Automated screening tool for Subcutaneous Implantable Defibrillator in Brugada syndrome has a high eligibility rate which is predicted by simple electrocardiographic parameters

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
S Marelli ◽  
D Kukavica ◽  
A Mazzanti ◽  
T Chargeishvili ◽  
A Trancuccio ◽  
...  

Abstract Background Manual electrocardiographic (ECG) screening tools for the use of subcutaneous cardiac defibrillator (S-ICD) have been associated with high ineligibility rates in Brugada syndrome patients (BrS). Although recent works identified ECG parameters for S-ICD eligibility in general population, automated screening tool (AST) for S-ICD eligibility have not even been assessed in large series of patients with BrS. Purpose This study evaluates the AST-derived eligibility rates for an S-ICD in patients with BrS, and ECG parameters associated with S-ICD eligibility. Methods Screening for S-ICD eligibility was performed using AST in 194 consecutive patients with BrS. Eligibility was defined when at least one of the three vectors was acceptable both in supine and standing position. Twelve-lead ECGs were registered during the screening. ECG parameters associated with AST eligibility were identified using multivariable logistical regression. Results Our study population consisted of 194 patients, with male preponderance (n=165/194; 85%); and were 43±12 years old at the time of screening. Majority of patients presented a spontaneous type 1 pattern during screening (n=128/194; 66%), with an average pattern height of 3±3 mm. Remarkably, 93% of patients passed the screening with AST. No differences in eligibility rates in terms of gender (93% males vs. 93% females eligible; p=1) and age (48±9 years non-eligible vs. 42±12 eligible; p=0.07) existed. Notably, our eligibility rate was 2.5 times higher than rates reported in literature when using manual screening tools (p=0.023). Independent 12-lead ECG parameters (Table) associated with AST eligibility were duration of S wave <80 ms in aVF and R/T ratio ≥3 in lead II (Figure), which have a high positive predictive value (97% and 99%, respectively) for screening eligibility. Conclusions Most BrS patients (93%) are eligible for S-ICD when AST is used. S wave <80 ms in aVF, and R/T ratio ≥3 in lead II have a high positive predictive value for S-ICD eligibility. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): The Italian Ministry of Research and University Dipartimenti di Eccellenza 2018–2022 grant to the Molecular Medicine Department (University of Pavia)

2016 ◽  
Vol 9 (2) ◽  
pp. 122-126 ◽  
Author(s):  
Mohamed S Teleb ◽  
Anna Ver Hage ◽  
Jaqueline Carter ◽  
Mahesh V Jayaraman ◽  
Ryan A McTaggart

BackgroundIdentification of emergent large vessel occlusion (ELVO) stroke has become increasingly important with the recent publications of favorable acute stroke thrombectomy trials. Multiple screening tools exist but the length of the examination and the false positive rate range from good to adequate. A screening tool was designed and tested in the emergency department using nurse responders without a scoring system.MethodsThe vision, aphasia, and neglect (VAN) screening tool was designed to quickly assess functional neurovascular anatomy. While objective, there is no need to calculate or score with VAN. After training participating nurses to use it, VAN was used as an ELVO screen for all stroke patients on arrival to our emergency room before physician evaluation and CT scan.ResultsThere were 62 consecutive code stroke activations during the pilot study. 19 (31%) of the patients were VAN positive and 24 (39%) had a National Institutes of Health Stroke Scale (NIHSS) score of ≥6. All 14 patients with ELVO were either VAN positive or assigned a NIHSS score ≥6. While both clinical severity thresholds had 100% sensitivity, VAN was more specific (90% vs 74% for NIHSS ≥6). Similarly, while VAN and NIHSS ≥6 had 100% negative predictive value, VAN had a 74% positive predictive value while NIHSS ≥6 had only a 58% positive predictive value.ConclusionsThe VAN screening tool accurately identified ELVO patients and outperformed a NIHSS ≥6 severity threshold and may best allow clinical teams to expedite care and mobilize resources for ELVO patients. A larger study to both validate this screening tool and compare with others is warranted.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Melissa Macalli ◽  
Marie Navarro ◽  
Massimiliano Orri ◽  
Marie Tournier ◽  
Rodolphe Thiébaut ◽  
...  

