溃疡性结肠炎并发坏疽性脓皮病患者发生营养风险的因素及预测模型

doi:10.12122/j.issn.1673-4254.2025.03.09

南方医科大学学报 ›› 2025, Vol. 45 ›› Issue (3): 514-521.doi: 10.12122/j.issn.1673-4254.2025.03.09

• • 上一篇

溃疡性结肠炎并发坏疽性脓皮病患者发生营养风险的因素及预测模型

申琳¹(), 宋翠豪¹(), 王聪敏², 高西³, 安俊红⁴, 李承新¹(), 梁斌⁵(), 李霞⁶()

^1.解放军总医院第一医学中心皮肤科，北京 100853
^2.解放军总医院第七医学中心皮肤科，北京 100010
^3.重庆医科大学附属大学城医院中医科，重庆 401331
^4.山西医科大学第一医院整形科，山西太原 030032
^5.解放军空军特色医学中心皮肤科，北京 100142
^6.解放军总医院第一医学中心康复科，北京 100853

收稿日期:2024-12-16 出版日期:2025-03-20 发布日期:2025-03-28
通讯作者: 李承新,梁斌,李霞 E-mail:linlinshen1995@126.com;18110026396@163.com;chengxinderm@163.com;echo_lb666@163.com;1648248514@qq.com
作者简介:申琳，硕士，E-mail: linlinshen1995@126.com
宋翠豪，博士，E-mail: 18110026396@163.com
第一联系人：申琳、宋翠豪共同为第一作者
基金资助:
国家自然科学基金(82273530)

Risk factors for malnutrition in ulcerative colitis complicated with pyoderma gangrenosum and construction of a lasso regression-based prediction model

Lin SHEN¹(), Cuihao SONG¹(), Congmin WANG², Xi GAO³, Junhong AN⁴, Chengxin LI¹(), Bin LIANG⁵(), Xia LI⁶()

^1.Department of Dermatology, First Medical Center of PLA General Hospital, Beijing 100853, China
^2.Department of Dermatology, Seventh Medical Center of PLA General Hospital, Beijing 100010, China
^3.Department of Traditional Chinese Medicine, University Town Hospital Affiliated to Chongqing Medical University, Chongqing 401331, China
^4.Department of Plastic Surgery, First Hospital of Shanxi Medical University, Taiyuan 030032, China
^5.Department of Dermatology, PLA Air Force Medical Center, Beijing 100142, China
^6.Department of Rehabilitation, First Medical Center of PLA General Hospital, Beijing 100853, China

Received:2024-12-16 Online:2025-03-20 Published:2025-03-28
Contact: Chengxin LI, Bin LIANG, Xia LI E-mail:linlinshen1995@126.com;18110026396@163.com;chengxinderm@163.com;echo_lb666@163.com;1648248514@qq.com
Supported by:
National Natural Science Foundation of China(82273530)

摘要/Abstract

摘要：

目的探索溃疡性结肠炎伴发坏疽性脓皮病患者发生营养不良的风险因素，并建立本类患者营养风险预测模型。方法纳入2019~2024年277例溃疡性结肠炎伴坏疽性脓皮病患者为研究对象，根据是否发生营养不良分为不良组（n=185）和良好组（n=92）。比较两组患者一般人口学、生活饮食习惯、疾病相关资料共25项潜在相关因素的差异。采用Lasso回归筛选危险因素，建立列线图模型并验证模型预测性能。结果不良组与良好组间性别、年龄、文化程度、BMI指数、居住地、病程、SAS语评分等共21个指标存在差异（P<0.05）。Lasso回归分析发现溃疡性结肠炎病程、溃疡性结肠炎活动度、坏疽性脓皮病病程、合并慢性病数量、SAS评分、睡眠质量6个因素与本类患者营养不良相关性较大。基于上述6个因素建立列线图预测模型，预测该类患者营养不良AUC（95% CI）=0.992（0.984~1.000），对14例患者的应用显示准确率100%。结论溃疡性结肠炎病程、结肠炎活动度、坏疽性脓皮病病程、合并慢性病数量、焦虑程度、睡眠质量与溃疡性结肠炎伴发坏疽性脓皮病患者营养不良相关性较大，基于上述6个因素建立列线图预测模型有较高临床应用价值。

