other:Article Title: Textile-Integrated Liquid Metal Electrodes for Electrophysiological Monitoring.
Article Snippet: Next generation textile-based wearable sensing systems will require flexibility and strength to maintain capabilities over a wide range of deformations.. However, current material sets used for textile-based skin contacting electrodes lack these key properties, which hinder applications such as electrophysiological sensing.. In this work, a facile spray coating approach to integrate liquid metal nanoparticle systems into textile form factors for conformal, flexible, and robust electrodes is presented.
Software:
Article Title: Sustained heart rate-corrected QT prolongation during recovery from hypoglycaemia in people with type 1 diabetes, independently of recovery to hyperglycaemia or euglycaemia.
Article Snippet: Clinical Research, Copenhagen University Hospital – Steno Diabetes Center Copenhagen, Herlev, Denmark Center for Clinical Metabolic Research, Gentofte Hospital, University of Copenhagen, Hellerup, Denmark Department of Medicine, Herlev Hospital, University of Copenhagen, Herlev, Denmark Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark Department of Endocrinology and Nephrology, Nordsjællands Hospital Hillerød, University of Copenhagen, Hillerød, Denmark
Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Sugrue, Noseworthy, et al. ( ) , N/A , 12 lead ECG Bazett formula Automated QT‐alert system (QTc ≥500 ms) Cardiologist review , Novel proprietary TW program: TW left/right slope, TW amplitude, TW area, TW COG x/y coordinates, COG first 25% TW, COG last 25% of the TW, Tpeak–Tend interval Diagnostic accuracy: Sn, Sp, NPV, PPV Sensitivity analysis (age, sex) , aLQTS TWM biomarkers: Lead V 5 Shallower TW right slope (−2322 vs. −3593 mV/s; p < .001) Greater T‐peak‐Tend (109 vs. 92 ms; p < .001) Smaller TW COG (290 ms vs. 310 ms; p < .001) cLQTS vs. aLQTS: Lead V 5 distinguishes cLQTS from aLQTS in 77% cases Sn 90%, Sp 58%, PPV 83%, NPV 71% Sensitivity analysis: Age 78.3% No sex difference (M: 76%, F: 78%). .. Sugrue et al. ( ) , Sotalol Dofetilide , 12 lead ECG Bazett formula Automated TW analysis software (MATLAB) , Novel proprietary TW program QT interval and QTc Pre and post TdP ECG Risk prediction: Sn, Sp, NPV, PPV , Discrimination accuracy Lead V 3 : QTc discrimination ( p < .001, r = .72) Drug: 480 ms Control: 420 ms Lead I: TW right slope ( p = .002, r = .45) Torsadogenic risk prediction: ECG biomarkers TWRS: 88% QTc alone: 79% Risk prediction accuracy Sn: 92.1% (combined), 88.1% (QTc), 79.7% (TWRS) Sp: 81.4% (combined), 72% (QTc), 46% (TWRS) PPV: 90.3% (combined), 85% (QTc), 58.9% (TWRS) NPV: 84.6% (combined), 76.9% (QTc), 70% (TWRS). .. Vicente et al. ( ) , Dofetilide (500 mcg) Quinidine (400 mg) Ranolazine (1500 mg) Verapamil (120 mg) 24 hr treatment period 7 day washout period Plasma drug level paired with ECG , 12 lead ECG (THEW): Baseline 15 time‐points postdose (0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 5, 6, 7, 8, 12, 14, 24 hr) Fridericia formula QTGuard+ automated TWM and vectorcardiographic biomarker analysis , ECG biomarkers: QT interval, QRS, J‐Tpeak interval, Tpeak–Tend interval TWM architectural patterns: Flatness, asymmetry, notching Vectorcardiographic biomarkers: ERD 30% , LRD 30% , QRS‐T angle, ventricular gradient, maximum magnitude of T vector, TCRT Patch clamp experiments: Ion channel block (hERG, late sodium, calcium) , Ion channel block: Dofetilide: 55% hERG Quinidine: 71% hERG, 8% calcium, 3% sodium Ranolazine: 26% hERG, 21% sodium Verapamil: 17% calcium, 7% hERG ΔQTc & TWM metrics: Dofetilide: ΔQTc 73.6 ms, flatness 0.16, asymmetry 0.25, notching 55% ( p < .001) Quinidine: ΔQTc 78.9 ms, flatness 0.21, asymmetry 0.34 ( p < .01), notching 69.7% ( p < .001) Ranolazine: ΔQTc 12 ms, flatness 0.06 ( p < .01), asymmetry 0.10, notching 1.4% ( p < .001) Vectorcardiographic biomarkers: ERD 30% , LRD 30% increase for dofetilide, quinidine, ranolazine QRS‐T angle decrease for dofetilide, quinidine TCRT decrease for dofetilide.
Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Hermans et al. ( ) , N/A , 12 lead ECG Bazett formula Automated ECG analysis software (MATLAB) , TW characterization: Hermite‐Gauss polynomials STT segment (1st order polynomials) Tpeak (2nd order polynomials) Machine learning: QTc cutoffs: >480 ms >450/460 ms (M/F) 99th percentile healthy subjects Models: Baseline (age, sex, QTc) Morphology (c 1 , c 2 , fitting error, age, sex) Extended (baseline and morphology features) QT expert: Cardiologist review ROC analysis (AUC, Sn, Sp) Youden's index Delong method (ROC comparison) , Extended model: 84% cLQTS classified correctly (QTc 400–460 ms) Accuracy: 84% (Amsterdam), 79% (Leuven) AUC > baseline>morphology models ( p < .001) Sn: 83% (Amsterdam), 75% (Leuven) Enhanced performance vs. QTc cutoffs QTc cutoffs: Accuracy: ≥480 ms: 62% (Amsterdam), 52% (Leuven) >450/460 ms: 72% (Amsterdam), 65% (Leuven) Sp: 99% (Amsterdam), 98% (Leuven) Sn: 24% (Amsterdam), 24% (Leuven) LQTS subtypes: Highest accuracy for LQT3 (extended model) QT expert: Accuracy: 79% (Leuven) Sn: 75% (Leuven) Sp: 86% (Leuven) Extended model comparison: 87% agreement. .. Hermans et al. ( ) , N/A , 12 lead ECG Bazett, Fridericia, Framingham, Hodges formulae Automated ECG analysis software (MATLAB) , Baseline model: Age, sex, RR‐interval, QT‐interval, QTc Extended model: Baseline model features TWM features Support network machine: Elastic net regularization (lasso and ridge regression) Mixing and tuning parameter (ROC analysis) Performance analysis: Maximal Youden's index (YI max ) = Sn + Sp ‐ 1 , AUC: Baseline model: 0.821 Extended model: 0.901 Maximal Youden's index: Baseline model: Sn 0.694, Sp 0.829 Extended model: Sn 0.820, Sp 0.861 QTc‐interval cut‐off values: Extended model: Reduction in false negative LQTS classification. .. Platonov et al. ( ) , N/A , 12 lead ECG Bazett formula Cardiologist review , TWM: Flat, notched, negative (leads II, V 5 ) Risk of cardiac events: Syncope, aborted cardiac arrest, defibrillator therapy, SCD , Distribution of abnormal TWM: Control: 55 LQT2: 64 Higher risk of cardiac events: Females with abnormal TWM (HR, 3.31; 95% CI, 1.68–6.52; p = .001) LQT2 men with pore‐located mutations vs. nonpore (HR, 6.01; 95% CI, 1.50–24.08; p = .011).
Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Moss et al. ( ) , n = 153 Six LQTS families U = 77 A = 76 Chromosome 3 ( n = 47) U = 28 A = 19 Chromosome 7 ( n = 30) U = 13 A = 17 Chromosome 11 ( n = 76) U = 36 A = 40 , Chromosome 3: Family 1: 20 ± 17 (U) 27 ± 20 (A) Family 2: 30 ± 19 (U) 19 ± 13 (A) Chromosome 7: Family 3: 35 ± 23 (U) 27 ± 17(A) Family 4: 29 ± 13 (U) 29 ± 24 (A) Chromosome 11: Family 5: 19 ± 19 (U) 15 ± 12 (A) Family 6: 24 ± 23 (U) 27 ± 25 (A) , Chromosome 3: (F/M) Family 1: 9/13 (U) 3/10 (A) Family 2: 4/2 (U) 2/4 (A) Chromosome 7: (F/M) Family 3: 1/2 (U) 4/1 (A) Family 4: 6/4 (U) 6/6 (A) Chromosome 11: (F/M) Family 5: 2/5 (U) 4/3 (A) Family 6: 17/12 (U) 23/10 (A) , Chromosome 3: Family 1: 417 ± 35 (U) 535 ± 46(A) Family 2: 420 ± 30 (U) 523 ± 40 (A) Chromosome 7: Family 3: 407 ± 12 (U) 502 ± 49 (A) Family 4: 410 ± 35 (U) 458 ± 51 (A) Chromosome 11: Family 5: 417 ± 49 (U) 514 ± 44 (A) Family 6: 416 ± 36 (U) 491 ± 43 (A) , LQTS family Genotype positive Control: healthy, genotype negative from same families Exclusion: congenital hearing loss, left cervicothoracic sympathetic ganglionectomy. .. Hermans et al. ( ) , N/A , 12 lead ECG Bazett formula Automated ECG analysis software (MATLAB) , TW characterization: Hermite‐Gauss polynomials STT segment (1st order polynomials) Tpeak (2nd order polynomials) Machine learning: QTc cutoffs: >480 ms >450/460 ms (M/F) 99th percentile healthy subjects Models: Baseline (age, sex, QTc) Morphology (c 1 , c 2 , fitting error, age, sex) Extended (baseline and morphology features) QT expert: Cardiologist review ROC analysis (AUC, Sn, Sp) Youden's index Delong method (ROC comparison) , Extended model: 84% cLQTS classified correctly (QTc 400–460 ms) Accuracy: 84% (Amsterdam), 79% (Leuven) AUC > baseline>morphology models ( p < .001) Sn: 83% (Amsterdam), 75% (Leuven) Enhanced performance vs. QTc cutoffs QTc cutoffs: Accuracy: ≥480 ms: 62% (Amsterdam), 52% (Leuven) >450/460 ms: 72% (Amsterdam), 65% (Leuven) Sp: 99% (Amsterdam), 98% (Leuven) Sn: 24% (Amsterdam), 24% (Leuven) LQTS subtypes: Highest accuracy for LQT3 (extended model) QT expert: Accuracy: 79% (Leuven) Sn: 75% (Leuven) Sp: 86% (Leuven) Extended model comparison: 87% agreement. .. Hermans et al. ( ) , N/A , 12 lead ECG Bazett, Fridericia, Framingham, Hodges formulae Automated ECG analysis software (MATLAB) , Baseline model: Age, sex, RR‐interval, QT‐interval, QTc Extended model: Baseline model features TWM features Support network machine: Elastic net regularization (lasso and ridge regression) Mixing and tuning parameter (ROC analysis) Performance analysis: Maximal Youden's index (YI max ) = Sn + Sp ‐ 1 , AUC: Baseline model: 0.821 Extended model: 0.901 Maximal Youden's index: Baseline model: Sn 0.694, Sp 0.829 Extended model: Sn 0.820, Sp 0.861 QTc‐interval cut‐off values: Extended model: Reduction in false negative LQTS classification.
Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Immanuel et al. ( ) , N/A , Holter ECG (THEW) Automated signal processing toolbox (MATLAB) , Frequency binned averaged ECGs and TW extraction (lead I) Boltzmann sigmoidal functions (upslope, downslope, switch) 9th order polynomial functions (upslope, downslope) Neural network classifiers Normal QTc subgroup analysis (400–450 ms) , TW parameters: Sigmoidal and polynomial classifiers LQTS subtypes>conventional parameters ( p < .0001) No difference control vs. LQTS ( p = .19) or LQT1 vs. LQT2 Neural network classifiers: Control vs. LQTS: 92% LQT1 vs. LQT2: 88% Normal QTc subgroup analysis: TWM: 90% QTC: 71%. .. Sugrue et al. ( ) , N/A , 12 lead ECG Bazett formula Automated TW analysis software (MATLAB) , Novel proprietary TW program Training and validation phases Manifest and concealed LQTS TW features vs. QTc Diagnostic accuracy: Sn, Sp, NPV, PPV , Discrimination accuracy TWM Lead V 6 : Manifest LQTS: 86.8% Concealed LQTS: 83.3% TW features: Tpeak‐Tend, left slope, COG x axis Sn: 83% (manifest), 76% (concealed) Sp: 91% (manifest), 91% (concealed) PPV: 90% (manifest), 89% (concealed) NPV: 84% (manifest), 79% (concealed). .. Vaglio et al. ( ) , N/A , 12 lead Holter ECG Bazett and Fridericia formulae Automated custom‐made algorithms , Scalar and vectorial repolarization parameters: QTpeak, Tpeak‐Tend interval, TW magnitude, T‐loop morphology, alpha‐R (right slope), alpha‐L (left slope) RI (derived from Hill equation) RI( t ) = V max × ( t n /[ k m n + t n ]) V max : total TW area K m : time when 50% TW area reached n : slope of the sigmoid RI , Discriminatory TWM biomarkers: QTpeak (lead II) Alpha‐R (Tpeak‐Tend) H‐R effect: H‐R bin 75–77.5 bpm: best discrimination H‐R range 60–100 bpm: 89% control, 84% LQT1, 92% LQT2 Bradycardia>tachycardia Scalar model: RR, QTpeak, Tpeak‐Tend, TW magnitude 90% discrimination with automated computer system (89% control, 90% LQT1, 92% LQT2) Vectorial model: Alpha‐R (vectorgraphic leads), QTpeak (lead II) 90% discrimination with automated computer system (92% control, 88% LQT1, 91% LQT2) RI: H‐R range 75 to 77.5 bpm Amplitude and morphology for LQT2 < LQT1 n ( p < .001) V max ( p < .018).
Control:Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Sugrue, Noseworthy, et al. ( ) , N/A , 12 lead ECG Bazett formula Automated QT‐alert system (QTc ≥500 ms) Cardiologist review , Novel proprietary TW program: TW left/right slope, TW amplitude, TW area, TW COG x/y coordinates, COG first 25% TW, COG last 25% of the TW, Tpeak–Tend interval Diagnostic accuracy: Sn, Sp, NPV, PPV Sensitivity analysis (age, sex) , aLQTS TWM biomarkers: Lead V 5 Shallower TW right slope (−2322 vs. −3593 mV/s; p < .001) Greater T‐peak‐Tend (109 vs. 92 ms; p < .001) Smaller TW COG (290 ms vs. 310 ms; p < .001) cLQTS vs. aLQTS: Lead V 5 distinguishes cLQTS from aLQTS in 77% cases Sn 90%, Sp 58%, PPV 83%, NPV 71% Sensitivity analysis: Age 78.3% No sex difference (M: 76%, F: 78%). .. Sugrue et al. ( ) , Sotalol Dofetilide , 12 lead ECG Bazett formula Automated TW analysis software (MATLAB) , Novel proprietary TW program QT interval and QTc Pre and post TdP ECG Risk prediction: Sn, Sp, NPV, PPV , Discrimination accuracy Lead V 3 : QTc discrimination ( p < .001, r = .72) Drug: 480 ms Control: 420 ms Lead I: TW right slope ( p = .002, r = .45) Torsadogenic risk