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<article article-type="research-article" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xml:lang="EN">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Surg.</journal-id>
<journal-title>Frontiers in Surgery</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Surg.</abbrev-journal-title>
<issn pub-type="epub">2296-875X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fsurg.2025.1507434</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Surgery</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Development and validation of a nomogram for predicting postoperative intraluminal hemorrhage in patients undergoing laparoscopic pancreaticoduodenectomy</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Wang</surname><given-names>Shuai</given-names></name><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author"><name><surname>Li</surname><given-names>Dongrui</given-names></name><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/></contrib>
<contrib contrib-type="author"><name><surname>Du</surname><given-names>Chengxu</given-names></name><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author"><name><surname>Yang</surname><given-names>Xinda</given-names></name><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Haitao</surname><given-names>Lv</given-names></name>
<xref ref-type="corresp" rid="cor1">&#x002A;</xref><uri xlink:href="https://loop.frontiersin.org/people/2841694/overview"/><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/></contrib>
</contrib-group>
<aff><institution>Department of Hepatobiliary Surgery, Second Hospital of Hebei Medical University</institution>, <addr-line>Shijiazhuang</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p><bold>Edited by:</bold> Gabriel Sandblom, Karolinska Institutet (KI), Sweden</p></fn>
<fn fn-type="edited-by"><p><bold>Reviewed by:</bold> Heba Taher, Cairo University, Egypt</p>
<p>Alessandro Esposito, Verona Integrated University Hospital, Italy</p></fn>
<corresp id="cor1"><label>&#x002A;</label><bold>Correspondence:</bold> Lv Haitao <email>gandanlvhaitao@163.com</email></corresp>
</author-notes>
<pub-date pub-type="epub"><day>05</day><month>08</month><year>2025</year></pub-date>
<pub-date pub-type="collection"><year>2025</year></pub-date>
<volume>12</volume><elocation-id>1507434</elocation-id>
<history>
<date date-type="received"><day>07</day><month>10</month><year>2024</year></date>
<date date-type="accepted"><day>18</day><month>07</month><year>2025</year></date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2025 Wang, Li, Du, Yang and Haitao.</copyright-statement>
<copyright-year>2025</copyright-year><copyright-holder>Wang, Li, Du, Yang and Haitao</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract><sec><title>Purpose</title>
<p>This study aims to investigate the risk factors for postoperative intraluminal hemorrhage (IPPH) after laparoscopic pancreaticoduodenectomy (LPD), with the aim of enhancing clinical management through the exploration and development of a risk prediction model with those factors.</p>
</sec><sec><title>Method</title>
<p>The clinical data of 326 hospitalized patients between January 2020 and August 2023 who underwent LPD for malignancies were retrospectively selected. The data consisted of general conditions, comorbidities, preoperative treatments, laboratory tests, and postoperative complications. We explored the risk factors associated with postoperative intraluminal hemorrhage using univariate and multivariate logistic regression analyses and developed a predictive model of IPPH after LPD.</p>
</sec><sec><title>Results</title>
<p>The incidence of IPPH in LPD patients was 7.06&#x0025;. Advanced age (OR&#x2009;&#x003D;&#x2009;1.065, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.001&#x2013;1.133, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.045), low fibrinogen level (OR&#x2009;&#x003D;&#x2009;0.485, 95&#x0025; CI&#x2009;&#x003D;&#x2009;0.242&#x2013;0.972, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.041), low albumin level (OR&#x2009;&#x003D;&#x2009;0.840, 95&#x0025; CI&#x2009;&#x003D;&#x2009;0.739&#x2013;0.956, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.008), clinically relevant postoperative pancreatic fistula (CR POPF, OR&#x2009;&#x003D;&#x2009;4.300, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.347&#x2013;13.722, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.014), and intra-abdominal infection (IAI, OR&#x2009;&#x003D;&#x2009;6.347, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.454&#x2013;27.716, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.014) were associated with an increased incidence of IPPH. A nomogram was developed and validated with a specificity of 82.2&#x0025;, a sensitivity of 82.6&#x0025;, and an AUC value of 0.861 (95&#x0025; CI 0.783&#x2013;0.939).</p>
</sec><sec><title>Conclusion</title>
<p>Risk factors for IPPH include advanced age, low fibrinogen levels, low albumin levels, CR POPF, and IAI. These risk factors were used to develop a nomogram for identifying patients at high risk of IPPH, allowing for targeted interventions to address modifiable risk factors promptly and improve patient outcomes.</p>
</sec>
</abstract>
<kwd-group>
<kwd>laparoscopic pancreaticoduodenectomy</kwd>
<kwd>periampullary carcinoma</kwd>
<kwd>postoperative intraluminal hemorrhage</kwd>
<kwd>risk factors</kwd>
<kwd>nomogram</kwd>
</kwd-group><counts>
<fig-count count="5"/>
<table-count count="2"/><equation-count count="0"/><ref-count count="56"/><page-count count="10"/><word-count count="0"/></counts><custom-meta-wrap><custom-meta><meta-name>section-at-acceptance</meta-name><meta-value>Visceral Surgery</meta-value></custom-meta></custom-meta-wrap>
</article-meta>
