Literature DB >> 17149403

Neutropenia: state of the knowledge part II.

Anita Nirenberg1, Annette Parry Bush, Arlene Davis, Christopher R Friese, Theresa Wicklin Gillespie, Robert David Rice.   

Abstract

PURPOSE/
OBJECTIVES: To summarize the current available evidence for oncology nurses so that they may predict and prevent complications of chemotherapy-induced neutropenia (CIN), provide optimal education to patients, and become familiar with the state of the knowledge of neutropenia by understanding the evidence and guidelines for patients with cancer who may experience CIN. DATA SOURCES: Review of primary literature, meta-analyses, available systematic reviews, clinical practice guidelines, and discussions at the State of the Knowledge on Neutropenia Symposium. DATA SYNTHESIS: The evidence for nursing interventions to prevent CIN complications is underdeveloped. Strong empirical support to prevent infection in patients with CIN (e.g., restrictions in diet, isolation procedures, providing accurate patient education) is lacking. Several areas of preventive measures by patients, hand washing, and skin care have a stronger evidence base and should have high priority on patient education plans.
CONCLUSIONS: Strong evidence is available for several nursing interventions to prevent infection in patients with CIN. Many existing practices lack empirical support and should be identified and reviewed in the clinical setting for appropriate patient management. IMPLICATIONS FOR NURSING: Oncology nurses can use the findings from the symposium to revise their care standards for patients anticipated to experience CIN. Research and practice performance improvement projects may be undertaken by oncology nurses to improve the delivery of evidence-based nursing care to this vulnerable patient population.

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Year:  2006        PMID: 17149403     DOI: 10.1188/06.ONF.1202-1208

Source DB:  PubMed          Journal:  Oncol Nurs Forum        ISSN: 0190-535X            Impact factor:   2.172


  2 in total

1.  National Cancer Institute Cancer Center designation and 30-day mortality for hospitalized, immunocompromised cancer patients.

Authors:  Christopher R Friese; Jeffrey H Silber; Linda H Aiken
Journal:  Cancer Invest       Date:  2010-08       Impact factor: 2.176

2.  Shapley-Additive-Explanations-Based Factor Analysis for Dengue Severity Prediction using Machine Learning.

Authors:  Shihab Uddin Chowdhury; Sanjana Sayeed; Iktisad Rashid; Md Golam Rabiul Alam; Abdul Kadar Muhammad Masum; M Ali Akber Dewan
Journal:  J Imaging       Date:  2022-08-26
  2 in total

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