Which is more useful in predicting hospital mortality--dichotomised blood test results or actual test values? A retrospective study in two hospitals

Routine blood tests are an integral part of clinical medicine and in interpreting blood test results clinicians have two broad options. (1) Dichotomise the blood tests into normal/abnormal or (2) use the actual values and overlook the reference values. We refer to these as the "binary" and...

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Bibliographic Details
Published in:PloS one 2012-10, Vol.7 (10), p.e46860-e46860
Main Authors: Mohammed, Mohammed A, Rudge, Gavin, Wood, Gordon, Smith, Gary, Nangalia, Vishal, Prytherch, David, Holder, Roger, Briggs, Jim
Format: Article
Language:English
Subjects:
Adult
Aged
Aged, 80 and over
Analysis
Biology
Blood
Blood tests
Cell culture
Clinical decision making
Clinical medicine
Creatinine
Death
Decision making
Education
Emergency medical care
Emergency medical services
Ethics
Female
Females
Health aspects
Hematologic Tests
Hemoglobin
Hospital Mortality
Hospitals
Humans
Informatics
Laboratories
Leukocytes
Male
Mathematics
Medicine
Middle Aged
Models, Statistical
Mortality
Patients
Potassium
Primary care
Retrospective Studies
Risk
Risk Assessment - methods
ROC Curve
Sodium
Strategy
Survival analysis
Urea
Values
White blood cell count
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Summary:Routine blood tests are an integral part of clinical medicine and in interpreting blood test results clinicians have two broad options. (1) Dichotomise the blood tests into normal/abnormal or (2) use the actual values and overlook the reference values. We refer to these as the "binary" and the "non-binary" strategy respectively. We investigate which strategy is better at predicting the risk of death in hospital based on seven routinely undertaken blood tests (albumin, creatinine, haemoglobin, potassium, sodium, urea, and white blood cell count) using tree models to implement the two strategies. A retrospective database study of emergency admissions to an acute hospital during April 2009 to March 2010, involving 10,050 emergency admissions with routine blood tests undertaken within 24 hours of admission. We compared the area under the Receiver Operating Characteristics (ROC) curve for predicting in-hospital mortality using the binary and non-binary strategy. The mortality rate was 6.98% (701/10050). The mean predicted risk of death in those who died was significantly (p-value
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0046860