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Article(id=1322218686103011917, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322218660677140862, articleNumber=null, orderNo=null, doi=10.16016/j.2097-0927.202411118, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1732550400000, receivedDateStr=2024-11-26, revisedDate=1741104000000, revisedDateStr=2025-03-05, acceptedDate=null, acceptedDateStr=null, onlineDate=1793171100402, onlineDateStr=2026-10-28, pubDate=1748534400000, pubDateStr=2025-05-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793171100402, onlineIssueDateStr=2026-10-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793171100402, creator=13701087609, updateTime=1793171100402, updator=13701087609, issue=Issue{id=1322218660677140862, tenantId=1146029695717560320, journalId=1319373162502258839, year='2025', volume='47', issue='10', pageStart='1029', pageEnd='1144', issueExtLink='null', onlineDate='null', pubDate='1748534400000', pubDateStr='2025-05-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793171094339, creator='13701087609', updateTime=1793325331065, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322865576456868294, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322218660677140862, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322865576456868295, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322218660677140862, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1092, endPage=1101, ext={EN=ArticleExt(id=1322218686329504334, articleId=1322218686103011917, tenantId=1146029695717560320, journalId=1319373162502258839, language=EN, title=Construction and accuracy analysis of a malnutrition prediction model for patients after proximal femoral nail anti rotation internal fixation, columnId=1320435174995772212, journalTitle=Journal of Army Medical University, columnName=Clinical Medicine, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the related factors of postoperative nutritional risk in elderly patients with proximal femoral nail anti rotation (PFNA) internal fixation and establish a prediction model of malnutrition.

Methods‍

A total of 574 elderly patients who underwent PFNA internal fixation in the First Medical Center of Chinese PLA General Hospital from January 2021 to June 2024 were included and divided into malnutrition group (n=389) and good nutrition group (n=185). The differences in 39 indicators in aspects of physiological, psychological, social, economic, environmental and medical fields were compared between the 2 groups. Logistic analysis was used to screen the nutritional risk factors, and then a nomogram model was constructed based on these factors.

Results‍

Advanced age, lower BMI, higher postoperative Self-Rating Anxiety Scale (SAS) score, less exercise before fracture, being farmers, higher economic pressure, lower preoperative albumin, preprotein and hemoglobin, and lower Barthel index before fracture were independent risk factors for nutritional risk in patients undergoing PFNA internal fixation (P<0.05). The nomogram prediction model based on the above factors had an AUC value of 0.995 (95%CI: 0.987~1.000) in predicting the risk of malnutrition in these patients. When the threshold probability >0.02, this model could be clinically beneficial in predicting the risk of postoperative malnutrition in patients after PFNA internal fixation.

Conclusion‍

Our nutritional risk prediction model based on age, BMI, economic pressure, pre-fracture exercise and preoperative albumin and other indicators is constructed for the elderly patients after PFNA internal fixation, and the model has high accuracy and clinical application value.

, authors=Lin SHEN1, Xiaojia BAI2, Gang WANG3, Lijuan XUE4, Chunhua ZHANG5, Xia LI3, authorsList=Lin SHEN, Xiaojia BAI, Gang WANG, Lijuan XUE, Chunhua ZHANG, Xia LI, authorCompany=null, correspAuthors=Xia LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=© 2025 Journal of Army Medical University, copyrightOwner=Editorial Office of Journal of Army Medical University, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322218687466160727, articleId=1322218686103011917, tenantId=1146029695717560320, journalId=1319373162502258839, language=CN, title=PFNA内固定术后患者营养不良预测模型构建及其准确性分析, columnId=1322185541475488183, journalTitle=陆军军医大学学报, columnName=临床医学, runingTitle=null, highlight=null, articleAbstract=

‍

目的

探索股骨近端防旋髓内钉（proximal femoral nail anti-rotatio，PFNA）内固定术老年患者术后营养风险相关因素并建立营养不良预测模型。

方法

纳入2021年1月至2024年6月于我院接受PFNA内固定术老年患者574例，分为营养不良组（389例）和营养良好组（185例），比较2组患者生理、心理、社会、经济、环境、医学等因素共39个指标的差异，采用Logistic分析筛选营养风险危险因素并构建列线图模型。

结果

年龄偏高、BMI指数偏低、术后SAS评分偏高、骨折前较少锻炼、农民、经济压力较高，及术前白蛋白、前蛋白、血红蛋白偏低，骨折前Barthel指数偏低是PFNA内固定术患者营养风险的独立危险因素（P<0.05）。纳入上述因素构建列线图预测模型，预测该类患者发生营养不良风险的AUC（95%CI）=0.995（0.987~1.000），在阈概率>0.02时采用本模型预测PFNA内固定术患者术后营养不良风险均可临床获益。

结论

基于年龄、BMI指数、经济压力、骨折前锻炼情况及术前白蛋白等指标构建老年患者PFNA内固定术术后营养风险预测模型，有较高的准确性和临床应用价值。

, authors=申琳1, 白小嘉2, 王刚3, 薛丽娟4, 张春华5, 李霞3, authorsList=申琳, 白小嘉, 王刚, 薛丽娟, 张春华, 李霞, authorCompany=null, correspAuthors=李霞, authorNote=

同等贡献者

SHEN Lin and BAI Xiaojia contributed equally to the article.

