Methodological Evaluation of High-Density Fractionation Mapping Parameters for Cardioneuroablation: A Pilot Derivation and Validation Study

Methodological Evaluation of High-Density Fractionation Mapping Parameters for Cardioneuroablation: A Pilot Derivation and Validation Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Methodological Evaluation of High-Density Fractionation Mapping Parameters for Cardioneuroablation: A Pilot Derivation and Validation Study Juan F. Agudelo-Uribe, Rafael Correa-Velásquez, Juan D. Ramírez-Barrera, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8467859/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Cardioneuroablation (CNA) targets atrial ganglionated plexuses to treat vagally mediated bradyarrhythmias. Automated electrogram fractionation mapping has been proposed as a surrogate tool for ganglionated plexus localization; however, optimal software parameter settings for real-time use remain undefined. This study was designed as a methodological pilot investigation. Methods Data from a total of 28 patients were analyzed, including a prospective derivation cohort of 12 patients undergoing atrial fibrillation ablation in sinus rhythm and an independent validation cohort of 14 patients undergoing CNA. Using high-density electroanatomical mapping, three predefined values were tested for each fractionation parameter—signal width, refractoriness, and amplitude threshold—yielding 27 automated configurations. A purely anatomical localization strategy was also assessed, resulting in 28 total mapping configurations. All configurations were systematically generated for each patient in the derivation cohort, producing 336 fractionation maps and 870 ablation sites. Parasympathetic response during radiofrequency ablation was defined as an RR interval change > 10%, transient atrioventricular block, or sinus pause/asystole. The most sensitive configuration was subsequently applied to the validation cohort (614 ablation sites). Results In the derivation cohort, 25 of 27 automated parameter combinations showed significant association with parasympathetic response. The configuration with signal width 15 ms, refractoriness 25 ms, and amplitude threshold 0.05 mV was selected as the most sensitive. When applied to the validation cohort, this predefined configuration demonstrated preserved diagnostic performance, with a sensitivity of 74.1%, specificity of 73.9%, and negative predictive value of 94.9%. Fractionation-guided localization outperformed a purely anatomical approach. Conclusions This pilot study provides a reproducible methodological framework for evaluating automated fractionation mapping parameters associated with parasympathetic responses during CNA. These exploratory findings warrant prospective validation in larger cohorts. Cardioneuroablation Ganglionated plexus Fractionated electrograms Autonomic nervous system Electroanatomical mapping Figures Figure 1 Capsule Summary This pilot study provides a standardized methodological framework for automated fractionation mapping associated with parasympathetic responses during CNA. The findings are exploratory and hypothesis-generating, warranting prospective validation in larger cohorts to determine procedural and clinical relevance. Introduction The intrinsic cardiac autonomic nervous system comprises clusters of post-ganglionic parasympathetic neurons, known as ganglionated plexuses (GP) located mainly within the atrial walls or nearby para-cardiac regions.[ 1 , 2 ] Their discovery enabled the development of catheter-based techniques to selectively ablate GP and attenuate vagal influence.[ 3 , 4 ] It has been postulated that the proximity of GP affects local electrogram (EGM) characteristics, such as fractionation.[ 5 ] By using Fast Fourier Transform analysis Pachon et al described two types of myocardium: a compact myocardium demonstrating uniform and fast conduction properties and a fibrillar atrial myocardium demonstrating fragmented and heterogeneous conduction properties.[ 5 ] Thus, fibrillar potentials may be used as a surrogate marker to localize GP during electrophysiological study.[ 4 ] If GP can be localized, radiofrequency (RF) ablation on these sites may result in damage to both neuronal bodies and axons in the parasympathetic system.[ 4 ] In 2007, Lellouche et al. , analyzing regular bipolar signals, identified key characteristics of fractionated EGM associated with parasympathetic responses during ablation and thereby supporting GP localization.[ 6 ] However, their approach relied on subjective, off-line visual analysis and was not applicable in real time. Recently, automated fractionation mapping software integrated into three-dimensional (3D) electroanatomical mapping systems has enabled real-time detection of complex EGM patterns. [ 7 , 8 ] This software uses programmable parameters: signal width, amplitude threshold (referred to as “roving sensitivity” in the proprietary algorithm) and refractoriness, to define EGM fractionation, yet the optimal settings for localizing GP remain undetermined.[ 9 ] As a result, parameter selection has largely relied on empirical choices rather than systematic evaluation. In the present study we systematically tested multiple configurations of a fractionation mapping algorithm to identify the settings most closely associated with parasympathetic responses, with the aim of informing a reproducible methodological approach to GP localization. Patients undergoing atrial fibrillation ablation were intentionally selected in order to evaluate fractionation mapping performance across atrial regions with high likelihood of parasympathetic response, as well as regions where such responses were unlikely to occur, thereby enabling systematic assessment of both true-positive and true-negative sites. The best configuration was subsequently evaluated off-line in a separate group of patients undergoing cardioneuroablation, as an exploratory validation step. Methods Derivation cohort We prospectively analyzed EGM signals from 12 patients in their first paroxysmal atrial fibrillation (AF) radiofrequency (RF) ablation performed during sinus rhythm. This population was selected to allow evaluation of fractionation mapping across atrial regions both likely and unlikely to exhibit parasympathetic response. The entire protocol was approved by the local ethics committee. Informed consent was obtained from all patients prior to each procedure. A standard institutional protocol was followed in all cases. Exclusion criteria included moderate or severe left atrial enlargement (defined as a left atrial volume index ≥ 42 mL/m²) the development of a rhythm different than sinus at any time during the procedure and permanent pacing. Validation cohort Once the most sensitive combination of parameters was identified, a retrospective off-line analysis of EGM signals was conducted in 14 patients undergoing a cardioneuroablation procedure for functional bradycardia, functional atrioventricular block, or cardioinhibitory vasovagal syncope. Ablation sites were selected based on both the standard anatomical locations of major ganglionated plexuses and the visualized fractionation pattern obtained using predefined parameter values [ 10 ]: signal width 5 ms, refractoriness 30 ms, and amplitude threshold (roving sensitivity) 0.1 mV. Procedures In both cohorts, procedures were performed under general anesthesia. Patients then underwent electroanatomical mapping during sinus rhythm using the EnSite NavX™ Cardiac Mapping System (St. Jude Medical, Abbott. Sylmar, CA, USA) and a high-density multielectrode mapping catheter (Advisor™ HD Grid Mapping Catheter, Sensor Enabled™, Abbott, Minneapolis, MN, USA). Fractionation maps were acquired prior to any radiofrequency application, ensuring that EGM characteristics were not influenced by ablation lesions. Bipolar recordings were filtered between 30 and 300 Hz, with mapping parameters standardized at 7 mm for internal and external projections, 7 mm for interpolation, and 0.1 mV for low-voltage identification.[ 10 ] This filtering range and fractionation parameter framework are supported by prior electrogram-guided CNA studies, in which automated fractionation mapping using similar characteristics was shown to reliably identify GP regions during sinus rhythm.[ 10 ] In the derivation cohort pulmonary vein (PV) isolation was performed during sinus rhythm using an irrigated catheter (TactiCath™ or TactiFlex™ Ablation Catheter, Sensor Enabled™, Abbott, Minneapolis, MN, USA). All patients underwent wide-area circumferential ablation encircling the PVs. RF applications were delivered at a power of 35 Watts (W), reduced to 30 W in the posterior wall, with an endpoint lesion index (LSI) of 4.5 to 5 in the posterior wall and 5.5 in other walls. Cardiac cycle length (RR interval) and lesion locations were recorded before and after each application. In the validation cohort each GP was ablated during sinus rhythm based on its standard anatomical location and the location suggested by the fractionation software (signal width 5 ms, refractoriness 30 ms, and amplitude threshold (roving sensitivity) 0.1 mV). Cardiac cycle length (RR interval) and ablation sites were recorded before and after each radiofrequency application. Operators were not blinded to the fractionation maps during ablation. This approach reflects real-world procedural conditions and was considered appropriate given the exploratory and methodological nature of the study. In addition, as the validation cohort was retrospective, ablation was performed according to the GP locations suggested by the fractionation map using the predefined configuration described above. Off-line Analysis Once the map of each patient was obtained and stored, an off-line point-by-point analysis of RR response, transient AV block or sinus pauses, and corresponding fractionation mapping was performed. In the derivation cohort, for each patient, ten non-consecutive RR intervals (one every 10 beats) were measured before starting ablation to calculate the mean and the standard deviation (SD) of the RR interval under the conditions in which ablation will take place (anesthesia, catheter insertion and manipulation, etc.). During ablation, a parasympathetic response was considered present if any of the following occurred: an absolute change in RR interval exceeding 10%, transient asystole lasting more than 3 seconds, or a temporary complete atrioventricular block. The fractionation mapping software (EnSite NavX™ Cardiac Mapping System, St. Jude Medical, Abbott, Sylmar, CA, USA) allows adjustment of three parameters (see Fig. 1 ): width (5, 10, or 15 ms); amplitude threshold (0.05, 0.1, or 0.15 mV); and refractoriness (20, 25, or 30 ms). A combination of these parameters determines the number of deflections which, in turn identifies fractionation based on a predetermined threshold. Fractionation areas were visualized on the map using a color scale.