False-negative RT-PCR for COVID-19 and a diagnostic risk score: a retrospective cohort study among patients admitted to hospital von Gupta-Wright, Ankur, Macleod, Colin Kenneth, Barrett, Jessica, Filson, Sarah Ann, Corrah, Tumena, Parris, Victoria, Sandhu, Gurjinder, Harris, Miriam, Tennant, Rachel, Vaid, Nidhi, Takata, Junko, Duraisingham, Sai, Gandy, Nemi, Chana, Harmeet, Whittington, Ashley, McGregor, Alastair, Papineni, Padmasayee

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Utility of the FebriDx point-of-care assay in supporting a triage algorithm for medical admissions with possible COVID-19: an observational cohort study von Houston, Hamish, Deas, Gavin, Naik, Shivam, Shah, Kamal, Patel, Shiras, Greca Dottori, Maria, Tay, Michael, Filson, Sarah Ann, Biggin-Lamming, James, Ross, John, Vaughan, Natalie, Vaid, Nidhi, Gopal Rao, Guduru, Amin, Amit K, Gupta-Wright, Ankur, John, Laurence

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Pneumoperitoneum, a urological source von Hateley, Charlotte, MRCP, Alçada, Joana, MRCP, Park, Mirae, MRCP, Vaid, Nidhi, MRCP, Buckley, Jim, Dr

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Cross-sectional observational study of epidemiology of COVID-19 and clinical outcomes of hospitalised patients in North West London during March and April 2020 von Gopal Rao, Guduru, Allen, Alexander, Papineni, Padmasayee, Wang, Liyang, Anderson, Charlotte, McGregor, Alastair, Whittington, Ashley, John, Laurence, Harris, Miriam, Hiles, Stephen, Nicholas, Thomas, Adams, Katherine, Akbar, Ayesha, Blomquist, Paula, Decraene, Valerie, Patel, Bharat, Manuel, Rohini, Chow, Yimmy, Kuper, Martin, Roger, Sharpe, David, Cohen, Rachel, Tennant, Nidhi, Vaid, Kapil, Sahnan, Jamie, Gross, Tariq, Husain, Victoria, Parris, Gurjinder, Sandhu, Stuart, Rosen, Charles, Cayley, Sangita, Patel, Mitchel, Blair, Simon, Lewis, Sunder, Chita, Trish, Winn, James, Biggin-Lamming, Catherine, Sewel, Laila, Gregory, Philip, Tozer, Stephen, Littler

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Temporal trends in severe malaria in Chittagong, Bangladesh von Maude, Richard James, Hasan, Mahtab Uddin, Hossain, Md Amir, Sayeed, Abdullah Abu, Kanti Paul, Sanjib, Rahman, Waliur, Maude, Rapeephan Rattanawongnara, Vaid, Nidhi, Ghose, Aniruddha, Amin, Robed, Samad, Rasheda, Yunus, Emran Bin, Rahman, M Ridwanur, Bangali, Abdul M, Hoque, M Gofranul, Day, Nicholas P J, White, Nicholas J, White, Lisa J, Dondorp, Arjen M, Faiz, M Abul

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A single-centre observational cohort study of admission National Early Warning Score (NEWS) von Abbott, Tom E.F, Vaid, Nidhi, Ip, Dorothy, Cron, Nicholas, Wells, Matt, Torrance, Hew D.T, Emmanuel, Julian

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Pre-hospital National Early Warning Score (NEWS) is associated with in-hospital mortality and critical care unit admission: A cohort study von Abbott, Tom E.F., Cron, Nicholas, Vaid, Nidhi, Ip, Dorothy, Torrance, Hew D.T., Emmanuel, Julian

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A single-centre cohort study of National Early Warning Score (NEWS) and near patient testing in acute medical admissions von Abbott, Tom E.F, Torrance, Hew D.T, Cron, Nicholas, Vaid, Nidhi, Emmanuel, Julian

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The Significance of Measuring Non‐HDL‐Cholesterol von Hirsch, Glenn A., Vaid, Nidhi, Blumenthal, Roger S.

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Post‐exposure prophylaxis in resource‐poor settings: review and recommendations for pre‐departure risk assessment and planning for expatriate healthcare workers von Vaid, Nidhi, Langan, Katherine M., Maude, Richard J.

