Publications by authors named "S K Chaya"

Thin-section CT (TSCT) is currently the most sensitive imaging modality for detecting bronchiectasis. However, conventional TSCT or HRCT may overlook subtle lung involvement such as alveolar and interstitial changes. Artificial Intelligence (AI)-based analysis offers the potential to identify novel information on lung parenchymal involvement that is not easily detectable with traditional imaging techniques.

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: Pulmonary tuberculosis (TB) remains a major public health issue in India, with high incidence and mortality. The current literature on post-TB sequelae functional defects focuses heavily on spirometry, with conflicting obstruction vs. restriction data, lacks advanced statistical analysis, and has insufficient data on diffusion limitation and functional impairment.

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Introduction: Major methodological issues with the existing algorithm (WBreath) used for the analysis of speed-of-sound-based infant sulfur hexafluoride (SF) multiple-breath washout (MBW) measurements lead to implausible results and complicate the comparison between different age groups and centers.

Methods: We developed OASIS-a novel algorithm to analyze speed-of-sound-based infant SF MBW measurements. This algorithm uses known context of the measurements to replace the dependence of WBreath on model input parameters.

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BACKGROUNDConfirming the aetiology of pleural effusion in children may be difficult in TB-endemic settings. We investigated the role of polymerase chain reaction (PCR) and routine biochemical tests in discriminating pleural effusion caused by bacteria from other aetiologies.METHODSThis is a cross-sectional post-hoc analysis among children with pleural effusion in a tertiary hospital in South Africa, incorporating new data from PCR testing of stored pleural fluid.

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Article Synopsis
  • Early-life lung development significantly impacts long-term lung function and health, with lower respiratory tract infections (LRTIs) playing a crucial role during childhood.
  • A study followed 966 South African children from birth to age 5, revealing that 50.1% experienced LRTI, which negatively affected lung function, leading to reduced compliance and increased resistance.
  • Maternal health factors, socioeconomic status, and the occurrence of respiratory syncytial virus (RSV) LRTI were also linked to impaired lung development, highlighting the need for targeted public health measures to prevent LRTIs, especially in low-income communities.
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