</front>
<body><sec id="s1" sec-type="intro"><label>1</label><title>Introduction</title>
<p>Periampullary carcinoma is the most aggressive malignancy, including carcinomas located in pancreatic head, distal bile duct, and periampullary duodenal (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). According to reliable statistics, untreated populations have short survival times, averaging less than 18 months (<xref ref-type="bibr" rid="B3">3</xref>). Several high-level evidences have indicated that pancreaticoduodenectomy (PD) is currently recommended as the optimal treatment method for periampullary carcinoma, as it provides a complete resection of the tumor margins, thus increasing the possibility of recurrence-free survival for an extended period (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). In recent years, the intensification of the concept of minimally invasive laparoscopic pancreaticoduodenectomy (LPD) has become increasingly popular due to its disadvantages of reduced blood loss, shorter hospital stays, and decreased pain (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>). Unfortunately, post-pancreatectomy hemorrhage (PPH) negatively affects the efficacy of laparoscopic pancreaticoduodenectomy and causes secondary injuries. These patients may suffer from secondary surgeries and even die (<xref ref-type="bibr" rid="B9">9</xref>&#x2013;<xref ref-type="bibr" rid="B11">11</xref>), which poses a severe threat to their survival.</p>
<p>The incidence of PPH ranges from 3&#x0025; to 16&#x0025; (<xref ref-type="bibr" rid="B12">12</xref>&#x2013;<xref ref-type="bibr" rid="B14">14</xref>). According to the definition provided by the International Study Group of Pancreatic Surgery (ISGPS), PPH is divided into two categories: intraluminal PPH (IPPH) and extraluminal PPH (EPPH) (<xref ref-type="bibr" rid="B15">15</xref>). Studies conducted at various institutions have shown that the prevalence of IPPH is steadily increasing compared to EPPH due to advances in surgical approaches (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). IPPH poses challenges in its initial stages because of its elusive detection. In the case of progression to grade C PPH, the associated secondary mortality rate could reach an alarming level 60&#x0025; (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B17">17</xref>&#x2013;<xref ref-type="bibr" rid="B19">19</xref>). Numerous factors, including but not limited to age and pancreatic fistula, are related to PPH (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B19">19</xref>). However, results from contemporary studies showed inconsistency, and the prognostic instruments currently employed in clinical settings demonstrate limited efficacy in anticipating the onset of PPH (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B20">20</xref>). Currently, there is a lack of research on IPPH. Several studies have shown that surgical factors (e.g., operation time, vascular clamping, C-reactive protein) were risk factors for EPPH and improved surgical procedures to reduce its occurrence (<xref ref-type="bibr" rid="B19">19</xref>, <xref ref-type="bibr" rid="B21">21</xref>&#x2013;<xref ref-type="bibr" rid="B26">26</xref>). Nevertheless, it is worth noting that few study investigates the risk factors associated with IPPH.</p>
<p>Given the above conditions, this study analyzed the risk factors for IPPH. Subsequently, these identified factors were employed to develop a prognostic model, enabling the identification of patients with an increased susceptibility to IPPH and ultimately improving their prognosis.</p>
</sec>
<sec id="s2" sec-type="methods"><label>2</label><title>Materials and methods</title>
<sec id="s2a"><label>2.1</label><title>Ethical issue</title>
<p>All procedures in the study were performed according to the principles of the Declaration of Helsinki and by the guidelines of Strengthening the Reporting of Surgical Cohort Studies (STROCSS). All patients signed an informed consent form, which was approved by the Ethics Committee of the Second Hospital of Hebei Medical University (2019-R209). To protect the privacy of our patients, all data were anonymized by removing sensitive personal information.</p>
</sec>
<sec id="s2b"><label>2.2</label><title>Participants</title>
<p>A total of 407 hospitalized patients who underwent LPD at the Department of Hepatobiliary Surgery in the Second Hospital of Hebei Medical University between January 2020 and August 2023 for periampullary carcinoma were selected as the objects. The exclusion criteria are: patients with (1) incomplete clinical data; (2) hematological diseases; (3) malignant tumors of other organs; (4) autoimmune disease; (5) long-term use of non-steroidal drugs; (6) non-cooperation with postoperative treatment (<xref ref-type="fig" rid="F1">Figure&#x00A0;1</xref>). This was done to keep the excellent population homogeneous and to allow straightforward interpretation of results.</p>
<fig id="F1" position="float"><label>Figure 1</label>
<caption><p>Patients selection flowchart.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fsurg-12-1507434-g001.tif"><alt-text content-type="machine-generated">Flowchart illustrating patient selection from January 2020 to August 2023. Initially, 326 patients with periampullary conditions were included. Exclusions were due to various reasons: incomplete study data (36 patients), hematological diseases (2 patients), malignant tumors of other organs (4 patients), autoimmune disease (1 patient), long-term steroid drug use (16 patients), and non-cooperation with postoperative treatment (4 patients). The training cohort consists of 326 patients divided into a non-IPPH group with 303 patients and an IPPH group with 23 patients.</alt-text>
</graphic>
</fig>
</sec>
