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<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Ann Lab Med</journal-id>
<journal-title-group>
<journal-title>Annals of Laboratory Medicine</journal-title>
<abbrev-journal-title abbrev-type="publisher">Ann Lab Med</abbrev-journal-title>
</journal-title-group>
<issn pub-type="ppub">2234-3806</issn>
<issn pub-type="epub">2234-3814</issn>
<publisher>
<publisher-name>Korean Society for Laboratory Medicine</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3343/alm.2025.0232</article-id>
<article-id pub-id-type="publisher-id">alm-46-3-338</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Brief Communication</subject>
<subj-group>
<subject>Clinical Chemistry</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Comparison of Plasma N-Terminal Pro-B-Type Natriuretic Peptide Levels Between European and Japanese Patients with Acute Heart Failure: An International Study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes" equal-contrib="yes">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6356-2284</contrib-id>
<name><surname>Bruno</surname><given-names>Jolie</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff1" ref-type="aff">1</xref>
<xref rid="aff2" ref-type="aff">2</xref>
<xref rid="aff3" ref-type="aff">3</xref>
<xref rid="aff4" ref-type="aff">4</xref>
<xref rid="cor1" ref-type="corresp"/>
<xref rid="fn1" ref-type="author-notes">*</xref>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5648-5834</contrib-id>
<name><surname>Daghmouri</surname><given-names>Aziz</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff5" ref-type="aff">5</xref>
<xref rid="fn1" ref-type="author-notes">*</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4654-4065</contrib-id>
<name><surname>Asakage</surname><given-names>Ayu</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff6" ref-type="aff">6</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5237-8182</contrib-id>
<name><surname>Gobeaux</surname><given-names>Camille</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff7" ref-type="aff">7</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6753-9356</contrib-id>
<name><surname>&#268;erlinskait&#279;-Bajor&#279;</surname><given-names>Kamil&#279;</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff1" ref-type="aff">1</xref>
<xref rid="aff2" ref-type="aff">2</xref>
<xref rid="aff8" ref-type="aff">8</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-3562-9274</contrib-id>
<name><surname>&#268;elutkien&#279;</surname><given-names>Jelena</given-names></name>
<degrees>M.D., Ph.D.</degrees>
<xref rid="aff8" ref-type="aff">8</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5550-0083</contrib-id>
<name><surname>Sato</surname><given-names>Naoki</given-names></name>
<degrees>M.D., Ph.D.</degrees>
<xref rid="aff9" ref-type="aff">9</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0213-1509</contrib-id>
<name><surname>Takagi</surname><given-names>Koji</given-names></name>
<degrees>M.D.</degrees>
<xref rid="aff10" ref-type="aff">10</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8715-7753</contrib-id>
<name><surname>Mebazaa</surname><given-names>Alexandre</given-names></name>
<degrees>M.D., Ph.D.</degrees>
<xref rid="aff1" ref-type="aff">1</xref>
<xref rid="aff2" ref-type="aff">2</xref>
<xref rid="aff3" ref-type="aff">3</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5879-6369</contrib-id>
<name><surname>Deniau</surname><given-names>Benjamin</given-names></name>
<degrees>M.D., Ph.D.</degrees>
<xref rid="aff2" ref-type="aff">2</xref>
<xref rid="aff3" ref-type="aff">3</xref>
<xref rid="aff11" ref-type="aff">11</xref>
<xref rid="fn2" ref-type="author-notes">&#8224;</xref>
</contrib>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9377-4301</contrib-id>
<name><surname>Ishihara</surname><given-names>Shiro</given-names></name>
<degrees>M.D., Ph.D.</degrees>
<xref rid="aff12" ref-type="aff">12</xref>
<xref rid="fn2" ref-type="author-notes">&#8224;</xref>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label>INSERM UMR-S 942, Cardiovascular Markers in Stress Condition (MASCOT), Paris, <country>France</country></aff>
<aff id="aff2"><label>2</label>Universit&#233; de Paris Cit&#233;, Paris, <country>France</country></aff>
<aff id="aff3"><label>3</label>Department of Anesthesiology, Critical Care and Burn Unit, University Hospitals Saint-Louis et Lariboisi&#232;re, AP-HP, Paris, <country>France</country></aff>
<aff id="aff4"><label>4</label>Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern, <country>Switzerland</country></aff>
<aff id="aff5"><label>5</label>Department of Anesthesiology and Critical Care, Groupment Hospitalier de Territoire Grand Paris Nord-Est, H&#244;pital Andr&#233; Gr&#233;goire, Montreil, <country>France</country></aff>
<aff id="aff6"><label>6</label>Department of Emergency Medicine and Critical Care, National Center for Global Health and Medicine, Tokyo, <country>Japan</country></aff>
<aff id="aff7"><label>7</label>Biochemistry Laboratory, Assistance Publique-H&#244;pitaux de Paris, Centre-Universit&#233; de Paris Cit&#233;, Cochin Hospital, Paris, <country>France</country></aff>
<aff id="aff8"><label>8</label>Clinic of Cardiac and Vascular Diseases, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, <country>Lithuania</country></aff>
<aff id="aff9"><label>9</label>Department of Cardiovascular medicine, Kawaguchi Cardiovascular and Respiratory Hospital, Kawaguchi, <country>Japan</country></aff>
<aff id="aff10"><label>10</label>Momentum Research, Inc., Durham, North Carolina, <country>USA</country></aff>
<aff id="aff11"><label>11</label>INSERM PARCC UMR 970, Paris, <country>France</country></aff>
<aff id="aff12"><label>12</label>Department of Cardiovascular Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, <country>Japan</country></aff>
<author-notes>
<corresp id="cor1">Corresponding author: Jolie Bruno, M.D. INSERM UMR-S 942, Cardiovascular Markers in Stress Condition (MASCOT), H&#244;pital Lariboisi&#232;re, Bat Viggo Petersen, Porte 5 au 2&#232;me &#233;tage, 43 boulevard de la chapelle, Paris 75010, France E-mail: <email xlink:href="jolieb28@hotmail.com">jolieb28@hotmail.com</email></corresp>
