Risk Stratification Algorithms Research Articles

Risk Stratification as a Tool to Rationalize Quarantine of Health Care Workers Exposed to COVID-19 Cases: Evidence From a Tertiary Health Care Center in India.

Quarantine of health care workers (HCWs) exposed to COVID-19-confirmed cases is a well-known strategy for limiting the transmission of infection. However, during a pandemic situation in a resource-constraint setting, we require an evidence-based guideline for quarantining HCWs. We developed an algorithm for exposure-based risk stratification and quarantine of HCWs. We did contact tracing and risk stratification of 3853 HCWs, of whom 560 (14.5%) were categorized as high-risk contacts. High-risk contacts were quarantined for 14 days and underwent testing for COVID-19, while low-risk contacts continued their work with adherence to physical distancing, hand hygiene, appropriate use of personal protective equipment, and self-monitoring of symptoms. Overall, 118 (3.1%) contacts tested positive for COVID-19. The positivity rate among high-risk contacts was 7.1% (95% confidence interval = 5.2-9.6). Our strategy of risk stratification prevented 3215 HCWs from being quarantined and thus saved 45 010 person-days of health workforce in the institution.

Declining interest in clinical imaging during the COVID-19 pandemic: An analysis of Google Trends data

ObjectiveCurrent evidence suggests a decrease in elective diagnostic imaging procedures during the COVID-19 pandemic with potentially severe long-term consequences. The aim of this study was to quantify recent trends in public interest and related online search behavior for a range of imaging modalities, and “nowcast” future scenarios with respect to imaging use. MethodsWe used Google Trends, a publicly available database to access search query data in systematic and quantitative fashion, to search for key terms related to clinical imaging. We queried the search volume for multiple imaging modalities, identified the most common terms, extracted data for the United States over the time range from August 1, 2016 to August 1, 2020. Results were given in relative terms, using the Google metric ‘search volume index’. ResultsWe report a decrease in public interest across all imaging modalities since March 2020 with a subsequent slow increase starting in May 2020. Mean relative search volume (RSV) has changed by −19.4%, −38.3%, and −51.0% for the search terms “Computed tomography”, “Magnetic resonance imaging”, and “Mammography”, respectively, and comparing the two months prior to and following March 1, 2020. RSV has since steadily recuperated reaching all-year highs. ConclusionDecrease in public interest coupled with delays and deferrals of diagnostic imaging will likely result in a high demand for healthcare in the coming months. To respond to this challenge, measures such as risk-stratification algorithms must be developed to allocate resources and avoid the risk of overstraining the healthcare system.

Left Atrial Strain Is the Best Predictor of Adverse Cardiovascular Outcomes in Patients with Chronic Kidney Disease

Patients with chronic kidney disease (CKD) are at increased risk of adverse cardiovascular events, which is underestimated by traditional risk stratification algorithms. We sought to determine clinical and echocardiographic predictors of adverse outcomes in CKD patients. Two hundred forty-three prospectively recruited stage 3/4 CKD patients (male, 63%; mean age, 59.2±14.4years) without previous cardiac disease made up the study cohort. All participants underwent a transthoracic echocardiogram, with left ventricular (LV) and left atrial (LA) strain analysis. Participants were followed for 3.9±2.7years for the primary end point of cardiovascular death and major adverse cardiovascular event (MACE). The secondary end point was the composite of all-cause death and MACE. Fifty-four patients met the primary end point, and 65 the secondary end point. On log-rank tests, older age, diabetes mellitus, anemia, greater LV mass, reduced LV global longitudinal strain, larger indexed LA volume, higher E/e' ratio, and reduced LA reservoir strain (LASr; P<.01 for all) were independent predictors of cardiovascular death and MACE. On multivariable regression analysis of univariate predictors, LASr (P<.01) was the only independent predictor for the primary end point as well as for the secondary end point. Receiver operating characteristic curve analysis showed LASr was a stronger predictor of adverse events (area under the curve [AUC]=0.84) compared to the Framingham (AUC=0.58) and Atherosclerotic Cardiovascular Disease (AUC=0.59) risk scores. LASr is an independent predictor of cardiovascular death and MACE in CKD patients, superior to clinical risk scores, LV parameters, and LA volume.

Novel Target Genes and Epigenetic Pathways Involved in High Risk Acute Lymphoblastic Leukemia

