A binary logistic regression approach to identify factors affecting extravasation in chemotherapy treatment


Author(s): Nihar Ranjan Panda, Jitendra Kumar Pati and Ruchi Bhuyan*

Extravasations exert extra pressure on patients in terms of morbidity, mortality, health care expenses, and quality of life. Hence it is the need of the hour to know about the existing prevalence of extravasations to develop the protocol for the administration of chemotherapy. The main spotlight of the study is to determine the factors that affect extravasations and use these factors to reconstitute the existing mathematical model which can predict the status of extravasation for hospitalized patients who are going through chemotherapy.

Based on the data from a multispecialty hospital in Bhubaneswar, Odisha, a binary Logistic Regression model is fitted to deduce the relationship between independent and dependent variables to detect significant parameters.

The mean age of the patients was 33.17 ± 12. Keeping 5% as the level of significance, we find the parameters namely gender (p=0.043) cannula to articulation (p=0.023), flushing after chemotherapy (p<0.000), and history of extravasation (p<0.000) are very significant. The model is adequate up to 79% on a case-to-case basis by establishing these factors in respect of their variation.

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Awards Nomination

Editors List

  • Prof. Elhadi Miskeen

    Obstetrics and Gynaecology Faculty of Medicine, University of Bisha, Saudi Arabia

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh




  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis


  • Fava Maria Giovanna


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