<fn id="fn1" fn-type="equal"><label>*</label><p>These authors contributed equally to this study as co-first authors.</p></fn>
<fn id="fn2" fn-type="equal"><label>&#8224;</label><p>These authors jointly supervised this work.</p></fn> 
</author-notes>
<pub-date pub-type="ppub">
<day>1</day>
<month>5</month>
<year>2026</year>
</pub-date>
<pub-date pub-type="epub">
<day>27</day>
<month>11</month>
<year>2025</year>
</pub-date>
<volume>46</volume>
<issue>3</issue>
<fpage>338</fpage>
<lpage>344</lpage>
<history>
<date date-type="received">
<day>5</day>
<month>5</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>20</day>
<month>8</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>5</day>
<month>11</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>&#169; Korean Society for Laboratory Medicine</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/4.0">http://creativecommons.org/licenses/by-nc/4.0</ext-link>) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
</license>
</permissions>
<abstract>
<p>Plasma biomarkers levels, essential for diagnosing cardiovascular diseases, may vary by ethnicity. In this international prospective study, we compared plasma biomarker levels between European and Asian patients with clinically similar acute heart failure (AHF). Data were collected on emergency admission for acute dyspnea. Blood samples were obtained within 4 hrs of presentation and analyzed for N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity troponin-T, growth differentiation factor 15, interleukin-6, and C-reactive protein levels. Overall, 907 AHF patients were enrolled; of which, 135 (15%) were Japanese, and 772 (85%) were European. NT-proBNP levels were significantly higher in Japanese than in Europeans [4,060 ng/L (interquartile range (IQR) 2,081&#8211;12,218) vs. 3,390 ng/L (IQR 1,410&#8211;7,682), <italic>P</italic>=0.004]. After propensity score matching (PSM), no biomarker levels differed significantly. After stratification according to left ventricular ejection fraction (LVEF) at admission, higher NT-proBNP levels were observed in Japanese AHF patients with LVEF &#62;50% (<italic>P</italic>=0.02) than in European patients. After PSM, the difference was insignificant (<italic>P</italic>=0.35). In Asian and Caucasian AHF patients with similar clinical profiles, plasma cardiovascular biomarker levels did not differ significantly, regardless of LVEF, suggesting that NT-proBNP and related biomarkers can be applied across these ethnicities.</p>
</abstract>
<kwd-group>
<kwd>Biomarkers</kwd>
<kwd>Ethnicity</kwd>
<kwd>Europe</kwd>
<kwd>Japan</kwd>
<kwd>NT-proBNP</kwd>
</kwd-group>
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<institution>Ingelheim</institution>
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<institution>AstraZeneca</institution>
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<institution>Bayer</institution>
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</front>
<body>
<p>Acute heart failure (AHF), defined as the rapid onset or worsening of heart failure (HF) symptoms, requires urgent treatment [<xref rid="ref1" ref-type="bibr">1</xref>]. Accurate diagnosis is critical, and natriuretic peptides (NPs) are essential in HF diagnostic algorithms [<xref rid="ref2" ref-type="bibr">2</xref>]. Besides modest interpatient variability, several other factors, including ethnicity [<xref rid="ref3" ref-type="bibr">3</xref>, <xref rid="ref4" ref-type="bibr">4</xref>], can affect NP levels. Asian-American and African-American patients have been shown to have higher B-type NP (BNP) levels than Caucasian patients [<xref rid="ref3" ref-type="bibr">3</xref>], whereas N-terminal pro-BNP (NT-proBNP) levels have been reported to be similar in stable HF patients in Asian and Western settings [<xref rid="ref4" ref-type="bibr">4</xref>]. Notably, data on Asian populations are scarce, and the accuracy of NP thresholds in multiethnic populations and the potential underlying disparities remain to be studied. To the best of our knowledge, no prior research has evaluated NP levels in European and Asian AHF patients with comparable clinical features. Thus, we conducted an international, prospective, observational cohort study comparing cardiovascular biomarker profiles between these populations to assess the potential impact of ethnic background on biomarker levels.</p>
<p>A total of 1,668 patients were initially evaluated for inclusion. After excluding those with missing data for any study variable, 907 AHF patients were retained in the final analysis [135 (15%) from Japan and 772 (85%) from Europe]. Japanese patients were enrolled at Nippon Medical School Musashikosugi Hospital (Kawasaki, Japan) and Kawaguchi Cardiovascular and Respiratory Hospital (Kawaguchi, Japan), while European patients were enrolled from two pre-registered prospective studies: the Lithuanian Echocardiography Study of Dyspnoea in Acute Settings (NCT03048032) and Diagnostic and Prognostic Value of New Biomarkers in Patients With Heart Disease study (NCT01374880), conducted at multiple European sites. The study was approved by local ethics committees: Lithuanian Bioethics Committee (No. L-15-01), Comit&#233; d&#8217;Evaluation de l&#8217;Ethique des Projets de Recherche Biom&#233;dicale (CEERB) (No. 10-017), Nippon Medical School Musashi-Kosugi Hospital (No. 220-24-20) and Kawaguchi Cardiovascular and Respiratory Hospital (No. 2016-003). Informed consent was obtained from all patients.</p>
<p>AHF was defined according to European Society of Cardiology guidelines [<xref rid="ref1" ref-type="bibr">1</xref>]. Clinical and biological data were collected upon admission into the emergency department for acute dyspnea by reviewing electronic medical records. Blood samples were collected within 4 hrs of presentation, stored at &#8211;80&#176;C, and transferred to INSERM UMR-S 942 (Paris, France) for centralized biomarker analyses, including single baseline measurements of NT-proBNP, high-sensitivity troponin-T (hs-TnT), growth differentiation factor 15 (GDF-15), interleukin-6 (IL-6), and C-reactive protein (CRP) levels, using commercial assays (Roche Diagnostics, Mannheim, Germany, Europe). NT-proBNP, hs-TnT, GDF-15, and IL-6 levels were measured using electrochemiluminescence immunoassays on a Cobas E801 analyzer (Roche Diagnostics, Meylan, France). CRP concentrations were measured using the Tina-quant CRP-Gen.3 immunoturbidimetric assay on a Cobas c701 analyzer (Roche Diagnostics). Analytical performance metrics (including limits of detection and measurement ranges) were provided by the manufacturer. CVs, obtained through internal QC testing during the study, were &#60;5% and in accordance with our laboratory standards.</p>