, correspAuthorsNote=
李 霞，E-mail：
LI Xia，E-mail：.
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Osteoporos Int，2023，34（7）：1207-1221., articleTitle=Geriatric nutritional risk index as the prognostic factor in older patients with fragility hip fractures, refAbstract=null), Reference(id=1322218700682412735, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.3760/cma.j.cn431274-20231108-00528, pmid=null, pmcid=null, year=2024, volume=26, issue=6, pageStart=876, pageEnd=880, url=null, language=null, rfNumber=23, rfOrder=30, authorNames=马小芬, 张士奇, 薛丹丹, journalName=中国医师杂志, refType=null, unstructuredReference=马小芬，张士奇，薛丹丹，等. 血清OPN、BMP2、RBP4与糖尿病肾病患者肾功能及骨密度的相关性［J］. 中国医师杂志，2024，26（6）：876-880., articleTitle=血清OPN、BMP2、RBP4与糖尿病肾病患者肾功能及骨密度的相关性, refAbstract=null), Reference(id=1322218700762104512, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.3760/cma.j.cn431274-20231108-00528, pmid=null, pmcid=null, year=2024, volume=26, issue=6, pageStart=876, pageEnd=880, url=null, language=null, rfNumber=23, rfOrder=31, authorNames=MA X F, ZHANG S Q, XUE D D, journalName=J Chin Physician, refType=null, unstructuredReference=MA X F，ZHANG S Q，XUE D D，et al. Correlation between serum OPN，BMP2，RBP4 and renal function and bone mineral density in diabetes nephropathy patients［J］. J Chin Physician，2024，26（6）：876-880., articleTitle=Correlation between serum OPN，BMP2，RBP4 and renal function and bone mineral density in diabetes nephropathy patients, refAbstract=null), Reference(id=1322218700845990593, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.13898/j.cnki.issn.1000-2200.2023.07.026, pmid=null, pmcid=null, year=2023, volume=48, issue=7, pageStart=967, pageEnd=970，975, url=null, language=null, rfNumber=24, rfOrder=32, authorNames=李蕾, 陈燕, 邵松, journalName=蚌埠医学院学报, refType=null, unstructuredReference=李蕾，陈燕，邵松，等. 创伤骨折术后病人营养不良风险预测模型的构建［J］. 蚌埠医学院学报，2023，48（7）：967-970，975., articleTitle=创伤骨折术后病人营养不良风险预测模型的构建, refAbstract=null), Reference(id=1322218700938265282, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.13898/j.cnki.issn.1000-2200.2023.07.026, pmid=null, pmcid=null, year=2023, volume=48, issue=7, pageStart=967, pageEnd=970，975, url=null, language=null, rfNumber=24, rfOrder=33, authorNames=LI L, CHEN Y, SHAO S, journalName=J Bengbu Med Coll, refType=null, unstructuredReference=LI L，CHEN Y，SHAO S，et al. Construction of a risk prediction model for malnutrition in patients after traumatic fracture surgery［J］. J Bengbu Med Coll，2023，48（7）：967-970，975., articleTitle=Construction of a risk prediction model for malnutrition in patients after traumatic fracture surgery, refAbstract=null), Reference(id=1322218701085065923, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.3969/j.issn.1002-3429.2024.06.007, pmid=null, pmcid=null, year=2024, volume=37, issue=6, pageStart=30, pageEnd=35, url=null, language=null, rfNumber=25, rfOrder=34, authorNames=秦晗, 段锦涛, 郝棚娜, journalName=临床误诊误治, refType=null, unstructuredReference=秦晗，段锦涛，郝棚娜，等. GNRI、PNI、PAB与老年髋部骨折营养风险和营养不良预后的关系研究［J］. 临床误诊误治，2024，37（6）：30-35., articleTitle=GNRI、PNI、PAB与老年髋部骨折营养风险和营养不良预后的关系研究, refAbstract=null), Reference(id=1322218701194117828, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, doi=10.3969/j.issn.1002-3429.2024.06.007, pmid=null, pmcid=null, year=2024, volume=37, issue=6, pageStart=30, pageEnd=35, url=null, language=null, rfNumber=25, rfOrder=35, authorNames=QIN H, DUAN J T, HAO P N, journalName=Clin Misdiagnosis Mistherapy, refType=null, unstructuredReference=QIN H，DUAN J T，HAO P N，et al. Study on the relationship between GNRI，PNI，PAB and nutritional risk and prognosis of malnutrition in elderly hip fracture patients［J］. Clin Misdiagnosis Mistherapy，2024，37（6）：30-35., articleTitle=Study on the relationship between GNRI，PNI，PAB and nutritional risk and prognosis of malnutrition in elderly hip fracture patients, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322218687734596184, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, xref=1, ext=[AuthorCompanyExt(id=1322218687742984793, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, companyId=1322218687734596184, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Department of Dermatology the First Medical Center，Chinese PLA General Hospital，), AuthorCompanyExt(id=1322218687751373402, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, companyId=1322218687734596184, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, 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生理因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
年龄/岁74.89±6.3269.38±7.4615.6780.000
性别16.8800.000
男性158（40.62）109（58.02）
女性231（59.38）76（41.08）
身高/cm165.71±10.32166.24±10.83-0.0250.980
体质量/kg65.99±16.2166.74±14.96-0.1800.857
BMI指数/
（kg/m2）		20.31±3.1422.43±3.87-11.3600.000
饮酒史159（40.87）72（38.92）0.1990.655
吸烟史143（36.76）61（32.97）0.7850.376
高血压史71（18.25）26（14.05）1.5730.210
高血脂史63（16.20）32（17.30）0.1100.740
糖尿病史55（14.14）8（4.32）12.360.000
), ArticleFig(id=1322218694856524438, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表1, caption=

营养不良组与营养良好组生理因素比较 ［x¯±s, n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
生理因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
年龄/岁74.89±6.3269.38±7.4615.6780.000
性别16.8800.000
男性158（40.62）109（58.02）
女性231（59.38）76（41.08）
身高/cm165.71±10.32166.24±10.83-0.0250.980
体质量/kg65.99±16.2166.74±14.96-0.1800.857
BMI指数/
（kg/m2）		20.31±3.1422.43±3.87-11.3600.000
饮酒史159（40.87）72（38.92）0.1990.655
吸烟史143（36.76）61（32.97）0.7850.376
高血压史71（18.25）26（14.05）1.5730.210
高血脂史63（16.20）32（17.30）0.1100.740
糖尿病史55（14.14）8（4.32）12.360.000
), ArticleFig(id=1322218694969770647, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
社会因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
婚姻状态2.0970.148
未婚/离异/丧偶69（17.74）24（12.97）
在婚320（82.26）161（87.03）
学历水平1.3500.245
高中及以下224（57.58）97（52.43）
高中以上165（42.42）88（47.57）
骨折前锻炼评分/分2.58±1.423.34±1.58-6.2420.000
), ArticleFig(id=1322218695070433944, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表2, caption=