<sec id="s2c"><label>2.3</label><title>Data collection</title>
<p>The data included demographics, medical comorbidities, treatment-related, laboratory biomarkers, and postoperative complications. The demographic data includes age, gender (male or female), severe addiction (alcohol or smoking), BMI. Comorbidities included hypertension, diabetes mellitus, coronary heart disease, hepatitis, liver cirrhosis, pancreatitis, previous abdominal surgery. Treatment-related variables included percutaneous transhepatic cholangial drainage (PTCD), blood loss during the surgery, transfusion and operation time. Preoperative laboratory rusults included red blood cell count (RBC), white blood cell count (WBC), platelet count (PLT), albumin (Alb), total bilirubin (TBIL); alanine transaminase (ALT), aspartate transaminase (AST), fibrinogen (FIB), international normalized ratio (INR), creatinine (Cr), prothrombin time (PT). They activated partial thromboplastin time (APTT). Postoperative complications included clinically relevant postoperative pancreatic fistula (CR-POPF), bile leak, intra-abdominal infection (IAI), delayed gastric emptying (DGE), ileusand chyle leak.</p>
<p>ISGPS defined POPF as an amylase level in the abdominal drainage fluid that exceeds three times the upper limit of the average serum value for 3 days or more after surgery. ISGPS further categorized POPF into grades A to C based on the severity of the condition. Grade A represents biochemical fistulae, grade B indicates POPF requiring clinical treatment or intervention, and grade C signifies POPF combined with organ failure or life-threatening situations necessitating surgical intervention. Grades B and C POPF are collectively called clinically relevant POPF (CR-POPF) due to their significant association with prognosis (<xref ref-type="bibr" rid="B27">27</xref>). Three days after pancreaticoduodenectomy (PD), the bilirubin concentration in the drainage fluid exceeds three times the concentration in the serum. In such cases, interventional drainage or surgical intervention is necessary to address bile accumulation or diagnose cholestatic peritonitis, indicating a bile leak (<xref ref-type="bibr" rid="B28">28</xref>). Intra-abdominal infection (IAI) is characterized by symptoms such as chills, high fever, abdominal distension, and intestinal paralysis, persisting for more than 24&#x2005;h. Laboratory tests show a significant increase in white blood cell count, hypoproteinemia, and anemia, while imaging studies reveal the presence of fluid in the abdominal cavity. Diagnosis can be confirmed by aspirating pus or detecting bacteria (<xref ref-type="bibr" rid="B29">29</xref>). In accordance with the ISGPS, delayed gastric emptying (DGE) is the inability to resume a regular diet by the end of the first week after surgery, including patients requiring prolonged nasogastric tube usage (<xref ref-type="bibr" rid="B30">30</xref>). The ISGPS defines chyle leak as the discharge of chyle-like fluid from drains, drain orifices, or wounds occurring on or after the third day following surgery if the concentration of triglycerides exceeds 1.2&#x2005;mmol/L regardless of the volume (<xref ref-type="bibr" rid="B31">31</xref>).</p>
</sec>
<sec id="s2d"><label>2.4</label><title>LPD procudures</title>
<p>Pneumoperitoneum was created through a routine 5-hole approach. Subsequently, the operation was divided into two distinct phases: resection and reconstruction. The resection phase included the following steps: (1) performing a Kocher incision, (2) severing the stomach, (3) dissecting the hepatoduodenal ligament, (4) amputating the pancreas, (5) severing the jejunum, (6) dissecting the superior mesenteric vein-portal vein system, and (7) dissecting the superior mesenteric artery-celiac trunk system. The arterial or venous approach selection during surgery is contingent upon the tumor&#x0027;s positioning in relation to the blood vessels. After the resection, a 5-cm specimen was extracted through an incision located beneath the xiphoid process of the upper abdomen, and pneumoperitoneum was reinstated. The digestive tract reconstruction was accomplished using the Child method, which involved implementing various techniques, including the end-to-end mucosal-to-mucosal anastomosis method for pancreatic enterostomy. In this technique, the placement of the pancreatic duct stent was determined by intermittently or continuously suturing it, considering the diameter of the duct. Choledochojejunostomy was performed using an end-to-side anastomosis technique&#x2014;the anastomosis procedure involved a linear cutting occluder, followed by manual suturing of the joint opening. Two standard abdominal drainage tubes were placed during the surgery. One tube was positioned above the pancreaticojejunostomy and drained through the left abdominal wall, while the other tube was placed below the choledochojejunostomy and drained through the right abdominal wall. No additional drainage methods were employed in this particular case.</p>
</sec>
<sec id="s2e"><label>2.5</label><title>Definition</title>
<p>The definition of intraluminal post-pancreatectomy hemorrhage (IPPH) adhered strictly to the guidelines set forth by the International Study Group of Pancreatic Surgery (ISGPS). The ISGPS classification system distinguishes between intraluminal and extraluminal types of hemorrhage based on the location of the bleeding. Within the category of IPPH, various manifestations (e.g., pancreatic surface hemorrhage, peri-anastomotic ulcers, erosions, and biliary hemorrhage) are encompassed (<xref ref-type="bibr" rid="B31">31</xref>). The identification of the hemorrhage site was accomplished by gastroscopy or cesarean section.</p>
</sec>
<sec id="s2f"><label>2.6</label><title>Statistical analysis</title>
