bronchiolitis diagnosis, treatment, and prevention in children: an evidence-based clinical practice guideline adapted for the use in Egypt based on the ‘Adapted ADAPTE’ Methodology

Background The presented evidence-based clinical practice guideline (CPG) is proposed as a National CPG using an evidence-based and formal CPG adaptation methodology. The purpose of this study was to adapt the international CPGs’ recommendations for children with bronchiolitis to suit the healthcare system in the Egyptian context. This CPG, ‘diagnosis, treatment, and prevention of Bronchiolitis’, applies to children from 1 through 23 months of age. Other exclusions are noted. The quality of evidence, benefit-harm relationship, and strength of recommendations are indicated. This study is part of a larger collaborative initiative with the faculty staff of pediatric departments of 15 Egyptian universities and a national research center to formulate a national Committee (EPG) that aims to define the topics of, assign authors to, and assist in the adaptation of pediatric evidence-based CPGs according to a national strategic plan. The committee is guided by a formal CPG adaptation methodology: the ‘Adapted ADAPTE’. Results The Bronchiolitis Guideline Adaptation Group (BGAG) reviewed the results of the AGREE II assessment and decided to adapt mainly the Australasian (PREDICT) CPG and for the questions not answered in PREDICT we adapted the relevant recommendations from the American Academy of Pediatrics (AAP) CPG. Seven implementation tools were included: a care pathway for assessment of severity, a clinical algorithm for treatment of acute bronchiolitis in the emergency room, a separate flowchart for assessing babies with bronchiolitis, a power point slide presentation lecture for treatment of acute bronchiolitis, patient information in Arabic, a clinical score (Modified Tal Score) for prediction of bronchiolitis severity, and the criteria for admission and discharge in the hospital. A comprehensive set of multifaceted CPG implementation strategies was provided for the clinicians, patients, nurses, and other relevant stakeholders contextualized to the national settings Conclusion Our experience with this adaptation methodology provides useful insight into its utilization on a national level in Egypt. The BGAG recommended the next review of this adapted CPG to be after 3 years from its publication (i.e., 2022) after checking for updates in the original CPG.

Vitronectin-derived bioactive peptide prevents spondyloarthritis by modulating Th17/Treg imbalance in mice with curdlan-induced spondyloarthritis

Purpose Spondyloarthritis (SpA) is a systemic inflammatory arthritis mediated mainly by interleukin (IL)-17. The vitronectin-derived bioactive peptide, VnP-16, exerts an anti-osteoporotic effect via β1 and αvβ3 integrin signaling. SpA is associated with an increased risk of osteoporosis, and we investigated the effect of VnP-16 in mice with SpA. Methods SpA was induced by curdlan in SKG ZAP-70W163C mice, which were treated with vehicle, celecoxib, VnP-16, or VnP-16+celecoxib. The clinical score, arthritis score, spondylitis score, and proinflammatory cytokine expression of the spine were evaluated by immunohistochemical staining. Type 17 helper T cell (Th17) and regulatory T cell (Treg) differentiation in the spleen was evaluated by flow cytometry and in the spine by confocal staining. Splenocyte expression of signal transducer and activator of transcription (STAT) 3 and pSTAT3 was evaluated by in vitro Western blotting. Results The clinical score was significantly reduced in the VnP16+celecoxib group. The arthritis and spondylitis scores were significantly lower in the VnP-16 and VnP16+celecoxib groups than the vehicle group. In the spine, the levels of IL-1β, IL-6, tumor necrosis factor-α, and IL-17 expression were reduced and Th17/Treg imbalance was regulated in the VnP-16 alone and VnP-16+celecoxib groups. Flow cytometry of splenocytes showed increased polarization of Tregs in the VnP-16+celecoxib group. In vitro, VnP-16 suppressed pSTAT3. Conclusions VnP-16 plus celecoxib prevented SpA progression in a mouse model by regulating the Th17/Treg imbalance and suppressing the expression of proinflammatory cytokines.

AKI Risk Score (AKI-RiSc): Developing an Interpretable Clinical Score for Early Identification of Acute Kidney Injury at the Emergency Department

Acute kidney injury (AKI) in hospitalised patients is a common syndrome associated with poorer patient outcomes. Clinical risk scores can be used for the early identification of patients at risk of AKI. We conducted a retrospective study using electronic health records of Singapore General Hospital emergency department patients who were admitted from 2008 to 2016. The primary outcome was inpatient AKI of any stage within 7 days of admission based on Kidney Disease Improving Global Outcome (KDIGO) 2012 guidelines. A machine learning AutoScore algorithm was used to generate clinical scores from the study sample which was divided into training, validation and testing cohorts. Model performance was evaluated using area under the curve (AUC). Among the 119,468 admissions, 10,693 (9.0%) developed AKI. 8,491 were stage 1 (79.4%), 906 stage 2 (8.5%) and 1,296 stage 3 (12.1%). The AKI Risk Score (AKI-RiSc) was a summation of the integer scores of 6 variables: serum creatinine, serum bicarbonate, pulse, systolic blood pressure, and diastolic blood pressure. AUC of AKI-RiSc was 0.730 (95% CI: 0.713 – 0.747), outperforming an existing AKI Prediction Score model which achieved AUC of 0.665 (95% CI: 0.646 – 0.679) on the testing cohort. At a cut-off of 4 points, AKI-RiSc had a sensitivity of 82.5% and specificity of 46.7%. AKI-RiSc is a simple clinical score that can be easily implemented on the ground for early identification of AKI and potentially be applied in international settings.

