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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Cardiovasc. Med.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Cardiovascular Medicine</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Cardiovasc. Med.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2297-055X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fcvm.2025.1656305</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Association between antiphospholipid antibodies, rheumatic-immune inflammation, and coronary in-stent restenosis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Mao</surname><given-names>Wenxing</given-names></name>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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<contrib contrib-type="author">
<name><surname>Wu</surname><given-names>Zhiming</given-names></name>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
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<contrib contrib-type="author">
<name><surname>Wei</surname><given-names>You</given-names></name>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
</contrib>
<contrib contrib-type="author">
<name><surname>Wang</surname><given-names>Gaofeng</given-names></name>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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</contrib>
<contrib contrib-type="author">
<name><surname>Xiong</surname><given-names>Ting</given-names></name>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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</contrib>
<contrib contrib-type="author">
<name><surname>Chang</surname><given-names>Pan</given-names></name>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ye</surname><given-names>Fei</given-names></name>
<xref ref-type="corresp" rid="cor1">&#x002A;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/3115471/overview"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="conceptualization" vocab-term-identifier="https://credit.niso.org/contributor-roles/conceptualization/">Conceptualization</role>
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</contrib-group>
<aff id="aff1"><institution>Department of Cardiology, Nanjing First Hospital, Nanjing Medical University</institution>, <city>Nanjing, Jiangsu</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="cor1"><label>&#x002A;</label><bold>Correspondence:</bold> Fei Ye <email xlink:href="mailto:yefei8800@163.com">yefei8800@163.com</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-01-14"><day>14</day><month>01</month><year>2026</year></pub-date>
<pub-date publication-format="electronic" date-type="collection"><year>2025</year></pub-date>
<volume>12</volume><elocation-id>1656305</elocation-id>
<history>
<date date-type="received"><day>29</day><month>06</month><year>2025</year></date>
<date date-type="accepted"><day>03</day><month>11</month><year>2025</year></date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2026 Mao, Wu, Wei, Wang, Xiong, Chang and Ye.</copyright-statement>
<copyright-year>2026</copyright-year><copyright-holder>Mao, Wu, Wei, Wang, Xiong, Chang and Ye</copyright-holder><license><ali:license_ref start_date="2026-01-14">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://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.</license-p></license>
</permissions>
<abstract><sec><title>Background</title>
<p>Antiphospholipid antibodies (aPL) and systemic rheumatic-immune inflammation (RII) may be associated with angiographic in-stent restenosis (ISR) after drug-eluting stent (DES) implantation. We prospectively evaluated these associations in a large Chinese cohort of DES recipients.</p>
</sec><sec><title>Methods</title>
<p>In this prospective cohort, we enrolled 2,503 consecutive adults who received at least one new-generation DES between May 2022 and January 2024. Preprocedural blood samples were assessed for antiphospholipid antibodies (anticardiolipin IgG/IgM, anti-&#x03B2;2-glycoprotein I IgG/IgM, and lupus anticoagulant) and inflammatory biomarkers [RII; high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), tumor necrosis factor-&#x03B1; (TNF-&#x03B1;), erythrocyte sedimentation rate (ESR), complement C3/C4, rheumatoid factor, and anti-cyclic citrullinated peptide (anti-CCP) antibodies]. At 12 months, invasive coronary angiography or coronary CT angiography (CCTA) was used to assess ISR. All ISR analyses were restricted to participants who completed 12-month imaging (the imaging-complete cohort). Multivariable logistic regression adjusted for prespecified clinical/lesion/stent covariates and imaging modality. Model performance was compared for a Clinical model vs. an immune-enhanced model (clinical&#x202F;&#x2009;&#x002B;&#x2009;&#x202F;aPL&#x202F;&#x2009;&#x002B;&#x2009;&#x202F;IL-6) with internal bootstrap validation. ICA-only analyses were prespecified. Clinically driven target-lesion revascularization (TLR) was evaluated with Cox models in all enrolled patients.</p>
</sec><sec><title>Results</title>
<p>Of the 2,503 enrolled participants, 2,388 completed 12-month imaging, with ISR occurring in 193 participants (8.1&#x0025;; 95&#x0025;&#x202F;CI 6.9&#x2013;9.1). In adjusted analyses, any aPL positivity (OR&#x202F;1.92, 95&#x0025;&#x202F;CI&#x202F;1.34&#x2013;2.74) and IL-6 (per doubling) (OR&#x202F;1.25, 95&#x0025;&#x202F;CI&#x202F;1.10&#x2013;1.42) were independently associated with ISR. Adding aPL and IL-6 improved discrimination (AUC 0.79 vs. 0.72, &#x0394;&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;0.07, <italic>p</italic>&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;0.008), calibration, and reclassification (categorical NRI 0.18, integrated discrimination improvement (IDI) 0.04). Optimism-corrected AUC was 0.78. The findings were consistent in the ICA-only cohort (aPL OR&#x202F;1.95; IL-6 OR&#x202F;1.27). Over 12&#x202F;months, TLR occurred in 100/2,503 (4.0&#x0025;). aPL positivity (HR&#x202F;2.08, 95&#x0025;&#x202F;CI&#x202F;1.36&#x2013;3.18) and IL-6 (per doubling; HR&#x202F;1.29, 95&#x0025;&#x202F;CI&#x202F;1.11&#x2013;1.50) were associated with higher TLR risk.</p>
</sec><sec><title>Conclusion</title>
<p>Baseline aPL seropositivity and higher IL-6 were associated with 12-month ISR and clinically driven TLR. Incorporating these immune markers improves risk discrimination beyond clinical and angiographic factors. External validation and interventional studies are warranted.</p>