Acute leukemias (AL) is a major cause of cancer death in young age. Extensive research is being conducted to identify novel and innovative approaches for leukemia treatment. Transcriptomic and epigenetic studies might help to discover potential targets, paving the way for molecular-targeted therapies. We analyzed a cohort of 34 AL at diagnosis: 10 pediatric Acute Lymphoblastic Leukemias (8 B-cell, 1 T-cell and 1 bi-phenotypic ALL), 4 young adult ALL (2 B-cell and 2 T-cell phenotype), and 20 pediatric Acute Myeloid Leukemias (AML: 3 M1, 4 M2, 1 M3, 5 M4, 7 M5) with an average blasts population higher than 80% (85+/-11% in ALL; 83+/-13% in AML). Six out of 14 ALL, and 12 out of 20 AML fell under "high risk" category according to clinical standard risk stratification algorithms. On all patients we performed mRNA sequencing (20-million-reads on Illumina Hiseq 4000). Analyses were performed adjusting &amp;lt;0.05 significant p values for multiple testing with the FDR Benjamini-Hochberg procedure. The expression of a set of 800 microRNAs (miRNAs) was evaluated by means of Nanostring miRNA panel. Expression signatures and associations among the different risk groups were calculated with t-tests and linear regression analyses. Applying stringent FDR statistical measurement, we discovered 3 genes that significantly differentiate the transcriptomic profile of high vsintermediate/standard-risk ALL in mRNAseq. The expression of PGR3 (p53 Responsive Gene) and long-non-coding RNAs (lncRNAs) ENSG00000228737 and ENSG00000253174 were respectively 45.5, 4.2 and 3.9 time downregulated in high-risk ALL. To explore more deeply the apoptosis pathway in ALL, we measured Tp53 expression and found it significantly downregulated in the high-risk vsintermediate-standard-risk ALL (p=&amp;lt;0.05, not adj for FDR). Consistently also the linear regression between PGR3 and p53 was significant (p&amp;lt;0.01). No differences in the expression of these genes were detected in AML samples. Tp53 dysregulation is a known hallmark for tumor progression; Tp53 mutations - ranging from 1-2% to 10% in pediatric and adult ALs - correlate with worse prognosis. However, in our cohorts, this gene signature was found significant only in high-risk ALL, homogeneously distinguishing them from intermediate/standard-risk ALL. Transcriptome clinical variant analyses excluded pathogenetic known variants that could explain such marked difference. Also, it is unlikely that somatic genetic mutations acquired by the tumor would explain such a homogeneous behavior of high-risk ALL. Thus, we analyzed the p53 regulatory pathway. Interestingly we found that miRNAs known to be involved in p53 control were significantly upregulated in high-risk vs intermediate-standard-risk ALL (p&amp;lt;0.0404) (Fig.1f-g), suggesting that an epigenetic control is active in high-risk ALL. Also, 2 lncRNAs were highly downregulated in high-risk ALL. Their function is still unknown, but interestingly, one of them ENSG00000253174correlates with GINS4, part of a protein complex implicated in DNA replication and cell proliferation and known to be upregulated in multiple neoplasia like gastric, colon and lung cancer. In our cohorts we found GINS4 significantly downregulated in high-risk vs standard/intermediate-risk ALL (Fig.1d). GINS4 axis is still unknown in AL. We found PRG3 and Tp53 significantly downregulated in high-risk ALL, with PRG3 expression 45 times lower than intermediate/low-risks ALL. Deeper analyses pointed out to an apoptosis control program not generated by a somatic mutation in the tumor, nor a germline clinical patient variant, but by an epigenetic mechanism. We are currently validating these data in a larger cohort, adding also methylome analyses. It will be interesting also to explore the function of the lncRNAs markedly downregulated in our cohort, whose functions are still unknown or partially known. Because of the small numerosity of the ALL high-risk cohort, we were not able to dissect high-risk young adults (4/6) from pediatric ALL (2/6). Although the homogeneity of data suggests a shared apoptosis control mechanism, it will be worthy to explore in a larger cohort whether the general worse prognosis of young adults/adults vs pediatric ALL is at least partially explained by this mechanism. Disclosures No relevant conflicts of interest to declare.

Telomere Length and CD49d Cooperate with IGHV Gene Status As Predictors of Long-Term Progression-Free Survival in CLL Patients Treated with FCR-Based Regimens