AbstractSuicidal thoughts and behaviours are prevalent among college students. Yet little is known about screening tools to identify students at higher risk. We aimed to develop a risk algorithm to identify the main predictors of suicidal thoughts and behaviours among college students within one-year of baseline assessment. We used data collected in 2013–2019 from the French i-Share cohort, a longitudinal population-based study including 5066 volunteer students. To predict suicidal thoughts and behaviours at follow-up, we used random forests models with 70 potential predictors measured at baseline, including sociodemographic and familial characteristics, mental health and substance use. Model performance was measured using the area under the receiver operating curve (AUC), sensitivity, and positive predictive value. At follow-up, 17.4% of girls and 16.8% of boys reported suicidal thoughts and behaviours. The models achieved good predictive performance: AUC, 0.8; sensitivity, 79% for girls, 81% for boys; and positive predictive value, 40% for girls and 36% for boys. Among the 70 potential predictors, four showed the highest predictive power: 12-month suicidal thoughts, trait anxiety, depression symptoms, and self-esteem. We identified a parsimonious set of mental health indicators that accurately predicted one-year suicidal thoughts and behaviours in a community sample of college students.


Author(s):  
Teng Hoo ◽  
Ee Mun Lim ◽  
Mina John ◽  
Lloyd D’Orsogna ◽  
Andrew McLean-Tooke

Background Calculated globulin fraction is derived from the liver function tests by subtracting albumin from the total protein. Since immunoglobulins comprise the largest component of the serum globulin concentration, increased or decreased calculated globulins and may identify patients with hypogammaglobulinaemia or hypergammaglobulinaemia, respectively. Methods A retrospective study of laboratory data over 2.5 years from inpatients at three tertiary hospitals was performed. Patients with paired calculated globulins and immunoglobulin results were identified and clinical details reviewed. The results of serum electrophoresis testing were also assessed where available. Results A total of 4035 patients had paired laboratory data available. A calculated globulin ≤20 g/L (<2nd percentile) had a low sensitivity (5.8%) but good positive predictive value (82.5%) for hypogammaglobulinaemia (IgG ≤5.7 g/L), with a positive predictive value of 37.5% for severe hypogammaglobulinaemia (IgG ≤3 g/L). Paraproteins were identified in 123/291 (42.3%) of patients with increased calculated globulins (≥42 g/L) who also had a serum electrophoresis performed. Significantly elevated calculated globulin ≥50 g/L (>4th percentile) were seen in patients with either liver disease (37%), haematological malignancy (36%), autoimmune disease (13%) or infections (9%). Conclusions Calculated globulin is an inexpensive and easily available test that assists in the identification of hypogammaglobulinaemia or hypergammaglobulinaemia which may prompt further investigation and reduce diagnostic delays.


2018 ◽  
Vol 23 (suppl_1) ◽  
pp. e37-e37
Author(s):  
Vinusha Gunaseelan ◽  
Patricia Parkin ◽  
Imaan Bayoumi ◽  
Patricia Jiang ◽  
Alexandra Medline ◽  
...  

Abstract BACKGROUND The Canadian Paediatric Society (CPS) recommends that every Canadian physician caring for young children provide an enhanced 18-month well-baby visit including the use of a developmental screening tool, such as the Nipissing District Developmental Screen (NDDS). The Province of Ontario implemented an enhanced 18-month well-baby visit specifically emphasizing the NDDS, which is now widely used in Ontario primary care. However, the diagnostic accuracy of the NDDS in identifying early developmental delays in real-world clinical settings is unknown. OBJECTIVES To assess the predictive validity of the NDDS in primary care for identifying developmental delay and prompting a specialist referral at the 18-month health supervision visit. DESIGN/METHODS This was a prospective longitudinal cohort study enrolling healthy children from primary care practices. Parents completed the 18-month NDDS during their child’s scheduled health supervision visit between January 2012 and February 2015. Using a standardized data collection form, research personnel abstracted data from the child’s health records regarding the child’s developmental outcomes following the 18-month assessment. Data collected included confirmed diagnoses of a development delay, specialist referrals, family history, and interventions. Research personnel were blind to the results of the NDDS. We assessed the diagnostic test properties of the NDDS with a confirmed diagnosis of developmental delay as the criterion measure. The specificity, sensitivity, positive predictive value, and negative predictive value were calculated, with 95% confidence intervals. RESULTS We included 255 children with a mean age of 18.5 months (range, 17.5–20.6) and 139 (55%) were male. 102 (40%) screened positive (1+ flag result on their NDDS). A total of 48 (19%) children were referred, and 23 (9%) had a confirmed diagnosis of a developmental delay (speech and language: 14; gross motor: 4; autism spectrum disorder: 3; global developmental delay: 1; developmental delay: 1). The sensitivity was 74% (95% CI: 52–90%), specificity was 63% (95% CI: 57–70%), positive predictive value was 17% (95% CI:10–25%), and the negative predictive value was 96% (95% CI: 92–99%). CONCLUSION For developmental screening tools, sensitivity between 70%-80% and specificity of 80% have been suggested. The NDDS has moderate sensitivity and specificity in identifying developmental delay at the 18-month health supervision visit. The 1+NDDS flag cut-point may lead to overdiagnosis with more children with typical development being referred, leading to longer wait times for specialist referrals among children in need. Future work includes investigating the diagnostic accuracy of combining the NDDS with other screening tools.