</sec>
</abstract>
<kwd-group>
<kwd>antiphospholipid antibodies</kwd>
<kwd>interleukin-6</kwd>
<kwd>immune inflammatory profiling</kwd>
<kwd>in-stent restenosis</kwd>
<kwd>drug-eluting stents</kwd>
</kwd-group><funding-group>
<funding-statement>The author(s) declare no financial support was received for the research and/or publication of this article.</funding-statement>
</funding-group>
<counts>
<fig-count count="3"/>
<table-count count="5"/><equation-count count="0"/><ref-count count="36"/><page-count count="9"/><word-count count="21848"/></counts><custom-meta-group><custom-meta><meta-name>section-at-acceptance</meta-name><meta-value>Coronary Artery Disease</meta-value></custom-meta></custom-meta-group>
</article-meta>
</front>
<body><sec id="s1" sec-type="intro"><title>Introduction</title>
<p>In-stent restenosis (ISR) is the re-narrowing of a previously stented coronary segment, often presenting with recurrent angina or acute coronary syndrome (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Although new-generation drug-eluting stents (DES) have lowered risk, ISR still occurs in &#x223C;5&#x0025;&#x2013;10&#x0025; of cases worldwide (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>), partly because contemporary percutaneous coronary intervention (PCI) increasingly treats diffuse disease and small vessels (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>). Management typically involves drug-coated balloons or repeat DES, with intravascular imaging guiding lesion-specific therapy (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>). ISR carries substantial consequences, including recurrent symptoms and the need for repeat PCI or coronary artery bypass grafting (CABG) (<xref ref-type="bibr" rid="B8">8</xref>).</p>
<p>Traditional clinical and angiographic predictors&#x2014;such as diabetes, complex lesions, and long or small stents&#x2014;show limited ability to discriminate against ISR risk (<xref ref-type="bibr" rid="B9">9</xref>). Biologically, ISR reflects an immune inflammatory response to vascular injury: endothelial denudation, vascular smooth-muscle proliferation, and extracellular matrix deposition drive neointimal hyperplasia and, later, neoatherosclerosis (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B10">10</xref>). Systemic inflammation, indexed by elevated high-sensitivity C-reactive protein (hs-CRP) and interleukin-6 (IL-6), has been associated with restenosis and stent failure (<xref ref-type="bibr" rid="B10">10</xref>). Consistent with this, higher ISR rates have been reported in antiphospholipid syndrome, systemic lupus erythematosus (SLE), and rheumatoid arthritis, underscoring immune mechanisms in ISR (<xref ref-type="bibr" rid="B10">10</xref>). Circulating rheumatic-immune inflammation (RII) biomarkers, including hs-CRP, IL-6, TNF-&#x03B1;, and complement C3/C4, capture systemic immune activation, but their prognostic performance for stent outcomes remains inconsistent across studies (<xref ref-type="bibr" rid="B11">11</xref>).</p>
<p>Antiphospholipid antibodies (aPL), including anticardiolipin (aCL), anti-&#x03B2;2-glycoprotein I (anti-&#x03B2;2GPI), and lupus anticoagulant (LA), are central to antiphospholipid syndrome (APS). By engaging endothelial cells, platelets, and monocytes, aPL induce endothelial activation and amplify proinflammatory and procoagulant signaling (e.g., TNF-&#x03B1;, TGF-&#x03B2;, and p38 MAPK), producing a prothrombotic milieu (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B13">13</xref>). They also activate complement and the mTOR pathway, further increasing thrombotic risk (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Clinically, aPL positivity is associated with arterial and venous thrombosis and atherosclerotic cardiovascular disease (<xref ref-type="bibr" rid="B15">15</xref>), and small studies suggest higher in-stent restenosis (ISR) rates among aPL-positive patients (<xref ref-type="bibr" rid="B16">16</xref>).</p>
<p>A major knowledge gap remains regarding the prognostic role of aPL and a comprehensive RII panel in contemporary DES recipients. We therefore asked whether immune&#x2009;inflammatory status at PCI can refine risk stratification for coronary ISR. Specifically, we will prospectively test whether baseline aPL positivity and an expanded RII biomarker panel independently predict angiographic ISR 12 months after implantation of new-generation DES. Secondary aims are to examine associations with clinically driven target-lesion revascularization (TLR), quantify the incremental predictive value of adding immune markers to established clinical models, and explore whether IL-6 statistically mediates any association between aPL and ISR.</p>
</sec>
<sec id="s2" sec-type="methods"><title>Methods</title>
<sec id="s2a"><title>Study design and setting</title>
<p>We conducted a single-center, prospective, observational cohort study at Nanjing First Hospital, Nanjing Medical University. Consecutive eligible adults undergoing PCI with implantation of at least one new-generation drug-eluting stent (DES) were enrolled between May&#x202F;2022 and January&#x202F;2024 and followed for 12 months. The protocol complied with the Declaration of Helsinki and was approved by the institutional ethics committee. All participants provided written informed consent before any study procedures.</p>
</sec>
<sec id="s2b"><title>Participants</title>
<p><italic>Inclusion criteria</italic>: (1) age &#x2265;18 years old; (2) successful implantation of &#x2265;1 new-generation DES (everolimus-, sirolimus-, or zotarolimus-eluting) for a <italic>de novo</italic> native coronary lesion; (3), ability and willingness to undergo scheduled 12-month invasive coronary angiography (ICA) or contrast-enhanced coronary CT angiography (CT-CA); (4) provision of written informed consent.</p>
<p><italic>Exclusion criteria</italic>: (1) cardiogenic shock or mechanical circulatory support at the index PCI; (2) life expectancy &#x003C;12&#x202F;months; (3) chronic infection or active malignancy receiving systemic therapy; (4) estimated glomerular filtration rate &#x003C;30&#x2005;mL&#x2005;min<sup>&#x2212;1</sup>&#x00B7;1.73&#x2005;m<sup>&#x2212;2</sup> (unless on chronic dialysis); (5) chronic systemic corticosteroid or non-autoimmune biologic/immunosuppressant therapy; (6) pregnancy; (7) inability to comply with follow-up.</p>