营养不良组与营养良好组社会因素比较 ［x¯±s, n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
社会因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
婚姻状态2.0970.148
未婚/离异/丧偶69（17.74）24（12.97）
在婚320（82.26）161（87.03）
学历水平1.3500.245
高中及以下224（57.58）97（52.43）
高中以上165（42.42）88（47.57）
骨折前锻炼评分/分2.58±1.423.34±1.58-6.2420.000
), ArticleFig(id=1322218695192068761, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
经济因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
职业状态28.3980.000
农民105（26.99）19（10.27）
普通工人22（5.66）5（2.70）
专业技术人员18（4.63）14（7.57）
公务员24（6.17）21（11.35）
个体经商62（15.94）30（16.22）
离退休158（40.62）96（51.89）
经济压力评分/分3.32±1.282.88±1.333.8180.000
医疗支付方式30.8970.000
农村医保102（26.22）19（10.27）
城镇医保258（66.32）163（88.11）
无医保29（7.46）3（1.62）
), ArticleFig(id=1322218695292732058, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表3, caption=

营养不良组与营养良好组经济因素比较 ［x¯±s, n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
经济因素营养不良组
（n=389）		营养良好组
（n=185）		t/χ2P
职业状态28.3980.000
农民105（26.99）19（10.27）
普通工人22（5.66）5（2.70）
专业技术人员18（4.63）14（7.57）
公务员24（6.17）21（11.35）
个体经商62（15.94）30（16.22）
离退休158（40.62）96（51.89）
经济压力评分/分3.32±1.282.88±1.333.8180.000
医疗支付方式30.8970.000
农村医保102（26.22）19（10.27）
城镇医保258（66.32）163（88.11）
无医保29（7.46）3（1.62）
), ArticleFig(id=1322218695401783963, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
环境因素营养不良组（n=389）营养良好组（n=185）χ2P
居住地25.0340.000
农村127（32.65）24（12.97）
城镇262（67.35）161（87.03）
居住方式7.4910.024
独居48（12.34）11（5.95）
与配偶/子女居住322（82.78）169（91.35）
与亲戚朋友居住19（4.86）5（2.70）
), ArticleFig(id=1322218695510835868, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表4, caption=

营养不良组与营养良好组环境因素比较 ［n（%）］

, figureFileSmall=null, figureFileBig=null, tableContent=
环境因素营养不良组（n=389）营养良好组（n=185）χ2P
居住地25.0340.000
农村127（32.65）24（12.97）
城镇262（67.35）161（87.03）
居住方式7.4910.024
独居48（12.34）11（5.95）
与配偶/子女居住322（82.78）169（91.35）
与亲戚朋友居住19（4.86）5（2.70）
), ArticleFig(id=1322218695598916253, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
医学因素营养不良组（n=389）营养良好组（n=185）t/χ2P
入院心率/（次/min）73.39±8.8173.51±8.32-0.2020.840
入院平均动脉压/（mmHg）84.10±9.0884.58±9.46-0.3190.750
术前总蛋白/（g/L）61.47±6.2265.94±7.31-13.8800.000
术前白蛋白/（g/L）30.51±2.2635.08±2.71-26.5960.000
术前前白蛋白/（g/L）124.30±57.22173.85±42.36-20.3470.000
术前血红蛋白/（g/L）96.76±17.84115.17±19.38-15.5330.000
术前总胆固醇/（mmol/L）3.92±1.044.01±1.08-0.9500.343
术前血小板计数/（×109L-1）172.85±67.09175.62±68.35-0.9950.320
术前淋巴细胞计数/（×109L-1）0.85±0.330.81±0.381.0140.311
骨折前Barthel指数/分54.40±9.0673.75±11.59-21.7840.000
骨折致伤机制0.8280.363
高能量损伤152（39.07）65（35.14）
低能量损伤237（60.93）120（64.86）
骨折Evans-Jensen分型3.8860.422
Ⅰ型68（17.48）36（19.46）
Ⅱ型72（18.51）43（23.24）
Ⅲ型101（25.96）48（25.95）
Ⅳ型85（21.85）37（20.00）
Ⅴ型63（16.20）21（11.35）
骨折侧0.0660.798
左侧189（48.59）92（49.73）
右侧200（51.41）93（50.27）
手术类型1.0400.308
闭合复位211（51.67）104（56.22）
小切口辅助复位188（48.33）81（43.78）
麻醉方式0.5890.745
腰硬联合麻醉261（67.10）123（66.49）
连续硬膜外麻醉97（24.94）50（27.03）
全身麻醉31（7.96）12（6.48）
手术时长/min59.64±9.8160.38±9.45-0.2380.812
术中出血量/mL105.80±18.6793.14±15.7216.3190.000
围术期并发症2.1600.144
有32（8.23）9（4.86）
无357（91.77）176（95.14）
住院时长/d20.36±3.4017.41±5.5310.3200.000
出院前Harris评分/d56.90±14.2157.16±13.96-0.4590.646
), ArticleFig(id=1322218695686996638, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表5, caption=

