Mapping the landscape of machine learning models used for predicting transfusions in surgical procedures: a scoping review

Table 4 Variables studied, ranked according to the number of studies in which the variable was studied

Biological variables	Number of studies	Clinical variables	Number of studies
Haemoglobin	31	Age	28
Platelets	16	Sex	21
Haematocrit	14	Surgery Type	18
Creatinine	14	Blood pressure	14
INR	12	Weight	14
APTT	9	Surgery duration	14
Albumin	8	ASA Status	13
White blood Cells	7	Blood loss	12
PT	6	BMI	11
TEG	5	Diabetes	10
Fibrinogen	5	BSA	7
ASAT	4	Height	6
RBC	4	COPD	6
Thrombin time	4	Surgeon	6
PaCO2	3	LVEF	5
Urea	3	Charlson Index	3
MCV	3	RR	2
PaO2	3
Base deficit	2
Lactate	2

INR: International Normalized Ratio, APTT: Activated Partial Thromboplastin Time, PT: Prothrombin Time, TEG: Thromboelastography, ASAT: Aspartate Aminotransferase, RBC: Red Blood Cell, PaCO2: Partial Pressure of Carbon Dioxide in Arterial Blood, MCV: Mean Corpuscular Volume, PaO2: Partial Pressure of Oxygen in Arterial Blood, ASA Status: American Society of Anesthesiologists Physical Status, BMI: Body Mass Index, BSA: Body Surface Area, COPD: Chronic Obstructive Pulmonary Disease, LVEF: Left Ventricular Ejection Fraction, RR: Respiratory Rate

ISSN: 1472-6947