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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Physiol.</journal-id>
<journal-title>Frontiers in Physiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Physiol.</abbrev-journal-title>
<issn pub-type="epub">1664-042X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1608584</article-id>
<article-id pub-id-type="doi">10.3389/fphys.2025.1608584</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Physiology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Athletic pseudonephritis in male cross-country ultra-marathoners: a comparative observational study</article-title>
<alt-title alt-title-type="left-running-head">Chen et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/fphys.2025.1608584">10.3389/fphys.2025.1608584</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Kai-Hung</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Lee</surname>
<given-names>Cheng-Hsun</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Pang-Yen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/942122/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Li-Hua</given-names>
</name>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="aff" rid="aff7">
<sup>7</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/687700/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>How</surname>
<given-names>Chorng-Kuang</given-names>
</name>
<xref ref-type="aff" rid="aff8">
<sup>8</sup>
</xref>
<xref ref-type="aff" rid="aff9">
<sup>9</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/662112/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Yen-Kuang</given-names>
</name>
<xref ref-type="aff" rid="aff10">
<sup>10</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2272119/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chiu</surname>
<given-names>Yu-Hui</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2245097/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/methodology/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Feng-Lin</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kao</surname>
<given-names>Wei-Fong</given-names>
</name>
<xref ref-type="aff" rid="aff11">
<sup>11</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Ming-Kun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff12">
<sup>12</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chien</surname>
<given-names>Ding-Kuo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2636864/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chang</surname>
<given-names>Wen-Han</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1017072/overview"/>
<role content-type="https://credit.niso.org/contributor-roles/Writing - review &#x26; editing/"/>
<role content-type="https://credit.niso.org/contributor-roles/supervision/"/>
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</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Emergency Medicine</institution>, <institution>MacKay Memorial Hospital</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Emergency Medicine</institution>, <institution>Saint Paul&#x2019;s Hospital</institution>, <addr-line>Taoyuan</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Institute of Biomedical Engineering</institution>, <institution>National Tsing Hua University</institution>, <addr-line>Hsinchu</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Artificial Intelligence and Medical Application, MacKay Junior College of Medicine, Nursing, and Management</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>School of Medicine, College of Medicine</institution>, <institution>MacKay Medical University</institution>, <addr-line>New TaipeiCity</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Department of Pathology and Laboratory Medicine</institution>, <institution>Taipei Veterans General Hospital</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff7">
<sup>7</sup>
<institution>Ph.D. Program of Medical Biotechnology</institution>, <institution>Taipei Medical University</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff8">
<sup>8</sup>
<institution>Department of Emergency Medicine</institution>, <institution>Taipei Veterans General Hospital</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff9">
<sup>9</sup>
<institution>Department of Emergency Medicine</institution>, <institution>School of Medicine</institution>, <institution>National Yang Ming Chiao Tung University</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff10">
<sup>10</sup>