<p>Baseline characteristics were compared using Pearson&#8217;s chi-squared or Fisher&#8217;s exact test for categorical variables and Wilcoxon rank-sum test for continuous or ordinal variables, as appropriate. Biomarkers levels were compared between groups using both the Wilcoxon rank-sum test and standardized mean differences (SMDs) with 95% confidence intervals. An absolute SMD &#60;0.1 was considered indicative of adequate balance. Propensity score matching (PSM) was conducted using logistic regression to estimate scores based on age, sex, body mass index (BMI), left ventricular ejection fraction (LVEF), systolic blood pressure, heart rate, estimated glomerular filtration rate, history of diabetes mellitus, chronic HF, atrial fibrillation, and coronary artery disease. Patients were matched in a 3:1 ratio via nearest-neighbor matching with a caliper of 0.8 SDs of the logit of the propensity score. For sensitivity analysis, multivariable logistic regression was used to assess the association between ethnicity and NT-proBNP levels after matching, adjusting for renal function (serum creatinine), age, and BMI, which are known clinical confounders influencing NT-proBNP levels.</p>
<p>Several differences were noted prior to PSM. Japanese patients had significantly lower Hb levels [119 g/L (IQR 100.5, 134.0) vs. 130 g/L (IQR 115.0, 143.0), <italic>P</italic>&#60;0.001]. Median LVEF was 40% (IQR 20, 54) in European patients and 45% (IQR 32, 60) in Japanese patients (<italic>P</italic>&#60;0.001). Japanese patients were less frequently treated with standard HF medications at discharge [beta-blockers: 12 (8.9%) vs. 450 (59%), <italic>P</italic>&#60;0.001, renin-angiotensin antagonists: 52 (39%) vs. 395 (52%), <italic>P</italic>=0.02]. After 3:1 PSM, differences became either non-significant or were markedly reduced (<xref rid="T1" ref-type="table">Table 1</xref>, <xref rid="S1" ref-type="supplementary-material">Supplemental Data Table S1</xref>, and <xref rid="S1" ref-type="supplementary-material">Supplemental Data Fig. S1</xref>).</p>
<p>NT-proBNP levels were significantly higher in Japanese AHF patients than in their European counterparts [4,060 ng/L (IQR 2,081, 12,218) vs. 3,390 ng/L (IQR 1,410, 7,682), <italic>P</italic>=0.004] (<xref rid="T2" ref-type="table">Table 2</xref>). After PSM, NT-proBNP levels showed no significant difference between the two groups [4,040 ng/L (IQR 2,084, 11,356) in Japan vs. 3,722 ng/L (IQR 1,324, 8,727), <italic>P</italic>=0.083], with a SMD of &#8211;0.09, suggesting an adequate balance between the cohorts. After stratification according to LVEF at admission (&#60;40%, 40%&#8211;50%, and &#62;50%), NT-proBNP levels were significantly higher in Japanese AHF patients, particularly in the group with LVEF &#62;50% (N=118 vs. 47, <italic>P</italic>=0.02) (<xref rid="F1" ref-type="fig">Fig. 1A</xref>), with no significant differences in the &#60;40% (N=208 vs. 45, <italic>P</italic>=0.97) and 40%&#8211;50% subgroups (N=100 vs. 29, <italic>P</italic>=0.11). However, post-PSM NT-proBNP levels were not significantly different in any LVEF subgroup (&#60;40%, N=55 vs. 36, <italic>P</italic>=0.79; 40%&#8211;50%, N=137 vs. 26, <italic>P</italic>=0.21; &#62;50%, N=51 vs. 34, <italic>P</italic>=0.36) (<xref rid="F1" ref-type="fig">Fig. 1B</xref>).</p>
<p>hs-TnT, GDF-15, IL-6, and CRP levels did not significantly differ between Japanese and European AHF patients at baseline or after PSM. The sensitivity analysis revealed that, after adjusting for renal function (serum creatinine), age, and BMI, the NT-proBNP levels did not differ significantly between Japanese and European patients (estimate=0.935, <italic>P</italic>=0.666; <xref rid="S1" ref-type="supplementary-material">Supplemental Data Table S2</xref>).</p>
<p>This study demonstrated that biomarker levels, particularly NT-proBNP levels, do not differ significantly between European and Japanese AHF patients. Analyses based on LVEF subclasses also did not reveal significant differences. However, importantly, our study was underpowered to conclusively detect differences among the LVEF subgroups.</p>
<p>Precipitating factors in AHF show ethnic differences [<xref rid="ref5" ref-type="bibr">5</xref>]; for instance, anemia, primarily caused by iron deficiency, is more prevalent in the Japanese population [<xref rid="ref6" ref-type="bibr">6</xref>], as also observed in our cohort. Iron deficiency affects up to 80% of AHF patients and may act as a triggering factor [<xref rid="ref1" ref-type="bibr">1</xref>].</p>
<p>As for HF medications, the higher rate of beta-blocker use at admission in European patients likely reflects a greater prevalence of chronic HF in this group, as opposed to the more frequent <italic>de novo</italic> presentations in Japanese patients. However, this difference is unlikely to have significantly influenced NT-proBNP levels, particularly given the absence of between-group differences in diuretic prescription at admission after matching, suggesting comparable disease severity at presentation. Regarding medications for HF at discharge, the observed differences should not be interpreted in the context of different clinical guidelines. We analyzed data collected between 2011 and 2017, when older HF guidelines comparable between regions were in use. Hence, the observed differences in medical therapy cannot be attributed to variations in treatment indications. European patients better adhered to the guidelines from that period, as opposed to the suboptimal management among Japanese HF patients. Although data on sodium glucose cotransporter 2 inhibitor (SGLT2i) and angiotensin receptor/neprilysin inhibitor (ARNI) use were not available for our cohorts, these treatments represent key components of modern HF management and may influence NT-proBNP levels. NT-proBNP levels do not typically increase through neprilysin inhibition during ARNI treatment; instead, persistently elevated values are associated with worse outcomes because of ongoing congestion or disease progression [<xref rid="ref7" ref-type="bibr">7</xref>]. In contrast, SGLT2is lower NT-proBNP levels, likely through diuretic effects exerted both alone and synergistically with other HF therapies and favorable cardiac remodeling [<xref rid="ref8" ref-type="bibr">8</xref>, <xref rid="ref9" ref-type="bibr">9</xref>].</p>