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Epilepsy, poverty and early under-nutrition in rural Ethiopia von Vaid, Nidhi, Fekadu, Sintayehu, Alemu, Shitaye, Dessie, Abere, Wabe, Genale, Phillips, David I.W, Parry, Eldryd H.O, Prevett, Martin

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Nutritional Status of ICDS and Non-ICDS Children von Vaid, Sumati, Vaid, Nidhi

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A single-centre cohort study of National Early Warning Score (NEWS) and near patient testing in acute medical admissions von Abbott, Tom E.F, Torrance, Hew D.T, Cron, Nicholas, Vaid, Nidhi, Emmanuel, Julian

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Perspectives: The significance of measuring non-HDL-cholesterol von Hirsch, Glenn A, Vaid, Nidhi, Blumenthal, Roger S

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Deep learning and the electrocardiogram: review of the current state-of-the-art von Somani, Sulaiman, Russak, Adam J, Richter, Felix, Zhao, Shan, Vaid, Akhil, Chaudhry, Fayzan, De Freitas, Jessica K, Naik, Nidhi, Miotto, Riccardo, Nadkarni, Girish N, Narula, Jagat, Argulian, Edgar, Glicksberg, Benjamin S

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Comprehensive review on therapeutic and phytochemical exploration of diosmetin: A promising moiety von Garg, Madhukar, Chaudhary, Sushil Kumar, Goyal, Anju, Sarup, Prerna, Kumari, Sapna, Garg, Nidhi, Vaid, Lavish, Shiveena, Bhatia

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Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation von Vaid, Akhil, Somani, Sulaiman, Russak, Adam J, De Freitas, Jessica K, Chaudhry, Fayzan F, Paranjpe, Ishan, Johnson, Kipp W, Lee, Samuel J, Miotto, Riccardo, Richter, Felix, Zhao, Shan, Beckmann, Noam D, Naik, Nidhi, Kia, Arash, Timsina, Prem, Lala, Anuradha, Paranjpe, Manish, Golden, Eddye, Danieletto, Matteo, Singh, Manbir, Meyer, Dara, O'Reilly, Paul F, Huckins, Laura, Kovatch, Patricia, Finkelstein, Joseph, Freeman, Robert M, Argulian, Edgar, Kasarskis, Andrew, Percha, Bethany, Aberg, Judith A, Bagiella, Emilia, Horowitz, Carol R, Murphy, Barbara, Nestler, Eric J, Schadt, Eric E, Cho, Judy H, Cordon-Cardo, Carlos, Fuster, Valentin, Charney, Dennis S, Reich, David L, Bottinger, Erwin P, Levin, Matthew A, Narula, Jagat, Fayad, Zahi A, Just, Allan C, Charney, Alexander W, Nadkarni, Girish N, Glicksberg, Benjamin S

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Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19 von Vaid, Akhil, Chan, Lili, Chaudhary, Kumardeep, Jaladanki, Suraj K, Paranjpe, Ishan, Russak, Adam, Kia, Arash, Timsina, Prem, Levin, Matthew A, He, John Cijiang, Böttinger, Erwin P, Charney, Alexander W, Fayad, Zahi A, Coca, Steven G, Glicksberg, Benjamin S, Nadkarni, Girish N

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Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19 von Chan, Lili, Jaladanki, Suraj K, Somani, Sulaiman, Paranjpe, Ishan, Kumar, Arvind, Zhao, Shan, Kaufman, Lewis, Leisman, Staci, Sharma, Shuchita, He, John Cijiang, Murphy, Barbara, Fayad, Zahi A, Levin, Matthew A, Bottinger, Erwin P, Charney, Alexander W, Glicksberg, Benjamin S, Coca, Steven G, Nadkarni, Girish N

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Contrastive learning improves critical event prediction in COVID-19 patients von Wanyan, Tingyi, Honarvar, Hossein, Jaladanki, Suraj K., Zang, Chengxi, Naik, Nidhi, Somani, Sulaiman, De Freitas, Jessica K., Paranjpe, Ishan, Vaid, Akhil, Zhang, Jing, Miotto, Riccardo, Wang, Zhangyang, Nadkarni, Girish N., Zitnik, Marinka, Azad, Ariful, Wang, Fei, Ding, Ying, Glicksberg, Benjamin S.

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