Background - Although there has been a revolution in the treatment of chronic lymphocytic leukemia (CLL), the challenge remains to identify the right drugs for the right patients. It is widely accepted that CIT, including the 'gold standard' fludarabine, cyclophosphamide and rituximab (FCR), is contraindicated for patients with TP53 disruption and, more recently, unmutated IGHV genes. Also patients with short, dysfunctional telomeres were shown to have inferior outcomes when treated with FCR-based regimens. To date, a role for CD49d in this setting has not been established. Aims - Here we evaluated the ability of telomere lenght (TL) and CD49d to cooperate with IGHV gene status to predict progression-free survival (PFS) in patients treated with FCR-based regimens in the frontline setting in three UK trials, ARCTIC, ADMIRE and CLL4. Methods - The study included a discovery cohort of 245 CLL treated with FCR/FCR-like regimens according to the two UK trials ARCTIC and ADMIRE. As there was no significant difference in PFS between the three arms of the study (P = 0.97), analysis was performed on the combined cohort. The median follow-up was 77.5 months with 157 progressions and 76 deaths. Twenty-nine patients were TP53 deleted and/or mutated, with shorter PFS compared to cases without TP53 disruption (final cohort, 216 TP53 wild-type CLL). The validation cohort was composed of 119 CLL samples derived from patients randomised to receive fludarabine, cyclophosphamide (FC) from the UK CLL4 trial. The median follow-up was 67.2 months with 99 progressions and 77 deaths. Fifteen CLL were TP53 mutated/deleted, with shorter PFS compared to cases without TP53 disruption (final cohort, 104 TP53 wild-type CLL). TL was measured using the high-throughput STELA assay and patients were bifurcated into two groups with either short telomeres inside the fusogenic range (TL-IFR) or long telomeres outside the fusogenic range (TL-OFR). CD49d was measured by flow cytometry and dichotomized as CD49dpos and CD49dneg based on the established 30% cut-off. For IGHV gene status, the 2% cutoff was used to split patients in mutated (IGHV-M) and ummutated (IGHV-UM). Results - In the 216 CLL with wild-type TP53 status from the ARCTIC/ADMIRE trials, CD49d expression was a predictor of PFS (P=0.02; HR=1.46 [1.03-2.06]). In keeping with previous reports, patients with IGHV-UM genes (P&amp;lt;.0001; HR=2.53 [1.79-3.58]) or TL-IFR (P=0.0002; HR=1.97 [1.30-2.98]) showed also significantly shorter PFS. This data was used as a starting point for a risk-stratification algorithm (Figure 1A). IGHV-UM cases could not be further dissected by TL or CD49d expression (P=0.76 log-rank test), their 8-year PFS being just 19.0%; (HR=5.58 [3.70-8.42]). In contrast, the IGHV-M group could be stratified by TL and CD49d expression (P&amp;lt;0.001 log-rank test). In particular, 13/84 (15.5%) of IGHV-M CLL with TL-IFR showed a median PFS of 3.0 years with a 8-year PFS of 15.4% (HR=6.45 [1.84-22.58]), similar to IGHV-UM cases (P = 0.19). Patients with IGHV-M genes and TL-OFR could be further stratified by CD49d expression into categories with different 8-year PFS: 43.1% in IGHV-M/TL-OFR/CD49dpos cases (HR=2.52 [1.08-5.89]), and 75.5% in the IGHV-M/TL-OFR/CD49dneg reference group (Table 1). Figure 1B shows the overlaid Kaplan-Meier curves for this hierarchical stratification. The proposed algorithm was then evaluated in the UK CLL4 trial. In keeping with the known inferiority of FC when compared with FCR, the 8-year PFS was just 5.2% in the IGHV-UM subset, irrespective of TL or CD49d expression. In concordance with the discovery cohort, the IGHV-M subset with TL-IFR had a similar median PFS to IGHV-UM cases (P=0.84). Furthermore, CD49d expression was able to stratify cases with TL-OFR; in particular, 18/104 (17.3%) were IGHV-M/TL-OFR/CD49dneg CLL which had a 8-year PFS of 77.8% (summary in Table 1 and Figure 1C). Conclusion - Our analysis shows that only IGHV-M/TL-OFR/ CD49dneg patients may benefit from CIT; this group represented just 56/321 cases (17.4%) of the combined cohort, suggesting that approximately 82% of patients should be considered for alternative therapies. Incorporation of this algorithm into clinical trial design and real-world practice would enable rational, risk-adapted, clinical management with the aim of treating all CLL patients with the optimal therapeutic regimen in the frontline setting. Disclosures Norris: TeloNostiX Ltd: Current equity holder in private company, Patents &amp; Royalties. Hillmen:Gilead: Other: Financial or material support, Research Funding; Alexion: Consultancy, Research Funding, Speakers Bureau; Apellis: Consultancy, Research Funding, Speakers Bureau; AstraZeneca: Consultancy, Speakers Bureau; Acerta: Other: Financial or material support; Roche: Consultancy, Other: Financial or material support, Research Funding, Speakers Bureau; AbbVie: Consultancy, Other: Financial or material support, Research Funding, Speakers Bureau; Pharmacyclics: Other: Financial or material support, Research Funding; Janssen: Consultancy, Other: Financial or material support, Research Funding, Speakers Bureau. Rawstron:BD Biosciences (Intrasure): Patents &amp; Royalties. Baird:TeloNostiX Ltd: Current equity holder in private company, Patents &amp; Royalties. Fegan:TeloNostiX Ltd: Current equity holder in private company, Patents &amp; Royalties. Pepper:TeloNostiX Ltd: Current equity holder in private company, Patents &amp; Royalties.

Implantable cardiac monitor after cryptogenic stroke: atrial fibrillation detection and predictors