[ 8 ] We systematically tested three predefined values for each parameter: Width (5, 10, or 15 ms), refractoriness (20, 25, or 30 ms), and amplitude threshold (0.05, 0.1, or 0.15 mV), resulting in 27 mapping configurations (Table 1 , supplementary material). For each combination map, each ablation point was reviewed to identify if fractionation was present and determine if a significant parasympathetic response occurred, as part of an off-line, exploratory point-by-point analysis. For schematic purposes, each PV antrum was divided into quadrants as follows: anterosuperior, anteroinferior, posterosuperior, and posteroinferior. An additional mapping configuration was created based on an anatomical approach. Ablation zones were delineated according to anatomical schemes proposed by Sun et al.[ 4 ] The effectiveness of this configuration was evaluated to assess the performance of a purely anatomical strategy. Table 1 Baseline characteristics of the population. Derivation cohort Validation cohort Patients (n) 12 14 Age (years) 60.1 +/- 11.1 30.9 +/- 11.6 Female (%) 33.3 71.4 Hypertension (%) 66.6 0 Sleep apnea (%) 8.3 0 Heart failure (%) 8.3 0 Ejection fraction (%) 55 +/- 8.5 63 +/- 3.1 LA volume (mL) 37.7 +/- 7.8 21.1 +/- 5.1 Maps analyzed 336 14 Maps analyzed per patient 28 1 Ablation points analyzed 870 614 Ablation points analyzed per patient 72.6 +/- 6.2 43.9 +/- 19.4 In the validation cohort fractionation mapping analysis was performed using just one automated software configuration (configuration #6), without visual or manual adjustment by the operators. Statistical Analysis For each of the 27 mapping configurations and for the anatomical configuration, a 2×2 contingency table (fractionation vs. parasympathetic response) was created.[ 4 ] Chi-square tests were performed for each configuration, with p < 0.05 considered significant. Given the pilot nature of the study, statistical analyses were intended to explore associations and performance trends rather than to formally compare configurations using advanced comparative modeling. The statistical analysis was performed on a point-by-point basis, considering each ablation site as an individual data entry. This approach allowed the generation of a large analytical dataset despite the relatively small number of patients. As a result, meaningful associations between fractionation parameters and parasympathetic responses could be identified, achieving statistical significance even within the framework of a pilot study. Despite including points outside known GP regions, we opted to analyze all mapping sites to enhance statistical power and better assess the global performance of fractionation parameters. This strategy was chosen to evaluate global parameter performance rather than restrict the analysis to predefined anatomical regions. For configurations with significant association, sensitivity, specificity, and predictive values (95% CI) were calculated. Continuous variables were expressed as mean ± SD, categorical variables as numbers or percentages. Statistical analysis was performed using Microsoft Excel™ for Mac (version 16.84), IBM SPSS Statistics™ (version 29.0.2.0), and Calcupedev Version 11. Results Derivation cohort An analysis of 870 ablation sites from 12 patients (mean age 60.17 ± 11.14 years; 33% female) with an average of 72.5 sites per patient was performed. Patient characteristics are detailed in Table 1 . For each patient, ten non-consecutive RR interval measurements were taken before any RF application. The average basal RR interval was 1166 ms with a mean SD of 39.78 ms. Thus, the mean SD variation (or coefficient of variation = SD/mean x100) was 3.41% of the baseline RR interval. Since a deviation of more than double the SD of the RR interval was deemed indicative of parasympathetic response, RR intervals exceeding 6.62% of the mean RR interval would indicate a parasympathetic response. To ensure that a parasympathetic response had occurred and to provide a standardized criterion in accordance with a previous publication, a variation of more than 10% in the RR interval was used as an indicator of abnormal response. [ 11 ] Accordingly, 27 parameter combinations and empirical anatomical ablation area map were analyzed for each ablation site. Table 2 shows sensitivity, specificity, and predictive values for the 25 significant configurations, as well as the purely anatomical configuration (non-significant). Sensitivity ranged 21–76%, and specificity 47–89%. Table 2 Sensitivity, Specificity and predictive values for each configuration. Combination (Width in ms – refractoriness in ms – amplitude threshold in mV) p value Sensitivity (95%CI) Specificity (95%CI) +PV (95%CI) -PV (95%CI) Derivation cohort Anatomy (non-significative.) 0.815 31.4 (18.6–44.1) 47.4 (43.9–50.8) 3.6 (1.85–5) 91.72 (89.1–94.3) #1: 5–20–0.05 0.012 62.7 (49.5–76.0) 55.3 (51.9–58.7) 8 (5.4–10.7) 96 (94.2–97.7) #2: 10–20 − 0.05 0.001 74.5 (62.5–86.5) 51.6 (48.2–55.1) 8.7 (6.1–11.4) 97 (95.4–98.6) #3: 15–20–0.05 0.002 74.5 (62.5–86.5) 47.7 (44.3–51.2) 8.1 (5.7–10.6) 96.8 (95.1–98.5) #4: 5–25–0.05 0.001 64.7 (51.6–77.8) 64.1 (60.8–67.4) 10.1 (6.8–13.3) 96.7 (95.2–98.2) #5: 10–25 − 0.05 0.001 72.5 (60.4–85) 57.0 (53.6–60.4) 9.5 (6.6–12.4) 97.1 (95.6–98.6) #6: 15–25 − 0.05 0.001 76.5* (64.8–88.1) 53.6 (50.2–57.0) 9.3 (6.5–12.1) 97.3* (95.8–98.8) #7: 5–30 − 0.05 0.002 49.0 (35.3–62.7) 71.1 (67.9–74.2) 9.5 (6–13.1) 95.7 (94.1–97.3) #8: 10–30 − 0.05 0.002 56.9 (43.3–70.5) 64.9 (61.7–68.2) 9.2 (6–12.4) 96 (94.4–97.6) #9: 15–30 − 0.05 0.010 56.9 (43.3–70.5) 61.4 (58.1–64.7) 8.4 (5.47–11.33) 95.8 (94.1–97.5) #10 5–20 − 0.1 0.011 58.8 (45.3–72.3) 59.2 (55.8–62.6) 8.2 (5.4–11.1) 95.8 (94.1–97.6) #11: 10–20 − 0.1 0.017 64.7 (51.6–77.8) 52.5 (49.1–55.9) 7.82 (5.2–10.4) 96 (94.2–98) #13: 5–25 − 0.1 0.004 49.0 (35.3–62.7) 70.1 (66.9–73.2) 9.2 (5.8–12.7) 95.7 (94–97.3) #14: 10–25 − 0.1 0.0001 68.6 (55.9–81.4) 64.8 (61.6–68.1) 10.8 (7.4–14.2) 97.1 (95.7–98.5) #15: 15–25 − 0.1 0.0001 66.7 (53.7–79.6) 59.8 (56.5–63.2) 9.4 (6.4–12.4) 96.6 (95.1–98.2) #16: 5–30 − 0.1 0.0001 45.1 (31.4–58.8) 80.5 (77.5–83.2) 12.6 (7.8–17.4) 95.9 (94.4–97.4) #17: 10–30 − 0.1 0.0001 49.0 (35.3–62.7) 76.7 (73.8–79.6) 11.6 (7.3–15.8) 96 (94.5–97.5) #18: 15–30 − 0.1 0.0001 50.9 (37.3–64.7) 74.3 (71.4–77.3) 11 (7–15) 96 (94.5–97.6) #20: 10–20 − 0.15 0.01 60.8 (47.4–74.2) 56.9 (53.4–60.3) 8.1 (5.4–10.9) 95.8 (94–97.6) #21: 15–20 − 0.15 0.005 64.7 (51.6–77.8) 55.5 (52.1–58.9) 8.3 (5.6–11) 96.2 (94.5–97.9) #22: 5–25 − 0.15 0.0001 45.1 (31.4–58.8) 80.6 (77.9–83.3) 12.6* (7.8–17.5) 95.93 (94.45–97.4) #23: 10–25 − 0.15 0.0001 54.9 (41.2–68.6) 68.6 (65.4–71.8) 9.8 (6.4–13.3) 96.1 (94.5–97.6) #24: 15–25 − 0.15 0.0001 64.7 (51.6–77.8) 64 (60.7–67.3) 10.1 (6.8–13.3) 96.7 (95.2–98.2) #25: 5–30 − 0.15 0.016 21.6 (10.3–32.9) 89.4* (87.3–91.5) 11.2 (5–17.5) 94.8 (93.2–96.4) #26: 10–30 − 0.15 0.0001 39.2 (25.2–52.6) 82.5 (79.9–85.1) 12.3 (7.2–17.3) 95.6 (94.1–97.1) #27: 15–30 − 0.15 0.0001 45.1 (31.4–58.8) 77.5 (74.7–80.4) 11.1 (6.8–15.4) 95.8 (94.2–97.3) Validation cohort #6: 15–25 − 0.05 0.001 74.1 63.6–82.4 73.9 (70–77.5) 30.1 (24.2–36.8) 94.9 (92.4–96.7) Except for anatomy, non – significative combinations were not shown. Abbreviations: CI: confidence interval; +PV: positive predictive value; -PV: negative predictive value; * best value. Across parameter subsets, sensitivity varied according to refractoriness and amplitude threshold, but not width (Table 2 , supplementary material). The highest sensitivity was obtained with refractoriness 20 ms and amplitude threshold 0.05 mV; width 15 ms performed numerically best but did not differ statistically from 10 ms. As expected, specificity varied inversely with sensitivity. Spatially, sites with parasympathetic responses most commonly localized to the right superior-anterior quadrant (9.4%) and the left anterosuperior and anteroinferior quadrants (11.3% each), consistent with the anatomical distribution of right anterior GP and left lateral/Marshall-area GP, respectively (Table 3 , supplementary material).[ 4 ] In total, 61/870 sites (7.01%) exhibited a parasympathetic response. Table 3 comparison of sensitivity, specificity, positive and negative predictive values. HAFE pattern (95%CI) [ 6 ] Present study Derivation cohort (best combination) (95%CI) Validation cohort (95%CI) a Sensitivity (%) 72 (49.4–94.5) 76.4 a (64.8–88.1) 74.1 (63.6–82.4) Specificity (%) 91 (85.2–97.2) 89.3 b (87.2–91.4) 73.9 (70–77.5) Positive predictive value (%) 51 CI non reported 12.6 c (7.8–17.4) 30.1 (24.2–36.8) Negative predictive value (%) 96 CI non reported 97.3 a (95.8–98.8) 94.9 (92.4–96.7) a. Width 15 ms; refractoriness 25 ms; amplitude threshold 0.05 mV. b. Width 5 ms; refractoriness 30 ms; amplitude threshold 0.15 mV. c. Width 5 ms; refractoriness 25 ms; amplitude threshold 0.15 mV. Validation cohort The validation cohort included 14 patients (mean age 30.9 ± 11.6 years; 71.4% female). The most common clinical indication was functional bradycardia (57%). On average, 43.9 ablation points were delivered per patient. Mean heart rate increased from 61.8 bpm pre-procedure to 88.4 bpm post-procedure (Table 1 ). Using the most sensitive parameter set from derivation cohort (configuration #6: width 15 ms, refractoriness 25 ms, amplitude threshold 0.05 mV), the association between fractionation and parasympathetic response remained significant (χ²=73.93). Sensitivity was 74.1% (95% CI 63.6–82.4), specificity 73.9% (95% CI 70–77.5), positive predictive value 30.1% (95% CI 24.2–36.8), and negative predictive value 94.9% (95% CI 92.4–96.7) (Table 2 ). Restricting analysis to the first lesion per GP per patient (to account for physiologic modification after initial RF) increased sensitivity to 82.35% and NPV to 88%, with a tradeoff in specificity (57.5%) and PPV (45.2%) (χ²=7.63; p = 0.006). Exploratory clinical observations Although not a predefined endpoint of the study, exploratory clinical follow-up data were collected in the validation cohort. During follow-up after CNA procedure, mean annualized presyncopal episodes per patient decreased from 120.39 pre-procedure to 10.24 events/year post-procedure. Annualized syncope rates decreased from 26.75 to 0.71 events/year. Reductions were statistically significant for both presyncope (p = 0.003) and syncope (p = 0.007) per Wilcoxon signed-rank test, with no increases in any patient. Discussion Main findings This study analyzed parameters from an automated fractionation mapping software in relation to parasympathetic responses during pulmonary vein isolation procedures in a derivation cohort and subsequently evaluated the performance of the selected parameters in an independent validation cohort of patients undergoing CNA procedures. Key findings are: (1) multiple parameter combinations, but not all, were significantly associated with parasympathetic responses; (2) within tested values, lower amplitude threshold and shorter refractoriness improved sensitivity; width showed a non-significant trend favoring values between 10 and 15 ms; (3) an anatomically guided approach showed non-significant association; and (4) the association between fractionation and parasympathetic response was preserved in a validation cohort using the most sensitive configuration. Compared with a purely anatomical ablation strategy, the selected fractionation configuration demonstrated higher sensitivity and negative predictive value, supporting its potential utility as real-time procedure aid. Peculiarities of the study design We intentionally selected paroxysmal AF patients with non-severe atrial dilatation in sinus rhythm for the derivation cohort, allowing systematic sampling of atrial regions both likely and unlikely to harbor GP and balancing positive/negative sites for analysis. By minimizing fibrosis-related fractionation and standardizing anesthesia protocol, we optimized detection of software configurations associated with GP localization. Our definition of parasympathetic response accounts for established observations that both[ 12 ] heart rate slowing and paradoxical acceleration may occur during acute vagal modulation, particularly during ablation near the right anterior GP.