营养不良组与营养良好组医学因素比较 ［x¯±s, n（%）］

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医学因素营养不良组（n=389）营养良好组（n=185）t/χ2P
入院心率/（次/min）73.39±8.8173.51±8.32-0.2020.840
入院平均动脉压/（mmHg）84.10±9.0884.58±9.46-0.3190.750
术前总蛋白/（g/L）61.47±6.2265.94±7.31-13.8800.000
术前白蛋白/（g/L）30.51±2.2635.08±2.71-26.5960.000
术前前白蛋白/（g/L）124.30±57.22173.85±42.36-20.3470.000
术前血红蛋白/（g/L）96.76±17.84115.17±19.38-15.5330.000
术前总胆固醇/（mmol/L）3.92±1.044.01±1.08-0.9500.343
术前血小板计数/（×109L-1）172.85±67.09175.62±68.35-0.9950.320
术前淋巴细胞计数/（×109L-1）0.85±0.330.81±0.381.0140.311
骨折前Barthel指数/分54.40±9.0673.75±11.59-21.7840.000
骨折致伤机制0.8280.363
高能量损伤152（39.07）65（35.14）
低能量损伤237（60.93）120（64.86）
骨折Evans-Jensen分型3.8860.422
Ⅰ型68（17.48）36（19.46）
Ⅱ型72（18.51）43（23.24）
Ⅲ型101（25.96）48（25.95）
Ⅳ型85（21.85）37（20.00）
Ⅴ型63（16.20）21（11.35）
骨折侧0.0660.798
左侧189（48.59）92（49.73）
右侧200（51.41）93（50.27）
手术类型1.0400.308
闭合复位211（51.67）104（56.22）
小切口辅助复位188（48.33）81（43.78）
麻醉方式0.5890.745
腰硬联合麻醉261（67.10）123（66.49）
连续硬膜外麻醉97（24.94）50（27.03）
全身麻醉31（7.96）12（6.48）
手术时长/min59.64±9.8160.38±9.45-0.2380.812
术中出血量/mL105.80±18.6793.14±15.7216.3190.000
围术期并发症2.1600.144
有32（8.23）9（4.86）
无357（91.77）176（95.14）
住院时长/d20.36±3.4017.41±5.5310.3200.000
出院前Harris评分/d56.90±14.2157.16±13.96-0.4590.646
), ArticleFig(id=1322218695787659935, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
风险因素BS.EWald χ2POR（95%CI）
年龄0.3580.09613.950.0001.430（1.185~1.726）
女性2.5541.5832.6580.1012.853（1.264~4.661）
BMI指数-0.9240.3138.7090.0030.397（0.215~0.733）
糖尿病2.0301.9021.1380.2867.611（0.183~16.602）
术后SAS评分0.1180.0544.8280.0281.125（1.013~1.249）
骨折前锻炼评分-1.2410.4089.2690.0020.289（0.130~0.643）
农民2.7461.0806.4640.0115.575（1.876~9.329）
经济压力评分0.9080.4264.5440.0332.480（1.076~5.718）
独居2.6711.9471.8830.1704.460（0.318~6.618）
术前总蛋白-0.0210.0920.0510.8220.980（0.818~1.173）
术前白蛋白-0.5240.1877.880.0050.592（0.411~0.854）
术前前白蛋白-0.0200.0144.370.0370.941（0.875~1.007）
术前血红蛋白-0.0430.0244.9830.0150.928（0.814~1.004）
骨折前Barthel指数-0.3280.08310.4910.0000.721（0.612~0.848）
术中出血量0.3270.0851.9620.1641.387（0.975~1.636）
住院时长0.2140.1472.1190.1451.239（0.928~1.654）
), ArticleFig(id=1322218695879934624, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322218686103011917, language=CN, label=表6, caption=

PFNA内固定术后患者营养风险的多因素Logistic回归分析

, figureFileSmall=null, figureFileBig=null, tableContent=
风险因素BS.EWald χ2POR（95%CI）
年龄0.3580.09613.950.0001.430（1.185~1.726）
女性2.5541.5832.6580.1012.853（1.264~4.661）
BMI指数-0.9240.3138.7090.0030.397（0.215~0.733）
糖尿病2.0301.9021.1380.2867.611（0.183~16.602）
术后SAS评分0.1180.0544.8280.0281.125（1.013~1.249）
骨折前锻炼评分-1.2410.4089.2690.0020.289（0.130~0.643）
农民2.7461.0806.4640.0115.575（1.876~9.329）
经济压力评分0.9080.4264.5440.0332.480（1.076~5.718）
独居2.6711.9471.8830.1704.460（0.318~6.618）
术前总蛋白-0.0210.0920.0510.8220.980（0.818~1.173）
术前白蛋白-0.5240.1877.880.0050.592（0.411~0.854）
术前前白蛋白-0.0200.0144.370.0370.941（0.875~1.007）
术前血红蛋白-0.0430.0244.9830.0150.928（0.814~1.004）
骨折前Barthel指数-0.3280.08310.4910.0000.721（0.612~0.848）
术中出血量0.3270.0851.9620.1641.387（0.975~1.636）
住院时长0.2140.1472.1190.1451.239（0.928~1.654）
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PFNA内固定术后患者营养不良预测模型构建及其准确性分析
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申琳 1 , 白小嘉 2 , 王刚 3 , 薛丽娟 4 , 张春华 5 , 李霞 3
陆军军医大学学报 | 临床医学 2025,47(10): 1092-1101
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陆军军医大学学报 |临床医学 2025 , 47 (10) : 1092 -1101
PFNA内固定术后患者营养不良预测模型构建及其准确性分析
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申琳1, 白小嘉2, 王刚3, 薛丽娟4, 张春华5, 李霞3
作者信息
  • 1解放军总医院第一医学中心：皮肤科，北京
  • 2解放军总医院第一医学中心：康复科，北京
  • 3解放军总医院第一医学中心：血管外科，北京
  • 4陆军军医大学（第三军医大学）士官学校基础部，石家庄
  • 5南方医科大学南方医院整形美容外科，广州
通讯作者:
李 霞，E-mail：
LI Xia，E-mail：.
作者简介:

同等贡献者

SHEN Lin and BAI Xiaojia contributed equally to the article.