<p>Data were analyzed using SPSS 27.0 (IBM). Measurements were expressed as <italic>x</italic>&#x2009;&#x00B1;&#x2009;<italic>s</italic>. In normal distribution, the independent sample <italic>t</italic>-test was utilized to compare the two groups, while the rank sum test of two samples was employed for non-normal distribution. Counting data was analyzed using either the <italic>&#x03C7;</italic><sup>2</sup> test or the Fisher exact test. Multivariate logistic regression analysis was performed to identify independent risk factors for predicting IPPH among variables with <italic>P</italic>&#x2009;&#x003C;&#x2009;0.10. Subsequently, a nomogram was developed based on these factors using R Programming Language V.4.2.1 (R Foundation). The accuracy, sensitivity and specificity of the nomogram were assessed by the area under the curve (AUC) using receiver operating characteristic (ROC) analysis. Besides, decision curve analysis (DCA) was utilized to investigate the clinical predictive significance of different nomogram variables about the occurrence of IPPH.</p>
</sec>
</sec>
<sec id="s3" sec-type="results"><label>3</label><title>Results</title>
<sec id="s3a"><label>3.1</label><title>Characteristics of the study patients</title>
<p>A total of 326 patients out of 407 who underwent LPD were deemed eligible for inclusion criteria in this study. Among the enrolled participants, 200 (61.35&#x0025;) were male, and 126 (38.65&#x0025;) were female, with a mean age of 59.76&#x2009;&#x00B1;&#x2009;11.24. After LPD, a complication rate of 62.88&#x0025; (205/326) was observed. Among these patients, 23 were confirmed to have IPPH with a prevalence rate of 7.06&#x0025; (23/326). IPPH involved the surface of pancreas in 8 (34.78&#x0025;,8/23), the surface of gastrointestinal anastomosis in 14 (60.87&#x0025;,14/23), and ulcer of choledochojejunostomy complicated with erosive hemorrhage in 1 (4.34&#x0025;, 1/23).</p>
</sec>
<sec id="s3b"><label>3.2</label><title>Univariate and multivariate analysis</title>
<p>After univariate analysis, seven potential predictors were identified in all variables. Then, this study used multivariate regression analysis to examine the independent risk factors of IPPH (<xref ref-type="table" rid="T1">Tables&#x00A0;1</xref>, <xref ref-type="table" rid="T2">2</xref>). The findings indicate that advanced age (OR&#x2009;&#x003D;&#x2009;1.065, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.001&#x2013;1.133, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.045), low Fib level (OR&#x2009;&#x003D;&#x2009;0.485, 95&#x0025; CI&#x2009;&#x003D;&#x2009;0.242&#x2013;0.972, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.041), low Alb level (OR&#x2009;&#x003D;&#x2009;0.840, 95&#x0025; CI&#x2009;&#x003D;&#x2009;0.739&#x2013;0.956), and CR POPF (OR&#x2009;&#x003D;&#x2009;4.300, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.347&#x2013;13.722) were associated with an increased incidence of IPPH. IAI (OR&#x2009;&#x003D;&#x2009;6.347, 95&#x0025; CI&#x2009;&#x003D;&#x2009;1.454&#x2013;27.716, <italic>P</italic>&#x2009;&#x003D;&#x2009;0.014) was also identified as a significant factor. The differences in other factors were not statistically significant (<italic>P</italic>&#x2009;&#x003E;&#x2009;0.05).</p>
<table-wrap id="T1" position="float"><label>Table 1</label>
<caption><p>Univariate analysis of variables with interest between IPPH and non-IPPH patients.</p></caption>
<table frame="hsides" rules="groups">
<colgroup>
<col align="left"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
</colgroup>
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">Patients without IPPH (<italic>n</italic>&#x2009;&#x003D;&#x2009;303)</th>
<th valign="top" align="center">Patients with IPPH (<italic>n</italic>&#x2009;&#x003D;&#x2009;23)</th>
<th valign="top" align="center"><italic>P</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">52.93&#x2009;&#x00B1;&#x2009;11.372</td>
<td valign="top" align="center">66.83&#x2009;&#x00B1;&#x2009;6.00</td>
<td valign="top" align="center">0.001<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">Gender (Female)</td>
<td valign="top" align="center">118 (38.94&#x0025;)</td>
<td valign="top" align="center">8 (34.78&#x0025;)</td>
<td valign="top" align="center">0.639</td>
</tr>
<tr>
<td valign="top" align="left">BMI</td>
<td valign="top" align="center">24.28&#x2009;&#x00B1;&#x2009;3.73</td>
<td valign="top" align="center">23.69&#x2009;&#x00B1;&#x2009;3.51</td>
<td valign="top" align="center">0.049<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">Alcohol</td>
<td valign="top" align="center">68 (22.44&#x0025;)</td>
<td valign="top" align="center">6 (26.09&#x0025;)</td>
<td valign="top" align="center">0.687</td>
</tr>
<tr>
<td valign="top" align="left">Smoking</td>
<td valign="top" align="center">74 (24.42&#x0025;)</td>
<td valign="top" align="center">7 (30.43&#x0025;)</td>
<td valign="top" align="center">0.520</td>
</tr>
<tr>
<td valign="top" align="left">Hypertension</td>
<td valign="top" align="center">110 (36.30&#x0025;)</td>
<td valign="top" align="center">7 (30.43&#x0025;)</td>
<td valign="top" align="center">0.572</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes mellitus</td>
<td valign="top" align="center">64 (21.12&#x0025;)</td>
<td valign="top" align="center">5 (21.74&#x0025;)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Coronary heart disease</td>
<td valign="top" align="center">23 (7.59&#x0025;)</td>
<td valign="top" align="center">3 (13.04&#x0025;)</td>
<td valign="top" align="center">0.595</td>
</tr>
<tr>
<td valign="top" align="left">Hepatitis</td>
<td valign="top" align="center">8 (2.64&#x0025;)</td>
<td valign="top" align="center">1 (4.35&#x0025;)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Cirrhosis</td>