prediction: ECG biomarkers TWRS: 88% QTc alone: 79% Risk prediction accuracy Sn: 92.1% (combined), 88.1% (QTc), 79.7% (TWRS) Sp: 81.4% (combined), 72% (QTc), 46% (TWRS) PPV: 90.3% (combined), 85% (QTc), 58.9% (TWRS) NPV: 84.6% (combined), 76.9% (QTc), 70% (TWRS). .. Vicente et al. ( ) , Dofetilide (500 mcg) Quinidine (400 mg) Ranolazine (1500 mg) Verapamil (120 mg) 24 hr treatment period 7 day washout period Plasma drug level paired with ECG , 12 lead ECG (THEW): Baseline 15 time‐points postdose (0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 5, 6, 7, 8, 12, 14, 24 hr) Fridericia formula QTGuard+ automated TWM and vectorcardiographic biomarker analysis , ECG biomarkers: QT interval, QRS, J‐Tpeak interval, Tpeak–Tend interval TWM architectural patterns: Flatness, asymmetry, notching Vectorcardiographic biomarkers: ERD 30% , LRD 30% , QRS‐T angle, ventricular gradient, maximum magnitude of T vector, TCRT Patch clamp experiments: Ion channel block (hERG, late sodium, calcium) , Ion channel block: Dofetilide: 55% hERG Quinidine: 71% hERG, 8% calcium, 3% sodium Ranolazine: 26% hERG, 21% sodium Verapamil: 17% calcium, 7% hERG ΔQTc & TWM metrics: Dofetilide: ΔQTc 73.6 ms, flatness 0.16, asymmetry 0.25, notching 55% ( p < .001) Quinidine: ΔQTc 78.9 ms, flatness 0.21, asymmetry 0.34 ( p < .01), notching 69.7% ( p < .001) Ranolazine: ΔQTc 12 ms, flatness 0.06 ( p < .01), asymmetry 0.10, notching 1.4% ( p < .001) Vectorcardiographic biomarkers: ERD 30% , LRD 30% increase for dofetilide, quinidine, ranolazine QRS‐T angle decrease for dofetilide, quinidine TCRT decrease for dofetilide.
Comparison:Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Moss et al. ( ) , n = 153 Six LQTS families U = 77 A = 76 Chromosome 3 ( n = 47) U = 28 A = 19 Chromosome 7 ( n = 30) U = 13 A = 17 Chromosome 11 ( n = 76) U = 36 A = 40 , Chromosome 3: Family 1: 20 ± 17 (U) 27 ± 20 (A) Family 2: 30 ± 19 (U) 19 ± 13 (A) Chromosome 7: Family 3: 35 ± 23 (U) 27 ± 17(A) Family 4: 29 ± 13 (U) 29 ± 24 (A) Chromosome 11: Family 5: 19 ± 19 (U) 15 ± 12 (A) Family 6: 24 ± 23 (U) 27 ± 25 (A) , Chromosome 3: (F/M) Family 1: 9/13 (U) 3/10 (A) Family 2: 4/2 (U) 2/4 (A) Chromosome 7: (F/M) Family 3: 1/2 (U) 4/1 (A) Family 4: 6/4 (U) 6/6 (A) Chromosome 11: (F/M) Family 5: 2/5 (U) 4/3 (A) Family 6: 17/12 (U) 23/10 (A) , Chromosome 3: Family 1: 417 ± 35 (U) 535 ± 46(A) Family 2: 420 ± 30 (U) 523 ± 40 (A) Chromosome 7: Family 3: 407 ± 12 (U) 502 ± 49 (A) Family 4: 410 ± 35 (U) 458 ± 51 (A) Chromosome 11: Family 5: 417 ± 49 (U) 514 ± 44 (A) Family 6: 416 ± 36 (U) 491 ± 43 (A) , LQTS family Genotype positive Control: healthy, genotype negative from same families Exclusion: congenital hearing loss, left cervicothoracic sympathetic ganglionectomy. .. Hermans et al. ( ) , N/A , 12 lead ECG Bazett formula Automated ECG analysis software (MATLAB) , TW characterization: Hermite‐Gauss polynomials STT segment (1st order polynomials) Tpeak (2nd order polynomials) Machine learning: QTc cutoffs: >480 ms >450/460 ms (M/F) 99th percentile healthy subjects Models: Baseline (age, sex, QTc) Morphology (c 1 , c 2 , fitting error, age, sex) Extended (baseline and morphology features) QT expert: Cardiologist review ROC analysis (AUC, Sn, Sp) Youden's index Delong method (ROC comparison) , Extended model: 84% cLQTS classified correctly (QTc 400–460 ms) Accuracy: 84% (Amsterdam), 