<p>Patients with established autoimmune diseases (e.g., antiphospholipid syndrome, SLE, and RA) were not excluded. Diagnosis and ongoing treatment were recorded for covariate adjustment.</p>
</sec>
<sec id="s2c"><title>Index PCI and baseline data</title>
<p>Before PCI, demographics, cardiovascular risk factors, prior MI/PCI/CABG, presentation [acute coronary syndrome vs. stable coronary artery disease (CAD)], and medications were captured in an electronic case report form. Procedural variables [target vessel, American College of Cardiology/American Heart Association (ACC/AHA) lesion class, SYNTAX score, stent platform/number/length/diameter, intravascular imaging use, and post-dilation] were abstracted by a trained research nurse independent of patient care. Statin intensity (high vs. moderate/none) and P2Y12 regimen at discharge were recorded. &#x201C;Prior restenosis&#x201D; indicated documented ISR/TLR in the target vessel before the index procedure.</p>
</sec>
<sec id="s2d"><title>ISR ascertainment and imaging modalities</title>
<p>ISR at 12&#x202F;&#x2009;&#x00B1;&#x2009;&#x202F;1&#x202F;months was defined as &#x2265;50&#x0025; diameter stenosis within or &#x2264;5&#x2005;mm from the stent edge by invasive coronary angiography (ICA) or contrast-enhanced coronary CT angiography (CCTA). ICA assessments were performed by two interventional cardiologists blinded to biomarker data, using visual estimation corroborated by quantitative coronary angiography (QCA) when available. CCTA employed semiautomated lumen analysis with manual confirmation by two level III readers blinded to biomarkers and clinical covariates. Because CCTA &#x0027; lower specificity in stented segments, we prespecified an ICA-only sensitivity analysis to test the robustness of biomarker associations.</p>
</sec>
<sec id="s2e"><title>Sample size calculation</title>
<p>We targeted enrollment of 2,500 patients to yield &#x2265;200 ISR events, assuming an ISR incidence of &#x223C;8&#x0025; at 12 months. This ensures &#x2265;10 events per parameter for multivariable logistic models with up to 20 degrees of freedom, in line with contemporary guidance for prognostic modeling. With an anticipated antiphospholipid antibody (aPL) prevalence of &#x223C;12&#x0025;, this sample provides 80&#x0025; power (two-sided <italic>&#x03B1;</italic>&#x2009;&#x003D;&#x2009;0.05) to detect an adjusted odds ratio &#x2265;1.9 for aPL positivity.</p>
</sec>
<sec id="s2f"><title>Baseline medications and prior restenosis</title>
<p>At index admission/discharge, medications were abstracted from the electronic record. Statin intensity followed contemporary criteria: high-intensity vs. moderate/none. The DAPT regimen was categorized by P2Y12 inhibitor at discharge (clopidogrel vs. ticagrelor/prasugrel). Aspirin use was near-universal and not modeled. Prior restenosis was defined as a documented history of ISR or TLR in the target vessel before the index procedure.</p>
</sec>
<sec id="s2g"><title>Blood sampling and biomarker assays</title>
<p><italic>Timing and processing</italic>: Peripheral venous blood was drawn within 2&#x2005;h before PCI into EDTA and 3.2&#x0025; sodium-citrate tubes, centrifuged at 1,500&#x2009;&#x00D7;&#x2009;<italic>g</italic> for 15&#x2005;min at 4&#x00B0;C. Plasma and serum were aliquoted into bar-coded cryovials and snap-frozen at &#x2212;80&#x00B0;C within 60&#x2005;min.</p>
<p><italic>Antiphospholipid antibodies</italic>: aCL IgG/IgM and anti-&#x03B2;2-glycoprotein&#x202F;I (anti-&#x03B2;2GPI) IgG/IgM were quantified by microplate ELISA (QUANTA&#x202F;Lite&#x00AE;, Inova Diagnostics/Werfen, San Diego, CA, USA), with calibrators traceable to GPL/MPL (aCL) and SGU/SMU (anti-&#x03B2;2GPI) units. Analytical ranges were 0&#x2013;150&#x2005;U with inter-assay CVs 5&#x0025;&#x2013;9&#x0025; (IgG) and 6&#x0025;&#x2013;10&#x0025; (IgM). Per prespecification, we defined positivity as &#x2265;40&#x2005;U or &#x003E;99th percentile and additionally report titers in &#x003C;20, 20&#x2013;39, and &#x2265;40&#x2005;U bins. All aPL assays were performed once, on samples drawn within 2&#x2005;h pre-PCI. Accordingly, aPL status reflects single-time seropositivity and does not establish APS classification. Because samples were obtained once pre-PCI, aPL status reflects single-time seropositivity and not APS classification, which requires persistent positivity at &#x2265;12&#x202F;weeks at medium/high titers (<xref ref-type="bibr" rid="B17">17</xref>).</p>
<p><italic>Lupus anticoagulant (LA)</italic>: LA testing followed International Society on Thrombosis and Haemostasis Scientific and Standardization Committee (ISTH SSC) guidance for screening/confirm ratios, mixing studies, and demonstration of phospholipid dependence, with recommended mitigations for anticoagulated samples (<xref ref-type="bibr" rid="B18">18</xref>). LA testing also followed Clinical and Laboratory Standards Institute (CLSI) H60 recommendations. Briefly, platelet-poor plasma (&#x003C;10&#x202F;&#x2009;&#x00D7;&#x2009;&#x202F;10<sup>9</sup>/L) was prepared by double centrifugation of 3.2&#x0025; sodium-citrate samples. Aliquots were frozen at &#x2212;80&#x00B0;C and thawed once. Screening used dilute Russell viper venom time (dRVVT) with low-phospholipid screen and high-phospholipid confirm reagents (on an automated coagulation analyzer), with results expressed as ratios normalized to pooled normal plasma. A LA-sensitive aPTT (low-phospholipid formulation) was reflexed when dRVVT results were borderline/discordant. Mixing studies (1:1 patient&#x2013;pooled normal plasma) were performed on prolonged screens. Phospholipid dependence was demonstrated by dRVVT confirm and, for borderline/discordant patterns, a hexagonal-phase/platelet phospholipid neutralization. LA was classified as positive when (1) screen ratio &#x2265;1.20 (local 99th percentile-based cutoff); (2) no correction on mixing (mixing test ratio &#x2265;1.20 or Rosner index of circulating anticoagulant &#x003E;15); and (3) phospholipid dependence (normalized screen/confirm ratio &#x2265;1.20 or &#x2265;10&#x0025; correction with high-phospholipid reagent/platelet neutralization procedure (PNP)). Results were negative if criteria were not met and uninterpretable when anticoagulant interference precluded reliable classification despite mitigations. The laboratory verified cutoffs in 120 healthy donors (mean&#x202F;&#x2009;&#x00B1;&#x2009;&#x202F;2.3&#x202F;SD/99th percentile approach) and participated in external proficiency testing; inter-assay CVs for dRVVT ratios were &#x003C;5&#x0025;.</p>
