Retrospective analysis of nursing interventions using artificial intelligence multimodal emotion recognition for perioperative depression in head and neck tumors

Table 1 Comparison of baseline data and preoperative emotional parameters between the two groups of patients, n (%)

Project	Conventional care group (n = 27)	Artificial intelligence personalized care group (n = 33)	t/χ2 value	P value
Age (years)	58.48 ± 9.73	57.94 ± 10.18	0.208	0.836
Male	17 (62.96)	22 (66.67)	0.090	0.765
History of smoking	16 (59.26)	21 (63.64)	0.120	0.729
Oral cancer	10 (37.04)	12 (36.36)	0.003	0.957
Laryngeal cancer	8 (29.63)	10 (30.30)	0.003	0.955
Oropharyngeal/hypopharyngeal cancer	9 (33.33)	11 (33.33)	0.000	1.000
ASA class II	20 (74.07)	25 (75.76)	0.022	0.881
TNM stage III-IV	21 (77.78)	27 (81.82)	0.152	0.697
Total laryngectomy	8 (29.63)	10 (30.30)	0.003	0.955
HAMD score (points)	24.93 ± 4.11	24.12 ± 4.36	0.734	0.466
Comprehensive Emotional Score (point)	37.84 ± 10.22	38.67 ± 9.85	-0.319	0.751
Baseline EMI	0.39 ± 0.11	0.37 ± 0.10	0.737	0.464
Baseline proportion of positive emotions (%)	28.10 ± 9.23	29.22 ± 8.95	-0.476	0.636
Facial modal quality score	0.85 ± 0.07	0.86 ± 0.07	-0.551	0.584

ASA: American Society of Anesthesiologists; TNM: Tumor-node-metastasis; HAMD: Hamilton Depression Rating Scale; EMI: Emotional Mood Index.