Construction and accuracy analysis of a malnutrition prediction model for patients after proximal femoral nail anti rotation internal fixation
Lin SHEN1, Xiaojia BAI2, Gang WANG3, Lijuan XUE4, Chunhua ZHANG5, Xia LI3
Affiliations
  • 1Department of Dermatology the First Medical Center，Chinese PLA General Hospital，
  • 2Department of Rehabilitation the First Medical Center，Chinese PLA General Hospital，
  • 3Department of Vascular Surgery，the First Medical Center，Chinese PLA General Hospital，
  • 4Department of Basic Courses，Noncommissioned Officer School，Army Medical University （Third Military Medical University），Shijiazhuang，Hebei
  • 5Department of Plastic and Cosmetic Surgery，Southern Hospital，Southern Medical University，Guangzhou，Guangdong，China
出版时间: 2025-05-30 doi: 10.16016/j.2097-0927.202411118
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摘要
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‍

目的

探索股骨近端防旋髓内钉（proximal femoral nail anti-rotatio，PFNA）内固定术老年患者术后营养风险相关因素并建立营养不良预测模型。

方法

纳入2021年1月至2024年6月于我院接受PFNA内固定术老年患者574例，分为营养不良组（389例）和营养良好组（185例），比较2组患者生理、心理、社会、经济、环境、医学等因素共39个指标的差异，采用Logistic分析筛选营养风险危险因素并构建列线图模型。

结果

年龄偏高、BMI指数偏低、术后SAS评分偏高、骨折前较少锻炼、农民、经济压力较高，及术前白蛋白、前蛋白、血红蛋白偏低，骨折前Barthel指数偏低是PFNA内固定术患者营养风险的独立危险因素（P<0.05）。纳入上述因素构建列线图预测模型，预测该类患者发生营养不良风险的AUC（95%CI）=0.995（0.987~1.000），在阈概率>0.02时采用本模型预测PFNA内固定术患者术后营养不良风险均可临床获益。

结论

基于年龄、BMI指数、经济压力、骨折前锻炼情况及术前白蛋白等指标构建老年患者PFNA内固定术术后营养风险预测模型，有较高的准确性和临床应用价值。

股骨近端防旋髓内钉  /  内固定术式  /  营养风险  /  预测模型
Objective

To explore the related factors of postoperative nutritional risk in elderly patients with proximal femoral nail anti rotation (PFNA) internal fixation and establish a prediction model of malnutrition.

Methods‍

A total of 574 elderly patients who underwent PFNA internal fixation in the First Medical Center of Chinese PLA General Hospital from January 2021 to June 2024 were included and divided into malnutrition group (n=389) and good nutrition group (n=185). The differences in 39 indicators in aspects of physiological, psychological, social, economic, environmental and medical fields were compared between the 2 groups. Logistic analysis was used to screen the nutritional risk factors, and then a nomogram model was constructed based on these factors.

Results‍

Advanced age, lower BMI, higher postoperative Self-Rating Anxiety Scale (SAS) score, less exercise before fracture, being farmers, higher economic pressure, lower preoperative albumin, preprotein and hemoglobin, and lower Barthel index before fracture were independent risk factors for nutritional risk in patients undergoing PFNA internal fixation (P<0.05). The nomogram prediction model based on the above factors had an AUC value of 0.995 (95%CI: 0.987~1.000) in predicting the risk of malnutrition in these patients. When the threshold probability >0.02, this model could be clinically beneficial in predicting the risk of postoperative malnutrition in patients after PFNA internal fixation.

Conclusion‍

Our nutritional risk prediction model based on age, BMI, economic pressure, pre-fracture exercise and preoperative albumin and other indicators is constructed for the elderly patients after PFNA internal fixation, and the model has high accuracy and clinical application value.