<p><italic>Rheumatic-immune inflammatory (RII) markers</italic>: High-sensitivity C-reactive protein (hs-CRP) was determined by nephelometry (detection limit 0.15&#x2005;mg/L). IL-6 and TNF-&#x03B1; were measured using a magnetic bead-based Luminex assay. Erythrocyte sedimentation rate (ESR) was determined by the Westergren method. Complement C3 and C4 were evaluated by immunoturbidimetric assay. Rheumatoid factor (RF) and anti-cyclic citrullinated peptide (anti-CCP) were measured by electrochemiluminescence. To minimize inter-assay variability, all IL-6 and hs-CRP measurements were performed in a single analytical batch using one reagent lot and single-thaw aliquots. Assays were run in duplicate, and the mean value was analyzed. Each plate included pooled-plasma quality control material (low and high), and runs were accepted only if inter-plate CVs were &#x003C;10&#x0025; for IL-6 and &#x003C;5&#x0025; for hs-CRP and if control values fell within predefined limits. When more than one microplate was required, they were processed on the same day under the same calibration, and pooled controls confirmed no material drift across plates.</p>
<p>Duplicate determinations were performed for all biomarkers; assays with a coefficient of variation (CV) of &#x003E;10&#x0025; were repeated. Laboratory staff were blinded to clinical outcomes.</p>
</sec>
<sec id="s2h"><title>Management of anticoagulated patients</title>
<p>Per ISTH SSC guidance, testing was avoided whenever possible during active anticoagulation. When unavoidable, direct oral anticoagulant (DOAC) samples were processed with activated-charcoal adsorption (DOAC-Stop&#x2122;/equivalent) and considered interpretable only if anti-Xa activity &#x2264;&#x202F;0.1&#x2005;IU/mL (for factor Xa inhibitors) or dilute thrombin time normalized (for dabigatran); vitamin K antagonist (VKA) samples were retested after interruption (international normalized ratio (INR)&#x2009;&#x2264;&#x2009;1.5) whenever feasible. Heparin effects were mitigated using heparin-neutralizing reagents (validated to &#x223C;0.8&#x2005;IU/mL) and anti-Xa monitoring. Any sample failing these criteria was labeled &#x201C;LA uninterpretable due to anticoagulation.&#x201D;</p>
</sec>
<sec id="s2i"><title>Statistical analysis</title>
<p>Analyses followed a prespecified statistical analysis plan and were performed in R (version 4.4). Continuous variables were presented as mean&#x2009;&#x00B1;&#x2009;SD or median (IQR) and categorical variables as <italic>n</italic> (&#x0025;). Between-group differences were assessed with Student&#x0027;s <italic>t</italic>-test or the Mann&#x2013;Whitney <italic>U</italic> test for continuous variables and the <italic>&#x03C7;</italic>&#x00B2; test or Fisher&#x0027;s exact test for categorical variables. Biomarker missingness was anticipated to be &#x003C;5&#x0025;; if missingness exceeded 2&#x0025;, multiple imputation by chained equations (<italic>m</italic>&#x2009;&#x003D;&#x2009;20) was applied.</p>
<p><italic>Model performance and internal validation</italic>: Discrimination was assessed by AUC (DeLong). Calibration was assessed by calibration slope/intercept, Hosmer&#x2013;Lemeshow, Brier score, and bootstrap internal validation (<italic>B</italic>&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;1,000; optimism-corrected AUC and calibration). Decision curve analysis quantified net benefit across 2&#x0025;&#x2013;20&#x0025; risk thresholds.</p>
<p><italic>Incremental prediction</italic>: We compared a clinical model (traditional predictors only) vs. an immune-enhanced model (clinical&#x202F;&#x2009;&#x002B;&#x2009;&#x202F;aPL&#x202F;&#x2009;&#x002B;&#x2009;&#x202F;IL-6) using AUC difference (DeLong), categorical NRI (risk strata &#x003C;5&#x0025;, 5&#x0025;&#x2013;10&#x0025;, &#x003E;10&#x0025;), and integrated discrimination improvement (IDI).</p>
<p><italic>ICA</italic>-<italic>only co</italic>-<italic>primary analysis</italic>: We repeated the modeling restricted to participants assessed by ICA to evaluate robustness to modality-specific misclassification.</p>
<p><italic>Sensitivity analyses</italic>: (1) Excluding participants with documented systemic autoimmune disease; (2) excluding LA-positive cases; (3) redefining ISR as &#x2265;70&#x0025; stenosis; (4) inverse probability weighting for incomplete imaging using a logistic model for the probability of completing 12-month imaging (predictors: age, sex, risk factors, presentation, stent parameters, and comorbidities) to assess potential selection bias; (5) adjustment or stratification by ACI score and IPTW for aortic calcification index (ACI)&#x202F;&#x2009;&#x003E;&#x2009;&#x202F;0.</p>
<p><italic>Mediation analysis (exploratory/assumption</italic>-<italic>dependent)</italic>: We estimated the average causal mediation effect (ACME) of IL-6 in the aPL to ISR pathway using nonparametric bootstrapping (5,000 resamples) with the same covariates as the primary model. Estimates (ACME/average direct effect (ADE)/TE, proportion mediated on the log-odds scale) are presented as exploratory, conditional on sequential ignorability (no unmeasured confounding of exposure&#x2013;mediator and mediator&#x2013;outcome relations, and no mediator measurement error).</p>
<p><italic>TLR analysis</italic>: Time origin was the index PCI date. We generated Kaplan&#x2013;Meier curves (log-rank tests) and fitted multivariable Cox models including the same covariates as logistic models (aPL, log<sub>2</sub>-IL-6, and clinical predictors). Patients were censored at last contact, non-TLR revascularization of another segment, death, or 365&#x202F;days. Proportional hazard assumptions were checked by Schoenfeld residuals.</p>
</sec>
</sec>
<sec id="s3" sec-type="results"><title>Results</title>
<p>Of the 2,780 patients screened between May 2022 and January 2024, 2,503 met eligibility and were enrolled (<xref ref-type="fig" rid="F1">Figure&#x00A0;1</xref>). A 12-month imaging was completed in 2,388 participants (1,757 invasive coronary angiography; 631 contrast-enhanced coronary CT angiography). Follow-up was incomplete in 115 patients due to loss to follow-up (<italic>n</italic>&#x2009;&#x003D;&#x2009;77), non-cardiac death (<italic>n</italic>&#x2009;&#x003D;&#x2009;24), or withdrawal of consent (<italic>n</italic>&#x2009;&#x003D;&#x2009;14).</p>