[ 13 ] In validation cohort, the pretest probability of parasympathetic response was higher because ablation was restricted to presumed GP regions; accordingly, the proportion of positive sites increased from 7.34% to 13.19%. Despite this, the fractionation–response association remained significant, supporting generalizability to CNA. Amplitude threshold (formerly “roving sensitivity”) and refractoriness were the parameters most strongly associated with detection of parasympathetic responses. Lower amplitude thresholds (≈ 0.05 mV) likely facilitate identification of low-voltage, high-frequency deflections commonly observed in regions of autonomic innervation; shorter refractory periods (≈ 20 ms) may allow counting of closely spaced deflections within fragmented electrograms. Together, these observations are consistent with the hypothesis that low‑amplitude, high‑frequency EGM are preferentially encountered near autonomically innervated atrial regions. Lellouche et al.[ 6 ] described a high-amplitude fractionation electrogram (HAFE) pattern associated with parasympathetic responses based on off-line visual analysis using conventional ablation catheter. A comparison between approaches can be founded in Supplementary table 4. Aksu and colleagues[ 8 ] demonstrated the feasibility of software-based fractionation mapping during sinus rhythm, although parameter choices were arbitrary. A recent multicenter study[ 14 ] reported an association between a greater number of RF applications and improved clinical outcomes after CNA irrespective of PG localization technique. This observation is consistent with the notion that extensive ablation may partially compensate for imperfect localization strategies. Although our software could not distinguish HAFE and LAFE, fractionation correlated with parasympathetic responses across most configurations. In typical CNA populations without structural disease, fibrosis‑ related LAFE is less likely to confound results 6 . To prioritize sensitivity and NPV intra‑procedurally, we favor configurations with shorter refractoriness (≈ 20 ms) and lower amplitude threshold (≈ 0.05 mV). Notably, PPV remained suboptimal, underscoring the need for improved tools. See Table 3 . Although the negative predictive value was high, the relatively low positive predictive value (~ 30%) indicates that fractionation alone may be insufficient to reliably predict parasympathetic response. This finding underscores the role of fractionation mapping as a complementary intraprocedural tool rather than a standalone determinant of ablation targets. Limitations This pilot exploratory study has a relatively small sample size, limiting precision of performance estimates, particularly for specificity and PPV. Findings were derived using a single mapping system and may not be directly generalizable to other software platforms employing different signal acquisition and processing algorithms. Fractionated EGMs may also reflect mechanisms other than autonomic innervation, including localized fibrosis, PV potentials, inter‑atrial signal overlap, or slow conduction (e.g., AV nodal slow pathway).[ 9 ] In typical CNA patients treated for reflex syncope, significant fibrosis is less likely; however, these mechanisms cannot be fully excluded. Voltage data in relation to fractionation and parasympathetic responses was not systematically analyzed in this study and represents an additional limitation. The derivation cohort consisted of patients undergoing pulmonary vein isolation for paroxysmal atrial fibrillation rather than typical candidates for CNA. Although this population does not fully represent patients with functional bradyarrhythmias or reflex syncope, it was intentionally selected to enable systematic assessment of fractionation patterns in atrial regions both proximal and remote from the usual anatomic locations of GP. Restricting inclusion to individuals with non-severe atrial dilatation further allowed approximation of electrophysiological substrate encountered in CNA while facilitating balanced evaluation of present and absent parasympathetic response sites. As an exploratory methodological study, these findings require confirmation in larger, prospective cohorts to determine whether parameter-guided fractionation mapping translates into improved procedural or clinical outcomes after CNA procedures. Conclusion Specific parameter configurations for automated fractionation mapping, when combined with high-density electroanatomical mapping, were associated with identification of atrial sites exhibiting parasympathetic responses during radiofrequency ablation. Findings derived from a prospective atrial fibrillation cohort were subsequently evaluated in an independent, real-world CNA population. The consistent association between software-defined fractionation and parasympathetic response supports further investigation of this approach in larger prospective studies. Given the relatively small sample size in both cohorts—particularly the validation group—these findings should be considered exploratory, and the precision of sensitivity, specificity and predictive value estimates is limited, warranting confirmation in larger prospective studies. See Central graphical figure. Declarations Ethics approval All procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study protocol was reviewed and approved by the institutional ethics committee of CardioVID Clinic. Consent to participate Informed consent was obtained from all individual participants included in this study. Competing interests Juan F. Agudelo-Uribe reports receiving modest honoraria from Abbott Medical Colombia for proctoring electrophysiology procedures, lectures, and scientific presentations. Juan D. Ramírez Barrera declares no competing interests. Rafael Correa-Velásquez declares no competing interests. Margarita Londoño-Arango is an employee of Abbott Medical Colombia. Teresa Barrio-López declares no competing interests. Jesús Almendral declares no competing interests. Funding No specific funding was received for conducting this study or for the preparation of this manuscript. Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Authors’ contributions The initial conception of the study was performed by Jesús Almendral and Teresa Barrio-López. Final study design was developed by Juan F. Agudelo-Uribe, Jesús Almendral, and Rafael Correa-Velásquez. Data collection was carried out by Juan F. Agudelo-Uribe, Juan D. Ramírez Barrera, and Rafael Correa-Velásquez. Data analysis was performed by Juan F. Agudelo-Uribe and Margarita Londoño-Arango. The first draft of the manuscript was written by Juan F. Agudelo-Uribe, and critical revisions were performed by Jesús Almendral and Teresa Barrio-López. All authors reviewed and approved the final version of the manuscript. References Armour JA, Murphy DA, Yuan BX, Macdonald S, Hopkins DA. Gross and microscopic anatomy of the human intrinsic cardiac nervous system. Anat Rec. 1997;247:289–98. https://doi.org/10.1002/(SICI)1097-0185(199702)247:2%3C289::AID-AR15%3E3.0.CO;2-L . Randall WC, Milosavljevic M, Wurster RD, Geis GS, Ardell JL. Selective vagal innervation of the heart. Ann Clin Lab Sci 1986;16. Scanavacca M, Hachul D, Pisani C, Sosa E. Selective vagal denervation of the sinus and atrioventricular nodes, guided by vagal reflexes induced by high frequency stimulation, to treat refractory neurally mediated syncope. J Cardiovasc Electrophysiol. 2009;20:558–63. https://doi.org/10.1111/j.1540-8167.2008.01385.x . Sun W, Zheng L, Qiao Y, Shi R, Hou B, Wu L, et al. Catheter Ablation as a Treatment for Vasovagal Syncope: Long-Term Outcome of Endocardial Autonomic Modification of the Left Atrium. J Am Heart Assoc. 2016;5. https://doi.org/10.1161/JAHA.116.003471 . Pachon MJC, Pachon M, EI, Pachon MJC, Lobo TJ, Pachon MZ, Vargas RNA, et al. Cardioneuroablation - New treatment for neurocardiogenic syncope, functional AV block and sinus dysfunction using catheter RF-ablation. Europace. 2005;7:1–13. https://doi.org/10.1016/j.eupc.2004.10.003 . Lellouche N, Buch E, Celigoj A, Siegerman C, Cesario D, De Diego C, et al. Functional Characterization of Atrial Electrograms in Sinus Rhythm Delineates Sites of Parasympathetic Innervation in Patients With Paroxysmal Atrial Fibrillation. J Am Coll Cardiol. 2007;50:1324–31. https://doi.org/10.1016/j.jacc.2007.03.069 . Aksu T, Guler TE. Electroanatomical mapping-guided ablation during atrial fibrillation: a novel usage of fractionation mapping in a case with sinus bradycardia and paroxysmal atrial fibrillation. J Interventional Cardiac Electrophysiol. 2020;57:331–2. https://doi.org/10.1007/s10840-019-00633-9 . Aksu T, Yalin K, Gopinathannair R. Fractionation mapping software to map ganglionated plexus sites during sinus rhythm. J Cardiovasc Electrophysiol. 2020;31:3326–9. https://doi.org/10.1111/jce.14753 . Aksu T, Brignole M, Calo L, Debruyne P, Biase L, Di, Deharo JC et al. Cardioneuroablation for the treatment of reflex syncope and functional bradyarrhythmias: A Scientific Statement of the European Heart Rhythm Association (EHRA) of the ESC, the Heart Rhythm Society (HRS), the Asia Pacific Heart Rhythm Society (APHRS) and the Latin American Heart Rhythm Society (LAHRS). Europace 2024;26. https://doi.org/10.1093/europace/euae206 Aksu T, Gupta D, D’Avila A, Morillo CA. Cardioneuroablation for vasovagal syncope and atrioventricular block: A step-by-step guide. J Cardiovasc Electrophysiol. 2022;33:2205–12. https://doi.org/10.1111/jce.15480 . Nunan D, Sandercock GRH, Brodie DA. A quantitative systematic review of normal values for short-term heart rate variability in healthy adults. PACE - Pacing Clin Electrophysiol. 2010;33:1407–17. https://doi.org/10.1111/j.1540-8159.2010.02841.x . Chiou CW, Eble JN, Zipes DP. Efferent vagal innervation of the canine atria and sinus and atrioventricular nodes: The third fat pad. Circulation. 1997;95:2573–84. https://doi.org/10.1161/01.CIR.95.11.2573 . Hu F, Zheng L, Liang E, Ding L, Wu L, Chen G, et al. Right anterior ganglionated plexus: The primary target of cardioneuroablation? Heart Rhythm. 