proximal femoral nail antirotation  /  internal fixation  /  nutritional risk  /  prediction model
申琳, 白小嘉, 王刚, 薛丽娟, 张春华, 李霞. PFNA内固定术后患者营养不良预测模型构建及其准确性分析. 陆军军医大学学报, 2025 , 47 (10) : 1092 -1101 . DOI: 10.16016/j.2097-0927.202411118
Lin SHEN, Xiaojia BAI, Gang WANG, Lijuan XUE, Chunhua ZHANG, Xia LI. Construction and accuracy analysis of a malnutrition prediction model for patients after proximal femoral nail anti rotation internal fixation[J]. Journal of Army Medical University, 2025 , 47 (10) : 1092 -1101 . DOI: 10.16016/j.2097-0927.202411118
正文
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股骨近端防旋髓内钉（proximal femoral nail antirotation，PFNA）是一种股骨粗隆部骨折常用的髓内钉系统，PFNA内固定术具有手术时间短、出血量低、关节功能恢复快的优点［1］。目前，PFNA内固定术应用于各类型股骨转子间骨折患者中，均表现出良好的适用性，是一种理想的治疗方案。但相关研究和临床报道显示，有较高比例的患者因术后营养不良导致感染、愈合不良、恢复缓慢等不利结局，影响手术疗效和患者生活质量［2-3］。既往相关研究显示，年龄、性别、重大病史、术前体质量指数是骨折手术患者术后营养风险的相关因素［4-5］。然而目前关于PFNA内固定术后营养风险因素的研究还较少，仅见2024年有1篇针对性研究报道显示高龄、体质指数、吸烟史、血红蛋白等与患者术后营养风险相关［6］。但该研究纳入病例仅76例，其中无营养风险组仅15例，且观测指标集中于血浆蛋白质指标和基础疾病。虽然关于骨折手术患者营养风险相关因素的研究较多，但这些因素是否与PFNA内固定术后营养风险相关尚不明确，此外还缺少高价值的PFNA内固定术后营养风险预测模型。有鉴于此，本研究纳入我院2021年1月至2024年6月收治行PFNA内固定术的股骨转子间骨折老年患者574例为研究对象展开回顾性研究，从生理、心理、社会、经济、环境、医学等维度共39个指标分析营养良好和营养不良组间的差异，探索患者术后营养风险的相关因素，构建患者术后营养不良风险的列线图预测模型，并验证模型预测患者术后营养不良的准确性，以期为临床制定治疗护理方案提供参考。
1　资料与方法
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1.1　研究对象
回顾性纳入2021年1月至2024年6月接受PFNA内固定术治疗的股骨转子间骨折老年患者574例，根据术后3个月内营养风险评估结果分为营养良好组（＜3分）和营养不良组（≥3分），其中营养良好组185例（32.23%），营养不良组389例（67.77%）。营养风险评估方法：采用欧洲肠内外营养学会制定的营养风险筛查量表（nutritional risk screening 2002，NRS 2002）［7］进行营养风险评估，从疾病状态、营养状态、年龄方面评估患者营养风险，总分最高7分，评分≥3分定义为发生营养不良。术前评估1次，术后每周评估1次，直至术后3个月。本研究经解放军总医院伦理委员会审批（S2023-720-02）。
纳入标准：（1）年龄60~85岁；（2）术前体质指数（BMI）>18.5；（3）确诊为股骨转子间骨折，并接受PFNA内固定术治疗；（4）单侧骨折；（5）临床资料完整者。
排除标准：（1）术前NRS 2002评分≥3分者；（2）有精神性疾病或认知功能障碍者，不能正常经口进食者；（3）合并消化道疾病者；（4）有重要脏器如肺、肝、肾、循环系统及呼吸系统疾病史者；（5）有肿瘤及心脑血管疾病史者；（6）合并严重的感染性疾病或传染性疾病者；（7）陈旧性骨折者；（8）骨代谢异常及骨质疏松症患者。
1.2　手术方法
错位较轻可通过手法复位患者，行闭合复位PFNA内固定术：患者取仰卧位，X线透视机调整确认复位，X线透视机确认导针位置，近端开孔沿导针置入PFNA主钉，置入螺旋刀片后探入远端螺钉，X线透视机确认骨折端、内固定位置妥善良好无误后冲洗逐层缝合切口。
错位严重难以通过手法复位患者，行小切口辅助复位PFNA内固定术：患者取仰卧位，X线透视机下定位骨折端行2~3 cm小切口，采用骨膜剥离器撬拨或复位钳复位骨折端，透视机确认位置满意后，克氏针临床固定。其余操作与闭合复位PFNA内固定术相同。
1.3　术后处理
患者术后均给予常规抗生素抗感染治疗，低分子肝素钙7~10 d预防深静脉血栓，骨质疏松给予钙剂及维生素D或经临床药师评估后给予地舒单抗治疗，肠内营养支持，指导患者进行股四头肌、关节主被动锻炼，术后4周扶双拐不负重活动，8周左右患者X线显示骨痂生长较好开始部分负重锻炼。
1.4　主要观察指标
1.4.1　生理因素指标
收集患者年龄、性别、身高、体质量、体质指数、饮酒史（近3年周均饮酒1次以上，或年均醉酒3次以上）、吸烟史（近3年日均吸烟3支以上）及合并高血压、高血脂、糖尿病等生理因素指标。
1.4.2　心理因素指标
收集患者术后焦虑自评量表评分：术后24 h内，采用焦虑自评量表（self-rating anxiety scale，SAS）［8］评估患者术后焦虑情况。量表共20个项目，总分80分，分值越高焦虑程度越强。
1.4.3　社会因素指标
收集患者婚姻状态（未婚/离异/丧偶、在婚）、学历水平（高中及以下、高中以上）、身体锻炼评分等社会因素指标。
身体锻炼评分方法：评估骨折前身体锻炼情况，周均锻炼次数≤1次或总锻炼时长≤1 h记1分；周均锻炼次数2~3次或总锻炼时长2~3 h记2分，周均锻炼次数4~5次或总锻炼时长4~5 h记3分，周均锻炼次数6~7次或总锻炼时长6~7 h记4分，周均锻炼次数>7次或总锻炼时长>7 h记5分。得分越低表明患者骨折前身体锻炼越少。
1.4.4　经济因素指标