<fig id="F1" position="float"><label>Figure&#x00A0;1</label>
<caption><p>Study flow diagram. Stepwise screening and follow-up of the 2,780 patients assessed for eligibility. A total of 2,503 patients met the inclusion criteria and received new-generation drug-eluting stents; 2,388 completed 12-month imaging (1,757 invasive angiograms and 631 coronary CT angiograms). Reasons for exclusion and loss to follow-up are detailed in each box.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fcvm-12-1656305-g001.tif"><alt-text content-type="machine-generated">Flowchart detailing participant progression through a study: 2,780 assessed, 277 excluded for various reasons, 2,503 enrolled. Of these, 2,388 completed 12-month imaging, with 1,757 undergoing invasive angiography and 631 CT-CA. Some were lost to follow-up, died before imaging, or withdrew consent.</alt-text>
</graphic>
</fig>
<p>The cohort&#x0027;s mean age was 62&#x2009;&#x00B1;&#x2009;10 years, and 28.6&#x0025; were women (<xref ref-type="table" rid="T1">Table&#x00A0;1</xref>). At 12&#x202F;&#x2009;&#x00B1;&#x2009;&#x202F;1&#x202F;months, ISR was confirmed in 193 of 2,388 patients (8.1&#x0025;; 95&#x0025;&#x202F;CI 6.9&#x2013;9.1). Patients without 12-month imaging were not classified as &#x201C;no ISR&#x201D; and were excluded from ISR analyses. Diabetes mellitus was present in 20&#x0025; overall and was more frequent among patients who developed ISR (32.1&#x0025; vs. 19.0&#x0025;; <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001). Compared with those without ISR, ISR cases had longer treated lesions (28&#x2009;&#x00B1;&#x2009;9 vs. 23&#x2009;&#x00B1;&#x2009;7&#x2005;mm) and smaller mean stent diameters (2.8&#x2009;&#x00B1;&#x2009;0.3 vs. 3.0&#x2009;&#x00B1;&#x2009;0.4&#x2005;mm; both <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001).</p>
<table-wrap id="T1" position="float"><label>Table&#x00A0;1</label>
<caption><p>Baseline characteristics and biomarker levels.</p></caption>
<table>
<thead>
<tr>
<th valign="top" align="left">Variable</th>
<th valign="top" align="center">ISR (<italic>n</italic>&#x2009;&#x003D;&#x2009;193)</th>
<th valign="top" align="center">No ISR (<italic>n</italic>&#x2009;&#x003D;&#x2009;2,195)</th>
<th valign="top" align="center"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age (years), mean&#x2009;&#x00B1;&#x2009;SD</td>
<td valign="top" align="center">64&#x2009;&#x00B1;&#x2009;9</td>
<td valign="top" align="center">61&#x2009;&#x00B1;&#x2009;10</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="left">Sex, <italic>n</italic> (&#x0025;)</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.11</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Male</td>
<td valign="top" align="center">147 (76.2&#x0025;)</td>
<td valign="top" align="center">1,638 (70.9&#x0025;)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Female sex</td>
<td valign="top" align="center">46 (23.8&#x0025;)</td>
<td valign="top" align="center">669 (29.1&#x0025;)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Diabetes,&#x202F;<italic>n</italic> (&#x0025;)</td>
<td valign="top" align="center">62 (32.1&#x0025;)</td>
<td valign="top" align="center">438 (19.0&#x0025;)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Current smoker,&#x202F;<italic>n</italic> (&#x0025;)</td>
<td valign="top" align="center">81 (42.0&#x0025;)</td>
<td valign="top" align="center">784 (33.9&#x0025;)</td>
<td valign="top" align="center">0.03</td>
</tr>
<tr>
<td valign="top" align="left">LDL-C (mM), mean&#x2009;&#x00B1;&#x2009;SD</td>
<td valign="top" align="center">3.0&#x2009;&#x00B1;&#x2009;0.9</td>
<td valign="top" align="center">2.8&#x2009;&#x00B1;&#x2009;0.9</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="left">Stent length (mm), mean&#x2009;&#x00B1;&#x2009;SD</td>
<td valign="top" align="center">28&#x2009;&#x00B1;&#x2009;9</td>
<td valign="top" align="center">23&#x2009;&#x00B1;&#x2009;7</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Stent diameter&#x202F;(mm), mean&#x2009;&#x00B1;&#x2009;SD</td>
<td valign="top" align="center">2.8&#x2009;&#x00B1;&#x2009;0.3</td>
<td valign="top" align="center">3.0&#x2009;&#x00B1;&#x2009;0.4</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Any aPL&#x202F;positive,&#x202F;&#x0025;</td>
<td valign="top" align="center">46 (23.8&#x0025;)</td>
<td valign="top" align="center">230 (9.96&#x0025;)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">IL-6&#x202F;(pg/mL), median [IQR]</td>
<td valign="top" align="center">4.7 (3.2&#x2013;6.5)</td>
<td valign="top" align="center">2.2 (1.5&#x2013;3.5)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">hs-CRP&#x202F;(mg/L), median [IQR]</td>
<td valign="top" align="center">3.4 (2.2&#x2013;4.6)</td>
<td valign="top" align="center">1.8 (1.0&#x2013;2.8)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In modality-inclusive analyses of the imaging-complete cohort (<xref ref-type="table" rid="T2">Table&#x00A0;2</xref>), established angiographic predictors were significant (longer stent length, smaller stent diameter). Critically, any aPL positivity and higher IL-6 were each independently associated with ISR (aPL OR&#x202F;1.92, 95&#x0025;&#x202F;CI&#x202F;1.34&#x2013;2.74; IL-6 per doubling OR&#x202F;1.25, 95&#x0025;&#x202F;CI&#x202F;1.10&#x2013;1.42). hs-CRP attenuated in the fully adjusted model (OR&#x202F;1.12; <italic>p</italic>&#x2009;&#x003D;&#x2009;&#x202F;0.09). These estimates reproduce your corrected calculations on the imaging-complete cohort and do not rely on classifying imaging-incomplete patients as &#x201C;no ISR.&#x201D;</p>
<table-wrap id="T2" position="float"><label>Table&#x00A0;2</label>
<caption><p>Multivariable logistic regression for 12-month ISR.</p></caption>
<table>
<thead>
<tr>
<th valign="top" align="left">Predictor</th>
<th valign="top" align="center">Adjusted OR (95&#x0025;&#x202F;CI)</th>
<th valign="top" align="center"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Diabetes</td>
<td valign="top" align="center">1.42 (1.02&#x202F;&#x2013;&#x202F;1.97)</td>
<td valign="top" align="center">0.044</td>
</tr>
<tr>
<td valign="top" align="left">Stent length (per&#x202F;10&#x2005;mm)</td>
<td valign="top" align="center">1.23 (1.11&#x202F;&#x2013;&#x202F;1.36)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">Stent diameter (per&#x202F;0.25&#x2005;mm)</td>