79% (Leuven) AUC > baseline>morphology models ( p < .001) Sn: 83% (Amsterdam), 75% (Leuven) Enhanced performance vs. QTc cutoffs QTc cutoffs: Accuracy: ≥480 ms: 62% (Amsterdam), 52% (Leuven) >450/460 ms: 72% (Amsterdam), 65% (Leuven) Sp: 99% (Amsterdam), 98% (Leuven) Sn: 24% (Amsterdam), 24% (Leuven) LQTS subtypes: Highest accuracy for LQT3 (extended model) QT expert: Accuracy: 79% (Leuven) Sn: 75% (Leuven) Sp: 86% (Leuven) Extended model comparison: 87% agreement. .. Hermans et al. ( ) , N/A , 12 lead ECG Bazett, Fridericia, Framingham, Hodges formulae Automated ECG analysis software (MATLAB) , Baseline model: Age, sex, RR‐interval, QT‐interval, QTc Extended model: Baseline model features TWM features Support network machine: Elastic net regularization (lasso and ridge regression) Mixing and tuning parameter (ROC analysis) Performance analysis: Maximal Youden's index (YI max ) = Sn + Sp ‐ 1 , AUC: Baseline model: 0.821 Extended model: 0.901 Maximal Youden's index: Baseline model: Sn 0.694, Sp 0.829 Extended model: Sn 0.820, Sp 0.861 QTc‐interval cut‐off values: Extended model: Reduction in false negative LQTS classification.
Biomarker Discovery:Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Immanuel et al. ( ) , N/A , Holter ECG (THEW) Automated signal processing toolbox (MATLAB) , Frequency binned averaged ECGs and TW extraction (lead I) Boltzmann sigmoidal functions (upslope, downslope, switch) 9th order polynomial functions (upslope, downslope) Neural network classifiers Normal QTc subgroup analysis (400–450 ms) , TW parameters: Sigmoidal and polynomial classifiers LQTS subtypes>conventional parameters ( p < .0001) No difference control vs. LQTS ( p = .19) or LQT1 vs. LQT2 Neural network classifiers: Control vs. LQTS: 92% LQT1 vs. LQT2: 88% Normal QTc subgroup analysis: TWM: 90% QTC: 71%. .. Sugrue et al. ( ) , N/A , 12 lead ECG Bazett formula Automated TW analysis software (MATLAB) , Novel proprietary TW program Training and validation phases Manifest and concealed LQTS TW features vs. QTc Diagnostic accuracy: Sn, Sp, NPV, PPV , Discrimination accuracy TWM Lead V 6 : Manifest LQTS: 86.8% Concealed LQTS: 83.3% TW features: Tpeak‐Tend, left slope, COG x axis Sn: 83% (manifest), 76% (concealed) Sp: 91% (manifest), 91% (concealed) PPV: 90% (manifest), 89% (concealed) NPV: 84% (manifest), 79% (concealed). .. Vaglio et al. ( ) , N/A , 12 lead Holter ECG Bazett and Fridericia formulae Automated custom‐made algorithms , Scalar and vectorial repolarization parameters: QTpeak, Tpeak‐Tend interval, TW magnitude, T‐loop morphology, alpha‐R (right slope), alpha‐L (left slope) RI (derived from Hill equation) RI( t ) = V max × ( t n /[ k m n + t n ]) V max : total TW area K m : time when 50% TW area reached n : slope of the sigmoid RI , Discriminatory TWM biomarkers: QTpeak (lead II) Alpha‐R (Tpeak‐Tend) H‐R effect: H‐R bin 75–77.5 bpm: best discrimination H‐R range 60–100 bpm: 89% control, 84% LQT1, 92% LQT2 Bradycardia>tachycardia Scalar model: RR, QTpeak, Tpeak‐Tend, TW magnitude 90% discrimination with automated computer system (89% control, 90% LQT1, 92% LQT2) Vectorial model: Alpha‐R (vectorgraphic leads), QTpeak (lead II) 90% discrimination with automated computer system (92% control, 88% LQT1, 91% LQT2) RI: H‐R range 75 to 77.5 bpm Amplitude and morphology for LQT2 < LQT1 n ( p < .001) V max ( p < .018).
