Long term nursing management of children with tuberculosis survivors: focus on sequelae prevention and improve quality of life.

PURPOSE: Pediatric tuberculosis (TB) remains a significant global health challenge, with high treatment success rates leading to a growing cohort of survivors who face under-recognized long-term sequelae, including pulmonary impairment, neurological deficits, musculoskeletal deformities, growth delays, and psychosocial issues. This review synthesizes evidence on nurse-led long-term management strategies to prevent sequelae and enhance quality of life (QOL) in these children. METHODS: This narrative review followed SWiM (Synthesis Without Meta-analysis) reporting guidelines. We searched PubMed, Embase, CINAHL, Scopus, Web of Science, and the WHO Global Tuberculosis Database from 1 January 2010 to 31 March 2026, yielding 152 sources after screening. Evidence certainty was graded using the GRADE framework. Statistical summaries (e.g., p-values, 95% CIs, z-scores) are reported where available to enhance transparency. FINDINGS: Drawing from pathophysiology insights, we outline a conceptual framework emphasizing surveillance, early detection, intervention, rehabilitation, and family-community support. Key nursing interventions include pulmonary monitoring via spirometry and physiotherapy, neurodevelopmental screening, nutritional rehabilitation, and mental health support. Family-centered approaches incorporate home-based care, community health worker integration, and school interventions, while multidisciplinary collaboration and assessment tools like PedsQL ensure holistic care. Implementation challenges in low-resource settings, such as stigma and system barriers, are addressed through task-shifting, education, and policy advocacy. Future directions highlight digital tools, AI integration, predictive models, and registries to bridge research gaps in neurocognitive outcomes. CONCLUSIONS: Integrating structured, evidence-informed survivorship care into national TB programs is essential to optimize functional outcomes and QOL, particularly in resource-limited contexts.