The utility of complete blood count-derived markers for characterising pulmonary tuberculosis severity and prediction of treatment response

A. Kivrane; V. Igumnova; A. Viksna; I. Simanovica; I. Ozere; I Pole; D. Bandere; R. Ranka

The utility of complete blood count-derived markers for characterising pulmonary tuberculosis severity and prediction of treatment response

A. Kivrane, V. Igumnova, A. Viksna, I. Simanovica, I. Ozere, I Pole, D. Bandere, R. Ranka

Rīga Stradiņš University

Research output: Contribution to journal › Meeting Abstract › peer-review

Original language	English
Pages (from-to)	160-160
Number of pages	1
Journal	FEBS Open Bio
Volume	12
Issue number	S1
Publication status	Published - Jul 2022

Field of Science*

1.6 Biological sciences
3.1 Basic medicine

Publication Type*

3.3. Publications in conference proceedings indexed in Web of Science and/or Scopus database

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

https://febs.onlinelibrary.wiley.com/doi/epdf/10.1002/2211-5463.13440

Cite this

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title = "The utility of complete blood count-derived markers for characterising pulmonary tuberculosis severity and prediction of treatment response",

author = "A. Kivrane and V. Igumnova and A. Viksna and I. Simanovica and I. Ozere and I Pole and D. Bandere and R. Ranka",

year = "2022",

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language = "English",

volume = "12",

pages = "160--160",

journal = "FEBS Open Bio",

issn = "2211-5463",

publisher = "Wiley-Blackwell",

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T1 - The utility of complete blood count-derived markers for characterising pulmonary tuberculosis severity and prediction of treatment response

AU - Kivrane, A.

AU - Igumnova, V.

AU - Viksna, A.

AU - Simanovica, I.

AU - Ozere, I.

AU - Pole, I

AU - Bandere, D.

AU - Ranka, R.

PY - 2022/7

Y1 - 2022/7

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M3 - Meeting Abstract

SN - 2211-5463

VL - 12

SP - 160

EP - 160

JO - FEBS Open Bio

JF - FEBS Open Bio

IS - S1

ER -

The utility of complete blood count-derived markers for characterising pulmonary tuberculosis severity and prediction of treatment response

Field of Science*

Publication Type*

UN SDGs

Access to Document

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Cite this