<institution>Graduate Institute of Athletics and Coaching Science</institution>, <institution>National Taiwan Sport University</institution>, <addr-line>Taoyuan</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff11">
<sup>11</sup>
<institution>Department of Emergency</institution>, <institution>School of Medicine</institution>, <institution>College of Medicine</institution>, <institution>Taipei Medical University</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<aff id="aff12">
<sup>12</sup>
<institution>Department of Electronic Engineering</institution>, <institution>National Taipei University of Technology</institution>, <addr-line>Taipei</addr-line>, <country>Taiwan</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/540278/overview">Emiliano C&#xe8;</ext-link>, University of Milan, Italy</p>
</fn>
<fn fn-type="edited-by">
<p>
<bold>Reviewed by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1079088/overview">Daniel Pinto</ext-link>, Federal University of Ceara, Brazil</p>
<p>
<ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3044456/overview">Runer Marson</ext-link>, Preparatory School for Army Cadets, Brazil</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Yu-Hui Chiu, <email>yuhui.5848@mmh.org.tw</email>
</corresp>
</author-notes>
<pub-date pub-type="epub">
<day>14</day>
<month>08</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>16</volume>
<elocation-id>1608584</elocation-id>
<history>
<date date-type="received">
<day>09</day>
<month>04</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>31</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Chen, Lee, Chen, Li, How, Lin, Chiu, Wang, Kao, Huang, Chien and Chang.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Chen, Lee, Chen, Li, How, Lin, Chiu, Wang, Kao, Huang, Chien and Chang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background/Objective</title>
<p>Athletes have commonly reported hematuria, cylindruria, and proteinuria, which are consistent with &#x201c;athletic pseudonephritis.&#x201d; To date, little is known about the overall consequences of 100 km (62.5-mile) cross-country ultra-marathons on Asian male runners. This study aimed to examine (i) acute urinary changes in runners with athletic pseudonephritis following a 100 km cross-country ultra-marathon and (ii) whether this phenomenon is associated with the runners average running speed.</p>
</sec>
<sec>
<title>Methods</title>
<p>Twenty male Taiwanese ultra-marathoners were prospectively recruited. Urinary parameters were analyzed before and immediately after the 2020 Taiwania 100 K Ultra Trail. Competitors ran on a rugged forest path and the official cut-off time was 15 h.</p>
</sec>
<sec>
<title>Results</title>
<p>Participants showed a statistically significant post-race increase (p &#x3c; 0.001) in urinary red blood cell counts. No significant difference was noted in urinary cast in the immediate post-race values compared to the pre-race values (p &#x3d; 0.488). Urinary chemistry showed statistically significant increases in specific gravity (p &#x3c; 0.001), osmolality (p &#x3c; 0.001), creatinine (p &#x3d; 0.027), microalbumin (p &#x3c; 0.001), protein (p &#x3c; 0.001), and myoglobin (p &#x3c; 0.001) between the pre- and post-race values. Additionally, 10 (50%) post-race specimens had albumin-to-creatinine ratios &#x3e;30 mg/g, and 9 (45%) specimens showed protein-to-creatinine ratios &#x3e;0.2 mg/mg. The association between running speed and red blood cells in urine showed a p-value of 0.368. There were no correlations between running speed and changes in albumin-to-creatinine ratio (rs &#x3d; &#x2212;0.105, p &#x3d; 0.661), protein-to-creatinine ratio (rs &#x3d; &#x2212;0.013, p &#x3d; 0.957), or myoglobin (rs &#x3d; 0.003, p &#x3d; 0.99) levels.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Exercise-related hematuria and proteinuria were frequently observed in the Asian male cross-country ultra-marathoners. A faster running speed was not associated with the degree of exercise-induced hematuria, proteinuria or myoglobinuria.</p>
</sec>
</abstract>
<kwd-group>
<kwd>cross-country ultra-marathon</kwd>
<kwd>hematuria</kwd>
<kwd>myoglobinuria</kwd>
<kwd>athletic pseudonephritis</kwd>
<kwd>proteinuria</kwd>
<kwd>urine cast</kwd>
</kwd-group>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Exercise Physiology</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1">
<title>1 Introduction</title>