2019;16:1545–51. https://doi.org/10.1016/j.hrthm.2019.07.018 . Barrio-Lopez MT, Álvarez-Ortega C, Minguito-Carazo C, Franco E, García-Granja PE, Alcalde-Rodríguez Ó, et al. Predictors of Clinical Success of Cardioneuroablation in Patients With Syncope. JACC Clin Electrophysiol. 2024. https://doi.org/10.1016/j.jacep.2024.07.027 . Additional Declarations Competing interest reported. Juan F. Agudelo-Uribe reports receiving modest honoraria from Abbott Medical Colombia for proctoring electrophysiology procedures, lectures, and scientific presentations. Juan D. Ramírez Barrera declares no competing interests. Rafael Correa-Velásquez declares no competing interests. Margarita Londoño-Arango is an employee of Abbott Medical Colombia. Teresa Barrio-López declares no competing interests. Jesús Almendral declares no competing interests. Supplementary Files supplementmaterialJICEdec2025.docx graphicabstractJICEdec2025.jpg Central graphical Figure : This central illustration summarizes the two-phase methodological workflow of the study. In the derivation cohort, patients undergoing pulmonary vein isolation for atrial fibrillation underwent high-density electroanatomical mapping in sinus rhythm, allowing systematic evaluation of 27 automated fractionation parameter configurations, plus anatomical approach in relation to parasympathetic responses during radiofrequency ablation. Parasympathetic response was defined by RR interval increase >10%, transient atrioventricular block, or sinus pause/asystole, and the most sensitive parameter configuration was selected. This predefined configuration was subsequently applied in an independent, real-world validation cohort of patients undergoing cardioneuroablation, demonstrating preservation of the fractionation–response association and diagnostic performance. Overall, the figure illustrates a standardized methodological framework to support identification of atrial sites associated with parasympathetic response during cardioneuroablation. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8467859","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571636176,"identity":"3577fac2-7665-4d62-ba31-de69f5b3e9e2","order_by":0,"name":"Juan F. Agudelo-Uribe","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYBACxgYgwcNgwcDA3sBwgIcELRJA4gCRWsAArEUiAcQgAjC3H78m8aZCQs7g5hvDA28YbPLlHZgfPsDrsJ6cMsk5ZySMDW7nGBycw5BmufEAm7EBXi0NOWnSvG0SiRtupyUc5mE4bGDYwMMmgVdL/xugln9ALTePEatlRvoxad4GoJYbzAfAWuQZCGp5w2w555iEseSZ5AMH5xikGRgwE/CLYX/6wxtvamzk+I4fbP7wpsLGQL69GX+IAV2ObCSQbXAYn3ogkGdgRzNSvoGAllEwCkbBKBhxAAADVEfwg2zcawAAAABJRU5ErkJggg==","orcid":"","institution":"CardioVID Clinic","correspondingAuthor":true,"prefix":"","firstName":"Juan","middleName":"F.","lastName":"Agudelo-Uribe","suffix":""},{"id":571636179,"identity":"e9208cc2-a3fc-49ca-959c-4ed19036ec96","order_by":1,"name":"Rafael Correa-Velásquez","email":"","orcid":"","institution":"CardioVID Clinic","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"","lastName":"Correa-Velásquez","suffix":""},{"id":571636181,"identity":"463a345f-57d1-4965-b1fa-a3d6c8b1156f","order_by":2,"name":"Juan D. 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1","display":"","copyAsset":false,"role":"figure","size":161479,"visible":true,"origin":"","legend":"\u003cp\u003eDefinitions and schematic of fractionation mapping algorithm parameters:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMaximum Width:\u003c/em\u003e maximum time allowed from the start of deflection until its return to isoelectric line to be counted as one deflection for the calculation of fractionation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAmplitude threshold:\u003c/em\u003e (Roving sensitivity) The minimum voltage amplitude required for a deflection to be counted as a fractionation. Set to just above the base line noise to eliminate any EGM noise from being mistaken as a fractionation.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRefractory:\u003c/em\u003e the minimum time allowed from start of one deflection until a second deflection may be counted. Is a sort of blanking period to prevent new detections (double counting) for a specified time after detection has occurred.[7]\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8467859/v1/7aba5964006aee84efd6a57b.png"},{"id":103472673,"identity":"0505cd42-2da7-4557-ad65-d5dfc70a6532","added_by":"auto","created_at":"2026-02-26 06:11:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1021588,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8467859/v1/3616aefc-5b95-45a5-8123-14abe462f746.pdf"},{"id":100361855,"identity":"a43f2054-ad07-4469-9d9b-d80778783b62","added_by":"auto","created_at":"2026-01-16 07:45:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33926,"visible":true,"origin":"","legend":"","description":"","filename":"supplementmaterialJICEdec2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-8467859/v1/4a8e084d83f0cd73ca6acc35.docx"},{"id":100362297,"identity":"391dd94f-267b-4f93-8e2d-92256f3a3d72","added_by":"auto","created_at":"2026-01-16 07:46:32","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":394223,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCentral graphical Figure : \u003c/strong\u003eThis central illustration summarizes the two-phase methodological workflow of the study. In the derivation cohort, patients undergoing pulmonary vein isolation for atrial fibrillation underwent high-density electroanatomical mapping in sinus rhythm, allowing systematic evaluation of 27 automated fractionation parameter configurations, plus anatomical approach in relation to parasympathetic responses during radiofrequency ablation. Parasympathetic response was defined by RR interval increase \u0026gt;10%, transient atrioventricular block, or sinus pause/asystole, and the most sensitive parameter configuration was selected. This predefined configuration was subsequently applied in an independent, real-world validation cohort of patients undergoing cardioneuroablation, demonstrating preservation of the fractionation–response association and diagnostic performance. Overall, the figure illustrates a standardized methodological framework to support identification of atrial sites associated with parasympathetic response during cardioneuroablation.\u003c/p\u003e","description":"","filename":"graphicabstractJICEdec2025.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8467859/v1/1ff4d806eb2adc9f242baf74.jpg"}],"financialInterests":"Competing interest reported. Juan F. Agudelo-Uribe reports receiving modest honoraria from Abbott Medical Colombia for proctoring electrophysiology procedures, lectures, and scientific presentations.\nJuan D. Ramírez Barrera declares no competing interests.\nRafael Correa-Velásquez declares no competing interests.\nMargarita Londoño-Arango is an employee of Abbott Medical Colombia.\nTeresa Barrio-López declares no competing interests.\nJesús Almendral declares no competing interests.","formattedTitle":"Methodological Evaluation of High-Density Fractionation Mapping Parameters for Cardioneuroablation: A Pilot Derivation and Validation Study","fulltext":[{"header":"Capsule Summary","content":"\u003cp\u003eThis pilot study provides a standardized methodological framework for automated fractionation mapping associated with parasympathetic responses during CNA. The findings are exploratory and hypothesis-generating, warranting prospective validation in larger cohorts to determine procedural and clinical relevance.\u003c/p\u003e\n"},{"header":"Introduction","content":"\u003cp\u003eThe intrinsic cardiac autonomic nervous system comprises clusters of post-ganglionic parasympathetic neurons, known as ganglionated plexuses (GP) located mainly within the atrial walls or nearby para-cardiac regions.[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Their discovery enabled the development of catheter-based techniques to selectively ablate GP and attenuate vagal influence.[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] It has been postulated that the proximity of GP affects local electrogram (EGM) characteristics, such as fractionation.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] By using Fast Fourier Transform analysis Pachon \u003cem\u003eet al\u003c/em\u003e described two types of myocardium: a compact myocardium demonstrating uniform and fast conduction properties and a fibrillar atrial myocardium demonstrating fragmented and heterogeneous conduction properties.[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] Thus, fibrillar potentials may be used as a surrogate marker to localize GP during electrophysiological study.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] If GP can be localized, radiofrequency (RF) ablation on these sites may result in damage to both neuronal bodies and axons in the parasympathetic system.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] In 2007, Lellouche \u003cem\u003eet al.\u003c/em\u003e, analyzing regular bipolar signals, identified key characteristics of fractionated EGM associated with parasympathetic responses during ablation and thereby supporting GP localization.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] However, their approach relied on subjective, off-line visual analysis and was not applicable in real time.\u003c/p\u003e \u003cp\u003eRecently, automated fractionation mapping software integrated into three-dimensional (3D) electroanatomical mapping systems has enabled real-time detection of complex EGM patterns. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] This software uses programmable parameters: signal width, amplitude threshold (referred to as \u0026ldquo;roving sensitivity\u0026rdquo; in the proprietary algorithm) and refractoriness, to define EGM fractionation, yet the optimal settings for localizing GP remain undetermined.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] As a result, parameter selection has largely relied on empirical choices rather than systematic evaluation.\u003c/p\u003e \u003cp\u003e In the present study we systematically tested multiple configurations of a fractionation mapping algorithm to identify the settings most closely associated with parasympathetic responses, with the aim of informing a reproducible methodological approach to GP localization. Patients undergoing atrial fibrillation ablation were intentionally selected in order to evaluate fractionation mapping performance across atrial regions with high likelihood of parasympathetic response, as well as regions where such responses were unlikely to occur, thereby enabling systematic assessment of both true-positive and true-negative sites. The best configuration was subsequently evaluated off-line in a separate group of patients undergoing cardioneuroablation, as an exploratory validation step.