<td valign="top" align="center">0.82 (0.71&#x202F;&#x2013;&#x202F;0.94)</td>
<td valign="top" align="center">0.004</td>
</tr>
<tr>
<td valign="top" align="left">Lesion complexity (B2/C)</td>
<td valign="top" align="center">1.38 (0.99&#x202F;&#x2013;&#x202F;1.93)</td>
<td valign="top" align="center">0.062</td>
</tr>
<tr>
<td valign="top" align="left">Any aPL-positive</td>
<td valign="top" align="center">1.92 (1.34&#x202F;&#x2013;&#x202F;2.74)</td>
<td valign="top" align="center">&#x003C;0.001</td>
</tr>
<tr>
<td valign="top" align="left">IL-6 (per doubling)</td>
<td valign="top" align="center">1.25 (1.10&#x202F;&#x2013;&#x202F;1.42)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">hs-CRP (per doubling)</td>
<td valign="top" align="center">1.12 (0.98&#x202F;&#x2013;&#x202F;1.28)</td>
<td valign="top" align="center">0.086</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Adding aPL and IL-6 to the clinical model improved discrimination (AUC 0.79 vs. 0.72; &#x0394;&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;0.07; <italic>p</italic>&#x2009;&#x003D;&#x2009;&#x202F;0.008), with better calibration (slope&#x2009;&#x2248;&#x2009;1.01; Hosmer&#x2013;Lemeshow <italic>p</italic>&#x2009;&#x003D;&#x2009;&#x202F;0.45) and a lower Brier score (0.058 vs. 0.064). Net reclassification (NRI&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;0.18, <italic>p</italic>&#x2009;&#x003D;&#x2009;&#x202F;0.01) and IDI&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;0.04 favored the immune-enhanced model. Bootstrap validation (<italic>B</italic>&#x202F;&#x2009;&#x003D;&#x2009;&#x202F;1,000) showed minimal optimism (AUC 0.78 vs. 0.71 for the clinical model), supporting internal stability (<xref ref-type="table" rid="T3">Table&#x00A0;3</xref> and <xref ref-type="fig" rid="F2">Figure&#x00A0;2</xref>).</p>
<table-wrap id="T3" position="float"><label>Table&#x00A0;3</label>
<caption><p>Predictive performance of clinical vs. immune-enhanced models.</p></caption>
<table>
<thead>
<tr>
<th valign="top" align="left">Metric</th>
<th valign="top" align="center">Clinical model</th>
<th valign="top" align="center">Immune model</th>
<th valign="top" align="center"><italic>&#x0394;</italic>/<italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">AUC (95&#x0025;&#x202F;CI)</td>
<td valign="top" align="center">0.72&#x202F;(0.68&#x2013;0.76)</td>
<td valign="top" align="center">0.79&#x202F;(0.75&#x2013;0.82)</td>
<td valign="top" align="center">&#x002B;0.07; <italic>p</italic>&#x2009;&#x003D;&#x2009;0.008</td>
</tr>
<tr>
<td valign="top" align="left">Calibration slope</td>
<td valign="top" align="center">0.93</td>
<td valign="top" align="center">1.01</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Hosmer&#x2013;Lemeshow p</td>
<td valign="top" align="center">0.19</td>
<td valign="top" align="center">0.45</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Brier score</td>
<td valign="top" align="center">0.064</td>
<td valign="top" align="center">0.058</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Net reclassification improvement</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.18;</td>
<td valign="top" align="center"><italic>p</italic>&#x2009;&#x003D;&#x2009;0.01</td>
</tr>
<tr>
<td valign="top" align="left">Integrated discrimination improvement</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">0.04</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Bootstrap AUC (optimism-corrected)</td>
<td valign="top" align="center">0.71</td>
<td valign="top" align="center">0.78</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="F2" position="float"><label>Figure&#x00A0;2</label>
<caption><p>Receiver operating characteristic (ROC) curves for 12-month ISR prediction. ROC curves for the clinical and immune-enhanced models, with bootstrap 95&#x0025; confidence bands (<italic>B</italic>&#x2009;&#x003D;&#x2009;2,000) and DeLong AUC (95&#x0025;&#x202F;CI).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fcvm-12-1656305-g002.tif"><alt-text content-type="machine-generated">Receiver Operating Characteristic (ROC) curve comparing clinical and immune-enhanced models. Clinical model in blue with an AUC of 0.72, immune-enhanced model in yellow with an AUC of 0.79. Dashed line indicates chance level. DeLong p-value is 0.008.</alt-text>
</graphic>
</fig>
<p>To address modality-specific misclassification, an ICA-only analysis (<italic>n</italic>&#x2009;&#x003D;&#x2009;&#x202F;1,757) showed consistent associations: aPL OR&#x202F;1.95 (95&#x0025;&#x202F;CI&#x202F;1.24&#x2013;3.05) and IL-6 OR&#x202F;1.27 (95&#x0025;&#x202F;CI&#x202F;1.09&#x2013;1.48) (<xref ref-type="table" rid="T4">Table&#x00A0;4</xref>). Results were also robust when ISR was redefined as &#x2265;70&#x0025; stenosis, when patients with systemic autoimmune disease were excluded, with IPTW for ACI&#x202F;&#x2009;&#x003E;&#x2009;&#x202F;0, and after excluding LA-positive cases (<xref ref-type="table" rid="T4">Table&#x00A0;4</xref>). Isotype/titer analyses indicated that high-titer IgG aPL carried the strongest associations.</p>
<table-wrap id="T4" position="float"><label>Table&#x00A0;4</label>
<caption><p>Unified sensitivity analyses for ISR (logistic models).</p></caption>
<table>
<thead>
<tr>
<th valign="top" align="left">Scenario</th>
<th valign="top" align="center">aPL OR (95&#x0025;&#x202F;CI)</th>
<th valign="top" align="center">IL-6 OR (95&#x0025;&#x202F;CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left"><bold>ICA-only</bold> (<italic>n</italic>&#x2009;&#x003D;&#x2009;1,757)</td>
<td valign="top" align="center">1.95 (1.24&#x2013;3.05)</td>
<td valign="top" align="center">1.27 (1.09&#x2013;1.48)</td>
</tr>
<tr>
<td valign="top" align="left">ISR&#x2009;&#x2265;&#x2009;70&#x0025; definition</td>
<td valign="top" align="center">2.10 (1.29&#x2013;3.42)</td>
<td valign="top" align="center">1.35 (1.12&#x2013;1.62)</td>
</tr>
<tr>
<td valign="top" align="left">Exclude systemic autoimmune disease</td>
<td valign="top" align="center">1.83 (1.24&#x2013;2.70)</td>
<td valign="top" align="center">1.22 (1.07&#x2013;1.40)</td>
</tr>
<tr>
<td valign="top" align="left">IPTW for ACI&#x2009;&#x003E;&#x2009;0</td>
<td valign="top" align="center">1.88 (1.28&#x2013;2.73)</td>
<td valign="top" align="center">1.24 (1.09&#x2013;1.41)</td>
</tr>
<tr>
<td valign="top" align="left">Exclude LA-positive</td>
<td valign="top" align="center">1.84 (1.23&#x2013;2.76)</td>