收集患者工作状态（农民、普通工人、专业技术人员、公务员、个体经商、离退休）、经济压力评分、医疗支付方式（农村医保、城镇医保、无医保）等经济因素指标。
经济压力评分方法：（1）无退休金或稳定的工作；（2）无医疗保险；（3）有借贷或欠款；（4）日常开支需要节约；（5）无子女。以上5项每项符合计1分，不符合计0分。得分越高表明患者经济压力越大。
1.4.5　环境因素指标
收集患者居住地（农村、城镇）、居住方式（独居、与配偶/子女居住、与亲戚朋友居住）等环境因素指标。
1.4.6　医学因素指标
收集患者入院心率、平均动脉压、骨折致伤机制（高能量损伤、低能量损伤）、住院时长、骨折Evans-Jensen分型、骨折侧（左侧、右侧）、手术类型（闭合复位、小切口辅助复位）、麻醉方式（腰硬联合麻醉、连续硬膜外麻醉、全身麻醉）、手术时长、术中出血量、住院时长、围术期并发症、骨折前日常活动能力评分、出院Harris髋关节功能量表评分及实验室检查指标。
骨折前日常活动能力评分方法：采用改良的日常生活活动能力（the barthel index of ADL，Barthel）［9］指数评分标准，患者入院后根据回忆填写骨折前情况，共10个项目，总分100分，分值越高独立日常生活活动能力越强。
出院Harris髋关节功能量表评分方法：出院前采用Harris提出的髋关节功能量表［10］，评估患者出院时的髋关节功能状态及恢复情况，量表包括疼痛、功能、畸形、关节活动度4个方面，满分100分，分值越高髋关节功能状态越好。
实验室检查指标：术前总蛋白、白蛋白、前白蛋白、血红蛋白、总胆固醇、血小板、淋巴细胞计数。前总蛋白、白蛋白、前蛋白、血红蛋白、总胆固醇采用全自动生化分析仪（迈瑞BS-600M/BS-800M/BS-1000M）完成检测，血小板、淋巴细胞计数采用全自动血细胞分析仪（迈瑞BC-5390CRP/BC-5310CRP/BC-5100CRP/BC-5180CRP）完成检测。
1.5　统计学分析
所有资料采用SPSS26.0及Python软件进行统计学分析。计量资料经Kolmogorov-Smirnov检验均符合正态分布，采用x¯±s表示，组间差异采用独立样本t检验；计数资料采用例（%）表示，组间差异采用χ2检验。P<0.05为差异有统计学意义。
1.6　预测模型构建及验证
纳入组间差异有统计学意义的指标，采用Pearson相关性检验和VIF检验排除多重共线性后，采用多因素Logistic回归分析探索患者术后3个月内发生营养风险的相关因素并构建列线图模型，采用ROC曲线分析检验模型预测性能，采用Bootstrap法重复抽样进行中介效应检验，采用DCA决策曲线检验分析列线图模型临床价值。
2　结果
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2.1　营养不良组与营养良好组生理因素比较
与营养良好组相比，营养不良组平均年龄更高、女性占比更大、BMI指数更低、糖尿病史占比更高（P<0.05），其余指标未见统计学差异。见表1。
2.2　营养不良组与营养良好组心理因素比较
术后24 h，营养不良组SAS评分为（53.61±12.81）分，营养良好组为（46.99±13.13）分，表明营养不良组焦虑程度更高（P<0.05）。
2.3　营养不良组与营养良好组社会因素比较
两组间婚姻状态、学历水平差异无统计学意义，营养不良组骨折前锻炼评分明显低于营养良好组（P<0.05）。见表2。
2.4　营养不良组与营养良好组经济因素比较
营养不良组农民占比、经济压力评分、农村医保占比明显高于营养良好组（P<0.05）。见表3。
2.5　营养不良组与营养良好组环境因素比较
营养不良组农村居住、独居占比明显高于营养良好组（P<0.05）。见表4。
2.6　营养不良组与营养良好组医学因素比较
营养不良组术前总蛋白、白蛋白、前白蛋白、血红蛋白、骨折前Barthel指数明显低于营养良好组，术中出血量、住院时长明显高于营养良好组（P<0.05）。骨折Evans-Jensen分型、骨折侧、手术类型等其余指标2组比较无统计学差异。见表5。
2.7　PFNA内固定术后患者营养风险的多因素分析
共线性检验发现“农民-农村居住-农村医保”“未婚/丧偶/离异-独居”“无医保-经济压力”3组指标内部存在严重的共线性问题（VIF>10），3组指标分别保留农民、独居、经济压力后消除多重共线性影响。Logistic回归分析显示，PFNA内固定术后患者营养风险与年龄、BMI指数、术后SAS评分、骨折前锻炼评分、农民、经济压力评分、术前白蛋白、术前前白蛋白、术前血红蛋白、骨折前Barthel指数共10个因素相关（P<0.05）。未见性别、糖尿病史、独居、术前总蛋白、术中出血量、住院时长与患者FPNA内固定术后营养风险相关。见表6。
2.8　PFNA内固定术后营养风险的列线图预测模型构建
基于多因素Logistic回归分析构建PFNA内固定术后营养风险的列线图预测模型，可见年龄、BMI指数、骨折前Barthel指数、术前白蛋白、术前前白蛋白在模型中的贡献较大。见图1。
2.9　PFNA内固定术后营养风险列线图预测模型准确性分析
以建立的列线图预测模型进行预测，并绘制ROC曲线，模型预测患者发生营养不良风险的曲线下面积为0.995（95%CI：0.987~1.000），预测准确性较高。见图2。
采用Bootstrap法对数据进行5 000次的重复抽样验证，校准曲线结果显示模型预测值与重复抽样拟合分布曲线贴合良好，Hosmer-Lemeshow检验χ2=5.887，P=0.660，模型拟合优度良好，模型校准具有良好的预测能力。见图3。
采用DCA决策曲线检测列线图模型的临床适用度，DCA曲线在阈值范围>0.02时位于None、All 2条无效线上方，在此范围内模型预测有效性较好，在阈概率>0.02时选择模型进行PFNA内固定术后营养风险的预测可临床获益。见图4。
3　讨论
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股骨转子间骨折是一类非常严重的损伤，PFNA内固定术治疗虽效果显著，但术后需要丰富的蛋白质、钙质、维生素等营养的支持，以促进骨折愈合和身体机能的恢复［11］。由于患者术后活动量减少、焦虑抑郁、睡眠障碍等多种因素的影响，患者术后自主摄食能力下降，极易发生营养不足造成不良结局［12］。既往相关研究显示，PFNA内固定术老年患者术后营养风险发生率在70%~80%［13-14］。本研究纳入的574例患者中，389例于术后3个月内发生营养风险，发生率为67.77%，略低于上述研究。其原因可能是本研究排除了合并消化道疾病及术前NRS2002评分≥3分的患者。但这一结果依然提示PFNA内固定术老年患者有极高的营养风险发生率，并可能因此而促进不良结局的发生。