<td valign="top" align="center">3 (0.99&#x0025;)</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Pancreatitis</td>
<td valign="top" align="center">14 (4.62&#x0025;)</td>
<td valign="top" align="center">1 (4.35&#x0025;)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Abdominal surgery</td>
<td valign="top" align="center">35 (11.55&#x0025;)</td>
<td valign="top" align="center">5 (21.74&#x0025;)</td>
<td valign="top" align="center">0.269</td>
</tr>
<tr>
<td valign="top" align="left">PTCD</td>
<td valign="top" align="center">103 (33.99&#x0025;)</td>
<td valign="top" align="center">7 (30.43&#x0025;)</td>
<td valign="top" align="center">0.728</td>
</tr>
<tr>
<td valign="top" align="left">Blood loss</td>
<td valign="top" align="center">571.75&#x2009;&#x00B1;&#x2009;1,034.22</td>
<td valign="top" align="center">573.91&#x2009;&#x00B1;&#x2009;632.43</td>
<td valign="top" align="center">0.323</td>
</tr>
<tr>
<td valign="top" align="left">Transfusion</td>
<td valign="top" align="center">153 (50.50&#x0025;)</td>
<td valign="top" align="center">13 (56.52&#x0025;)</td>
<td valign="top" align="center">0.577</td>
</tr>
<tr>
<td valign="top" align="left">Operation time</td>
<td valign="top" align="center">370.85&#x2009;&#x00B1;&#x2009;104.16</td>
<td valign="top" align="center">360.65&#x2009;&#x00B1;&#x2009;131.49</td>
<td valign="top" align="center">0.356</td>
</tr>
<tr>
<td valign="top" align="left">CR POPF</td>
<td valign="top" align="center">32 (10.56&#x0025;)</td>
<td valign="top" align="center">8 (34.78&#x0025;)</td>
<td valign="top" align="center">0.002<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">Bile leak</td>
<td valign="top" align="center">19 (6.27&#x0025;)</td>
<td valign="top" align="center">4 (17.39&#x0025;)</td>
<td valign="top" align="center">0.113</td>
</tr>
<tr>
<td valign="top" align="left">IAI</td>
<td valign="top" align="center">6 (1.98&#x0025;)</td>
<td valign="top" align="center">6 (26.09&#x0025;)</td>
<td valign="top" align="center">&#x003C;0.001<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">DGE</td>
<td valign="top" align="center">25 (8.25&#x0025;)</td>
<td valign="top" align="center">2 (8.70&#x0025;)</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Ileus</td>
<td valign="top" align="center">4 (1.32&#x0025;)</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">Chyle leak</td>
<td valign="top" align="center">2 (0.66&#x0025;)</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">1.000</td>
</tr>
<tr>
<td valign="top" align="left">RBC</td>
<td valign="top" align="center">3.98&#x2009;&#x00B1;&#x2009;0.56</td>
<td valign="top" align="center">3.74&#x2009;&#x00B1;&#x2009;0.66</td>
<td valign="top" align="center">0.057</td>
</tr>
<tr>
<td valign="top" align="left">WBC</td>
<td valign="top" align="center">6.29&#x2009;&#x00B1;&#x2009;2.08</td>
<td valign="top" align="center">6.37&#x2009;&#x00B1;&#x2009;2.26</td>
<td valign="top" align="center">0.710</td>
</tr>
<tr>
<td valign="top" align="left">Plt</td>
<td valign="top" align="center">303.99&#x2009;&#x00B1;&#x2009;989.66</td>
<td valign="top" align="center">253.30&#x2009;&#x00B1;&#x2009;78.67</td>
<td valign="top" align="center">0.744</td>
</tr>
<tr>
<td valign="top" align="left">Alb</td>
<td valign="top" align="center">37.94&#x2009;&#x00B1;&#x2009;4.23</td>
<td valign="top" align="center">34.08&#x2009;&#x00B1;&#x2009;3.76</td>
<td valign="top" align="center">&#x003C;0.001<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">TBIL</td>
<td valign="top" align="center">62.76&#x2009;&#x00B1;&#x2009;66.50</td>
<td valign="top" align="center">73.78&#x2009;&#x00B1;&#x2009;68.35</td>
<td valign="top" align="center">0.404</td>
</tr>
<tr>
<td valign="top" align="left">ALT</td>
<td valign="top" align="center">94.49&#x2009;&#x00B1;&#x2009;104.17</td>
<td valign="top" align="center">80.58&#x2009;&#x00B1;&#x2009;84.20</td>
<td valign="top" align="center">0.704</td>
</tr>
<tr>
<td valign="top" align="left">AST</td>
<td valign="top" align="center">71.04&#x2009;&#x00B1;&#x2009;148.41</td>
<td valign="top" align="center">76.07&#x2009;&#x00B1;&#x2009;90.55</td>
<td valign="top" align="center">0.689</td>
</tr>
<tr>
<td valign="top" align="left">FIB</td>
<td valign="top" align="center">3.49&#x2009;&#x00B1;&#x2009;0.81</td>
<td valign="top" align="center">3.13&#x2009;&#x00B1;&#x2009;0.74</td>
<td valign="top" align="center">0.018<xref ref-type="table-fn" rid="table-fn2">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">INR</td>
<td valign="top" align="center">1.13&#x2009;&#x00B1;&#x2009;1.68</td>
<td valign="top" align="center">1.11&#x2009;&#x00B1;&#x2009;0.28</td>
<td valign="top" align="center">0.209</td>
</tr>
<tr>
<td valign="top" align="left">Cr</td>
<td valign="top" align="center">61.67&#x2009;&#x00B1;&#x2009;14.41</td>
<td valign="top" align="center">71.48&#x2009;&#x00B1;&#x2009;46.08</td>
<td valign="top" align="center">0.575</td>
</tr>
<tr>
<td valign="top" align="left">PT</td>
<td valign="top" align="center">11.56&#x2009;&#x00B1;&#x2009;1.00</td>
<td valign="top" align="center">12.30&#x2009;&#x00B1;&#x2009;3.14</td>
<td valign="top" align="center">0.290</td>
</tr>
<tr>
<td valign="top" align="left">APTT</td>
<td valign="top" align="center">30.74&#x2009;&#x00B1;&#x2009;3.75</td>
<td valign="top" align="center">31.32&#x2009;&#x00B1;&#x2009;3.76</td>
<td valign="top" align="center">0.802</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="table-fn1"><p>BMI, body mass index; PTCD, percutaneous transhepatic cholangial drainage; CR-POPF, clinically relevant postoperative pancreatic fistula; IAI, Intra-abdominal infection; DGE, delayed gastric emptying; RBC, red blood cell count; WBC, white blood cell count; Plt, platelet count; Alb, albumin; TBIL, total bilirubin; ALT, alanine transaminase; AST, aspartate transaminase, FIB, fibrinogen; INR, international normalized ratio; Cr, creatinine; PT, prothrombin time; APTT, activated partial thromboplastin time;.</p></fn>