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDerivation cohort\u003c/h2\u003e \u003cp\u003eWe prospectively analyzed EGM signals from 12 patients in their first paroxysmal atrial fibrillation (AF) radiofrequency (RF) ablation performed during sinus rhythm. This population was selected to allow evaluation of fractionation mapping across atrial regions both likely and unlikely to exhibit parasympathetic response. The entire protocol was approved by the local ethics committee. Informed consent was obtained from all patients prior to each procedure. A standard institutional protocol was followed in all cases. Exclusion criteria included moderate or severe left atrial enlargement (defined as a left atrial volume index\u0026thinsp;\u0026ge;\u0026thinsp;42 mL/m\u0026sup2;) the development of a rhythm different than sinus at any time during the procedure and permanent pacing.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eValidation cohort\u003c/h3\u003e\n\u003cp\u003eOnce the most sensitive combination of parameters was identified, a retrospective off-line analysis of EGM signals was conducted in 14 patients undergoing a cardioneuroablation procedure for functional bradycardia, functional atrioventricular block, or cardioinhibitory vasovagal syncope. Ablation sites were selected based on both the standard anatomical locations of major ganglionated plexuses and the visualized fractionation pattern obtained using predefined parameter values [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]: signal width 5 ms, refractoriness 30 ms, and amplitude threshold (roving sensitivity) 0.1 mV.\u003c/p\u003e\n\u003ch3\u003eProcedures\u003c/h3\u003e\n\u003cp\u003eIn both cohorts, procedures were performed under general anesthesia. Patients then underwent electroanatomical mapping during sinus rhythm using the EnSite NavX\u0026trade; Cardiac Mapping System (St. Jude Medical, Abbott. Sylmar, CA, USA) and a high-density multielectrode mapping catheter (Advisor\u0026trade; HD Grid Mapping Catheter, Sensor Enabled\u0026trade;, Abbott, Minneapolis, MN, USA). Fractionation maps were acquired prior to any radiofrequency application, ensuring that EGM characteristics were not influenced by ablation lesions.\u003c/p\u003e \u003cp\u003eBipolar recordings were filtered between 30 and 300 Hz, with mapping parameters standardized at 7 mm for internal and external projections, 7 mm for interpolation, and 0.1 mV for low-voltage identification.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] This filtering range and fractionation parameter framework are supported by prior electrogram-guided CNA studies, in which automated fractionation mapping using similar characteristics was shown to reliably identify GP regions during sinus rhythm.[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn the derivation cohort pulmonary vein (PV) isolation was performed during sinus rhythm using an irrigated catheter (TactiCath\u0026trade; or TactiFlex\u0026trade; Ablation Catheter, Sensor Enabled\u0026trade;, Abbott, Minneapolis, MN, USA). All patients underwent wide-area circumferential ablation encircling the PVs. RF applications were delivered at a power of 35 Watts (W), reduced to 30 W in the posterior wall, with an endpoint lesion index (LSI) of 4.5 to 5 in the posterior wall and 5.5 in other walls. Cardiac cycle length (RR interval) and lesion locations were recorded before and after each application.\u003c/p\u003e \u003cp\u003eIn the validation cohort each GP was ablated during sinus rhythm based on its standard anatomical location and the location suggested by the fractionation software (signal width 5 ms, refractoriness 30 ms, and amplitude threshold (roving sensitivity) 0.1 mV). Cardiac cycle length (RR interval) and ablation sites were recorded before and after each radiofrequency application. Operators were not blinded to the fractionation maps during ablation. This approach reflects real-world procedural conditions and was considered appropriate given the exploratory and methodological nature of the study. In addition, as the validation cohort was retrospective, ablation was performed according to the GP locations suggested by the fractionation map using the predefined configuration described above.\u003c/p\u003e\n\u003ch3\u003eOff-line Analysis\u003c/h3\u003e\n\u003cp\u003eOnce the map of each patient was obtained and stored, an off-line point-by-point analysis of RR response, transient AV block or sinus pauses, and corresponding fractionation mapping was performed. In the derivation cohort, for each patient, ten non-consecutive RR intervals (one every 10 beats) were measured before starting ablation to calculate the mean and the standard deviation (SD) of the RR interval under the conditions in which ablation will take place (anesthesia, catheter insertion and manipulation, etc.). During ablation, a parasympathetic response was considered present if any of the following occurred: an absolute change in RR interval exceeding 10%, transient asystole lasting more than 3 seconds, or a temporary complete atrioventricular block.\u003c/p\u003e \u003cp\u003eThe fractionation mapping software (EnSite NavX\u0026trade; Cardiac Mapping System, St. Jude Medical, Abbott, Sylmar, CA, USA) allows adjustment of three parameters (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e): width (5, 10, or 15 ms); amplitude threshold (0.05, 0.1, or 0.15 mV); and refractoriness (20, 25, or 30 ms).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA combination of these parameters determines the number of deflections which, in turn identifies fractionation based on a predetermined threshold. Fractionation areas were visualized on the map using a color scale.[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] We systematically tested three predefined values for each parameter: Width (5, 10, or 15 ms), refractoriness (20, 25, or 30 ms), and amplitude threshold (0.05, 0.1, or 0.15 mV), resulting in 27 mapping configurations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, supplementary material). For each combination map, each ablation point was reviewed to identify if fractionation was present and determine if a significant parasympathetic response occurred, as part of an off-line, exploratory point-by-point analysis. For schematic purposes, each PV antrum was divided into quadrants as follows: anterosuperior, anteroinferior, posterosuperior, and posteroinferior. An additional mapping configuration was created based on an anatomical approach. Ablation zones were delineated according to anatomical schemes proposed by Sun et al.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] The effectiveness of this configuration was evaluated to assess the performance of a purely anatomical strategy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDerivation cohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValidation cohort\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatients (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.1 +/- 11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.9 +/- 11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep apnea (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEjection fraction (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 +/- 8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 +/- 3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLA volume (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37.7 +/- 7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.1 +/- 5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaps analyzed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaps analyzed per patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAblation points analyzed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAblation points analyzed per patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.6 +/- 6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.9 +/- 19.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the validation cohort fractionation mapping analysis was performed using just one automated software configuration (configuration #6), without visual or manual adjustment by the operators.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eFor each of the 27 mapping configurations and for the anatomical configuration, a 2\u0026times;2 contingency table (fractionation vs. parasympathetic response) was created.[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Chi-square tests were performed for each configuration, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant. Given the pilot nature of the study, statistical analyses were intended to explore associations and performance trends rather than to formally compare configurations using advanced comparative modeling.\u003c/p\u003e \u003cp\u003eThe statistical analysis was performed on a point-by-point basis, considering each ablation site as an individual data entry. This approach allowed the generation of a large analytical dataset despite the relatively small number of patients. As a result, meaningful associations between fractionation parameters and parasympathetic responses could be identified, achieving statistical significance even within the framework of a pilot study. Despite including points outside known GP regions, we opted to analyze all mapping sites to enhance statistical power and better assess the global performance of fractionation parameters. This strategy was chosen to evaluate global parameter performance rather than restrict the analysis to predefined anatomical regions.\u003c/p\u003e \u003cp\u003eFor configurations with significant association, sensitivity, specificity, and predictive values (95% CI) were calculated. Continuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, categorical variables as numbers or percentages. Statistical analysis was performed using Microsoft Excel\u0026trade; for Mac (version 16.84), IBM SPSS Statistics\u0026trade; (version 29.0.2.0), and Calcupedev Version 11.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDerivation cohort\u003c/h2\u003e \u003cp\u003eAn analysis of 870 ablation sites from 12 patients (mean age 60.17\u0026thinsp;\u0026plusmn;\u0026thinsp;11.14 years; 33% female) with an average of 72.5 sites per patient was performed. Patient characteristics are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. For each patient, ten non-consecutive RR interval measurements were taken before any RF application. The average basal RR interval was 1166 ms with a mean SD of 39.78 ms. Thus, the mean SD variation (or coefficient of variation\u0026thinsp;=\u0026thinsp;SD/mean x100) was 3.41% of the baseline RR interval. Since a deviation of more than double the SD of the RR interval was deemed indicative of parasympathetic response, RR intervals exceeding 6.62% of the mean RR interval would indicate a parasympathetic response. To ensure that a parasympathetic response had occurred and to provide a standardized criterion in accordance with a previous publication, a variation of more than 10% in the RR interval was used as an indicator of abnormal response. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eAccordingly, 27 parameter combinations and empirical anatomical ablation area map were analyzed for each ablation site. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows sensitivity, specificity, and predictive values for the 25 significant configurations, as well as the purely anatomical configuration (non-significant). Sensitivity ranged 21\u0026ndash;76%, and specificity 47\u0026ndash;89%.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity, Specificity and predictive values for each configuration.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCombination\u003c/p\u003e \u003cp\u003e(Width in ms \u0026ndash;\u003c/p\u003e \u003cp\u003erefractoriness in ms \u0026ndash;\u003c/p\u003e \u003cp\u003eamplitude threshold in mV)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+PV\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-PV\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDerivation cohort\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnatomy (non-significative.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003cp\u003e(18.6\u0026ndash;44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.4\u003c/p\u003e \u003cp\u003e(43.9\u0026ndash;50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003cp\u003e(1.85\u0026ndash;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91.72\u003c/p\u003e \u003cp\u003e(89.1\u0026ndash;94.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#1: 5\u0026ndash;20\u0026ndash;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.7\u003c/p\u003e \u003cp\u003e(49.5\u0026ndash;76.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003cp\u003e(51.9\u0026ndash;58.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003cp\u003e(5.4\u0026ndash;10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(94.2\u0026ndash;97.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#2: 10\u0026ndash;20 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003cp\u003e(62.5\u0026ndash;86.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.6\u003c/p\u003e \u003cp\u003e(48.2\u0026ndash;55.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003cp\u003e(6.1\u0026ndash;11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003cp\u003e(95.4\u0026ndash;98.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#3: 15\u0026ndash;20\u0026ndash;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.5\u003c/p\u003e \u003cp\u003e(62.5\u0026ndash;86.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003cp\u003e(44.3\u0026ndash;51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003cp\u003e(5.7\u0026ndash;10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.8\u003c/p\u003e \u003cp\u003e(95.1\u0026ndash;98.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#4: 5\u0026ndash;25\u0026ndash;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003cp\u003e(51.6\u0026ndash;77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.1\u003c/p\u003e \u003cp\u003e(60.8\u0026ndash;67.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003cp\u003e(6.8\u0026ndash;13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.7\u003c/p\u003e \u003cp\u003e(95.2\u0026ndash;98.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#5: 10\u0026ndash;25 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003cp\u003e(60.4\u0026ndash;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.0\u003c/p\u003e \u003cp\u003e(53.6\u0026ndash;60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003cp\u003e(6.6\u0026ndash;12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003cp\u003e(95.6\u0026ndash;98.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#6: 15\u0026ndash;25 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.5*\u003c/p\u003e \u003cp\u003e(64.8\u0026ndash;88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.6\u003c/p\u003e \u003cp\u003e(50.2\u0026ndash;57.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003cp\u003e(6.5\u0026ndash;12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.3*\u003c/p\u003e \u003cp\u003e(95.8\u0026ndash;98.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#7: 5\u0026ndash;30 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003cp\u003e(35.3\u0026ndash;62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.1\u003c/p\u003e \u003cp\u003e(67.9\u0026ndash;74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003cp\u003e(6\u0026ndash;13.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.7\u003c/p\u003e \u003cp\u003e(94.1\u0026ndash;97.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#8: 10\u0026ndash;30 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.9\u003c/p\u003e \u003cp\u003e(43.3\u0026ndash;70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.9\u003c/p\u003e \u003cp\u003e(61.7\u0026ndash;68.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003cp\u003e(6\u0026ndash;12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(94.4\u0026ndash;97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#9: 15\u0026ndash;30 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.9\u003c/p\u003e \u003cp\u003e(43.3\u0026ndash;70.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003cp\u003e(58.1\u0026ndash;64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003cp\u003e(5.47\u0026ndash;11.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003cp\u003e(94.1\u0026ndash;97.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#10 5\u0026ndash;20\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.8\u003c/p\u003e \u003cp\u003e(45.3\u0026ndash;72.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.2\u003c/p\u003e \u003cp\u003e(55.8\u0026ndash;62.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.2\u003c/p\u003e \u003cp\u003e(5.4\u0026ndash;11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003cp\u003e(94.1\u0026ndash;97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#11: 10\u0026ndash;20\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003cp\u003e(51.6\u0026ndash;77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.5\u003c/p\u003e \u003cp\u003e(49.1\u0026ndash;55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.82\u003c/p\u003e \u003cp\u003e(5.2\u0026ndash;10.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(94.2\u0026ndash;98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#13: 5\u0026ndash;25\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003cp\u003e(35.3\u0026ndash;62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.1\u003c/p\u003e \u003cp\u003e(66.9\u0026ndash;73.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003cp\u003e(5.8\u0026ndash;12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.7\u003c/p\u003e \u003cp\u003e(94\u0026ndash;97.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#14: 10\u0026ndash;25\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003cp\u003e(55.9\u0026ndash;81.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.8\u003c/p\u003e \u003cp\u003e(61.6\u0026ndash;68.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003cp\u003e(7.4\u0026ndash;14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003cp\u003e(95.7\u0026ndash;98.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#15: 15\u0026ndash;25\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003cp\u003e(53.7\u0026ndash;79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.8\u003c/p\u003e \u003cp\u003e(56.5\u0026ndash;63.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003cp\u003e(6.4\u0026ndash;12.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.6\u003c/p\u003e \u003cp\u003e(95.1\u0026ndash;98.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#16: 5\u0026ndash;30\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003cp\u003e(31.4\u0026ndash;58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.5\u003c/p\u003e \u003cp\u003e(77.5\u0026ndash;83.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.6\u003c/p\u003e \u003cp\u003e(7.8\u0026ndash;17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.9\u003c/p\u003e \u003cp\u003e(94.4\u0026ndash;97.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#17: 10\u0026ndash;30\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.0\u003c/p\u003e \u003cp\u003e(35.3\u0026ndash;62.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.7\u003c/p\u003e \u003cp\u003e(73.8\u0026ndash;79.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003cp\u003e(7.3\u0026ndash;15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(94.5\u0026ndash;97.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#18: 15\u0026ndash;30\u0026thinsp;\u0026minus;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.9\u003c/p\u003e \u003cp\u003e(37.3\u0026ndash;64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.3\u003c/p\u003e \u003cp\u003e(71.4\u0026ndash;77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003cp\u003e(7\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003e(94.5\u0026ndash;97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#20: 10\u0026ndash;20 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.8\u003c/p\u003e \u003cp\u003e(47.4\u0026ndash;74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.9\u003c/p\u003e \u003cp\u003e(53.4\u0026ndash;60.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003cp\u003e(5.4\u0026ndash;10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003cp\u003e(94\u0026ndash;97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#21: 15\u0026ndash;20 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003cp\u003e(51.6\u0026ndash;77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.5\u003c/p\u003e \u003cp\u003e(52.1\u0026ndash;58.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003cp\u003e(5.6\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.2\u003c/p\u003e \u003cp\u003e(94.5\u0026ndash;97.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#22: 5\u0026ndash;25 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003cp\u003e(31.4\u0026ndash;58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.6\u003c/p\u003e \u003cp\u003e(77.9\u0026ndash;83.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.6*\u003c/p\u003e \u003cp\u003e(7.8\u0026ndash;17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.93\u003c/p\u003e \u003cp\u003e(94.45\u0026ndash;97.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#23: 10\u0026ndash;25 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.9\u003c/p\u003e \u003cp\u003e(41.2\u0026ndash;68.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.6\u003c/p\u003e \u003cp\u003e(65.4\u0026ndash;71.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.8\u003c/p\u003e \u003cp\u003e(6.4\u0026ndash;13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.1\u003c/p\u003e \u003cp\u003e(94.5\u0026ndash;97.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#24: 15\u0026ndash;25 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003cp\u003e(51.6\u0026ndash;77.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003cp\u003e(60.7\u0026ndash;67.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003cp\u003e(6.8\u0026ndash;13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.7\u003c/p\u003e \u003cp\u003e(95.2\u0026ndash;98.