<p>Urinary changes in athletes have become a critical concern due to the increasing number of people engaging in exercise the past few decades (<xref ref-type="bibr" rid="B26">Scheer, 2019</xref>). The reported incidence of renal dysfunction during exercise varies widely, ranging from 11% to 100%, depending on the type and intensity of exercise and the athlete&#x2019;s hydration status (<xref ref-type="bibr" rid="B4">Bellinghieri et al., 2008</xref>). Among these changes, athletic pseudonephritis&#x2014;characterized by elevated urinary erythrocytes, casts, and protein&#x2014;is the most frequently observed renal dysfunction presentation (<xref ref-type="bibr" rid="B29">Van Biervliet et al., 2013</xref>). Given the well-established significance of hematuria and proteinuria as markers of urological and nephrological disorders, their evaluation is essential in cases of evident exercise-induced hematuria.</p>
<p>Prolonged strenuous exercise leads to a decrease in creatinine clearance, resulting in reduced urine flow. Several factors&#x2014;such as local vascular changes, local hypoxia, lactate accumulation, oxidative stress, hormonal changes, and a general septic reaction&#x2014;may influence glomerular membrane and tubular cells function in the kidneys during exercise (<xref ref-type="bibr" rid="B27">Shephard, 2016</xref>; <xref ref-type="bibr" rid="B32">Wo&#x142;yniec et al., 2020</xref>). These pathophysiological changes result in increased glomerular permeability and decreased renal tubule reabsorption of erythrocytes, casts, and protein (<xref ref-type="bibr" rid="B1">Abarbanel et al., 1990</xref>; <xref ref-type="bibr" rid="B11">Fan et al., 2020</xref>; <xref ref-type="bibr" rid="B12">Haugen et al., 1980</xref>). In addition, myoglobin, a heme-containing protein found in muscle tissues, can contribute to renal stress. During intense or prolonged exercise, the risk of exertional rhabdomyolysis increases due to excessive skeletal muscle breakdown, resulting in myoglobin in circulation and myoglobinuria when the renal threshold is crossed. The overflow of myoglobin can also contribute to proteinuria (<xref ref-type="bibr" rid="B17">Knochel, 1982</xref>; <xref ref-type="bibr" rid="B19">Milne, 1988</xref>; <xref ref-type="bibr" rid="B23">Rojas-Valverde et al., 2021</xref>).</p>
<p>Post-exercise hematuria and proteinuria are usually temporary and can be resolved within a few days without medical supports (<xref ref-type="bibr" rid="B13">Heathcote et al., 2009</xref>; <xref ref-type="bibr" rid="B24">Saeed et al., 2012</xref>; <xref ref-type="bibr" rid="B30">Varma et al., 2014</xref>). However, acute kidney injury (AKI) diagnosis criteria are met in approximately 16%&#x2013;50% of athletes participating in long-distance races, with endurance runners accounting for 97% of these cases (<xref ref-type="bibr" rid="B22">Rojas-Valverde et al., 2020</xref>; <xref ref-type="bibr" rid="B28">Tidmas et al., 2022</xref>). The cross-country ultra-marathon (CCUM), which exceeds the classical marathon distance of 42.195 km and takes place on open-air courses over natural terrain, has been growing in popularity. The greater intensity and longer duration of the race results in more evident pathologically and physiologically changes in the competitors&#x2019; organs and body systems.</p>
<p>Considering the increasing number of ultra-marathon participants, this observational study aimed to investigate the acute changes in the urinary erythrocytes, casts, and protein in Asian males after a 100 km CCUM race. The secondary aim was to evaluate whether post-exercise hematuria and proteinuria were associated with the participants&#x2019; average running speed of these finishers. We believe that these data could provide a practical reference for sports physicians and coaches to make decisions.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>2 Materials and methods</title>
<sec id="s2-1">
<title>2.1 Study design and population</title>
<p>Before conducting the observational study, ethical approval was obtained from the MacKay Memorial Hospital Institutional Review Board (20MMHIS114e). Registered runners of the 2020 Taiwania 100 K Ultra Trail were contacted by the study organizer informing them about the study purpose via phone call, 20 days before the race. Fifty competitors volunteered for the study and provided their signed consent before the race. Each of the participants were invited to fill in a questionnaire to provide basic information including their body height, previous marathon or ultra-marathon experience, training protocol for this competition, and their personal best marathon speed. Runners were excluded if they had a history of heart disease, renal dysfunction, seizure, or syncope of unknown origin. Although 36 participants completed the post-race urinary assessment and questionnaire, 15 were excluded from analysis as they failed to complete the race and their urine samples were not collected immediately upon withdrawal. Owing to the gender imbalance, one female finisher was also excluded. Ultimately, the final analysis included data from 20 experienced male Taiwanese ultra-marathoners (<xref ref-type="fig" rid="F1">Figure 1</xref>).</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>Flow chart of subject recruitment.</p>
