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  1. Fulltext Host-dependent molecular factors mediating SARS-CoV-2 infection to gain clinical insights for developing effective targeted therapy
    Shafi G, Desai S, Srinivasan K, Ramesh A, Chaturvedi R, Uttarwar M
    Mol Genet Genomics, 2021 May;296(3):501-511.
    PMID: 33743061 DOI: 10.1007/s00438-021-01774-1
    Coronavirus disease 2019 (COVID-19), a recent viral pandemic that first began in December 2019, in Hunan wildlife market, Wuhan, China. The infection is caused by a coronavirus, SARS-CoV-2 and clinically characterized by common symptoms including fever, dry cough, loss of taste/smell, myalgia and pneumonia in severe cases. With overwhelming spikes in infection and death, its pathogenesis yet remains elusive. Since the infection spread rapidly, its healthcare demands are overwhelming with uncontrollable emergencies. Although laboratory testing and analysis are developing at an enormous pace, the high momentum of severe cases demand more rapid strategies for initial screening and patient stratification. Several molecular biomarkers like C-reactive protein, interleukin-6 (IL6), eosinophils and cytokines, and artificial intelligence (AI) based screening approaches have been developed by various studies to assist this vast medical demand. This review is an attempt to collate the outcomes of such studies, thus highlighting the utility of AI in rapid screening of molecular markers along with chest X-rays and other COVID-19 symptoms to enable faster diagnosis and patient stratification. By doing so, we also found that molecular markers such as C-reactive protein, IL-6 eosinophils, etc. showed significant differences between severe and non-severe cases of COVID-19 patients. CT findings in the lungs also showed different patterns like lung consolidation significantly higher in patients with poor recovery and lung lesions and fibrosis being higher in patients with good recovery. Thus, from these evidences we perceive that an initial rapid screening using integrated AI approach could be a way forward in efficient patient stratification.
  2. Definition, diagnosis and classification of infection-related movement disorders: Consensus proposal
    Desai S, Ibrahim NM, Garg D, Yadav R, Iacono D, Ugawa Y, et al.
    Parkinsonism Relat Disord, 2024 Jul;124:106988.
    PMID: 38705765 DOI: 10.1016/j.parkreldis.2024.106988
    BACKGROUND: Infection-related movement disorders (IRMD) present a complex diagnostic challenge due to the broad phenotypic spectrum, the variety of possible infectious aetiologies, and the complicated underlying mechanisms. Yet, a comprehensive framework for classifying IRMD is lacking.

    METHODS: An international consensus panel under the directives of the Movement Disorders Society Infection-Related Movement Disorders Study Group developed a comprehensive definition and a consensus classification system. Case scenarios were used for validation.

    RESULTS: A definition for IRMD and a two-axis-based classification system consisting of six descriptors are proposed, intended as tools for researchers and clinicians. Collected information on clinical characteristics, investigational findings, the infectious organism and presumed pathogenesis facilitate the evaluation of diagnostic certainty.

    CONCLUSION: The proposed framework will serve for optimised diagnostic algorithms, systematic aggregation of informative datasets across studies, and ultimately improved care and outcome of patients with IRMDs.

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