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#25: 5\u0026ndash;30 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.6\u003c/p\u003e \u003cp\u003e(10.3\u0026ndash;32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.4*\u003c/p\u003e \u003cp\u003e(87.3\u0026ndash;91.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.2\u003c/p\u003e \u003cp\u003e(5\u0026ndash;17.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.8\u003c/p\u003e \u003cp\u003e(93.2\u0026ndash;96.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#26: 10\u0026ndash;30 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.2\u003c/p\u003e \u003cp\u003e(25.2\u0026ndash;52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.5\u003c/p\u003e \u003cp\u003e(79.9\u0026ndash;85.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003cp\u003e(7.2\u0026ndash;17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.6\u003c/p\u003e \u003cp\u003e(94.1\u0026ndash;97.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#27: 15\u0026ndash;30 \u0026minus;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003cp\u003e(31.4\u0026ndash;58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.5\u003c/p\u003e \u003cp\u003e(74.7\u0026ndash;80.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003cp\u003e(6.8\u0026ndash;15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.8\u003c/p\u003e \u003cp\u003e(94.2\u0026ndash;97.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eValidation cohort\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#6: 15\u0026ndash;25 \u0026minus;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003cp\u003e63.6\u0026ndash;82.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003cp\u003e(70\u0026ndash;77.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003cp\u003e(24.2\u0026ndash;36.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94.9\u003c/p\u003e \u003cp\u003e(92.4\u0026ndash;96.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eExcept for anatomy, non \u0026ndash; significative combinations were not shown.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003eAbbreviations: CI: confidence interval; +PV: positive predictive value; -PV: negative predictive value; * best value.\u0026nbsp;\u003c/p\u003e \u003cp\u003eAcross parameter subsets, sensitivity varied according to refractoriness and amplitude threshold, but not width (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, supplementary material). The highest sensitivity was obtained with refractoriness 20 ms and amplitude threshold 0.05 mV; width 15 ms performed numerically best but did not differ statistically from 10 ms. As expected, specificity varied inversely with sensitivity.\u003c/p\u003e \u003cp\u003eSpatially, sites with parasympathetic responses most commonly localized to the right superior-anterior quadrant (9.4%) and the left anterosuperior and anteroinferior quadrants (11.3% each), consistent with the anatomical distribution of right anterior GP and left lateral/Marshall-area GP, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, supplementary material).[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] In total, 61/870 sites (7.01%) exhibited a parasympathetic response.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ecomparison of sensitivity, specificity, positive and negative predictive values.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHAFE pattern\u003c/p\u003e \u003cp\u003e(95%CI) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ePresent study\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDerivation cohort\u003c/p\u003e \u003cp\u003e(best combination)\u003c/p\u003e \u003cp\u003e(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eValidation cohort (95%CI)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003cp\u003e(49.4\u0026ndash;94.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.4\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(64.8\u0026ndash;88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.1\u003c/p\u003e \u003cp\u003e(63.6\u0026ndash;82.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003cp\u003e(85.2\u0026ndash;97.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.3\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(87.2\u0026ndash;91.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.9\u003c/p\u003e \u003cp\u003e(70\u0026ndash;77.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive predictive value (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003cp\u003eCI non reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(7.8\u0026ndash;17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003cp\u003e(24.2\u0026ndash;36.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative predictive value (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003cp\u003eCI non reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.3\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95.8\u0026ndash;98.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.9\u003c/p\u003e \u003cp\u003e(92.4\u0026ndash;96.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ea. Width 15 ms; refractoriness 25 ms; amplitude threshold 0.05 mV.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eb. Width 5 ms; refractoriness 30 ms; amplitude threshold 0.15 mV.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ec. Width 5 ms; refractoriness 25 ms; amplitude threshold 0.15 mV.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eValidation cohort\u003c/h3\u003e\n\u003cp\u003eThe validation cohort included 14 patients (mean age 30.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6 years; 71.4% female). The most common clinical indication was functional bradycardia (57%). On average, 43.9 ablation points were delivered per patient. Mean heart rate increased from 61.8 bpm pre-procedure to 88.4 bpm post-procedure (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUsing the most sensitive parameter set from derivation cohort (configuration #6: width 15 ms, refractoriness 25 ms, amplitude threshold 0.05 mV), the association between fractionation and parasympathetic response remained significant (χ\u0026sup2;=73.93). Sensitivity was 74.1% (95% CI 63.6\u0026ndash;82.4), specificity 73.9% (95% CI 70\u0026ndash;77.5), positive predictive value 30.1% (95% CI 24.2\u0026ndash;36.8), and negative predictive value 94.9% (95% CI 92.4\u0026ndash;96.7) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRestricting analysis to the first lesion per GP per patient (to account for physiologic modification after initial RF) increased sensitivity to 82.35% and NPV to 88%, with a tradeoff in specificity (57.5%) and PPV (45.2%) (χ\u0026sup2;=7.63; p\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eExploratory clinical observations\u003c/h2\u003e \u003cp\u003eAlthough not a predefined endpoint of the study, exploratory clinical follow-up data were collected in the validation cohort. During follow-up after CNA procedure, mean annualized presyncopal episodes per patient decreased from 120.39 pre-procedure to 10.24 events/year post-procedure. Annualized syncope rates decreased from 26.75 to 0.71 events/year. Reductions were statistically significant for both presyncope (p\u0026thinsp;=\u0026thinsp;0.003) and syncope (p\u0026thinsp;=\u0026thinsp;0.007) per Wilcoxon signed-rank test, with no increases in any patient.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMain findings\u003c/h2\u003e \u003cp\u003eThis study analyzed parameters from an automated fractionation mapping software in relation to parasympathetic responses during pulmonary vein isolation procedures in a derivation cohort and subsequently evaluated the performance of the selected parameters in an independent validation cohort of patients undergoing CNA procedures. Key findings are: (1) multiple parameter combinations, but not all, were significantly associated with parasympathetic responses; (2) within tested values, lower amplitude threshold and shorter refractoriness improved sensitivity; width showed a non-significant trend favoring values between 10 and 15 ms; (3) an anatomically guided approach showed non-significant association; and (4) the association between fractionation and parasympathetic response was preserved in a validation cohort using the most sensitive configuration. Compared with a purely anatomical ablation strategy, the selected fractionation configuration demonstrated higher sensitivity and negative predictive value, supporting its potential utility as real-time procedure aid.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePeculiarities of the study design\u003c/h2\u003e \u003cp\u003eWe intentionally selected paroxysmal AF patients with non-severe atrial dilatation in sinus rhythm for the derivation cohort, allowing systematic sampling of atrial regions both likely and unlikely to harbor GP and balancing positive/negative sites for analysis. By minimizing fibrosis-related fractionation and standardizing anesthesia protocol, we optimized detection of software configurations associated with GP localization. Our definition of parasympathetic response accounts for established observations that both[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] heart rate slowing and paradoxical acceleration may occur during acute vagal modulation, particularly during ablation near the right anterior GP.[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eIn validation cohort, the pretest probability of parasympathetic response was higher because ablation was restricted to presumed GP regions; accordingly, the proportion of positive sites increased from 7.34% to 13.19%. Despite this, the fractionation\u0026ndash;response association remained significant, supporting generalizability to CNA.\u003c/p\u003e \u003cp\u003eAmplitude threshold (formerly \u0026ldquo;roving sensitivity\u0026rdquo;) and refractoriness were the parameters most strongly associated with detection of parasympathetic responses. Lower amplitude thresholds (\u0026asymp;\u0026thinsp;0.05 mV) likely facilitate identification of low-voltage, high-frequency deflections commonly observed in regions of autonomic innervation; shorter refractory periods (\u0026asymp;\u0026thinsp;20 ms) may allow counting of closely spaced deflections within fragmented electrograms. Together, these observations are consistent with the hypothesis that low‑amplitude, high‑frequency EGM are preferentially encountered near autonomically innervated atrial regions.\u003c/p\u003e \u003cp\u003eLellouche et al.[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] described a high-amplitude fractionation electrogram (HAFE) pattern associated with parasympathetic responses based on off-line visual analysis using conventional ablation catheter. A comparison between approaches can be founded in Supplementary table 4. Aksu and colleagues[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] demonstrated the feasibility of software-based fractionation mapping during sinus rhythm, although parameter choices were arbitrary. A recent multicenter study[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] reported an association between a greater number of RF applications and improved clinical outcomes after CNA irrespective of PG localization technique. This observation is consistent with the notion that extensive ablation may partially compensate for imperfect localization strategies.