2020 ◽  
Vol 2020 ◽  
pp. 1-6 ◽  
Author(s):  
Yi Rong ◽  
Shihan Wang ◽  
Hui Wang ◽  
Feng Wang ◽  
Jingjing Tang ◽  
...  

Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.


2020 ◽  
Vol 26 (8) ◽  
pp. 1843-1849
Author(s):  
Faisal Shakeel ◽  
Fang Fang ◽  
Kelley M Kidwell ◽  
Lauren A Marcath ◽  
Daniel L Hertz

Introduction Patients with cancer are increasingly using herbal supplements, unaware that supplements can interact with oncology treatment. Herb–drug interaction management is critical to ensure optimal treatment outcomes. Several screening tools exist to detect drug–drug interactions, but their performance to detect herb–drug interactions is not known. This study compared the performance of eight drug–drug interaction screening tools to detect herb–drug interaction with anti-cancer agents. Methods The herb–drug interaction detection performance of four subscription (Micromedex, Lexicomp, PEPID, Facts & Comparisons) and free (Drugs.com, Medscape, WebMD, RxList) drug–drug interaction tools was assessed. Clinical relevance of each herb–drug interaction was determined using Natural Medicine and each drug–drug interaction tool. Descriptive statistics were used to calculate sensitivity, specificity, positive predictive value, and negative predictive value. Linear regression was used to compare performance between subscription and free tools. Results All tools had poor sensitivity (<0.20) for detecting herb–drug interaction. Lexicomp had the highest positive predictive value (0.98) and best overall performance score (0.54), while Medscape was the best performing free tool (0.52). The worst subscription tools were as good as or better than the best free tools, and as a group subscription tools outperformed free tools on all metrics. Using an average subscription tool would detect one additional herb–drug interaction for every 10 herb–drug interactions screened by a free tool. Conclusion Lexicomp is the best available tool for screening herb–drug interaction, and Medscape is the best free alternative; however, the sensitivity and performance for detecting herb–drug interaction was far lower than for drug–drug interactions, and overall quite poor. Further research is needed to improve herb–drug interaction screening performance.


2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Mazzanti ◽  
S Marelli ◽  
T Chargeishvili ◽  
A Trancuccio ◽  
M Marino ◽  
...  

Abstract Background A conclusive estimate of the eligibility rate for the use of subcutaneous implantable cardioverter defibrillators (S-ICD) in patients with Brugada Syndrome (BrS) is lacking. Objective We aimed to: 1) evaluate the eligibility for S-ICD in patients with BrS using a novel automated tool; 2) investigate predictors of ineligibility for S-ICD, based on baseline 12-lead electrocardiogram. Methods Automated screening for S-ICD was performed in 118 consecutive BrS patients using the programmer provided by the S-ICD producer. The system automatically assessed the acceptability of each of the three sense vectors used by the S-ICD for the detection of cardiac rhythm. Eligibility was defined when at least one vector was acceptable both in supine and standing position. Results The clinical characteristics of 118 BrS patients were as follow: age 43±11 years; 89% males; 2% with aborted cardiac arrest; 14% with a history of syncope; 81% with spontaneous type 1 ECG pattern; 21% with a familial history of sudden cardiac death; 24% with an SCN5A mutation. No patients had an indication for pacing. Only 8/118 (7%) patients were ineligible for S-ICD. Of note, 5/8 (63%) patients who failed the screening exhibited a slurred S wave of ≥80 ms duration in the peripheral lead aVF on the 12-lead baseline electrocardiogram, vs. 4/110 (4%) of those who passed the screening (sensitivity of S wave in aVF for screening failure 63%, specificity 97%; p<0.001). Remarkably, the presence of a slurred S wave of ≥80 ms duration in lead aVF remained significantly associated to the failure of eligibility for S-ICD (odds ratio 50, p<0.001) in a multivariable analysis that included the previous history of symptoms, the presence of a spontaneous type 1 ECG pattern, the gender and the presence of SCN5A mutations. ECG predictor of S-ICD screening Conclusion Up to 93% of BrS patients are eligible for S-ICD when the automated screening tool is used. The presence of a slurred S wave in lead aVF on the 12-lead electrocardiogram is a powerful predictor of screening failure.


