International Journal of Infectious Diseases (Mar 2021)

The comparative ability of commonly used disease severity scores to predict death or a requirement for ICU care in patients hospitalised with possible sepsis in Yangon, Myanmar

  • Mar Mar Minn,
  • Ne Myo Aung,
  • De Zin Kyaw,
  • Thet Tun Zaw,
  • Pyae Nyein Chann,
  • Hnin Ei Khine,
  • Steven McLoughlin,
  • Anthony D. Kelleher,
  • Ne Lin Tun,
  • Thin Zar Cho Oo,
  • Nan Phyu Sin Toe Myint,
  • Matthew Law,
  • Mar Mar Kyi,
  • Josh Hanson

Journal volume & issue
Vol. 104
pp. 543 – 550

Abstract

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Objectives: To determine the comparative prognostic utility of commonly used disease prediction scores in adults with presumed community-acquired sepsis in a resource-limited tropical setting. Methods: This prospective, observational study was performed on the medical ward of a tertiary-referral hospital in Yangon, Myanmar. The ability of the National Early Warning Score 2 (NEWS2), quick NEWS (qNEWS), quick Sequential Organ Failure Assessment (qSOFA) score, Universal Vital Assessment (UVA) and Sequential Organ Failure Assessment (SOFA) scores to predict a complicated inpatient course (death or requirement for intensive care unit (ICU) support) in patients with two or more systemic inflammatory response syndrome criteria was determined. Results: Among the 509 patients, 30 (6%) were HIV-seropositive. The most commonly confirmed diagnoses were tuberculosis (30/509, 5.9%) and measles (26/509, 5.1%). Overall, 75/509 (14.7%) died or required ICU support. All the scores except the qSOFA score, which was inferior, had a similar ability to predict a complicated inpatient course. Conclusions: In this resource-limited tropical setting, disease severity scores calculated at presentation using only vital signs–such as the NEWS2 score–identified high-risk sepsis patient as well as the SOFA score, which is calculated at 24 h and which also requires laboratory data. Use of these simple clinical scores can be used to facilitate recognition of the high-risk patient and to optimise the use of finite resources.

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