\u003c/p\u003e \u003cp\u003eAlthough our software could not distinguish HAFE and LAFE, fractionation correlated with parasympathetic responses across most configurations. In typical CNA populations without structural disease, fibrosis‑ related LAFE is less likely to confound results \u003csup\u003e6\u003c/sup\u003e. To prioritize sensitivity and NPV intra‑procedurally, we favor configurations with shorter refractoriness (\u0026asymp;\u0026thinsp;20 ms) and lower amplitude threshold (\u0026asymp;\u0026thinsp;0.05 mV). Notably, PPV remained suboptimal, underscoring the need for improved tools. See Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAlthough the negative predictive value was high, the relatively low positive predictive value (~\u0026thinsp;30%) indicates that fractionation alone may be insufficient to reliably predict parasympathetic response. This finding underscores the role of fractionation mapping as a complementary intraprocedural tool rather than a standalone determinant of ablation targets.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis pilot exploratory study has a relatively small sample size, limiting precision of performance estimates, particularly for specificity and PPV. Findings were derived using a single mapping system and may not be directly generalizable to other software platforms employing different signal acquisition and processing algorithms. Fractionated EGMs may also reflect mechanisms other than autonomic innervation, including localized fibrosis, PV potentials, inter‑atrial signal overlap, or slow conduction (e.g., AV nodal slow pathway).[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] In typical CNA patients treated for reflex syncope, significant fibrosis is less likely; however, these mechanisms cannot be fully excluded. Voltage data in relation to fractionation and parasympathetic responses was not systematically analyzed in this study and represents an additional limitation.\u003c/p\u003e \u003cp\u003eThe derivation cohort consisted of patients undergoing pulmonary vein isolation for paroxysmal atrial fibrillation rather than typical candidates for CNA. Although this population does not fully represent patients with functional bradyarrhythmias or reflex syncope, it was intentionally selected to enable systematic assessment of fractionation patterns in atrial regions both proximal and remote from the usual anatomic locations of GP. Restricting inclusion to individuals with non-severe atrial dilatation further allowed approximation of electrophysiological substrate encountered in CNA while facilitating balanced evaluation of present and absent parasympathetic response sites.\u003c/p\u003e \u003cp\u003eAs an exploratory methodological study, these findings require confirmation in larger, prospective cohorts to determine whether parameter-guided fractionation mapping translates into improved procedural or clinical outcomes after CNA procedures.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSpecific parameter configurations for automated fractionation mapping, when combined with high-density electroanatomical mapping, were associated with identification of atrial sites exhibiting parasympathetic responses during radiofrequency ablation. Findings derived from a prospective atrial fibrillation cohort were subsequently evaluated in an independent, real-world CNA population. The consistent association between software-defined fractionation and parasympathetic response supports further investigation of this approach in larger prospective studies. Given the relatively small sample size in both cohorts\u0026mdash;particularly the validation group\u0026mdash;these findings should be considered exploratory, and the precision of sensitivity, specificity and predictive value estimates is limited, warranting confirmation in larger prospective studies. See Central graphical figure.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in this study were in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. The study protocol was reviewed and approved by the institutional ethics committee of CardioVID Clinic.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all individual participants included in this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eJuan F. Agudelo-Uribe reports receiving modest honoraria from Abbott Medical Colombia for proctoring electrophysiology procedures, lectures, and scientific presentations.\u003c/p\u003e\n\u003cp\u003eJuan D. Ram\u0026iacute;rez Barrera declares no competing interests.\u003c/p\u003e\n\u003cp\u003eRafael Correa-Vel\u0026aacute;squez declares no competing interests.\u003c/p\u003e\n\u003cp\u003eMargarita Londo\u0026ntilde;o-Arango is an employee of Abbott Medical Colombia.\u003c/p\u003e\n\u003cp\u003eTeresa Barrio-L\u0026oacute;pez declares no competing interests.\u003c/p\u003e\n\u003cp\u003eJes\u0026uacute;s Almendral declares no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for conducting this study or for the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eData availability\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe initial conception of the study was performed by Jes\u0026uacute;s Almendral and Teresa Barrio-L\u0026oacute;pez. Final study design was developed by Juan F. Agudelo-Uribe, Jes\u0026uacute;s Almendral, and Rafael Correa-Vel\u0026aacute;squez. Data collection was carried out by Juan F. Agudelo-Uribe, Juan D. Ram\u0026iacute;rez Barrera, and Rafael Correa-Vel\u0026aacute;squez. Data analysis was performed by Juan F. Agudelo-Uribe and Margarita Londo\u0026ntilde;o-Arango. The first draft of the manuscript was written by Juan F. Agudelo-Uribe, and critical revisions were performed by Jes\u0026uacute;s Almendral and Teresa Barrio-L\u0026oacute;pez. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArmour JA, Murphy DA, Yuan BX, Macdonald S, Hopkins DA. Gross and microscopic anatomy of the human intrinsic cardiac nervous system. 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PACE - Pacing Clin Electrophysiol. 2010;33:1407\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1540-8159.2010.02841.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1540-8159.2010.02841.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiou CW, Eble JN, Zipes DP. Efferent vagal innervation of the canine atria and sinus and atrioventricular nodes: The third fat pad. Circulation. 1997;95:2573\u0026ndash;84. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1161/01.CIR.95.11.2573\u003c/span\u003e\u003cspan address=\"10.1161/01.CIR.95.11.2573\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu F, Zheng L, Liang E, Ding L, Wu L, Chen G, et al. Right anterior ganglionated plexus: The primary target of cardioneuroablation? Heart Rhythm. 2019;16:1545\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.hrthm.2019.07.018\u003c/span\u003e\u003cspan address=\"10.1016/j.hrthm.2019.07.018\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarrio-Lopez MT, \u0026Aacute;lvarez-Ortega C, Minguito-Carazo C, Franco E, Garc\u0026iacute;a-Granja PE, Alcalde-Rodr\u0026iacute;guez \u0026Oacute;, et al. Predictors of Clinical Success of Cardioneuroablation in Patients With Syncope. JACC Clin Electrophysiol. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jacep.2024.07.027\u003c/span\u003e\u003cspan address=\"10.1016/j.jacep.2024.07.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cardioneuroablation, Ganglionated plexus, Fractionated electrograms, Autonomic nervous system, Electroanatomical mapping","lastPublishedDoi":"10.21203/rs.3.rs-8467859/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8467859/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eCardioneuroablation (CNA) targets atrial ganglionated plexuses to treat vagally mediated bradyarrhythmias. Automated electrogram fractionation mapping has been proposed as a surrogate tool for ganglionated plexus localization; however, optimal software parameter settings for real-time use remain undefined. This study was designed as a methodological pilot investigation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData from a total of 28 patients were analyzed, including a prospective derivation cohort of 12 patients undergoing atrial fibrillation ablation in sinus rhythm and an independent validation cohort of 14 patients undergoing CNA. Using high-density electroanatomical mapping, three predefined values were tested for each fractionation parameter\u0026mdash;signal width, refractoriness, and amplitude threshold\u0026mdash;yielding 27 automated configurations. A purely anatomical localization strategy was also assessed, resulting in 28 total mapping configurations. All configurations were systematically generated for each patient in the derivation cohort, producing 336 fractionation maps and 870 ablation sites. Parasympathetic response during radiofrequency ablation was defined as an RR interval change\u0026thinsp;\u0026gt;\u0026thinsp;10%, transient atrioventricular block, or sinus pause/asystole. The most sensitive configuration was subsequently applied to the validation cohort (614 ablation sites).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn the derivation cohort, 25 of 27 automated parameter combinations showed significant association with parasympathetic response. The configuration with signal width 15 ms, refractoriness 25 ms, and amplitude threshold 0.05 mV was selected as the most sensitive. When applied to the validation cohort, this predefined configuration demonstrated preserved diagnostic performance, with a sensitivity of 74.1%, specificity of 73.9%, and negative predictive value of 94.9%. Fractionation-guided localization outperformed a purely anatomical approach.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis pilot study provides a reproducible methodological framework for evaluating automated fractionation mapping parameters associated with parasympathetic responses during CNA. These exploratory findings warrant prospective validation in larger cohorts.\u003c/p\u003e","manuscriptTitle":"Methodological Evaluation of High-Density Fractionation Mapping Parameters for Cardioneuroablation: A Pilot Derivation and Validation Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 06:21:55","doi":"10.21203/rs.3.rs-8467859/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bcd1bfaf-d18d-4608-9a74-1917bc36e471","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T06:10:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 06:21:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8467859","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8467859","identity":"rs-8467859","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}