关键词: 溃疡性结肠炎, 坏疽性脓皮病, 营养风险, 预测模型

Abstract:

Objective To explore the risk factors for malnutrition in patients with ulcerative colitis complicated with pyoderma gangrenosum and establish a nutritional risk prediction model for these patients. Methods A total of 277 patients with ulcerative colitis complicated with pyoderma gangrenosum treated from 2019 to 2024 were divided into malnutrition group (n=185) and normal nutrition group (n=92) according to whether malnutrition occurred. The data of 25 potential related factors pertaining to general demography, living and eating habits, and disease-related data were compared between the two groups. Lasso regression was used to screen the risk factors, and a nomogram model was established based on the screened factors and its prediction performance was assessed. Results The patients in the malnutrition group and normal nutrition group showed significant differences in 21 factors including gender, age, education level, BMI, place of residence, course of disease, and SAS language score (P<0.05). Lasso regression analysis identified 6 factors associated with malnutrition in these patients, namely the duration of ulcerative colitis, activity of ulcerative colitis, duration of pyoderma gangrenosum, number of chronic diseases, SAS score, and sleep quality. The nomogram prediction model established based on these 6 factors had an AUC of 0.992 (95% CI: 0.984-1.000) for predicting malnutrition in these patients, and its application in 14 clinical cases achieved an accuracy rate of 100%. Conclusion The duration of ulcerative colitis, activity of colitis, duration of pyoderma gangrenosum, number of chronic diseases, anxiety, and sleep quality are closely related with malnutrition in patients with ulcerative colitis complicated by pyoderma gangrenosum, and the nomogram prediction model based on these factors can provide assistance for predicting malnutrition in these patients.

Key words: ulcerative colitis, pyoderma gangrenosum, nutritional risk, prediction model

申琳, 宋翠豪, 王聪敏, 高西, 安俊红, 李承新, 梁斌, 李霞. 溃疡性结肠炎并发坏疽性脓皮病患者发生营养风险的因素及预测模型[J]. 南方医科大学学报, 2025, 45(3): 514-521.

Lin SHEN, Cuihao SONG, Congmin WANG, Xi GAO, Junhong AN, Chengxin LI, Bin LIANG, Xia LI. Risk factors for malnutrition in ulcerative colitis complicated with pyoderma gangrenosum and construction of a lasso regression-based prediction model[J]. Journal of Southern Medical University, 2025, 45(3): 514-521.