Abstract Objective The main objective of our study was to analyze the incidence and predictors of atrial fibrillation (AF) in patients with cryptogenic stroke (CS) who received an implantable cardiac monitor (ICM) at our Institution. Methods From November 2013 to October 2017, a total of 133 patients who had suffered a CS were implanted with an ICM after a thorough screening process. The median time between the thromboembolic event and ICM implantation was 64 days [IQ range: 16–111]. All implanted patients were followed with remote monitoring until the first detected episode of AF or up to December 2018. Every remote monitoring transmission and related electrograms were analyzed by the dedicated Electrophysiology Nursing team and confirmed by experienced Electrophysiologists. AF was defined by any episode lasting greater than or equal to 2 minutes. Results During a median follow-up of 14.8 months [IQ range: 3.0–31.2], AF was detected in 65 out of 133 patients (48.9%). The median time from ICM implantation and AF detection was 3.5 months [IQ range: 0.9–6.7]. The prevalence of AF was 22.6%, 34.4%, 40.8% and 48.3% at 3, 6, 12 and 24 months respectively. At the multivariate analysis, high premature atrial contractions (PAC) burden and left atrium (LA) dilation were the only independent predictors of AF detection (HR 2.82, 95% CI 1.64–4.83, p&amp;lt;0.001 for PAC; HR 1.75, 95% CI 1.03–2.97, p=0.038 for LA dimension). Patients were dived into categories based on the probability of AF detection (low, intermediate and high risk) and a new risk stratification algorithm was implemented (Figure 1). Conclusion After a thorough screening process, AF detection in patients with CS and ILM was quite high. Having a high PAC burden and LA dilation predicted AF episodes at the multivariate analysis. A new risk stratification algorithm was developed. Figure 1 Funding Acknowledgement Type of funding source: None

A multiparametric ICD algorithm for heart failure risk stratification: an analysis in clinical practice

Abstract Purpose A novel multiparametric algorithm based on implantable cardioverter defibrillator (ICD) sensors has been recently developed. The HeartLogic index combines multiple parameters, i.e. heart sounds, intrathoracic impedance, respiration pattern, night heart rate, and patient activity, in a single index. In the validation study, the HeartLogic alert condition was shown to identify patients during periods of significantly increased risk of heart failure (HF) events. We sought to evaluate the risk stratification ability of the algorithm in a group of patients who received the system in clinical practice. Methods The HeartLogic feature was activated in 257 ICD and cardiac resynchronization therapy ICD patients (186 male, 70±11 years, left ventricular ejection fraction 30±8%) at 11 centers. The median follow-up duration was 14 months [25–75 percentile: 7–19]. The HeartLogic algorithm automatically calculates a daily HF index and identifies periods in or out of an alert state relative to a configurable threshold (in this analysis set to 16). Results Patients experienced 40 HF hospitalizations requiring at least 1 overnight stay (0.14/patient-year) during the observation period (285 patient-years). The HeartLogic index crossed the threshold value 191 times in 105 patients. The time in the alert state was 27 patient-years, i.e. 9.5% of the total observation period. HF hospitalization rate while in alert was 0.96/patient-year and 0.05/patient-year while out of alert. The occurrence of ≥1 index crossing during follow-up was associated with the risk of HF hospitalization (odds ratio: 4.70, CI 95%: 1.79–12.4, p=0.002), independently from other baseline clinical variables. Conclusions Our analysis of data collected in clinical practice confirms that the multiparametric ICD algorithm is an independent predictor of higher risk of HF. In particular, it allows dynamic identification of time-intervals when patients are at significantly increased risk of worsening HF. This potentially helps better triage resources to a more vulnerable patient population. Funding Acknowledgement Type of funding source: None

Venous lactate predicts adverse outcomes in normotensive pulmonary embolism

Abstract Background/Introduction Arterial lactate is an established risk marker in patients with acute pulmonary embolism (PE). However, its clinical application is limited by the need for an arterial puncture, a procedure not routinely performed in haemodynamically stable PE patients. In contrast, information on venous lactate can be easily obtained via peripheral venepuncture and might thus be more suitable for risk assessment in normotensive PE. Purpose To investigate the prognostic value of peripheral venous lactate for outcome prediction in normotensive patients with acute PE. Methods Consecutive normotensive PE patients enrolled in a prospective single-centre registry between 09/2008 and 03/2018 were studied. Study outcomes included in-hospital adverse outcome (PE-related death, cardiopulmonary resuscitation or vasopressor treatment) and all-cause mortality. An optimised venous lactate cut-off concentration was identified using receiver operating curve analysis and its prognostic value compared to the established cut-off value for arterial lactate (2.0 mmol/l) and the upper limit of normal for venous lactate (2.3 mmol/l). Furthermore, we tested if addition of venous lactate to the 2019 European Society of Cardiology (ESC) risk stratification algorithm improves risk prediction. Results We analysed data from 419 (age 70 [interquartile range (IQR) 57–79] years; 53% female) patients. Patients with an in-hospital adverse outcome had higher venous lactate concentrations than those with a favourable clinical course (3.1 [IQR 1.3–4.9] vs. 1.6 [IQR 1.2–2.3] mmol/l, p=0.001). An optimized cut-off value of 3.3 mmol/l predicted both, adverse outcome (OR 11.0 [95% CI 4.6–26.3]) and all-cause mortality (OR 3.8 [95% CI 1.3–11.3]). Venous lactate ≥2.0 mmol/l and ≥2.3 mmol/l had lower predictive value for an adverse outcome (OR 3.6 [95% CI 1.5–8.7] and OR 5.7 [95% CI 2.4–13.6], respectively) and did not predict all-cause mortality. If venous lactate was added to the 2019 ESC algorithm (Figure), a cut-off concentration of 2.3 mmol/l had high negative predictive value (0.99 [95% CI 0.97–1.00]) for an adverse outcome in intermediate-low-risk patients, whereas levels ≥3.3 mmol/l predicted adverse outcomes in the intermediate-high-risk group (OR 5.2 (95% CI 1.8–15.0). Conclusions Even modest venous lactate elevations above the upper limit of normal (2.3 mmol/l) were associated with increased risk for an in-hospital adverse outcome and a cut-off value of 3.3 mmol/l provided optimal prognostic performance predicting both, an adverse outcome and all-cause mortality. Adding venous lactate to the 2019 ESC algorithm seems to further improve risk stratification. Importantly, the established cut-off value for arterial lactate (2.0 mmol/l) has limited specificity in venous samples and should not be used. Venous lactate for risk stratification Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): This study was supported by the German Federal Ministry of Education and Research (BMBF 01EO1503). The authors are responsible for the contents of this publication. BRAHMS GmbH, part of Thermo Fisher Scientific, Hennigsdorf/Berlin, Germany provided financial support for biomarker measurements. The sponsor was neither involved in biomarker measurements, statistical analyses, writing of the abstract nor had any influence on the scientific contents.

