ArticleFrontiers in neurology2026
Real-world deep brain stimulation programming practices for Parkinson's disease in India: variability, technology adoption, and emerging trends from a multicentre clinician survey across India.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Deep brain stimulation (DBS) outcomes in Parkinson's disease (PD) are strongly influenced by postoperative programming, yet real-world workflows and adoption of newer technologies, including directional stimulation, sensing-enabled systems, and adaptive DBS, vary across clinical settings. This study aimed to describe contemporary real-world DBS programming practices for PD among clinicians across India. Methods: We conducted an anonymous, cross-sectional, web-based survey of Indian clinicians actively programming DBS for PD with ≥1 year of experience. The survey assessed initial programming workflows, symptom-specific optimization strategies, medication adjustment practices, use of sensing-enabled technologies, approaches to suboptimal response, respondent-level workflow patterns, and perceptions of adaptive DBS. Results were analyzed descriptively using item-specific denominators; multi-select responses were summarized as option-level proportions. Results: Fifty of 54 approached clinicians completed the survey. Respondents represented 37 DBS centres across 18 Indian cities. The subthalamic nucleus was the most commonly selected target (42/50, 84.0%). Stimulation was most often initiated within 1-2 weeks (25/50, 50.0%) or 3-4 weeks (14/50, 28.0%) after implantable pulse generator implantation. Initial programming strategies were captured as a multi-select item; the most frequently selected strategy was a combination of monopolar review and BrainSense (35/50, 70.0%), followed by traditional monopolar review (22/50, 44.0%). Current BrainSense use was reported by 42/50 respondents (84.0%); among current users, initiation most often occurred at initial programming (26/42, 61.9%). Symptom-specific optimization strategies varied by clinical problem: amplitude adjustment was most frequently selected for bradykinesia (42/50, 84.0%) and rigidity (45/50, 90.0%), while frequency adjustment was most frequently selected for tremor (47/50, 94.0%) and freezing of gait (43/50, 86.0%). For suboptimal response, imaging-based lead localization strategies were frequently selected, particularly pre-/post-operative imaging merge with lead location review (44/50, 88.0%). Exploratory respondent-level analysis identified overlapping workflow domains, including sensing-integrated programming (26/50, 52.0%) and technology-assisted troubleshooting (29/50, 58.0%); 31/50 respondents (62.0%) fell into the high workflow/technology-integration score category. Most respondents intended to incorporate adaptive DBS into routine clinical practice (45/50, 90.0%). Conclusion: This multicentre survey provides a snapshot of contemporary DBS programming practices for PD in India, highlighting practice variability, increasing adoption of technology-assisted programming, and strong interest in adaptive DBS. These findings support the need for context-specific training and future outcome-based research.
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