Evaluation of therapeutic efficacy of oxytetracycline against caprine respiratory mycoplasmosis using clinical score card method

Mycoplasmosis in goats is one of the challenging and continuous threats to small ruminant farming causing huge economic losses. This study was carried out to evaluate the therapeutic efficacy of oxytetracycline against caprine respiratory mycoplasmosis. Nasal swabs collected from fourteen goats showing clinical signs like cough, nasal discharge and abnormal breath sounds were screened for the presence of Mycoplasma spp. by polymerase chain reaction. The severity of the disease as well as the clinical improvement was recorded using a clinical score card. Oxytetracycline was administered intravenously at 15 mg/kg/day for 5 days along with supportive medications. Significant reduction in clinical score was observed after treatment and complete recovery was attained in 62.5 per cent animals.

National Early Warning Score 2 (NEWS2) to predict poor outcome in hospitalised COVID-19 patients in India

Background While several parameters have emerged as predictors of prognosis of COVID-19, a simple clinical score at baseline might help early risk stratification. We determined the ability of National Early Warning Score 2 (NEWS2) to predict poor outcomes among adults with COVID-19. Methods A prospective study was conducted on 399 hospitalised adults with confirmed SARS-CoV-2 infection between August and December 2020. Baseline NEWS2 score was determined. Primary outcome was poor outcomes defined as need for mechanical ventilation or death within 28 days. The sensitivity, specificity and Area under the curve were determined for NEWS2 scores of 5 and 6. Results Mean age of patients was 55.5 ± 14.8 years and 275 of 399 (68.9%) were male. Overall mortality was 3.8% and 7.5% had poor outcomes. Median (interquartile range) NEWS2 score at admission was 2 (0–6). Sensitivity and specificity of NEWS 2 of 5 or more in predicting poor outcomes was 93.3% (95% CI: 76.5–98.8) and 70.7% (95% CI: 65.7–75.3) respectively [area under curve 0.88 (95% CI: 0.847–0.927)]. Age, baseline pulse rate, baseline oxygen saturation, need for supplemental oxygen and ARDS on chest X ray were independently associated with poor outcomes. Conclusions NEWS2 score of 5 or more at admission predicts poor outcomes in patients with COVID-19 with good sensitivity and can easily be applied for risk stratification at baseline. Further studies are needed in the Indian setting to validate this simple score and recommend widespread use.

A Novel Clinical Score Predicting the Presence of Fatty Pancreas

Background: Fatty pancreas (FP) has become an increasingly encountered entity in recent years. Several studies have shown an association with several disease states. Aims: we aimed to generate a simple non-invasive scoring model to predict the presence of FP. Method: We performed a retrospective cross-sectional analysis at Galilee Medical Center. Inclusion criteria included patients who underwent endoscopic ultrasound (EUS) for hepatobiliary indications and who had either hyperechogenic pancreas consistent with FP or no sonographic evidence of fatty pancreas. Results: We included 569 patients. Among them, 78 patients had FP by EUS and 491 patients did not have FP. On univariate analysis, obesity (odds ratio (OR) 5.11, p < 0.0001), hyperlipidemia (OR 2.86, p = 0.0005), smoking (OR 2.02, p = 0.04), hypertension (OR 2.58, p = 0.0001) and fatty liver (OR 5.94, p < 0.0001) were predictive of FP. On multivariate analysis, obesity (OR 4.02, p < 0.0001), hyperlipidemia (OR 2.22, p = 0.01) and fatty liver (OR 4.80, p < 0.0001) remained significantly associated with FP. We developed a diagnostic score which included three parameters that were significant on multivariate regression analysis, with assignment of weights for each variable according to the OR estimate. A low cut-off score of ≤1 was associated with a negative predictive value (NPV) of 98.1% for FP, whereas a high cut-off score of ≥2 was associated with a positive predictive value (PPV) of 35–56%. Conclusion: We recommend incorporating this simple score as an aid to identify individuals with FP.

Current Status of Biomarkers in Anti-N-Methyl-D-Aspartate Receptor Encephalitis

The discovery of biomarkers in rare diseases is of paramount importance to allow a better diagnosis, improve predictions of outcomes, and prompt the development of new treatments. Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a rare autoimmune disorder associated with the presence of antibodies targeting the GluN1 subunit of the NMDAR. Since it was discovered in 2007, large efforts have been made towards the identification of clinical, paraclinical, and molecular biomarkers to better understand the immune mechanisms that govern the course of the disease as well as to define predictors of treatment response and long-term outcomes. However, most of these biomarkers are still in an exploratory phase, with only a few candidates reaching the final phases of the always-complex process of biomarker development, mainly due to the low incidence of the disease and its recent description. Clinical and paraclinical markers are probably the most widely explored in anti-NMDAR encephalitis, five of them combined in a clinical score to predict 1 year outcome. On the contrary, soluble molecules, such as persistent antibody positivity, antibody titers, cytokines, and other inflammatory mediators, have been proposed as biomarkers of clinical activity, inflammation, prognosis, and treatment response, but further studies are required for their clinical validation including larger and more homogenous cohorts of patients. Similarly, genetic susceptibility biomarkers are still in the exploratory phase and, therefore, weak conclusions can for now only be achieved. Thus, further studies are warranted to define biomarkers and unravel the underlying mechanisms driving rare diseases such as anti-NMDAR encephalitis. Future international collaborative studies with prospective designs that enable the enrollment of large cohorts will allow for the identification and validation of novel biomarkers for clinical decision-making.