<p>Underutilization of guideline-directed medical therapy (GDMT) has been observed across ethnic groups [<xref rid="ref10" ref-type="bibr">10</xref>], and achieving adequate prescription and dose titration of GDMT among demographic groups remains a challenge in ensuring quality HF care. A Japanese observational study revealed a reduced use of cardioprotective medications for HF with reduced ejection fraction at discharge [<xref rid="ref11" ref-type="bibr">11</xref>].</p>
<p>Our study had some limitations. First, this was an observational study, which may have led to selection and confounding biases. Second, in the European database, ethnicities were not specified. While this reflects real-world European clinical practice, with patients of various ethnicities, further large studies from both regional and ethnic perspectives are required. Third, the sample size was small, limiting representativeness and statistical power. Fourth, the absence of healthy control data limited contextualization of biomarker levels within normal ranges. Fifth, the statistical power was insufficient to reliably detect differences within LVEF subgroups, which may affect interpretation of subgroup analyses. Finally, data regarding medical therapy did not reflect current guidelines and clinical practice, although we believe that comparable treatment exposure would not have substantially affected our findings. In this regard, studies using contemporary data will provide more insights.</p>
<p>In conclusion, NT-proBNP levels do not differ significantly between Caucasian and Asian AHF patients with similar clinical presentations, regardless of LVEF. Our results support that NT-proBNP levels in AHF patients can be interpreted without requiring ethnicity-specific adjustments in these populations.</p>
</body>
<back>
<ack>
<title>ACKNOWLEDGEMENTS</title>
<p>None.</p>
</ack>
<fn-group>
<fn fn-type="con">
<p><bold>AUTHOR CONTRIBUTIONS</bold></p>
<p>Mebazaa A, Deniau B, and Ishihara S contributed to the conception and design of the study; Bruno J and Daghmouri A performed the statistical analysis and interpreted the results; Gobeaux C was responsible for biomarker measurements and interpretation of analytical results; &#268;erlinskait&#279;-Bajor&#279; K, &#268;elutkien&#279; J, and Sato N provided the clinical data; Bruno J drafted the manuscript; Asakage A and Takagi K contributed to review and editing of the manuscript; Mebazaa A and Deniau B supervised the study. All authors read and approved the final manuscript.</p>
</fn>
<fn fn-type="coi-statement">
<p><bold>CONFLICTS OF INTEREST</bold></p>
<p>None declared.</p>
</fn>
<fn fn-type="supported-by">
<p><bold>RESEARCH FUNDING</bold></p>
<p>&#268;erlinskait&#279;-Bajor&#279; K received speaker&#8217;s honoraria from Bayer, AstraZeneca, Boehringer Ingelheim, Pfizer. &#268;elutkien&#279; J reports receiving personal fees from Boehringer Ingelheim, AstraZeneca, Bayer, and Novartis. Takagi K is an employee of Momentum Research, which has received grants for research from the Heart Initiative, Corteria, Windtree, Echosens, and 4teen4. Deniau B received honoraria from BD and VYGON. Mebazaa A received research contracts from 4TEEN4, Roche, Sphingotec, Abbott Diagnostics, Windtree; consultation fees from Roche, Corteria, Adrenomed, Fire, Johnson &#38; Johnson; honoraria for lectures from Merck, Novartis, Roche, Bayer; is co-inventor of patent on combined therapies to treat dyspnea, owned by S-Form Pharma; member of Committee of trials for Secret-HF, sponsored by the French Government, and for S-Form Pharma, for 4TEEN4, Echosens and Implicity. All other authors have nothing to disclose.</p>
</fn>
</fn-group>
<app-group>
<app>
<title>SUPPLEMENTARY MATERIALS</title>
<p>Supplementary materials can be found via <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3343/alm.2025.0232">https://doi.org/10.3343/alm.2025.0232</ext-link>.</p>
<supplementary-material id="S1" content-type="local-data">
<media xlink:href="alm-46-3-338-supple.pdf" mimetype="application" mime-subtype="pdf"/>
</supplementary-material>
</app>
</app-group>
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<sec sec-type="display-objects">
<title>Figure and Tables</title>
<fig id="F1" position="float">
<label>Fig. 1</label>
<caption>
<p>Comparison of NT-proBNP levels across LVEF subgroups before (A) and after (B) propensity score matching.</p>
<p>Abbreviations: NT-proBNP, N-terminal pro-B-type natriuretic peptide; LVEF, left ventricular ejection fraction.</p>
</caption>
<graphic xlink:href="alm-46-3-338-f1.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table 1</label>
<caption>
<p>Patient characteristics at baseline before and after propensity score matching</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr style="background-color:#d8e2f1;">
<th valign="middle" align="center" rowspan="2">Patient characteristics</th>
<th valign="middle" align="center" style="border-bottom:solid 1px;" colspan="5">Before propensity score matching</th>
<th valign="middle" align="center" style="border-bottom:solid 1px;"/>
<th valign="middle" align="center" style="border-bottom:solid 1px;" colspan="5">After propensity score matching</th>
</tr>
<tr style="background-color:#d8e2f1;">
<th valign="middle" align="center">N</th>
<th valign="middle" align="center">Overall<break/>N=907<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Europe<break/>N=772<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Japan<break/>N=135<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center"><italic>P</italic><xref rid="t1fn2" ref-type="table-fn">&#8224;</xref></th>
<th valign="middle" align="center" style="border-bottom:solid 1px;"/>
<th valign="middle" align="center">N</th>