COVID-19 risk stratification algorithms based on sTREM-1 and IL-6 in emergency department

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has led to surges of patients presenting to emergency departments (EDs) and potentially overwhelming health systems.ObjectiveWe sought to assess the predictive accuracy of host biomarkers at clinical presentation to the ED for adverse outcome.MethodsProspective observational study of PCR-confirmed COVID-19 patients in the ED of a Swiss hospital. Concentrations of inflammatory and endothelial dysfunction biomarkers were determined at clinical presentation. We evaluated the accuracy of clinical signs and these biomarkers in predicting 30-day intubation/mortality, and oxygen requirement by calculating the area under the receiver-operating characteristic curve and by classification and regression tree analysis.ResultsOf 76 included patients with COVID-19, 24 were outpatients or hospitalized without oxygen requirement, 35 hospitalized with oxygen requirement, and 17 intubated/died. We found that soluble triggering receptor expressed on myeloid cells had the best prognostic accuracy for 30-day intubation/mortality (area under the receiver-operating characteristic curve, 0.86; 95% CI, 0.77-0.95) and IL-6 measured at presentation to the ED had the best accuracy for 30-day oxygen requirement (area under the receiver-operating characteristic curve, 0.84; 95% CI, 0.74-0.94). An algorithm based on respiratory rate and sTREM-1 predicted 30-day intubation/mortality with 94% sensitivity and 0.1 negative likelihood ratio. An IL-6–based algorithm had 98% sensitivity and 0.04 negative likelihood ratio for 30-day oxygen requirement.ConclusionssTREM-1 and IL-6 concentrations in COVID-19 in the ED have good predictive accuracy for intubation/mortality and oxygen requirement. sTREM-1– and IL-6–based algorithms are highly sensitive to identify patients with adverse outcome and could serve as early triage tools.

Diagnostic Value of Different Risk-Stratification Algorithms in Solid Breast Lesions

In the past few years, elastography has gained ground as a complementary method to ultrasonography in noninvasive breast cancer screening. Despite positive outcomes, there is a further need to refine the method, especially regarding BIRADS scores 3 and 4A, where the distinction between benignancy and malignancy is established. The aim of the present study was to evaluate the best risk-stratification system using both qualitative and semiquantitative elastographic methods for solid breast nodules. A total of 1405 solid nodules, described in 657 female patients, were examined in our endocrine unit between January 2018 and December 2019. The inclusion criterion for our retrospective study was the presence of any solid breast mass in women of all ages (mean, 40.85 ± SD 27.11), detected during ultrasound examination using a HITACHI PREIRUS machine (Hitachi Medical Corporation, Tokyo, Japan). The Breast Imaging Reporting and Data System (BIRADS)–US criteria were used in the assessment of each nodule by conventional US (gray-scale mode) and Doppler evaluation. The Ueno score and strain ratio were also measured for all the described lesions. We considered multiple algorithms for the risk reassessment of solid breast nodules: classical BIRADS–US, EFSUMB BIRADS, worst-case scenario BIRADS and BIRADS TM. There were 93 malignant nodules out of 1405. The diagnosis was based on histopathological results for all the malignant lesions. Benign lesions were diagnosed based on histopathological results, Tru-Cut biopsy, mammography and MRI. The Sensitivity (Se), Specificity (Sp), Positive Predictive Value (PPV), Negative Predictive Value (NPV) and Accuracy (Acc) were obtained for all the proposed risk-stratification reporting systems: conventional BIRADS-US (Se, 74.23%; Sp, 63.95%; PPV, 13.53%; NPV, 97.79%; Acc, 65%); EFSUMB BIRADS (Se, 71.23%; Sp, 81.55%; PPV, 22.68%; NPV, 97.99%; Acc, 81%); worst-case scenario BIRADS (Se, 84.23%; Sp, 58.23%; PPV, 13.29%; NPV, 98.84%; Acc, 60%); BIRADS TM (Se, 81.23%; Sp, 75.84%; PPV, 20.35%; NPV, 98.81%; Acc, 77%). We found that the most efficient risk-stratification reporting system was the proposed one, BIRADS TM, which considers both upgrading and downgrading the conventional BIRADS-US, followed by the worst-case scenario BIRADS and EFSUMB BIRADS.