图/表 8

参考文献 30

1	中国中西医结合学会. 溃疡性结肠炎中西医结合诊疗专家共识[J]. 中国中西医结合杂志, 2023, 43(1): 5-11.
2	宋泽军, 张明君, 任渝棠, 等. 改良Mayo内镜评分对溃疡性结肠炎有较高的评估价值[J]. 南方医科大学学报, 2022, 42(7): 997-1005.
3	焦雨竹, 杨青. 坏疽性脓皮病治疗进展[J]. 中国麻风皮肤病杂志, 2024, 40(3): 216-20.
4	单玮, 雷春明, 肖文, 等. 阙华发辨治溃疡性结肠炎并发坏疽性脓皮病经验[J]. 辽宁中医杂志, 2022, 49(3): 30-2.
5	Xu HM, Huang HL, Xu J, et al. Cross-talk between butyric acid and gut microbiota in ulcerative colitis following fecal microbiota transplantation[J]. Front Microbiol, 2021, 12: 658292.
6	Chen QY, Fan YY, Zhang BZ, et al. Capsulized fecal microbiota transplantation induces remission in patients with ulcerative colitis by gut microbial colonization and metabolite regulation[J]. Microbiol Spectr, 2023, 11(3): e0415222.
7	袁伟, 李娟, 杨小娟, 等. 肠内营养对活动期溃疡性结肠炎伴营养不良患者营养状况、肠黏膜屏障功能和肠道菌群的影响[J]. 现代生物医学进展, 2022, 22(14): 2658-62.
8	刘仁娟, 田字彬, 王丹丹, 等. 溃疡性结肠炎病人生物电阻抗相位角与营养状况的关系研究[J]. 肠外与肠内营养, 2023, 30(6): 328-33.
9	张文玉, 马贤纵, 谢惠, 等. 炎症性肠病患者营养障碍的研究[J]. 胃肠病学和肝病学杂志, 2024, 33(6): 641-5.
10	楚俊红, 王丽敏, 樊虹雨, 等. 活动期溃疡性结肠炎住院病人营养风险研究[J]. 护理研究, 2022, 36(22): 4131-3.
11	Kondrup J, Rasmussen HH, Hamberg O, et al. Nutritional risk screening (NRS 2002): a new method based on an analysis of controlled clinical trials[J]. Clin Nutr, 2003, 22(3): 321-36.
12	李军祥, 陈誩. 溃疡性结肠炎中西医结合诊疗共识意见(2017年)[J]. 中国中西医结合消化杂志, 2018, 26(2): 105-11, 120.
13	Jockenhöfer F, Wollina U, Salva KA, et al. The PARACELSUS score: a novel diagnostic tool for pyoderma gangrenosum[J]. Br J Dermatol, 2019, 180(3): 615-20.
14	王征宇, 迟玉芬. 抑郁自评量表(SDS)[J]. 上海精神医学, 1984, 2: 71-2.
15	Dunstan DA, Scott N. Norms for zung's self-rating anxiety scale[J]. BMC Psychiatry, 2020, 20(1): 90.
16	Sachan A, Thungapathra M, Kaur H, et al. Comprehensive assessment of nutritional and functional status of patients with ulcerative colitis and their impact on quality of life[J]. Indian J Gastroenterol, 2024, 43(1): 254-63.
17	Li XJ, Hu YD, Shi XD, et al. Prevalence and relevant factors of micronutrient deficiencies in hospitalized patients with inflammatory bowel disease[J]. Nutrition, 2022, 99/100: 111671.
18	刘仁娟, 田字彬, 荆雪, 等. GLIM标准诊断的营养不良与溃疡性结肠炎住院患者疾病活动度及不良临床结局的关系[J]. 中华临床营养杂志, 2024, 32(2): 98-104.
19	Ünal NG, Oruç N, Tomey O, et al. Malnutrition and sarcopenia are prevalent among inflammatory bowel disease patients with clinical remission[J]. Eur J Gastroenterol Hepatol, 2021, 33(11): 1367-75.
20	Kamel AY, Johnson ZD, Hernandez I, et al. Micronutrient deficiencies in inflammatory bowel disease: an incidence analysis[J]. Eur J Gastroenterol Hepatol, 2024, 36(10): 1186-92.
21	Zerouga I, Valeur J, Sommer C, et al. Dietary intake and nutritional status in patients with newly diagnosed inflammatory bowel disease: insights from the IBSEN III study[J]. Scand J Gastroenterol, 2024, 59(6): 652-60.
22	Day AS, Davis R, Costello SP, et al. The adequacy of habitual dietary fiber intake in individuals with inflammatory bowel disease: a systematic review[J]. J Acad Nutr Diet, 2021, 121(4): 688-708. e3.
23	Jabłońska B, Mrowiec S. Nutritional status and its detection in patients with inflammatory bowel diseases[J]. Nutrients, 2023, 15(8): 1991.
24	Whelan K, Murrells T, Morgan M, et al. Food-related quality of life is impaired in inflammatory bowel disease and associated with reduced intake of key nutrients[J]. Am J Clin Nutr, 2021, 113(4): 832-44.
25	Gold SL, Rabinowitz LG, Manning L, et al. High prevalence of malnutrition and micronutrient deficiencies in patients with inflammatory bowel disease early in disease course[J]. Inflamm Bowel Dis, 2023, 29(3): 423-9.
26	Dhaliwal A, Quinlan JI, Overthrow K, et al. Sarcopenia in inflammatory bowel disease: a narrative overview[J]. Nutrients, 2021, 13(2): 656.
27	Hashash JG, Elkins J, Lewis JD, et al. AGA clinical practice update on diet and nutritional therapies in patients with inflammatory bowel disease: expert review[J]. Gastroenterology, 2024, 166(3): 521-32.
28	Skrzypczak D, Ratajczak AE, Szymczak-Tomczak A, et al. A vicious cycle of osteosarcopeniain inflammatory bowel diseases-aetiology, clinical implications and therapeutic perspectives[J]. Nutrients, 2021, 13(2): 293.
29	荫士安, 董彩霞, 杨振宇. 遏制人群慢性病上升态势的全生命周期预防建议[J]. 中华预防医学杂志, 2024, 58(1): 107-13.
30	王禹毅, 卜志军, 李元晞, 等. 临床预测模型变量筛选方法及比较[J]. 现代中医临床, 2024, 31(2): 6-12.