<th valign="middle" align="center">Overall<break/>N=346<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Europe<break/>N=249<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Japan<break/>N=97<xref rid="t1fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center"><italic>P</italic><xref rid="t1fn2" ref-type="table-fn">&#8224;</xref></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Age (yrs)</td>
<td valign="top" align="center">907</td>
<td valign="top" align="center">73<break/>[64, 81]</td>
<td valign="top" align="center">72<break/>[63, 80]</td>
<td valign="top" align="center">79<break/>[70, 87]</td>
<td valign="top" align="center"><bold>&#60;0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">75<break/>[65, 83]</td>
<td valign="top" align="center">74<break/>[65, 82]</td>
<td valign="top" align="center">78<break/>[64, 86]</td>
<td valign="top" align="center"><bold>0.032</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Sex (male)</td>
<td valign="top" align="center">907</td>
<td valign="top" align="center">520<break/>(57%)</td>
<td valign="top" align="center">443<break/>(57%)</td>
<td valign="top" align="center">77<break/>(57%)</td>
<td valign="top" align="center">&#62;0.9</td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">204<break/>(59%)</td>
<td valign="top" align="center">148<break/>(59%)</td>
<td valign="top" align="center">56<break/>(58%)</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">BMI</td>
<td valign="top" align="center">636</td>
<td valign="top" align="center">28<break/>[24, 33]</td>
<td valign="top" align="center">30<break/>[25, 35]</td>
<td valign="top" align="center">23<break/>[21, 26]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">27.1<break/>[22.8, 28.3]</td>
<td valign="top" align="center">28.3<break/>[23.3, 28.3]</td>
<td valign="top" align="center">24.8<break/>[22.0, 27.9]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Comorbidities</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">DM</td>
<td valign="top" align="center">888</td>
<td valign="top" align="center">256<break/>(29%)</td>
<td valign="top" align="center">208<break/>(28%)</td>
<td valign="top" align="center">48<break/>(36%)</td>
<td valign="top" align="center"><bold>0.045</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">115<break/>(33%)</td>
<td valign="top" align="center">83<break/>(33%)</td>
<td valign="top" align="center">32<break/>(32%)</td>
<td valign="top" align="center">0.6</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Hypertension</td>
<td valign="top" align="center">896</td>
<td valign="top" align="center">737<break/>(82%)</td>
<td valign="top" align="center">650<break/>(85%)</td>
<td valign="top" align="center">87<break/>(65%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">343</td>
<td valign="top" align="center">261<break/>(76%)</td>
<td valign="top" align="center">197<break/>(80%)</td>
<td valign="top" align="center">64<break/>(67%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">COPD</td>
<td valign="top" align="center">888</td>
<td valign="top" align="center">90<break/>(10%)</td>
<td valign="top" align="center">86<break/>(11%)</td>
<td valign="top" align="center">4<break/>(3.0%)</td>
<td valign="top" align="center"><bold>0.003</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">338</td>
<td valign="top" align="center">28<break/>(8.3%)</td>
<td valign="top" align="center">26<break/>(11%)</td>
<td valign="top" align="center">2<break/>(2.1%)</td>
<td valign="top" align="center"><bold>0.005</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">CHF</td>
<td valign="top" align="center">888</td>
<td valign="top" align="center">657<break/>(74%)</td>
<td valign="top" align="center">622<break/>(82%)</td>
<td valign="top" align="center">35<break/>(26%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">176<break/>(51%)</td>
<td valign="top" align="center">144<break/>(58%)</td>
<td valign="top" align="center">32<break/>(33%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">CAD</td>
<td valign="top" align="center">890</td>
<td valign="top" align="center">361<break/>(41%)</td>
<td valign="top" align="center">339<break/>(45%)</td>
<td valign="top" align="center">22<break/>(16%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">87<break/>(25%)</td>
<td valign="top" align="center">69<break/>(28%)</td>
<td valign="top" align="center">18<break/>(19%)</td>
<td valign="top" align="center">0.065</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Chronic atrial fibrillation</td>
<td valign="top" align="center">888</td>
<td valign="top" align="center">489<break/>(55%)</td>
<td valign="top" align="center">443<break/>(59%)</td>
<td valign="top" align="center">46<break/>(34%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">338</td>
<td valign="top" align="center">156<break/>(46%)</td>
<td valign="top" align="center">121<break/>(50%)</td>
<td valign="top" align="center">35<break/>(36%)</td>
<td valign="top" align="center">0.12</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Clinical characteristics</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Systolic blood pressure (mmHg)</td>
<td valign="top" align="center">895</td>
<td valign="top" align="center">140<break/>[123, 60]</td>
<td valign="top" align="center">140<break/>[121, 160]</td>
<td valign="top" align="center">147<break/>[129, 173]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">140<break/>[124, 160]</td>
<td valign="top" align="center">140<break/>[122, 160]</td>
<td valign="top" align="center">142<break/>[126, 169]</td>
<td valign="top" align="center">0.6</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Diastolic blood pressure (mmHg)</td>
<td valign="top" align="center">893</td>
<td valign="top" align="center">80<break/>[70, 91]</td>
<td valign="top" align="center">80<break/>[70, 90]</td>
<td valign="top" align="center">86<break/>[74, 101]</td>
<td valign="top" align="center"><bold>0.007</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">344</td>
<td valign="top" align="center">81<break/>[73, 92]</td>
<td valign="top" align="center">80<break/>[73, 90]</td>
<td valign="top" align="center">85<break/>[73, 99]</td>
<td valign="top" align="center">0.7</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Heart rate (/min)</td>