</caption>
<graphic xlink:href="fphys-16-1608584-g001.tif">
<alt-text content-type="machine-generated">Flowchart detailing runner participation and race completion. Out of 125 competitors, 61.6% (77 runners) finished, and 38.4% (48 runners) did not. Fifty participants were recruited, with 36 completing post-race assessments. Of those, 58.3% (21 runners) finished the race, and 41.7% (15 runners) did not.</alt-text>
</graphic>
</fig>
<p>Body weight was measured before and immediately after the race. The competitors were asked to remove the back bag and water bottle that they carried when weighing. All competitors were free to drink any kind of fluid during the race. The mid-stream urine samples were collected before and immediately after the race. The official race records of this 100 K race were obtained to document each participant&#x2019;s performance.</p>
</sec>
<sec id="s2-2">
<title>2.2 Laboratory assessment</title>
<p>Urine samples were collected using the clean-catch midstream method to minimize contamination risk. Prior to collection, participants were instructed to cleanse the external genital area with sterile wipes. Urine was collected directly into sterile, clean, dry, and sealed urine tubes compatible with the analytical instruments used. To further reduce contamination, samples were transported to the laboratory within 2 h of collection and analyzed promptly. Samples were assigned non-identifiable codes and examiners were blinded to their origin.</p>
<p>Urinalysis was performed using the Siemens Clinitek Novus Analyzer (Siemens Healthcare, Erlangen, Germany), a fully automated system that integrates both urine chemistry and sediment analysis. The chemistry analyzer utilizes high-resolution digital imaging to interpret dipstick tests, providing semi-quantitative measurements for parameters including pH, red blood cell (RBC) counts, and specific gravity (SG). For sediment analysis, the system employs automated digital microscopy in combination with image recognition software to detect and classify urinary casts. When hematuria is suspected, the urine sample is centrifuged and examined microscopically to identify RBCs and other sediment components. A manual review by trained personnel is performed when results are flagged, ambiguous, or clinically significant, ensuring accurate interpretation and reporting. In accordance with the 2020 American Urological Association Guideline on Microhematuria, hematuria in this study was defined as &#x2265;3 RBCs per high-power field (HPF) in microscopic urine samples (<xref ref-type="bibr" rid="B3">Barocas et al., 2020</xref>).</p>
<p>Urinary osmolality was determined using the freezing point depression method using the Advanced Model 3,320 Micro-Osmometer (Advanced Instruments, Norwood, MA, United States). Urinary parameters including creatinine, microalbumin, myoglobin and protein were analyzed using the Beckman Coulter AU5800 Clinical Chemistry Analyzer (Beckman Coulter Inc., Brea CA, United States).</p>
</sec>
<sec id="s2-3">
<title>2.3 Track briefing and weather condition</title>
<p>The race was held on 19 September 2020, in one of the largest divine-tree gardens in Asia in Yilan, Taiwan (24&#xb0; 35&#x2032;N latitude and 121&#xb0; 26&#x2032;E longitude). The race was officially announced by the International Trail Running Association (ITRA) as a graded race. Competitors ran a total of 100 km on a rugged forest path, with an overall cut-off time of 15 h. The race was conducted on a sunny day with temperatures ranging between 15.4&#xb0;C and 32.8&#xb0;C. The relative humidity was between 62% and 100%, and the wind speed was between 0 m/s and 1.5 m/s, according to data provided by the Central Weather Bureau, Taiwan.</p>
</sec>
<sec id="s2-4">
<title>2.4 Statistical analysis</title>
