Abstract
Pelvic Inflammatory Disease (PID) is a multifactorial infection of the upper female reproductive tract, predominantly linked to sexually transmitted organisms such as Chlamydia trachomatis, Neisseria gonorrhoeae, and Mycoplasma genitalium. However, contemporary research highlights the broader polymicrobial etiology of PID, with increasing recognition of anaerobic bacteria and vaginal microbiome imbalances contributing to disease onset and progression. Microbial dysbiosis, particularly the depletion of beneficial Lactobacillus spp. and the proliferation of anaerobes like Gardnerella, Bacteroides, and Atopobium vaginae, impairs mucosal defense and facilitates pathogen ascension, triggering inflammation, and reproductive damage. PID is associated with serious health consequences, including infertility, chronic pelvic pain, and ectopic pregnancy. Traditional diagnostic techniques, such as microscopy and culture, often lack sensitivity and specificity. In contrast, advanced molecular tools like multiplex PCR and Next-Generation Sequencing (NGS) have revolutionized pathogen detection and microbial profiling in the female genital tract, enabling more accurate and early diagnosis. The application of Artificial Intelligence (AI), especially machine learning, further enhances PID management by enabling in-depth analysis of microbiome data, supporting personalized treatment, prognosis, and patient stratification. Additionally, AI-based mobile health platforms improve patient engagement and remote monitoring. Complementary to modern diagnostics and therapeutics, Ayurvedic interventions—including herbal formulations (Saraca asoca and Asparagus racemosus), detoxification, and dietary guidance—offer anti-inflammatory and immunoregulatory benefits. An integrative framework that combines AI, molecular diagnostics, and Ayurveda represents a promising advancement in precision medicine for PID, promoting more effective, individualized, and holistic care.
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