Project	Unhealthy group (n=185)	Good group (n=92)	t/x²	P
Gender			5.988	0.014
Male	109 (58.92)	68 (73.91)
Female	76 (41.08)	24 (26.09)
Age (year)	59.63±14.62	52.82±13.94	3.165	0.002
Education level			6.243	0.044
Elementary school or below	99 (53.51)	37 (40.22)
High school	58 (31.35)	31 (33.70)
University	28 (15.14)	24 (26.01)
Marital status in the past year			6.104	0.047
Unmarried	16 (8.65)	3 (3.26)
Divorced/widowed	34 (18.38)	10 (10.87)
In marriage	135 (72.97)	79 (85.87)
Body mass index (kg/m²)	21.80±3.47	24.52±2.95	-10.416	<0.001
Residential area in the past year			11.457	0.003
Rural area	92 (49.73)	33 (35.87)
Town	37 (20.00)	12 (13.04)
Urban area	56 (30.27)	47 (51.09)
Residential partner in the past year			7.497	0.024
Live alone	41 (22.16)	9 (9.78)
Friends/relatives	10 (5.41)	3 (3.26)
Spouse/children	134 (72.43)	80 (86.96)
Economic pressure in the past year			25.668	<0.001
No	30 (16.22)	39 (42.39)
General	67 (36.22)	31 (33.70)
Larger	88 (47.56)	22 (23.91)

Project	Unhealthy group (n=185)	Good group (n=92)	t/x²	P
Gender			5.988	0.014
Male	109 (58.92)	68 (73.91)
Female	76 (41.08)	24 (26.09)
Age (year)	59.63±14.62	52.82±13.94	3.165	0.002
Education level			6.243	0.044
Elementary school or below	99 (53.51)	37 (40.22)
High school	58 (31.35)	31 (33.70)
University	28 (15.14)	24 (26.01)
Marital status in the past year			6.104	0.047
Unmarried	16 (8.65)	3 (3.26)
Divorced/widowed	34 (18.38)	10 (10.87)
In marriage	135 (72.97)	79 (85.87)
Body mass index (kg/m²)	21.80±3.47	24.52±2.95	-10.416	<0.001
Residential area in the past year			11.457	0.003
Rural area	92 (49.73)	33 (35.87)
Town	37 (20.00)	12 (13.04)
Urban area	56 (30.27)	47 (51.09)
Residential partner in the past year			7.497	0.024
Live alone	41 (22.16)	9 (9.78)
Friends/relatives	10 (5.41)	3 (3.26)
Spouse/children	134 (72.43)	80 (86.96)
Economic pressure in the past year			25.668	<0.001
No	30 (16.22)	39 (42.39)
General	67 (36.22)	31 (33.70)
Larger	88 (47.56)	22 (23.91)

Project	unhealthy group (n=185)	Good group (n=92)	t/x²	P
Exercise frequency in past year			3.714	0.156
Less	43 (23.24)	16 (17.39)
General	81 (43.78)	35 (38.04)
Often	61 (32.98)	41 (44.57)
Types of food in past year			26.339	<0.001
Less	85 (45.95)	27 (29.35)
General	66 (35.68)	21 (22.83)
Often	34 (18.37)	44 (47.82)
Dietary preference in past year			7.407	0.025
Less	48 (25.95)	11 (11.96)
General	62 (33.51)	34 (36.96)
Often	75 (40.54)	47 (51.08)
Smoking in past year			0.827	0.661
Less	109 (58.92)	58 (63.04)
General	42 (22.70)	21 (22.83)
Often	34 (18.38)	13 (14.13)
Drinking in the past year			9.568	0.008
Less	95 (51.35)	62 (67.39)
General	48 (25.95)	22 (23.91)
Often	42 (22.70)	8 (8.70)