<p>The Shapiro-Wilk test (p &#x3e; 0.05) and an inspection of the participants&#x2019; histograms, normal Q-Q plots, and box plots were used to test the normality of the data. Descriptive results are reported as median (interquartile range (IQR)). The Fisher exact probability test was applied for categorical data and dependent-samples t-test (or Wilcoxon Signed Ranks test, when appropriate) for numerical data to evaluate the physiological and biochemical association between pre- and post-race parameters. Multiple comparisons were controlled using the Bonferroni correction. The Kruskal&#x2013;Wallis test was applied for evaluating the association between running speed and urine RBCs/HPF. The Spearman&#x2019;s rank correlation coefficient was used to evaluate the association between running speed and delta changes (i.e., post-race value - pre-race value) in body weights and urinary biochemistry. A commercially available statistical software (SPSS version 21.0, IBM Corp., Armonk, NY, United States) was used for statistical analysis. Differences were statistically significant when the two-tailed p-value was &#x3c;0.05.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>3 Results</title>
<sec id="s3-1">
<title>3.1 Race details and runner demographics</title>
<p>A total of 125 runners participated in this race. The median age of the runners was 46.5 years (IQR, 12 years). Furthermore, 110/125 (88%) runners were male, 77 (61.6%) finished the race, and 71 of the 77 finishers (92.2%) were male. The average finishing time was 13.6 h (range, 10&#x2013;14.9 h). Only 50 (40%) competitors volunteered to participate in this study and completed the pre-race urinary assessment and questionnaire. Of these, 36 participants (33 males and 3 females) completed the post-race urinary assessment and questionnaire, and of these 21 (20 males and 1 female) finished the race (<xref ref-type="fig" rid="F1">Figure 1</xref>). The characteristics of the included 20 male finishers are summarized in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Demographic data and outcome measurement of participants (n &#x3d; 20).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="left">Variable</th>
<th align="center">Median (IQR)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Age (years)</td>
<td align="center">46.5 (12)</td>
</tr>
<tr>
<td align="left">Pre-race BW (kg)</td>
<td align="center">69.9 (5.3)</td>
</tr>
<tr>
<td align="left">Height (m)</td>
<td align="center">172 (7)</td>
</tr>
<tr>
<td align="left">Body mass index (kg/m<sup>2</sup>)</td>
<td align="center">23.7 (2.1)</td>
</tr>
<tr>
<td align="left">Years of running marathon</td>
<td align="center">7 (5.8)</td>
</tr>
<tr>
<td align="left">Years of running ultra-marathon</td>
<td align="center">5 (6)</td>
</tr>
<tr>
<td colspan="2" align="left">Training protocol (/week)</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3c;40 km</td>
<td align="center">1</td>
</tr>
<tr>
<td align="left">&#x2003;40&#x2013;100 km</td>
<td align="center">10</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;100 km</td>
<td align="center">9</td>
</tr>
<tr>
<td align="left">Best marathon time (min)</td>
<td align="center">209.5 (34)</td>
</tr>
<tr>
<td align="left">Average running speed in this race (km/hr)</td>
<td align="center">7.09 (0.62)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>IQR, interquartile range; BW, body weight. Kg &#x3d; kilogram; m &#x3d; meter; min &#x3d; minute; hr &#x3d; hour.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-2">
<title>3.2 Analysis of urinary parameters</title>
<p>Urinalysis of the finishers&#x2019;s specimens were measured at two time points: before the race and immediately after the race. Comparison of the urine specimens&#x2019; RBCs and casts are shown in <xref ref-type="table" rid="T2">Table 2</xref>. No RBC counts above the reference interval (&#x2265;3 cells/HPF) were observed in the 20 participants pre-race. Post-race, twelve (60%) finishers presented with hematuria (RBC counts &#x2265;3 cells/HPF). The difference between pre- and post-race urine RBC was statistically significant (p &#x3c; 0.001). Regarding urine cast, 2 (10%) finishers presented with hyaline cast &#x3e;5 cells per low-power field (LPF) after the run. There was no significant difference in the immediate post-race values compared to the pre-race values (p &#x3d; 0.488). <xref ref-type="fig" rid="F2">Figure 2</xref> illustrates the pre- and post-race urinalyses results, demonstrating the microscopic images of urine casts observed in the samples.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Red blood cells (RBCs) and hyaline casts in urine (n &#x3d; 20).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th align="center">Parameter</th>
<th align="center">Pre-race</th>