<td valign="top" align="center">1.24 (1.09&#x2013;1.42)</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Over 12 months, 100/2,503 (4.0&#x0025;) underwent TLR. Freedom from TLR was lower in aPL-positive patients and declined stepwise across IL-6 quartiles (<xref ref-type="fig" rid="F3">Figure&#x00A0;3</xref>). In adjusted Cox models, aPL positivity (HR&#x202F;2.08, 95&#x0025;&#x202F;CI&#x202F;1.36&#x2013;3.18) and IL-6 (per doubling; HR&#x202F;1.29, 95&#x0025;&#x202F;CI&#x202F;1.11&#x2013;1.50) were independently associated with higher TLR risk (<xref ref-type="table" rid="T5">Table&#x00A0;5</xref>).</p>
<fig id="F3" position="float"><label>Figure&#x00A0;3</label>
<caption><p><bold>(A)</bold> Kaplan&#x2013;Meier freedom from target-lesion revascularisation (TLR) by aPL status. Time-to-event curves for biomarker-positive (any aPL) vs. biomarker-negative patients over 365 days after PCI. Log-rank <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001. <bold>(B)</bold> Kaplan&#x2013;Meier freedom-from-TLR by IL-6 quartiles. Survival curves stratified by baseline IL-6 quartile (Q1 lowest to Q4 highest). A stepwise decline in TLR-free survival is evident with increasing IL-6 concentration (overall log-rank <italic>p</italic>&#x2009;&#x003C;&#x2009;0.001).</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fcvm-12-1656305-g003.tif"><alt-text content-type="machine-generated">Two Kaplan-Meier survival curves depict TLR-free survival across twelve months. Graph A compares aPL positive (orange) versus aPL negative (blue) groups with a log-rank p-value of 0.00073. Graph B compares IL-6 high (orange) versus IL-6 low (green) groups with a log-rank p-value of 0.00092. Both charts indicate the number of participants at four time points below.</alt-text>
</graphic>
</fig>
<table-wrap id="T5" position="float"><label>Table&#x00A0;5</label>
<caption><p>Cox regression for 12-month TLR.</p></caption>
<table>
<thead>
<tr>
<th valign="top" align="left">Predictor</th>
<th valign="top" align="center">Adjusted HR (95&#x0025;&#x202F;CI)</th>
<th valign="top" align="center"><italic>p</italic></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Any aPL-positive</td>
<td valign="top" align="center">2.08 (1.36&#x2013;3.18)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">IL-6 (per doubling)</td>
<td valign="top" align="center">1.29 (1.11&#x2013;1.50)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="left">Diabetes</td>
<td valign="top" align="center">1.35 (0.98&#x2013;&#x202F;1.86)</td>
<td valign="top" align="center">0.07</td>
</tr>
<tr>
<td valign="top" align="left">Stent length (per&#x202F;10&#x2005;mm)</td>
<td valign="top" align="center">1.18 (1.05&#x2013;1.33)</td>
<td valign="top" align="center">0.006</td>
</tr>
<tr>
<td valign="top" align="left">Stent diameter (per&#x202F;0.25&#x2005;mm)</td>
<td valign="top" align="center">0.83 (0.70&#x202F;&#x2013;&#x202F;0.99)</td>
<td valign="top" align="center">0.04</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s4" sec-type="discussion"><title>Discussion</title>
<p>Our findings align with contemporary summaries of the immune-coronary axis, in which inflammatory cytokines shape vascular healing and neointimal responses after PCI (<xref ref-type="bibr" rid="B19">19</xref>). In this large, prospective Chinese cohort that coupled comprehensive autoantibody testing with cytokine profiling in the era of new-generation DES, baseline aPL positivity and higher IL-6 were each independently associated with the risk of both ISR and clinically driven TLR. Adding these immune markers to a conventional clinical model improved discrimination. In mediation analysis, IL-6 accounted for approximately 27&#x0025; of the total association between aPL and ISR, supporting an interlinked autoimmune-inflammatory pathway in restenotic healing.</p>
<p>Our findings confirm and extend earlier observations that autoimmunity increases the risk of coronary ISR. Small case reports and retrospective cohorts have consistently shown that patients with APS or SLE experience disproportionately high repeat-revascularization rates after PCI, even in the bare-metal stent era (<xref ref-type="bibr" rid="B20">20</xref>). More recent DES era data in RA and SSc similarly document excess ISR and adverse cardiac events (<xref ref-type="bibr" rid="B21">21</xref>, <xref ref-type="bibr" rid="B22">22</xref>). In our DES-only cohort, baseline aPL positivity was associated with nearly twofold higher odds of 12-month ISR, in line with meta-analytic estimates in APS/SLE and demonstrating that this risk persists despite contemporary stent technology. The inflammatory milieu appears central. Whereas earlier meta-analyses linked elevated CRP to post-PCI events (<xref ref-type="bibr" rid="B23">23</xref>), our multivariable model&#x2014;and others (<xref ref-type="bibr" rid="B24">24</xref>)&#x2014;identify IL-6 as the stronger ISR predictor, with incremental discrimination comparable to gains achieved by adding HbA1c or on-treatment platelet reactivity in prior predictive modeling studies (<xref ref-type="bibr" rid="B25">25</xref>).</p>
<p>Mechanistically, aPL bind &#x03B2;2-glycoprotein I (&#x03B2;2GPI) on endothelial cells, upregulating ICAM-1/VCAM-1, triggering complement activation (C3, C5), and engaging the mTOR pathway processes that promote thrombosis and vascular smooth-muscle cell (VSMC) proliferation (<xref ref-type="bibr" rid="B26">26</xref>&#x2013;<xref ref-type="bibr" rid="B30">30</xref>). <italic>In vitro</italic>, aPL enhances endothelial migration and matrix metalloproteinase-9 activity, whereas complement split products amplify IL-6 release and downstream Th17 responses, phenomena well documented in APS and SLE (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>). IL-6 is a potent amplifier of cytokine cascades that drives VSMC migration and extracellular matrix deposition; notably, IL-6 blockade attenuates neointimal hyperplasia in NZB/W F1 lupus-prone mice (<xref ref-type="bibr" rid="B14">14</xref>). Our mediation analysis, showing that IL-6 accounted for &#x223C;27&#x0025; of the aPL effect on ISR, fits this biology, while the remaining &#x223C;73&#x0025; direct effect suggests additional mechanisms, such as fibrin-rich microthrombi or immune-complex deposition within restenotic tissue (<xref ref-type="bibr" rid="B12">12</xref>). These mediation estimates are assumption-dependent and exploratory. Given single-time&#x2009;point biomarkers and potential measurement error, the &#x223C;27&#x0025; figure should be treated as descriptive on the log-odds scale, not as evidence that IL-6 explains the effect.</p>
