Predicting red blood cell transfusion in hospitalized patients: role of hemoglobin level, comorbidities, and illness severity

Table 4 Predictive model performance for specific medical conditions

Model¹	GI bleed		Infection		Cardiovascular		Malignancy		Orthopedic surgery
	N=12,388		N=57,473		N=47,996		N=27,831		N=24,264
	C-statistic	Pseudo-R²	C-statistic	Pseudo-R²	C-statistic	Pseudo -R²	C-statistic	Pseudo -R²	C-statistic	Pseudo-R²
Administrative Data²	0.587	0.032	0.616	0.038	0.666	0.058	0.828	0.379	0.686	0.121
(a) + Admission Hemoglobin	0.862	0.543	0.839	0.399	0.852	0.419	0.875	0.538	0.696	0.146
(b) + Severity of Illness	0.884	0.566	0.851	0.406	0.866	0.425	0.880	0.547	0.699	0.151
(c) + Prior RBC Transfusion	0.887	0.570	0.862	0.419	0.873	0.432	0.884	0.556	0.709	0.162
(d) + Initial Hospital Location	0.896	0.590	0.871	0.432	0.877	0.440	0.885	0.558	0.710	0.162
(e) + Hospital	0.900	0.599	0.875	0.441	0.884	0.451	0.890	0.563	0.729	0.191

Footnotes
¹Model performance in this table is measured using the area under the receiver operator characteristic curve (C-statistic) and Nagelkerke’s Pseudo R².
²Administrative data includes age, sex, comorbid conditions (COPS2), admission type (emergency or elective), and admission diagnosis.

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