TY - JOUR
T1 - Which is more useful in predicting hospital mortality - dichotomised blood test results or actual test values? a retrospective study in two hospitals
AU - Mohammed, M.
AU - Rudge, G.
AU - Wood, G.
AU - Smith, G.
AU - Nangalia, V.
AU - Prytherch, David
AU - Holder, R.
AU - Briggs, Jim
N1 - Funders:
National Institute for Health Research (NIHR).
Projects:
CHMI.
Health informatics.
Clinical outcome modelling.
PY - 2012/10/15
Y1 - 2012/10/15
N2 - Background
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.
Methodology
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.
Results
The mortality rate was 6.98% (701/10050). The mean predicted risk of death in those who died was significantly (p-value
AB - Background
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.
Methodology
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.
Results
The mortality rate was 6.98% (701/10050). The mean predicted risk of death in those who died was significantly (p-value
U2 - 10.1371/journal.pone.0046860
DO - 10.1371/journal.pone.0046860
M3 - Article
SN - 1932-6203
VL - 7
SP - e46860
JO - PLoS One
JF - PLoS One
IS - 10
ER -