Identifying the Hypertensive Adolescent

Research Article| October 01 2020 Identifying the Hypertensive Adolescent AAP Grand Rounds (2020) 44 (4): 47. https://doi.org/10.1542/gr.44-4-47 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Identifying the Hypertensive Adolescent. AAP Grand Rounds October 2020; 44 (4): 47. https://doi.org/10.1542/gr.44-4-47 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search toolbar search search input Search input auto suggest filter your search All PublicationsAll JournalsAAP Grand RoundsPediatricsHospital PediatricsPediatrics In ReviewNeoReviewsAAP NewsAll AAP Sites Search Advanced Search Topics: hypertension Source: Wieniawski P, Werner B. Prediction of the hypertension risk in teenagers [published online ahead of print June 9, 2020]. Cardiol J. 2020. doi: https://doi.org/10.5603/CJ.a2020.0079Google Scholar Investigators from the Medical University of Warsaw, Poland, conducted a cross-sectional study to create a hypertension risk stratification model and algorithm to detect hypertension in adolescents. Eligible participants were middle and high school students aged 15–17 years from schools in and around Warsaw who never had been diagnosed or suspected of having hypertension previously. Participants completed a questionnaire regarding their family history and risk factors for cardiovascular disease. Blood pressure measurements were taken 3 times on at least 2 separate visits at least a week apart. Anthropometric measurements, including weight; height; BMI; and hip, arm, and abdominal circumference, also were obtained. The primary outcome was hypertension, defined as systolic and/or diastolic blood pressure ≥95th percentile according to norms for gender, age, and/or height. Among those with hypertension after initial blood pressure measurement, 24-hour ambulatory blood pressure monitoring was performed for confirmation. Investigators used logistic regression to identify anthropometric and family history variables associated with hypertension, then developed a model including significant variables to predict the risk of hypertension. This model was tested by administering a questionnaire that included these variables to a separate sample of students to determine its sensitivity and specificity for estimating an individual as having a > 50% or > 75% risk of hypertension. There were 690 student participants included in the initial sample, 5.8% (N = 40) of whom were found to have hypertension. Variables significantly associated with hypertension included a high BMI and having at least one parent who had hypertension. In the predictive model, height, weight, waist-to-hip circumference, and family history of hypertension were included. There were 108 participants who completed the predictive model questionnaire. The sensitivity and specificity of the predictive model for estimating a > 50% risk of hypertension were 91% and 97%, respectively; for estimating a > 75% risk, the sensitivity and specificity were 54% and 100%, respectively. The authors conclude that an algorithm including height, weight, waist-to-hip circumference, and family history of hypertension can predict hypertension in adolescents. Dr Sanchez-Kazi has disclosed no financial relationship relevant to this commentary. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device. Hypertension in children is an increasing worldwide health problem (See AAP Grand Rounds. 2020;43[5];591 .) There is increased risk of chronic kidney disease and cardiovascular health problems in adults who were hypertensive as children (See AAP Grand Rounds. 2019;41[6];632,3 ), so identifying children who are at risk is important. In the current study, the authors proposed a risk stratification formula to identify adolescents who are at risk of developing hypertension using anthropometric measurements and family history. Multiple worldwide investigators have demonstrated in prospective, observational, and cross-sectional studies that increased weight, high waist-to-hip ratio, and elevated BMI raise the risk of hypertension significantly.3,4 The risk of... You do not currently have access to this content.

Preventive Cardiology

Key Points The etiology of premature cardiovascular disease in children is multifactorial Hypocholesteremia Obesity/lack of physical activity Smoking The goals of preventive cardiology are to Prevent, identify, and treat potential atherosclerotic cardiac risk factors. Educate children and families on preventive strategies. Intervene early to decrease the burden of atherosclerotic heart disease in adult life. The American Heart Association and American Academy of Pediatrics have proposed a risk stratification and treatment algorithm for children at increased risk for premature coronary heart disease. The National Cholesterol Education Program recommends 2 separate approaches to managing hypercholesterolemia in children. Broad, population-based approach Iindividualized patient approach

Should We Use Genetic Scores in the Determination of Treatment Strategies to Control Dyslipidemias?

Conventional risk stratification algorithms that rely on age, clustered phenotypic traits, and biomarkers under-recognize the sizeable subgroup of individuals at high polygenic risk for atherosclerotic cardiovascular disease (ASCVD). This review provides perspective on the promising role of genetic testing in cardiovascular prevention through the lens of lipid metabolism. Recent advances in cardiovascular genetics identified a number of common and rare variants affecting ASCVD risk. This genetic susceptibility can be assessed by polygenic risk scores (PRS) which quantify risk conferred by the cumulative impact of common variants. This results in a normally distributed spectrum of risk for coronary artery disease that is present at birth and amplifies the effects of modifiable risk factors including lipids. Polygenic risk is a significant determinant of ASCVD risk that is below the discrimination level of conventional guideline-based clinical frameworks. Genetic risk scores thus hold potential to refine phenotypic screening in cardiovascular prevention, identify subsets of the population that might derive particular benefit from early lifestyle and pharmaceutical interventions, and guide treatment eligibility. This might pave the way to personalized prevention aimed at reducing the unacceptable global burden of ASCVD.