<td valign="top" align="center">894</td>
<td valign="top" align="center">89<break/>[72, 106]</td>
<td valign="top" align="center">86<break/>[71, 103]</td>
<td valign="top" align="center">97<break/>[80, 117]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">90<break/>[74, 110]</td>
<td valign="top" align="center">88<break/>[72, 109]</td>
<td valign="top" align="center">96<break/>[81, 116]</td>
<td valign="top" align="center">0.064</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">LVEF (%)</td>
<td valign="top" align="center">557</td>
<td valign="top" align="center">40<break/>[26, 55]</td>
<td valign="top" align="center">40<break/>[25, 55]</td>
<td valign="top" align="center">45<break/>[32, 60]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">40<break/>[38, 50]</td>
<td valign="top" align="center">40<break/>[40, 46]</td>
<td valign="top" align="center">41<break/>[32, 55]</td>
<td valign="top" align="center">0.062</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Hb (g/L)</td>
<td valign="top" align="center">872</td>
<td valign="top" align="center">128<break/>[113, 142]</td>
<td valign="top" align="center">130<break/>[115, 143]</td>
<td valign="top" align="center">119<break/>[101, 134]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">127<break/>[111, 148]</td>
<td valign="top" align="center">128<break/>[115, 141]</td>
<td valign="top" align="center">121<break/>[102, 138]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Sodium (mmol/L)</td>
<td valign="top" align="center">828</td>
<td valign="top" align="center">139<break/>[136, 141]</td>
<td valign="top" align="center">139<break/>[136, 141]</td>
<td valign="top" align="center">139<break/>[136, 141]</td>
<td valign="top" align="center">&#62;0.9</td>
<td valign="top" align="center"/>
<td valign="top" align="center">324</td>
<td valign="top" align="center">139<break/>[136, 141]</td>
<td valign="top" align="center">139<break/>[136, 142]</td>
<td valign="top" align="center">139<break/>[136, 141]</td>
<td valign="top" align="center">0.7</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Creatinine (&#956;mol/L)</td>
<td valign="top" align="center">874</td>
<td valign="top" align="center">101<break/>[81, 135]</td>
<td valign="top" align="center">100<break/>[81, 132]</td>
<td valign="top" align="center">107<break/>[82, 158]</td>
<td valign="top" align="center">0.12</td>
<td valign="top" align="center"/>
<td valign="top" align="center">338</td>
<td valign="top" align="center">99<break/>[81, 136]</td>
<td valign="top" align="center">98<break/>[80, 130]</td>
<td valign="top" align="center">106<break/>[83, 154]</td>
<td valign="top" align="center">0.091</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">eGFR (mL/min/1.73 m<sup>2</sup>)</td>
<td valign="top" align="center">874</td>
<td valign="top" align="center">43<break/>[32, 56]</td>
<td valign="top" align="center">44<break/>[32, 56]</td>
<td valign="top" align="center">42<break/>[24, 56]</td>
<td valign="top" align="center"><bold>0.014</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">47<break/>[47]</td>
<td valign="top" align="center">47<break/>[47]</td>
<td valign="top" align="center">47<break/>[33, 58]</td>
<td valign="top" align="center">0.7</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Blood sugar (mmol/L)</td>
<td valign="top" align="center">719</td>
<td valign="top" align="center">6.3<break/>[5.5, 8.0]</td>
<td valign="top" align="center">6.1<break/>[5.4, 7.4]</td>
<td valign="top" align="center">7.7<break/>[6.1, 9.9]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">288</td>
<td valign="top" align="center">6.5<break/>[5.5, 8.6]</td>
<td valign="top" align="center">6.1<break/>[5.3, 7.8]</td>
<td valign="top" align="center">7.3<break/>[6.1, 9.9]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Medical therapy</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">&#946;-blocker at admission</td>
<td valign="top" align="center">899</td>
<td valign="top" align="center">462<break/>(51%)</td>
<td valign="top" align="center">450<break/>(59%)</td>
<td valign="top" align="center">12<break/>(8.9%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">139<break/>(40%)</td>
<td valign="top" align="center">129<break/>(52%)</td>
<td valign="top" align="center">10<break/>(10%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">ACEI/ARB2 at admission</td>
<td valign="top" align="center">891</td>
<td valign="top" align="center">447<break/>(50%)</td>
<td valign="top" align="center">395<break/>(52%)</td>
<td valign="top" align="center">52<break/>(39%)</td>
<td valign="top" align="center"><bold>0.006</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">341</td>
<td valign="top" align="center">159<break/>(47%)</td>
<td valign="top" align="center">120<break/>(49%)</td>
<td valign="top" align="center">39<break/>(41%)</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Aldosterone blocker at admission</td>
<td valign="top" align="center">899</td>
<td valign="top" align="center">206<break/>(23%)</td>
<td valign="top" align="center">189<break/>(25%)</td>
<td valign="top" align="center">17<break/>(13%)</td>
<td valign="top" align="center"><bold>0.002</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">64<break/>(18%)</td>
<td valign="top" align="center">52<break/>(21%)</td>
<td valign="top" align="center">12<break/>(12%)</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Diuretics at admission</td>
<td valign="top" align="center">892</td>
<td valign="top" align="center">476<break/>(53%)</td>
<td valign="top" align="center">428<break/>(56%)</td>
<td valign="top" align="center">48<break/>(36%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">341</td>
<td valign="top" align="center">153<break/>(45%)</td>
<td valign="top" align="center">116<break/>(47%)</td>
<td valign="top" align="center">37<break/>(39%)</td>
<td valign="top" align="center">0.3</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Nitrate at admission</td>
<td valign="top" align="center">899</td>
<td valign="top" align="center">68<break/>(7.6%)</td>
<td valign="top" align="center">57<break/>(7.5%)</td>
<td valign="top" align="center">11<break/>(8.1%)</td>
<td valign="top" align="center">0.8</td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">21<break/>(6.1%)</td>