Diagnostic Assay:Article Title: The diagnostic role of T wave morphology biomarkers in congenital and acquired long QT syndrome: A systematic review
Article Snippet: Immanuel et al. ( ) , N/A , Holter ECG (THEW) Automated signal processing toolbox (MATLAB) , Frequency binned averaged ECGs and TW extraction (lead I) Boltzmann sigmoidal functions (upslope, downslope, switch) 9th order polynomial functions (upslope, downslope) Neural network classifiers Normal QTc subgroup analysis (400–450 ms) , TW parameters: Sigmoidal and polynomial classifiers LQTS subtypes>conventional parameters ( p < .0001) No difference control vs. LQTS ( p = .19) or LQT1 vs. LQT2 Neural network classifiers: Control vs. LQTS: 92% LQT1 vs. LQT2: 88% Normal QTc subgroup analysis: TWM: 90% QTC: 71%. .. Sugrue et al. ( ) , N/A , 12 lead ECG Bazett formula Automated TW analysis software (MATLAB) , Novel proprietary TW program Training and validation phases Manifest and concealed LQTS TW features vs. QTc Diagnostic accuracy: Sn, Sp, NPV, PPV , Discrimination accuracy TWM Lead V 6 : Manifest LQTS: 86.8% Concealed LQTS: 83.3% TW features: Tpeak‐Tend, left slope, COG x axis Sn: 83% (manifest), 76% (concealed) Sp: 91% (manifest), 91% (concealed) PPV: 90% (manifest), 89% (concealed) NPV: 84% (manifest), 79% (concealed). .. Vaglio et al. ( ) , N/A , 12 lead Holter ECG Bazett and Fridericia formulae Automated custom‐made algorithms , Scalar and vectorial repolarization parameters: QTpeak, Tpeak‐Tend interval, TW magnitude, T‐loop morphology, alpha‐R (right slope), alpha‐L (left slope) RI (derived from Hill equation) RI( t ) = V max × ( t n /[ k m n + t n ]) V max : total TW area K m : time when 50% TW area reached n : slope of the sigmoid RI , Discriminatory TWM biomarkers: QTpeak (lead II) Alpha‐R (Tpeak‐Tend) H‐R effect: H‐R bin 75–77.5 bpm: best discrimination H‐R range 60–100 bpm: 89% control, 84% LQT1, 92% LQT2 Bradycardia>tachycardia Scalar model: RR, QTpeak, Tpeak‐Tend, TW magnitude 90% discrimination with automated computer system (89% control, 90% LQT1, 92% LQT2) Vectorial model: Alpha‐R (vectorgraphic leads), QTpeak (lead II) 90% discrimination with automated computer system (92% control, 88% LQT1, 91% LQT2) RI: H‐R range 75 to 77.5 bpm Amplitude and morphology for LQT2 < LQT1 n ( p < .001) V max ( p < .018).
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