99th Percentile Upper-Reference Limit of Cardiac Troponin and the Diagnosis of Acute Myocardial Infarction.

Concerns exist regarding how the 99th percentile upper reference limit (URL) of cardiac troponin (cTn) is determined and whether it should be derived from normal healthy individuals. The 99th percentile URL of cTn is an important criterion to standardize the diagnosis of myocardial infarction (MI) for clinical, research, and regulatory purposes. Statistical heterogeneity in its calculation exists but recommendations have been proposed. Some negativity has resulted from the fact that with some high-sensitivity (hs) cTn assays, a greater number of increases above the 99th percentile are observed when transitioning from a contemporary assay. Increases reflect acute or chronic myocardial injury and provide valuable diagnostic and prognostic information. The etiology of increases can sometimes be difficult to determine, making a specific treatment approach challenging. For those reasons, some advocate higher cutoff concentrations. This approach can contribute to missed diagnoses. Contrary to claims, neither clinical or laboratory guidelines have shifted away from the 99th percentile. To support the diagnosis of acute MI, the 99th percentile URL remains the best-established approach given the absence of cTn assay standardization. Importantly, risk stratification algorithms using hs-cTn assays predict the possibility of MI diagnoses established using the 99th percentile. The 99th percentile of cTn remains the best-established criterion for the diagnosis of acute MI. While not perfect, it is analytically and clinically evidence-based. Until there are robust data to suggest some other approach, staying with the 99th percentile, a threshold that has served the field well for the past 20 years, appears prudent.

The Quantitative Relationship Between Autonomous Cortisol Secretion, Dysglycemia and the Metabolic Syndrome

Autonomous cortisol secretion (ACS) is the most common endocrine abnormality in the evaluation of adrenal incidentalomas. The categorization of ACS is derived from a 1 mg dexamethasone suppression test (DST). Impaired DST is associated with several metabolic derangements. In this study we analyzed the association between post-DST cortisol level, analyzed as a continuous parameter, and indices of glycemic metabolism. We prospectively collected data of 1,976 patients evaluated for adrenal incidentalomas in a large tertiary medical center between December 1, 2017, and August 31, 2019. Seventy-three patients completed the evaluation process. Post-DST cortisol levels were analyzed for correlation with various metabolic parameters, including fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) among the general cohort and for subgroups stratified by the number of metabolic syndrome (MS) criteria. Post-DST cortisol demonstrated a linear association with FPG and HbA1c across its entire cortisol range (R = 0.51 and 0.41, respectively; P≤.01). The association between post-DST cortisol and FPG was strengthened with an increased number of metabolic syndrome criteria. Patients with 4 MS criteria show a stronger association (R = 0.92) compared to patients with only a single criterion (R = 0.509). Furthermore, mean post-DST cortisol levels increased as the number of MS criteria accumulated. Post-DST cortisol should be viewed as a continuous parameter in risk stratification algorithms for the development of MS and particularly dysglycemia.

Suspected penicillin allergy: risk assessment using an algorithm as an antibiotic stewardship project

Summary Background Beta-lactam antibiotics (BLA) are the treatment of choice for a large number of bacterial infections. Putative BLA allergies are often reported by patients, but rarely confirmed. Many patients do not receive BLA due to suspected allergy. There is no systematic approach to risk stratification in the case of a history of suspected BLA allergy. Methods Using the available stratification programs and taking current guidelines into account, an algorithm for risk stratification, including recommendations on the use of antibiotics in cases of compellingly indicated BLA despite suspected BLA allergy, was formulated by the authors for their maximum care university hospital. Results The hospital is in great need of recommendations on how to deal with BLA allergies. Patient-reported information in the history forms the basis for classifying the reactions into four risk categories: (1) BLA allergy excluded, (2) benign delayed reaction, (3) immediate reaction, and (4) severe cutaneous and extracutaneous drug reaction. Recommendations strictly depend on this classification and range from use of full-dose BLA or use of BLA under certain conditions (e.g., two-stage dose escalation, non-cross-reactive BLA only) to prohibiting all BLA and the use of alternative non-BLA. In case of suspected immediate or delayed allergic reactions, there is an additional recommendation regarding subsequent allergy testing during a symptom-free interval. Conclusion Triage of patients with suspected BLA is urgently required. While allergy testing, including provocation testing, represents the most reliable solution, this is not feasible in all patients due to the high prevalence of BLA allergies. The risk stratification algorithm developed for the authors’ hospital represents a tool suitable to making a contribution to rational antibiotic therapy.

Regional Mechanical Thrombectomy Imaging Protocol in Patients Presenting with Acute Ischemic Stroke during the COVID-19 Pandemic.