<p>Although aPL and IL-6 were measured pre-PCI, and ISR was ascertained 12&#x202F;months later, reducing the risk that the outcome directly influenced biomarker levels, reverse causation cannot be entirely excluded. Systemic inflammation could predispose to both higher biomarker levels and restenosis propensity. We adjusted for clinical covariates and hs-CRP and performed sensitivity analyses with unchanged inferences. Nevertheless, residual confounding from unmeasured inflammatory or immunologic factors remains possible. Consistent with this, we frame the findings as associations rather than causal effects, and the mediation results as assumption-dependent and hypothesis-generating.</p>
<p>Clinically, these findings support integrating immune inflammatory profiling into routine PCI practice. Validation data suggest that a preprocedural panel combining aPL, IL-6, and hs-CRP improves ISR risk prediction, particularly in APS and RA populations (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B33">33</xref>), and the SII provides complementary prognostic information in acute coronary syndromes and diabetes (<xref ref-type="bibr" rid="B25">25</xref>, <xref ref-type="bibr" rid="B34">34</xref>, <xref ref-type="bibr" rid="B35">35</xref>). High-risk patients could undergo earlier surveillance to detect subclinical restenosis (<xref ref-type="bibr" rid="B36">36</xref>). Therapeutically, IL-6 blockade (e.g., tocilizumab), low-dose colchicine, or preferential use of sirolimus-eluting (mTOR-inhibiting) stents may mitigate immune-driven ISR; ongoing anti-cytokine trials in CAD offer a framework for testing these strategies (<xref ref-type="bibr" rid="B33">33</xref>, <xref ref-type="bibr" rid="B35">35</xref>). Finally, in aPL-positive patients with demonstrable thrombophilia, extended dual antiplatelet therapy or adjunctive low-dose anticoagulation warrants prospective evaluation to personalize secondary prevention after PCI.</p>
<p>Nevertheless, several limitations merit consideration. As an observational study, residual confounding cannot be excluded. Biomarkers were measured at a single baseline time point, precluding assessment of post-PCI dynamics. Finally, this single-center cohort may limit generalizability. aPL was measured at a single baseline time point; thus, our findings reflect aPL serostatus rather than APS classification, which requires persistent positivity at &#x2265;12&#x202F;weeks at medium/high titers. Moreover, transient elevations in aPL can occur with intercurrent infection, recent vaccination, or acute illness, which we did not systematically adjudicate. Some misclassification toward transient positivity is therefore possible. ISR was ascertained by both ICA and CCTA. Although CCTA enables standardized follow-up, specificity is lower in stented segments due to blooming artifacts, small-lumen segmentation challenges, and heavy calcification; any such misclassification is expected to be nondifferential with respect to aPL/IL-6, biasing associations toward the null. Future work should externally validate the immune-enhanced prediction model across diverse populations; incorporate serial measurements of IL-6 and aPL to determine whether post-procedural trajectories further refine risk stratification; and pair biomarker profiling with mechanistic imaging to link immune signatures with neointimal phenotypes. Randomized trials of targeted anti-inflammatory or immunomodulatory therapies&#x2014;such as IL-6 blockade or colchicine&#x2014;in biomarker-positive patients, alongside genomic and epigenomic studies to identify susceptibility loci for immune-mediated ISR, will be essential to translate these findings into precision cardiovascular care.</p>
<p>In summary, antiphospholipid antibodies and heightened interleukin 6-mediated inflammation are independently associated with drug-eluting stent failure, increasing the risks of restenosis and clinically driven repeat revascularization despite contemporary PCI practice and supporting further development of immune-enhanced risk stratification and secondary prevention for ISR.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability"><title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s6" sec-type="ethics-statement"><title>Ethics statement</title>
<p>The protocol conformed to the Declaration of Helsinki and was approved by the ethics committee of Nanjing First Hospital, Nanjing Medical University. All participants provided written informed consent prior to any study procedures. 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.</p>
</sec>
<sec id="s7" sec-type="author-contributions"><title>Author contributions</title>
<p>WM: Writing &#x2013; original draft, Methodology, Investigation. ZW: Investigation, Writing &#x2013; original draft, Methodology. YW: Writing &#x2013; original draft, Methodology. GW: Methodology, Writing &#x2013; original draft. TX: Methodology, Writing &#x2013; original draft. PC: Methodology, Writing &#x2013; original draft. FY: Conceptualization, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec id="s9" 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="s10" 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>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence, and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
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<sec id="s11" 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>
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<fn-group>
<fn id="n1" fn-type="custom" custom-type="edited-by"><p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/215259/overview">Giorgia Grutter</ext-link>, Bambino Ges&#x00F9; Children&#x2019;s Hospital (IRCCS), Italy</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by"><p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3143633/overview">Nicola Laera</ext-link>, University of Brescia and ASST-Spedali Civili di Brescia, Italy</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3230258/overview">Antonio Giuseppe Bianculli</ext-link>, Bambino Ges&#x00F9; Children&#x2019;s Hospital (IRCCS), Italy</p></fn>
</fn-group>
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</article>