<td valign="top" align="center">11<break/>(4.4%)</td>
<td valign="top" align="center">10<break/>(10%)</td>
<td valign="top" align="center">0.052</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Aspirin at admission</td>
<td valign="top" align="center">899</td>
<td valign="top" align="center">223<break/>(25%)</td>
<td valign="top" align="center">206<break/>(27%)</td>
<td valign="top" align="center">17<break/>(13%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">76<break/>(22%)</td>
<td valign="top" align="center">62<break/>(25%)</td>
<td valign="top" align="center">14<break/>(14%)</td>
<td valign="top" align="center"><bold>0.019</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Statin at admission</td>
<td valign="top" align="center">899</td>
<td valign="top" align="center">133<break/>(15%)</td>
<td valign="top" align="center">114<break/>(15%)</td>
<td valign="top" align="center">19<break/>(14%)</td>
<td valign="top" align="center">0.8</td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">40<break/>(12%)</td>
<td valign="top" align="center">27<break/>(11%)</td>
<td valign="top" align="center">13<break/>(13%)</td>
<td valign="top" align="center">0.4</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">&#946;-blocker at discharge</td>
<td valign="top" align="center">875</td>
<td valign="top" align="center">604<break/>(69%)</td>
<td valign="top" align="center">531<break/>(72%)</td>
<td valign="top" align="center">73<break/>(54%)</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">336</td>
<td valign="top" align="center">211<break/>(63%)</td>
<td valign="top" align="center">157<break/>(66%)</td>
<td valign="top" align="center">54<break/>(56%)</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">ACEI/ARB2 at discharge</td>
<td valign="top" align="center">862</td>
<td valign="top" align="center">559<break/>(65%)</td>
<td valign="top" align="center">461<break/>(63%)</td>
<td valign="top" align="center">98<break/>(74%)</td>
<td valign="top" align="center"><bold>0.020</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">326</td>
<td valign="top" align="center">217<break/>(67%)</td>
<td valign="top" align="center">145<break/>(63%)</td>
<td valign="top" align="center">72<break/>(76%)</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Aldosterone blocker at discharge</td>
<td valign="top" align="center">875</td>
<td valign="top" align="center">357<break/>(41%)</td>
<td valign="top" align="center">292<break/>(39%)</td>
<td valign="top" align="center">65<break/>(48%)</td>
<td valign="top" align="center">0.059</td>
<td valign="top" align="center"/>
<td valign="top" align="center">336</td>
<td valign="top" align="center">122<break/>(36%)</td>
<td valign="top" align="center">77<break/>(32%)</td>
<td valign="top" align="center">45<break/>(46%)</td>
<td valign="top" align="center"><bold>0.001</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Outcomes</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Time of hospitalization</td>
<td valign="top" align="center">903</td>
<td valign="top" align="center">8<break/>[2, 13]</td>
<td valign="top" align="center">7<break/>[<xref rid="ref1" ref-type="bibr">1</xref>, <xref rid="ref11" ref-type="bibr">11</xref>]</td>
<td valign="top" align="center">15<break/>[9, 25]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
<td valign="top" align="center"/>
<td valign="top" align="center">342</td>
<td valign="top" align="center">9<break/>[4, 14]</td>
<td valign="top" align="center">7<break/>[<xref rid="ref1" ref-type="bibr">1</xref>, <xref rid="ref11" ref-type="bibr">11</xref>]</td>
<td valign="top" align="center">15<break/>[9, 26]</td>
<td valign="top" align="center"><bold>&#60;</bold><bold>0.001</bold></td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:20px; text-indent:-10px;">Death in hospital</td>
<td valign="top" align="center">907</td>
<td valign="top" align="center">38<break/>(4.2%)</td>
<td valign="top" align="center">30<break/>(3.9%)</td>
<td valign="top" align="center">8<break/>(5.9%)</td>
<td valign="top" align="center">0.3</td>
<td valign="top" align="center"/>
<td valign="top" align="center">346</td>
<td valign="top" align="center">10<break/>(4.0%)</td>
<td valign="top" align="center">4<break/>(3.2%)</td>
<td valign="top" align="center">6<break/>(4.8%)</td>
<td valign="top" align="center">0.2</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t1fn1"><p>*Values are expressed as median and interquartile range [IQR], or as count and percentage (%), as appropriate.</p></fn>
<fn id="t1fn2"><p><sup>&#8224;</sup>Categorical variables were compared using Pearson&#8217;s chi-squared or Fisher&#8217;s exact test, as appropriate; continuous and ordinal variables were analyzed using the Wilcoxon rank-sum test. Significance was set to a two-sided <italic>P</italic>&#60;0.05; Significant values are highlighted in bold.</p></fn>
<fn id="t1fn3"><p>Abbreviations: BMI, body mass index; DM, diabetes mellitus; CI, confidence interval; CHF, chronic heart failure; CAD, coronary artery disease; CHF, chronic heart failure; COPD, chronic obstructive pulmonary disease; LVEF, left ventricular ejection fraction; sBP, systolic blood pressure; eGFR, estimated glomerular filtration rate; CRP, C-reactive protein; ACEI, angiotensin-converting enzyme inhibitors; ARB2, angiotensin II receptor blockers.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap id="T2" position="float">
<label>Table 2</label>
<caption>
<p>Comparison of biomarker levels per region before and after propensity score matching</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr style="background-color:#d8e2f1;">
<th valign="middle" align="center" rowspan="2">Parameter</th>
<th valign="middle" align="center" style="border-bottom:solid 1px;" colspan="7">Before propensity score matching</th>
<th valign="middle" align="center" style="border-bottom:solid 1px;"/>
<th valign="middle" align="center" style="border-bottom:solid 1px;" colspan="7">After propensity score matching</th>
</tr>
<tr style="background-color:#d8e2f1;">
<th valign="middle" align="center">N</th>
<th valign="middle" align="center">Overall<break/>N=907<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Europe<break/>N=772<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Japan<break/>N=135<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">SMD<xref rid="t2fn2" ref-type="table-fn">&#8224;</xref></th>