Project	unhealthy group (n=185)	Good group (n=92)	t/x²	P
Exercise frequency in past year			3.714	0.156
Less	43 (23.24)	16 (17.39)
General	81 (43.78)	35 (38.04)
Often	61 (32.98)	41 (44.57)
Types of food in past year			26.339	<0.001
Less	85 (45.95)	27 (29.35)
General	66 (35.68)	21 (22.83)
Often	34 (18.37)	44 (47.82)
Dietary preference in past year			7.407	0.025
Less	48 (25.95)	11 (11.96)
General	62 (33.51)	34 (36.96)
Often	75 (40.54)	47 (51.08)
Smoking in past year			0.827	0.661
Less	109 (58.92)	58 (63.04)
General	42 (22.70)	21 (22.83)
Often	34 (18.38)	13 (14.13)
Drinking in the past year			9.568	0.008
Less	95 (51.35)	62 (67.39)
General	48 (25.95)	22 (23.91)
Often	42 (22.70)	8 (8.70)

Project	Unhealthy group (n=185)	Good group (n=92)	t/x²	P
Duration of ulcerative colitis (months)	93.19±48.83	49.01±31.29	12.18	0.000
Lesion site of colitis			15.374	0.000
Rectum	34 (18.38)	37 (40.22)
Colon	151 (81.62)	55 (59.78)
Colitis activity			48.751	0.000
Mild	41 (22.16)	55 (59.78)
Moderate	85 (45.95)	34 (36.96)
Severe	59 (31.89)	3 (3.26)
Course of pyoderma gangrenosum (months)	10.99±4.94	6.11±3.26	8.591	0.000
Classification of pyoderma			5.704	0.058
Kuitang type	78 (42.16)	29 (31.52)
Pustular type	42 (22.70)	17 (18.48)
Proliferative type	65 (35.14)	46 (50.00)
Number of chronic diseases (types)	4.18±2.85	2.89±2.02	6.814	0.000
Self care ability			14.304	0.001
Unable to care on self	11 (5.95)	1 (1.09)
Partially self-care	62 (33.51)	15 (16.30)
Completely self-care	112 (60.5)	76 (82.61)
Sds score	59.78±13.81	50.85±12.68	5.206	0.000
Sas score	62.98±12.26	51.83±11.33	6.004	0.000
Denture or dental problems	34 (18.38)	5 (5.43)	8.510	0.004
Sleep quality in recent half a year			47.101	0.000
Poor	85 (45.95)	22 (23.91)
General	94 (50.81)	41 (44.57)
Better	6 (3.24)	29 (31.52)

溃疡性结肠炎并发坏疽性脓皮病患者发生营养风险的因素及预测模型

Risk factors for malnutrition in ulcerative colitis complicated with pyoderma gangrenosum and construction of a lasso regression-based prediction model

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参考文献 30

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Factors	β	S.E	Z	P	OR (95% CI)
Duration of ulcerative colitis	0.065	0.017	3.922	0.000	1.067 (1.033-1.102)
Colitis activity
Mild					1.000
Moderate	2.541	1.116	2.277	0.023	2.694 (1.425-3.071)
Severe	2.600	1.046	2.484	0.013	3.460 (1.731-4.645)
Course of pyoderma gangrenosum	0.539	0.164	3.280	0.001	1.715 (1.242-2.367)
Number of chronic diseases	0.621	0.188	3.302	0.000	1.861 (1.287-2.690)
Sleep quality
Better					1.000
General	0.742	0.950	0.781	0.435	1.101 (0.326-3.529)
Poor	3.814	1.187	3.214	0.001	3.336 (1.429-6.088)
Sas score	0.192	0.052	3.727	0.000	1.112 (1.025-1.341)

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