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

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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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