<fn id="table-fn2"><label>&#x002A;</label>
<p>Significant variables.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float"><label>Table 2</label>
<caption><p>Multivariate analyses of the independent risk factors associated with IPPH.</p></caption>
<table frame="hsides" rules="groups">
<colgroup>
<col align="left"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
</colgroup>
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">Odds ratio</th>
<th valign="top" align="center">95&#x0025; CI</th>
<th valign="top" align="center"><italic>P</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Alb</td>
<td valign="top" align="center">0.840</td>
<td valign="top" align="center">0.739&#x2013;0.956</td>
<td valign="top" align="center">0.008<xref ref-type="table-fn" rid="table-fn4">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">CR POPF</td>
<td valign="top" align="center">4.300</td>
<td valign="top" align="center">1.347&#x2013;13.722</td>
<td valign="top" align="center">0.014<xref ref-type="table-fn" rid="table-fn4">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">IAI</td>
<td valign="top" align="center">6.347</td>
<td valign="top" align="center">1.454&#x2013;27.716</td>
<td valign="top" align="center">0.014<xref ref-type="table-fn" rid="table-fn4">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">FIB</td>
<td valign="top" align="center">0.485</td>
<td valign="top" align="center">0.242&#x2013;0.972</td>
<td valign="top" align="center">0.041<xref ref-type="table-fn" rid="table-fn4">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">1.065</td>
<td valign="top" align="center">1.001&#x2013;1.133</td>
<td valign="top" align="center">0.045<xref ref-type="table-fn" rid="table-fn4">&#x002A;</xref></td>
</tr>
<tr>
<td valign="top" align="left">BMI</td>
<td valign="top" align="center">0.887</td>
<td valign="top" align="center">0.768&#x2013;1.024</td>
<td valign="top" align="center">0.103</td>
</tr>
<tr>
<td valign="top" align="left">RBC</td>
<td valign="top" align="center">0.997</td>
<td valign="top" align="center">0.403&#x2013;2.467</td>
<td valign="top" align="center">0.995</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="table-fn3"><p>CI, confidential interval; Alb, albumin; CR-POPF, clinically relevant postoperative pancreatic fistula; IAI, Intra-abdominal infection; FIB, fibrinogen; RBC, red blood cell; BMI, Body mass index.</p></fn>
<fn id="table-fn4"><label>&#x002A;</label>
<p>Significant variables.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3c"><label>3.3</label><title>Construction and validation</title>
<p>The prediction nomogram was constructed based on multivariate analysis findings (<xref ref-type="fig" rid="F2">Figure&#x00A0;2</xref>), offering a more user-friendly and practical instrument for clinical implementation. The area under the curve (AUC) was determined to be 0.861 (95&#x0025; CI&#x2009;&#x003D;&#x2009;0.783&#x2013;0.939), indicating a substantial degree of sensitivity (82.6&#x0025;) and specificity (82.2&#x0025;), thereby attesting to the discriminatory capacity of the model (<xref ref-type="fig" rid="F3">Figure&#x00A0;3</xref>). Furthermore, the c-index and Brier score were computed as 0.862 and 0.052, respectively.</p>
<fig id="F2" position="float"><label>Figure 2</label>
<caption><p>Predictive nomogram for IPPH.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fsurg-12-1507434-g002.tif"><alt-text content-type="machine-generated">A risk assessment nomogram displays scales for Points, Age, CR_POPF, IAI, Fib, Alb, Total Points, and Risk. Each scale is marked with numbers, allowing for calculation of total points and risk.</alt-text>
</graphic>
</fig>
<fig id="F3" position="float"><label>Figure 3</label>
<caption><p>Receiver-operating characteristic (ROC) curves for the nomogram.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fsurg-12-1507434-g003.tif"><alt-text content-type="machine-generated">A receiver operating characteristic (ROC) curve showing the true positive rate against the false positive rate. The area under the curve (AUC) is 0.861. A point on the curve is marked with coordinates 0.085 (0.822, 0.826).</alt-text>
</graphic>
</fig>
<p>When utilizing the nomogram, the designated variable axis was employed to position the level of each variable. Subsequently, a vertical line was drawn along the axis from the corresponding point to ascertain the risk score. This procedure was iterated for each variable, culminating in the calculation of a cumulative score. The ultimate sum was then located on the &#x201C;total points&#x201D; axis, and a vertical line was drawn to intersect the probabilit<italic>y</italic> axis, thereby yielding the projected probability of experiencing IPPH.</p>
</sec>
<sec id="s3d"><label>3.4</label><title>Practical significance</title>
<p>To validate the net benefit for IPPH of patients who underwent LPD, a decision curve analysis (DCA) and a Hosmer-Lemeshow good of fit test were performed on the prediction model. The Hosmer-Lemeshow X2 statistics of the calibration curve (<xref ref-type="fig" rid="F4">Figure&#x00A0;4</xref>) illustrated a favorable consistency between the probability of predicting postoperative intraluminal hemorrhage and the actual probability of occurrence in patients undergoing LPD. As could be seen in <xref ref-type="fig" rid="F5">Figure&#x00A0;5</xref>, it was clear suggested that the model enhanced the net benefit of the &#x201C;treat all&#x201D; or &#x201C;no treatment&#x201D; scenario when the threshold probability was between 19&#x0025; and 100&#x0025;. The performance of the DCA showed that the model can guide clinical practice well.</p>