<th valign="middle" align="center">95% CI<xref rid="t2fn2" ref-type="table-fn">&#8225;</xref></th>
<th valign="middle" align="center"><italic>P</italic><xref rid="t2fn3" ref-type="table-fn">&#167;</xref></th>
<th valign="middle" align="center" style="border-bottom:solid 1px;"/>
<th valign="middle" align="center">N</th>
<th valign="middle" align="center">Overall<break/>N=346<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Europe<break/>N=249<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">Japan<break/>N=97<xref rid="t2fn1" ref-type="table-fn">*</xref></th>
<th valign="middle" align="center">SMD<xref rid="t2fn2" ref-type="table-fn">&#8224;</xref></th>
<th valign="middle" align="center">95% CI<xref rid="t2fn2" ref-type="table-fn">&#8225;</xref></th>
<th valign="middle" align="center"><italic>P</italic><xref rid="t2fn3" ref-type="table-fn">&#167;</xref></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">NT-proBNP (ng/L)</td>
<td valign="top" align="center">877</td>
<td valign="top" align="center">3,522<break/>[1,471, 7,876]</td>
<td valign="top" align="center">3,390<break/>[1,410, 7,682]</td>
<td valign="top" align="center">4,060<break/>[2,081, 12,218]</td>
<td valign="top" align="center">&#8211;0.21</td>
<td valign="top" align="center">&#8211;0.40, &#8211;0.03</td>
<td valign="top" align="center">0.004</td>
<td valign="top" align="center"/>
<td valign="top" align="center">339</td>
<td valign="top" align="center">3,833<break/>[1,630, 9,279]</td>
<td valign="top" align="center">3,722<break/>[1,324, 8,727]</td>
<td valign="top" align="center">4,040<break/>[2,084, 11,356]</td>
<td valign="top" align="center">&#8211;0.09</td>
<td valign="top" align="center">&#8211;0.33, 0.14</td>
<td valign="top" align="center">0.08</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">Troponin-T (pg/mL)</td>
<td valign="top" align="center">165</td>
<td valign="top" align="center">47<break/>[26, 91]</td>
<td valign="top" align="center">44<break/>[24, 61]</td>
<td valign="top" align="center">53<break/>[26, 94]</td>
<td valign="top" align="center">&#8211;0.25</td>
<td valign="top" align="center">&#8211;0.64, 0.13</td>
<td valign="top" align="center">0.2</td>
<td valign="top" align="center"/>
<td valign="top" align="center">114</td>
<td valign="top" align="center">47<break/>[25, 102]</td>
<td valign="top" align="center">47<break/>[30, 112]</td>
<td valign="top" align="center">47<break/>[24, 91]</td>
<td valign="top" align="center">&#8211;0.24</td>
<td valign="top" align="center">&#8211;0.75, 0.28</td>
<td valign="top" align="center">0.8</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">CRP (mg/L)</td>
<td valign="top" align="center">163</td>
<td valign="top" align="center">5<break/>[2, 19]</td>
<td valign="top" align="center">5<break/>[3, 15]</td>
<td valign="top" align="center">5<break/>[2, 20]</td>
<td valign="top" align="center">&#8211;0.04</td>
<td valign="top" align="center">&#8211;0.43, 0.34</td>
<td valign="top" align="center">0.8</td>
<td valign="top" align="center"/>
<td valign="top" align="center">112</td>
<td valign="top" align="center">5<break/>[2, 18]</td>
<td valign="top" align="center">5<break/>[2, 15]</td>
<td valign="top" align="center">5<break/>[2, 19]</td>
<td valign="top" align="center">0.13</td>
<td valign="top" align="center">&#8211;0.39, 0.64</td>
<td valign="top" align="center">0.7</td>
</tr>
<tr style="background-color:#f4f7fc;">
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">GDF-15 (pg/mL)</td>
<td valign="top" align="center">66</td>
<td valign="top" align="center">3,753<break/>[2,424, 5,894]</td>
<td valign="top" align="center">3,286<break/>[2,252, 6,119]</td>
<td valign="top" align="center">4,106<break/>[2,562, 5,487]</td>
<td valign="top" align="center">&#8211;0.10</td>
<td valign="top" align="center">&#8211;0.58, 0.38</td>
<td valign="top" align="center">0.6</td>
<td valign="top" align="center"/>
<td valign="top" align="center">43</td>
<td valign="top" align="center">4,093<break/>[2,481, 5,563]</td>
<td valign="top" align="center">2,981<break/>[2,121, 5,638]</td>
<td valign="top" align="center">4,202<break/>[2,762, 5,487]</td>
<td valign="top" align="center">&#8211;0.38</td>
<td valign="top" align="center">&#8211;1, 0.23</td>
<td valign="top" align="center">0.2</td>
</tr>
<tr>
<td valign="top" align="left" style="padding-left:10px; text-indent:-10px;">IL-6 (pg/mL)</td>
<td valign="top" align="center">165</td>
<td valign="top" align="center">16<break/>[9, 39]</td>
<td valign="top" align="center">11<break/>[8, 28]</td>
<td valign="top" align="center">17<break/>[9, 47]</td>
<td valign="top" align="center">&#8211;0.21</td>
<td valign="top" align="center">&#8211;0.59, 0.17</td>
<td valign="top" align="center">0.2</td>
<td valign="top" align="center"/>
<td valign="top" align="center">114</td>
<td valign="top" align="center">15<break/>[9, 45]</td>
<td valign="top" align="center">10<break/>[9, 28]</td>
<td valign="top" align="center">17<break/>[9, 48]</td>
<td valign="top" align="center">&#8211;0.21</td>
<td valign="top" align="center">&#8211;0.73, 0.30</td>
<td valign="top" align="center">0.3</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t2fn1"><p>*Values are expressed as median and [IQR].</p></fn>
<fn id="t2fn2"><p><sup>&#8224;,&#8225;</sup>SMDs and 95% confidence intervals were calculated to assess differences in continuous variables between groups; an absolute SMD of &#60;0.1 was considered indicative of adequate balance.</p></fn>
<fn id="t2fn3"><p><sup>&#167;</sup>Wilcoxon rank-sum test.</p></fn>
<fn id="t2fn4"><p>Significance was set to a two-sided <italic>P</italic>&#60;0.05.</p></fn>
<fn id="t2fn5"><p>Abbreviations: SMD, standard mean difference; NT-proBNP, N-terminal pro-B-type natriuretic peptide; GDF-15, growth/differentiation factor 15; IL-6, interleukin 6; BMI, body mass index; LVEF, left ventricular ejection fraction; sBP, HR, eGFR, estimated glomerular filtration rate; DM, diabetes mellitus; CHF, chronic heart failure; CAD, coronary artery disease.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
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</article>