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The combined role of NLR and PLR in predicting the severity of covid 19
Indian Journal of Hematology and Blood Transfusion ; 36(1 SUPPL):S115, 2020.
Article in English | EMBASE | ID: covidwho-1092792
ABSTRACT
Aims &

Objectives:

To monitor the Neutrophil lymphocyte ratio (NLR) and Platelet lymphocyte ratio (PLR) in admitted COVID positive patients and their use as prognostic factors for predicting COVID 19 severity. Patients/Materials &

Methods:

A retrospective single center study on 500 COVID positive patients who had been hospitalized in between 12th August 2020 and 5th September 2020 was conducted. The demographic, clinical details and CBC which was determined using SYSMEX CELL COUNTER at admission were collected. NLR and PLR were calculated. N/L R = ABSOLUTE NEUTROPHIL COUNT/ABSOULTE LYMPHOCYTE COUNT P/L R = PLATELET COUNT/ABSOLUTE LYMPHOCYTE COUNT Data was entered in Microsoft Excel and analyzed.

Results:

of the 500 patients, 269 patients with no oxygen support,164 patients under oxygen support and 67 patients were in ICU. NLR cut off value obtained = 3.84. PLR Cut off value obtained = 140 Result table attached. NLR and PLR were shown positively proportional to disease severity. Discussion &

Conclusion:

NLR and PLR ratios are easy to calculate which is novel, rapid & used as a prognostic factor in the early screening of critical illness in confirmed COVID 19 patients and may help the physician to stratify patients into prognostic categories at its early stage. These ratios can be easily implemented even in primary health centers to monitor the patients and predict the severity.

Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Prognostic study Language: English Journal: Indian Journal of Hematology and Blood Transfusion Year: 2020 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Type of study: Prognostic study Language: English Journal: Indian Journal of Hematology and Blood Transfusion Year: 2020 Document Type: Article