A random forest algorithm-based prediction model for moderate to severe acute postoperative pain after orthopedic surgery under general anesthesia

Table 2 The characteristics of all enrolled patients(Training set vs. Testing set)

Variables	Total patients (n = 327)	Training set (n = 228)	Testing set (n = 99)	t / χ² / Z	P-value
Demographics
Age, years	51.63 ± 14.38	52.32 ± 13.74	50.03 ± 15.71	-1.2564	0.2107
Perioperatives
Indwelling urinary catheters				0.9726	0.324
yes	227	154	73
no	100	74	26
Arteriovenous catheterization				0.84331	0.3585
yes	80	52	28
no	247	176	71
Secondary surgery in a short period				0.016849	0.8967
yes	19	14	5
no	308	214	94
Duration of surgery, minutes	124 (170-80)	124 (166.25-81.5)	113 (170-79)	2.1046	0.673
Blood loss during surgery, ml	150 (400-100)	150 (400-80)	200 (400-100)	1.3283	0.572
Time from withdrawal of medicine to awake, minutes	15.77 ± 3.76	15.82 ± 3.67	15.66 ± 3.97	-0.34078	0.7337
Immobilization				0.60667	0.436
yes	104	69	35
no	223	159	64
Tourniquet during surgery				4.2322	0.03966
yes	65	38	27
no	262	190	72
Moderate to severe postoperative pain				0.11243	0.7374
yes	135	96	39
no	192	132	60

ISSN: 1471-2253