2008 ◽  
Vol 29 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Michael Klompas ◽  
Ken Kleinman ◽  
Richard Platt

Objective.Surveillance for ventilator-associated pneumonia (VAP) using standard Centers for Disease Control and Prevention (CDC) criteria is labor intensive and involves many subjective assessments. We sought to improve the efficiency and objectivity of VAP surveillance by adapting the CDC criteria to make them amenable to evaluation with electronic data.Design.Prospective comparison of the accuracy of VAP surveillance by use of an algorithm with responses to prospective queries made to intensive care physicians. CDC criteria for VAP were used as a reference standard to evaluate the algorithm and clinicians' reports.Setting.Three surgical intensive care units and 2 medical intensive care units at an academic hospital.Methods.A total of 459 consecutive patients who received mechanical ventilation for a total of 2,540 days underwent surveillance by both methods during consecutive 3-month periods. Electronic surveillance criteria were chosen to mirror the CDC definition. Quantitative thresholds were substituted for qualitative criteria. Purely subjective criteria were eliminated. Increases in ventilator-control settings were taken to indicate worsening oxygenation. Semiquantitative Gram stain of pulmonary secretion samples was used to assess whether there was sputum purulence.Results.The algorithm applied to electronic data detected 20 patients with possible VAP. All cases of VAP were confirmed in accordance with standard CDC criteria (100% positive predictive value). Prospective survey of clinicians detected 33 patients with possible VAP. Seventeen of the 33 possible cases were confirmed (52% positive predictive value). Overall, 21 cases of confirmed VAP were identified by either method. The algorithm identified 20 (95%) of 21 known cases, whereas the survey of clinicians identified 17 (81%) of 21 cases.Conclusions.Surveillance for VAP using electronic data is feasible and has high positive predictive value for cases that meet CDC criteria. Further validation of this method is warranted.


Stroke ◽  
2020 ◽  
Vol 51 (12) ◽  
pp. 3765-3769
Author(s):  
Charles Esenwa ◽  
Ji-Ae Lee ◽  
Taha Nisar ◽  
Anna Shmukler ◽  
Inessa Goldman ◽  
...  

Background and Purpose: Evaluation of the lung apices using computed tomography angiography of the head and neck during acute ischemic stroke (AIS) can provide the first objective opportunity to screen for coronavirus disease 2019 (COVID-19). Methods: We performed an analysis assessing the utility of apical lung exam on computed tomography angiography for COVID-19–specific lung findings in 57 patients presenting with AIS. We measured the diagnostic accuracy of apical lung assessment alone and in combination with patient-reported symptoms and incorporate both to propose a COVID-19 era AIS algorithm. Results: Apical lung assessment when used in isolation, yielded a sensitivity of 0.67, specificity of 0.93, positive predictive value of 0.19, negative predictive value of 0.99, and accuracy of 0.92 for the diagnosis of COVID-19, in patients presenting to the hospital for AIS. When combined with self-reported clinical symptoms of cough or shortness of breath, sensitivity of apical lung assessment improved to 0.83. Conclusions: Apical lung assessment on computed tomography angiography is an accurate screening tool for COVID-19 and can serve as part of a combined screening approach in AIS.


2018 ◽  
Vol 113 (Supplement) ◽  
pp. S162-S163
Author(s):  
Jason D. Eckmann ◽  
Derek Ebner ◽  
Jamie Bering ◽  
Allon Kahn ◽  
Eduardo A. Rodriguez ◽  
...  

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