Chest CT is a rapid, useful additional screening tool for coronavirus disease 2019 (COVID-19) in emergent procedures. We describe the feasibility and interim outcome of implementing a modified imaging algorithm for COVID-19 risk stratification across a regional network of primary stroke centers in the work-up of acute ischemic stroke referrals for time-critical mechanical thrombectomy. We undertook a retrospective review of 49 patients referred to the regional neuroscience unit for consideration of mechanical thrombectomy between April 14, 2020, and May 21, 2020. During this time, all referring units followed a standard imaging protocol that included a chest CT in addition to a head CT and CT angiogram to identify Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) infective pulmonary changes. Overall, 2 patients had typical COVID-19 radiologic features and tested positive, while 7 patients had indeterminate imaging findings and tested negative. The others had normal or atypical changes and were not diagnosed with or suspected of having COVID-19. There was an overall sensitivity of 100%, specificity of 74.1%, negative predictive value of 100%, and positive predictive value of 22.2% when using chest CT to diagnose COVID-19 in comparison with the real-time reverse transcriptase-polymerase chain reaction test. The mean additional time and radiation dose incurred for the chest CT were 184 ± 65.5 seconds and 2.47 ± 1.03 mSv. Multiple cardiovascular and pulmonary incidental findings of clinical relevance were identified in our patient population. Chest CT provides a pragmatic, rapid additional tool for COVID-19 risk stratification among patients referred for mechanical thrombectomy. Its inclusion in a standardized regional stroke imaging protocol has enabled efficient use of hospital resources with minimal compromise or delay to the overall patient treatment schedule.

Uncommon cytogenetic abnormalities identifying high-risk acute myeloid leukemia in children.

Pediatric acute myeloid leukemia (AML) represents an aggressive disease and is the leading cause of childhood leukemic mortality. The genomic landscape of pediatric AML has been recently mapped and redefined thanks to large-scale sequencing efforts. Today, understanding how to incorporate the growing list of genetic lesions into a risk stratification algorithm for pediatric AML is increasingly challenging given the uncertainty regarding the prognostic impact of rare lesions. Here we review some uncommon cytogenetic lesions to be considered for inclusion in the high-risk groups of the next pediatric AML treatment protocols. We describe their main clinical characteristics, biological background and outcome. We also provide some suggestions for the management of these rare but challenging patients and some novel targeted therapeutic options.

Use of artificial intelligence and machine learning for estimating malignancy risk of thyroid nodules.

Current methods for thyroid nodule risk stratification are subjective, and artificial intelligence algorithms have been used to overcome this shortcoming. In this review, we summarize recent developments in the application of artificial intelligence algorithms for estimating the risks of malignancy in a thyroid nodule. Artificial intelligence have been used to predict malignancy in thyroid nodules using ultrasound images, cytopathology images, and molecular markers. Recent clinical trials have shown that artificial intelligence model's performance matched that of experienced radiologists and pathologists. Explainable artificial intelligence models are being developed to avoid the black box problem. Risk stratification algorithms using artificial intelligence for thyroid nodules are now commercially available in many countries. Artificial intelligence models could become a useful tool in a thyroidolgist's armamentarium as a decision support tool. Increased adoption of this emerging technology will depend upon increased awareness of the potential benefits and pitfalls in using artificial intelligence.

SAFEHEART risk-equation and cholesterol-year-score are powerful predictors of cardiovascular events in French patients with familial hypercholesterolemia

Background and aimsPatients with heterozygous familial hypercholesterolemia (HeFH) present elevated cardiovascular (CV) risk. Current CV risk stratification algorithms developed for the general population are not adapted for heFH patients. It is therefore of singular importance to develop and validate CV prediction tools, which are dedicated to the HeFH population. MethodsOur first objective was to validate the Spanish SAFEHEART-risk equation (RE) in the French HeFH cohort (REFERCHOL), and the second to compare SAFEHEART-RE with the low-density-lipoprotein-cholesterol (LDL-C)-year-score for the prediction of CV events in the HeFH French population. ResultsWe included HeFH (n = 1473) patients with a genetic or clinical diagnosis (DLCN score ≥8). Among them, 512 patients with a 5-year follow-up were included to validate the 5 year-CV-RE. A total of 152 events (10.3%) occurred in the entire population of 1473 patients during a mean follow-up of 3.9 years. Over the five-year follow-up, non-fatal CV events occurred in 103 patients (20.2%). Almost all the parameters used in the SAFEHEART-RE were confirmed as strong predictors of CV events in the REFERCHOL cohort. The C-statistic revealed a satisfactory performance of both the SAFEHEART-RE and LDL-C-year-scores in predicting CV events for all the patients (primary and secondary prevention) (C-index 0.77 and 0.70, respectively) as well as for those in primary prevention at inclusion (C-index 0.78 and 0.77, respectively). ConclusionsThis analysis represents the first external validation of the SAFEHEART-RE and demonstrated that both SAFEHEART-RE and the LDL-C-year-score are good predictors of CV events in primary prevention HeFH patients.