<th align="center">Post-race</th>
<th align="center">p value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td colspan="4" align="center">RBCs/HPF</td>
</tr>
<tr>
<td align="center">0&#x2013;2</td>
<td align="center">20</td>
<td align="center">8</td>
<td rowspan="4" align="center">
<bold>&#x3c;0.001</bold>
</td>
</tr>
<tr>
<td align="center">3&#x2013;50</td>
<td align="center">0</td>
<td align="center">4</td>
</tr>
<tr>
<td align="center">51&#x2013;100</td>
<td align="center">0</td>
<td align="center">4</td>
</tr>
<tr>
<td align="center">&#x3e;100</td>
<td align="center">0</td>
<td align="center">4</td>
</tr>
<tr>
<td colspan="4" align="center">Hyaline Casts/LPF</td>
</tr>
<tr>
<td align="center">0&#x2013;5</td>
<td align="center">20</td>
<td align="center">18</td>
<td rowspan="4" align="center">0.488</td>
</tr>
<tr>
<td align="center">6&#x2013;10</td>
<td align="center">0</td>
<td align="center">1</td>
</tr>
<tr>
<td align="center">11&#x2013;25</td>
<td align="center">0</td>
<td align="center">0</td>
</tr>
<tr>
<td align="center">&#x3e;25</td>
<td align="center">0</td>
<td align="center">1</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Pre- and post-race urinalyses with microscopic photographs of urine casts observed following the 100 km cross-country ultra-marathon. <bold>(A)</bold> Hyaline cast observed at a count of 0&#x2013;5 per low-power field (LPF) (green circle); <bold>(B)</bold> Hyaline casts increased to 5&#x2013;10 per LPF (green circle); <bold>(C)</bold> Numerous hyaline casts observed at &#x3e;25 per LPF, along with granular casts at 2&#x2013;5 per LPF (red circle).</p>
</caption>
<graphic xlink:href="fphys-16-1608584-g002.tif">
<alt-text content-type="machine-generated">Three panels labeled A, B, and C show urine samples and microscopic images. Each panel has pre-race and post-race urine samples in test tubes. Microscopic views reveal variations in sediment or particles pre- and post-race. Panel A shows minimal particles, B shows moderate particles, and C shows a significant increase in particles, especially post-race.</alt-text>
</graphic>
</fig>
<p>Urine chemistry of these finishers&#x2019; specimens were also measured at the two time points: before the race and immediately after the race. The exact measurement values are listed in <xref ref-type="table" rid="T3">Table 3</xref>. An increase in SG, osmolality, creatinine, microalbumin, albumin-to-creatinine ratio (ACR), protein, protein-to-creatinine ratio (PCR), and myoglobin showed significant differences (p &#x3c; 0.05) in the immediate post-race values compared to the pre-race values. After the run, 10 (50%) finishers presented ACR values greater than 30 mg/g. In addition, 9 (45%) finishers exhibited PCR values greater than 0.2 mg/mg in post-race specimens.</p>
<table-wrap id="T3" position="float">
<label>TABLE 3</label>
<caption>
<p>Urine chemistries before and after the ultra-marathon (n &#x3d; 20).</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Parameter</th>
<th colspan="4" align="center">Median (IQR)</th>
</tr>
<tr>
<th align="center">Pre-race</th>
<th align="center">Post-race</th>
<th align="center">p-value</th>
<th align="center">Effect size</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">PH</td>
<td align="center">6 (0.9)</td>
<td align="center">5.5 (1.4)</td>
<td align="center">1</td>
<td align="center">&#x2212;0.10</td>
</tr>
<tr>
<td align="left">Specific Gravity<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
<td align="center">1.02 (0.006)</td>
<td align="center">1.028 (0.01)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>1.33</bold>
</td>
</tr>
<tr>
<td align="left">Osmolality (mOsm/kg)<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
<td align="center">706 (284)</td>
<td align="center">932.5 (206)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>1.40</bold>
</td>
</tr>
<tr>
<td align="left">Creatinine (mg/dL)<xref ref-type="table-fn" rid="Tfn1">
<sup>a</sup>
</xref>
</td>
<td align="center">119.2 (54.1)</td>
<td align="center">160.1 (96)</td>
<td align="center">
<bold>0.027</bold>
</td>
<td align="center">
<bold>0.90</bold>
</td>
</tr>
<tr>
<td align="left">Microalbumin (mg/dL)</td>
<td align="center">0 (0.9)</td>
<td align="center">6.3 (21.7)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>0.59</bold>
</td>
</tr>
<tr>
<td align="left">ACR (mg/g)</td>
<td align="center">0 (5.8)</td>
<td align="center">31.8 (98.2)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>0.6</bold>
</td>
</tr>
<tr>
<td align="left">Protein (mg/dL)</td>
<td align="center">8.5 (6)</td>