<fig id="F4" position="float"><label>Figure 4</label>
<caption><p>Hosmer-Lemeshow good of fit curves for the nomogram test curves.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fsurg-12-1507434-g004.tif"><alt-text content-type="machine-generated">A decision curve analysis graph shows net benefit versus threshold probability. The red line represents the \"Positive Status prediction,\" which decays steadily. The orange line labeled \"All\" shows a rapid decrease. The purple line labeled \"None\" remains flat at zero.</alt-text>
</graphic>
</fig>
<fig id="F5" position="float"><label>Figure 5</label>
<caption><p>Decision curve analysis for the nomogram test curves.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fsurg-12-1507434-g005.tif"><alt-text content-type="machine-generated">Calibration plot showing observed probability versus predicted probability. The dashed blue line represents the apparent prediction, the solid red line indicates the ideal prediction, and the solid green line shows the bias-corrected prediction.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion"><title>Discussion</title>
<p>The data used in this study were collected by trained investigators who strictly adhere to standardized protocols and regularly update the database based on the patient&#x0027;s condition. This database has proven to be a valuable source of data support in our previous studies. With these data, we demonstrated that the incidence of IPPH was 7.06&#x0025; (<xref ref-type="bibr" rid="B32">32</xref>&#x2013;<xref ref-type="bibr" rid="B34">34</xref>). Advanced age, low Fib level, low Alb level, CR POPF and IAI were identified as independent risk factors for IPPH. We also developed a predictive nomogram model with strong discrimination power and clinical applicability in internal validation. Surgeons can use it to screen immediately on admission and actively optimize risk factors during the perioperative period, providing individualized early intervention if necessary to avoid catastrophic medical consequences in patients with high risk of IPPH.</p>
<p>In the study of risk factors associated with PPH in patients undergoing PD, preoperative elevated C-reactive protein (CRP), increased BMI, higher serum bilirubin levels, elevated international normalized ratio (INR), biliary stent placement, pancreatic duct diameter &#x003C;0.4&#x2005;cm, postoperative pancreatic fistula (POPF), and delayed gastric emptying (DGE) were identified as significant risk factors (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B35">35</xref>). Research on extraluminal PPH (EPPH) has confirmed that younger age, prolonged operative time, and postoperative pancreatic fistula are significant perioperative risk factors for arterial pseudoaneurysm formation (<xref ref-type="bibr" rid="B19">19</xref>). These findings differ from our study results, highlighting the complexity of bleeding mechanisms after LPD. Therefore, it is crucial to conduct research by distinguishing between different bleeding sites.</p>
<p>Firstly, regarding age, our study results indicate that advanced age is a significant risk factor for IPPH in patients undergoing LPD. Recent studies by Bingpeng et al. suggest that the short- and long-term outcomes of elderly patients after LPD are comparable to those of younger patients, our findings underscore the importance of considering age as a critical factor in the risk assessment for IPPH (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>). However, they also confirmed that elderly LPD patients had a higher frequency of comorbidities compared to younger patients. Another study by Shuichi Aoki, analyzing data from 17,564 patients in the Japanese National Clinical Database, concluded that advanced age is an independent determinant of severe complications following pancreaticoduodenectomy (<xref ref-type="bibr" rid="B38">38</xref>).</p>
<p>A research has shown that overweight patients undergoing LPD experience prolonged recovery times and an increased likelihood of developing bile leakage, POPF, and IAI (<xref ref-type="bibr" rid="B39">39</xref>). In our study, univariate analysis demonstrated that BMI was statistically significantly lower in patients with IPPH after LPD compared to those without IPPH after LPD (<italic>P</italic>&#x2009;&#x003D;&#x2009;0.022). However, binary logistic regression multifactorial analysis indicated that BMI was not an independent risk factor for IPPH after LPD (<italic>P</italic>&#x2009;&#x003D;&#x2009;0.214). In summary, BMI cannot be considered a protective factor against intraluminal bleeding following LPD.</p>
<p>This study indicates that Alb and Fib are protective factors against IPPH. Numerous studies have established that preoperative hypoalbuminemia serves as a prognostic indicator for severe postoperative complications in patients undergoing pancreatoduodenectomy (<xref ref-type="bibr" rid="B40">40</xref>&#x2013;<xref ref-type="bibr" rid="B45">45</xref>). Although the relationship between fibrinogen levels and the incidence of IPPH has not been extensively studied on a global scale, our research findings indicate that a 1&#x2005;g/L increase in Fib is associated with a 51.5&#x0025; decrease in the risk of IPPH following LPD.</p>
