Albumin level and patient age predict outcomes in patients referred for gastrostomy insertion: internal and external validation of a gastrostomy score and comparison with artificial neural networks.
BACKGROUND
Significant mortality after gastrostomy insertion remains and some risk factors have been identified, but no predictive scoring system exists.


OBJECTIVE
To identify risk factors for mortality, formulate a predictive scoring system, and validate the score. Comparison to an artificial neural network (ANN).


METHODS
Endoscopic database analysis.


METHODS
Six hospitals (2 teaching hospitals) in the South Yorkshire region, United Kingdom.


METHODS
This study involved all patients referred for gastrostomy insertion.


METHODS
Generation of clinical scores to predict 30-day mortality in patients undergoing gastrostomy insertion.


METHODS
Risk factors for 30-day mortality. Internal and external validation of the score. Comparison with an ANN.


RESULTS
Univariate analysis showed that 30-day mortality was associated with age, albumin levels, and cardiac and neurological comorbidities. Multivariate analysis showed that only age and albumin levels were independent. Modeling provided scores of 0, 1, 2, and 3 corresponding to 30-day mortalities of 0% (0-2.1), 7% (2.9-13.9), 21.3% (13.5-30.9), and 37.3% (24.1-51.9), respectively. Application of the scoring system at the other teaching hospital and the 4 district general hospitals gave 30-day mortality rates that were not significantly different from those predicted. Receiver operating characteristic curves for the score and the ANN were comparable.


CONCLUSIONS
Nonrandomized study. Score not used as a decision-making tool.


CONCLUSIONS
The gastrostomy score provides an estimate of 30-day mortality for patients (and their relatives) when gastrostomy insertion is being discussed. This score requires evaluation as a decision-making tool in clinical practice. ANN analysis results were similar to the outcomes from the clinical score.
Gastroenterology & Liver Unit, Royal Hallamshire Hospital, Sheffield, United Kingdom. j.leeds@nhs.net
John
J
Leeds
Mark E
ME
McAlindon
Julia
J
Grant
Helen E
HE
Robson
Stephen R
SR
Morley
Gary
G
James
Barbara
B
Hoeroldt
Kapil
K
Kapur
Keith
K
Dear
James
J
Hensman
Keith
K
Worden
David S
DS
Sanders
D000367:Age Factors; D000368:Aged; D003661:Decision Support Techniques; D005260:Female; D005774:Gastrostomy / Q000401:mortality*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D016571:Neural Networks, Computer; D012372:ROC Curve; D012709:Serum Albumin; D006113:United Kingdom
D012709:Serum Albumin