患者营养不良的风险因素一直是临床研究的重点，但目前相关研究多集中于肿瘤、血液疾病等领域，骨折领域的相关研究较少。何志强等［15］纳入14篇文献展开了Meta分析，发现女性、自理能力低、身体活动少、合并慢性病、居住地不在家、住院时间长、抑郁是老年骨折患者围术期营养不良的危险因素。本研究结果显示，PFNA内固定术患者术后营养风险的相关因素与上述研究并不完全一致。发生营养风险的患者在女性占比、居住方式、住院时长上与未发生营养风险的患者群体间虽然存在差异，但多因素分析结果未见相关性。分析其原因，可能与上述研究是Meta分析，未排除各因素的交互作用有关。但在2组的体育锻炼情况、抑郁水平方面，本研究得出与上述研究一致的结果，提示骨折前经常进行身体锻炼、Barthel指数越高、术后SAS评分越低的患者，术后的营养风险更低。分析其原因，骨折前经常进行锻炼、Barthel指数高的患者通常有更强的身体机能储备，更能抵抗骨折后食欲减退、睡眠不足、情绪低落等方面的负性影响［16］。而抑郁焦虑等情绪，会增加患者睡眠障碍、食欲降低的风险［17］。
SOLOU等［18］以创伤骨折手术患者为研究对象，发现年龄、BMI指数、合并糖尿病是创伤骨折术后患者营养不良的独立影响因素。LAN等［19］研究同样发现，年龄、BMI指数、糖尿病是老年骨质疏松椎体压缩性骨折患者的营养风险因素。本研究结果同样提示，年龄越大的患者PFNA内固定术后的营养风险越高，但糖尿病仅在单因素分析中表现出组间差异，而多因素分析未见相关性，提示糖尿病可能并非PFNA内固定术后营养风险的独立影响因素。其原因可能与本研究排除了术前NRS2002评分≥3分的患者有关，糖尿病患者有较高的营养风险发生率，但在排除了术前NRS2002评分≥3分的患者后，纳入研究的糖尿病患者营养风险较低，表明其在糖尿病发生以来有较强的饮食控制能力，胃肠道功能维护较好。相关研究显示，血红蛋白、白蛋白、前白蛋白水平是骨折患者营养风险的相关因素［20-21］。本研究得出与上述研究一致的结论，术前血红蛋白、白蛋白、前蛋白水平越低，术后中短期营养越高。分析其原因，血红蛋白是营养成分及氧气的主要运送载体，白蛋白维持人体渗透压并作为多种离子及有毒物质的载体，术前血红蛋白及白蛋白水平可以反映患者的机体营养运载能力、排毒能力及氨基酸储备水平［22］。前白蛋白则可直接反映患者的营养状态，既是甲状腺素和维生素A的转运蛋白，又在机体应激反应、坏死物质清除、组织修补中扮演着重要角色［23］。
此外，本研究按照生理-心理-社会-经济-环境现代医学模式要求，还纳入了职业特征、居住地、经济压力、婚姻状态、医疗费用支付方式等指标进行观察。研究结果显示，术后3个月发生营养风险的患者中，农民、居住地在农村、独居、农村医保、无医保患者占比高于未发生营养风险的患者，排除共线性影响后发现，农民及经济压力越大的患者营养风险越高。分析其原因，农民多居住于农村，可能在高蛋白、钙质、新鲜蔬果的获取上有所不便。同时，农民的经济压力整体上可能高于专业技术人员、公务员及离退休人员等。而经济压力越高，除了在营养获取的支出上有所受限外，还可能存在更高的抑郁、焦虑等情绪影响，导致肠胃功能下降、睡眠障碍等问题，进一步诱发营养风险。
目前，已有部分研究对骨折手术患者的营养风险预测模型展开研究。如李蕾等［24］研究中纳入了年龄、糖尿病、血红蛋白等指标建立列线图模型，预测准确率达到0.865。秦晗等［25］研究中，采用术前术后前蛋白水平预测老年髋部骨折患者营养风险，预测准确率达到0.835。在张强等［6］研究中，针对PFNA内固定术患者，纳入年龄、体质量、血红蛋白等指标建立术后营养风险预测模型，预测准确率为0.919，模型在阈概率0.02~0.80范围进行预测可临床获益，但该研究中纳入病例较少仅76例。本研究中，基于多因素Logistic回归分析排除各因素交互影响，共纳入了年龄、BMI指数、职业、骨折前Barthel指数、术前白蛋白等10个营养风险相关因子建立列线图预测模型，ROC曲线下面积为0.995，Hosmer-Lemeshow检验模型拟合优度良好，DCA决策曲线分析显示，阈值范围0.02~1.00采用本模型预测PFNA内固定术后营养风险可临床获益，表现出较高的预测能力。分析其原因，本研究中检测样本量达到574例，大样本量降低了样本偏倚风险的干扰，同时共收集检测了39个因子与PFNA内固定术后营养风险的相关性，并排除了各因子间的交互作用，从而提高了模型的预测性能。本研究的局限性在于所有样本均来自本院，缺乏多中心的对照，未来还需扩大样本量以进一步验证。
综上，本研究显示，年龄越高、BMI指数越低、农民、经济压力越大、骨折前锻炼越少、骨折前Barthel指数越低、术后SAS评分越高及术前白蛋白、前蛋白、血红蛋白水平越低的患者，PFNA内固定术后有更高的营养风险。基于上述指标构建列线图预测模型，对预测PFNA内固定术老年患者术后营养风险有较高价值。

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2025年第47卷第10期
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doi: 10.16016/j.2097-0927.202411118
  • 接收时间：2024-11-26
  • 首发时间：2026-10-28
  • 出版时间：2025-05-30
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  • 收稿日期：2024-11-26
  • 修回日期：2025-03-05
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    1解放军总医院第一医学中心：皮肤科，北京
    2解放军总医院第一医学中心：康复科，北京
    3解放军总医院第一医学中心：血管外科，北京
    4陆军军医大学（第三军医大学）士官学校基础部，石家庄
    5南方医科大学南方医院整形美容外科，广州

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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