<p>A previous research has demonstrated that CR POPF following LPD is lower than open pancreaticoduodenectomy (<xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B47">47</xref>). However, the overall incidence of CR POPF remains at 47.3&#x0025; (<xref ref-type="bibr" rid="B48">48</xref>). Researchers have reported that POPF is one of the risk factors for IAI after LPD (<xref ref-type="bibr" rid="B49">49</xref>&#x2013;<xref ref-type="bibr" rid="B51">51</xref>). Therefore, there may be an association between CR POPF and IAI, which can impact the prognosis of LPD patients (<xref ref-type="bibr" rid="B50">50</xref>). This study indicated both CR POPF and IAI can significantly impede the postoperative recovery of patients. IAI was found to have a more significant effect on IPPH after LPD than CR POPF (<xref ref-type="bibr" rid="B18">18</xref>). POPF can lead to alterations in the intra-abdominal microbiota. This disruption triggers a cascade of inflammatory responses, including peri-anastomotic irritation, increased tissue edema, and a higher likelihood of IAI (<xref ref-type="bibr" rid="B52">52</xref>). These inflammatory processes further exacerbate the progression of pancreatic fistula (<xref ref-type="bibr" rid="B49">49</xref>). Thus, patients experience prolonged postoperative hospitalization and a significant increase in the incidence of IPPH and mortality rate.</p>
<p>Naoya Ikeda et al. demonstrated that obstruction of the portal vein (PV) and superior mesenteric vein (SMV) are risk factors for gastrointestinal bleeding occurring more than 100 days after LPD (<xref ref-type="bibr" rid="B53">53</xref>). PV occlusion may be associated with local tumor recurrence or portal hypertension induced by the surgery. Therefore, we need not only perioperative but also longterm follow-up after LPD while taking into IPPH.</p>
<p>There are limitations in this study. First, the single-center design may limit the generalizability of the findings as the results are based on data from a specific population treated at one institution. This could introduce selection bias and affect the applicability of the findings to other settings. In addition, to improve the diagnostic validity of the model, patients with various specific conditions (e.g., hematological diseases, autoimmune disease, or long-term use of non-steroidal drugs) were excluded from this study, and therefore the final results of this study may not be applicable to those specific population.</p>
<p>The potential of artificial intelligence (AI) and machine learning (ML) to advance clinical risk prediction represents a significant avenue for future research endeavors. While our existing model relies on traditional statistical methodologies, AI technologies have exhibited considerable promise in the analysis of high-dimensional clinical datasets and the identification of complex, nonlinear interactions that conventional approaches may overlook. Within the domain of hepatobiliary and pancreatic surgery, recent investigations have highlighted the enhanced accuracy and adaptability of AI-driven models in forecasting postoperative complications, surpassing the performance of traditional methods (<xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B56">56</xref>). Considering the swift progression and increasing utilization of medical artificial intelligence (AI), especially within China, it is imperative for future research to investigate the incorporation of AI algorithms into predictive models for intraluminal post-pancreatectomy hemorrhage subsequent to laparoscopic pancreaticoduodenectomy. Such methodologies have the potential to enhance the precision of individualized risk stratification, aid in the timely implementation of clinical interventions, and ultimately optimize perioperative outcomes. Although AI was not utilized in the current study, its application signifies a promising direction for the enhancement of surgical risk assessment tools.</p>
</sec>
<sec id="s5" sec-type="conclusions"><label>5</label><title>Conclusion</title>
<p>Risk factors for IPPH include advanced age, low fibrinogen levels, low albumin levels, clinically relevant postoperative pancreatic fistula (CR POPF), and intra-abdominal infection (IAI). These risk factors were used to develop a nomogram for identifying patients at high risk of IPPH, allowing for targeted interventions to address modifiable risk factors promptly and improve patient outcomes.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability"><title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s12">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s7" sec-type="ethics-statement"><title>Ethics statement</title>
<p>The studies involving humans were approved by The Second Hospital of Hebei Medical University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.</p>
</sec>
<sec id="s8" sec-type="author-contributions"><title>Author contributions</title>
<p>SW: Data curation, Formal analysis, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. DL: Investigation, Writing &#x2013; original draft. CD: Investigation, Writing &#x2013; review &#x0026; editing. XY: Formal analysis, Writing &#x2013; review &#x0026; editing. LH: Data curation, Formal analysis, Writing &#x2013; review &#x0026; editing, Writing &#x2013; original draft.</p>
</sec>
<sec id="s9" sec-type="funding-information"><title>Funding</title>
<p>The author(s) declare that no financial support was received for the research and/or publication of this article.</p>
</sec>
<sec id="s10" sec-type="COI-statement"><title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="ai-statement"><title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s13" sec-type="disclaimer"><title>Publisher&#x0027;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12" sec-type="supplementary-material"><title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fsurg.2025.1507434/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fsurg.2025.1507434/full&#x0023;supplementary-material</ext-link></p>
<supplementary-material id="SD1" content-type="local-data">
<media mimetype="application" mime-subtype="vnd.openxmlformats-officedocument.spreadsheetml.sheet" xlink:href="Table1.xlsx"/></supplementary-material>
</sec>
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