<td align="center">32 (57)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>0.61</bold>
</td>
</tr>
<tr>
<td align="left">PCR (mg/g)</td>
<td align="center">72 (29)</td>
<td align="center">189.5 (216)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>0.61</bold>
</td>
</tr>
<tr>
<td align="left">Myoglobin (ng/mL)</td>
<td align="center">0 (0)</td>
<td align="center">16 (50.9)</td>
<td align="center">
<bold>&#x3c;0.001</bold>
</td>
<td align="center">
<bold>0.57</bold>
</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>vs &#x3d; versus; IQR, interquartile range; mg/dL &#x3d; milligrams per deciliter.</p>
</fn>
<fn>
<p>ACR, albumin to creatinine ratio; mg/g &#x3d; milligrams per Gram.</p>
</fn>
<fn>
<p>PCR, protein to creatinine ratio; ng/mL &#x3d; nanograms per milliliter.</p>
</fn>
<fn id="Tfn1">
<label>
<sup>a</sup>
</label>
<p>It follows normal distribution; p-values were obtained from parametric methods.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3-3">
<title>3.3 Correlation analyses between running speed and urinary parameters</title>
<p>The association between running speed and urine RBCs/HPF in immediately following species are shown in <xref ref-type="fig" rid="F3">Figure 3A</xref>. The significance was 0.368. No correlations were observed between running speed and changes in body weights (rs &#x3d; &#x2212;0.229 [&#x2212;0.609&#x2013;0.237], p &#x3d; 0.346), and the ACR (rs &#x3d; &#x2212;0.105 [&#x2212;0.523&#x2013;0.353], p &#x3d; 0.661), PCR (rs &#x3d; &#x2212;0.013 [&#x2212;0.541&#x2013;0.331], p &#x3d; 0.957), or myoglobin (rs &#x3d; 0.003 [&#x2212;0.418&#x2013;0.466], p &#x3d; 0.99) levels. The correlation between running speed with delta changes in body weights and urinary biochemistry is shown graphically in <xref ref-type="fig" rid="F3">Figures 3B&#x2013;E</xref> with ranked variables.</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Correlation between running speed and measured parameters following the 100 km cross-country ultra-marathon. <bold>(A)</bold> Box plot for comparing the running speed across various categories of urine red blood cells; <bold>(B)</bold> Ranked running speed versus ranked delta changes in body weight; <bold>(C)</bold> Ranked running speed versus ranked delta changes in albumin-to-creatinine ratio; <bold>(D)</bold> Ranked running speed versus ranked delta changes in protein-to-creatinine ratio; and <bold>(E)</bold> Ranked running speed versus ranked delta changes in myoglobin. rs &#x3d; Spearman rank correlation coefficient.</p>
</caption>
<graphic xlink:href="fphys-16-1608584-g003.tif">
<alt-text content-type="machine-generated">Image with five panels displaying different data visualizations: Panel A shows a box plot of running speed in kilometers per hour against red blood cells per high-power field, with categories 0-2, 3-50, 51-100, and greater than 100. Panels B, C, D, and E display scatter plots with fitted lines depicting associations between ranked running speed and various physiological measures: body weight, albumin-to-creatinine ratio, protein-to-creatinine ratio, and myoglobin. Each scatter plot includes correlation coefficient (rs) and p-values, indicating low to no significant correlations.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>4 Discussion</title>
<p>Exercise-induced hematuria is common among individuals who participate in a variety of sport categories. Although self-limiting, the repeated erythrocytes loss through the urine can be a contributing factor to the anemia (<xref ref-type="bibr" rid="B1">Abarbanel et al., 1990</xref>; <xref ref-type="bibr" rid="B9">Dang, 2001</xref>). The incidence of hematuria in ultra-marathoners following 90&#x2013;100 km races are reported to range from 12% to 54%, with studies indicating that it typically resolves within a few hours to 7 days (<xref ref-type="bibr" rid="B2">Alvarez et al., 1987</xref>; <xref ref-type="bibr" rid="B8">Chiu et al., 2015</xref>; <xref ref-type="bibr" rid="B14">Kallmeyer and Miller, 1993</xref>; <xref ref-type="bibr" rid="B30">Varma et al., 2014</xref>). The 60% incidence of hematuria in finishers included in the present study differs from the 24.4% reported in Kallmeyer&#x2019;s recruits (<xref ref-type="bibr" rid="B14">Kallmeyer and Miller, 1993</xref>), but it is similar to the 53.8% observed by Alvarez (<xref ref-type="bibr" rid="B2">Alvarez et al., 1987</xref>). Exercise-induced hematuria is influenced by both the duration and intensity of exercise (<xref ref-type="bibr" rid="B4">Bellinghieri et al., 2008</xref>; <xref ref-type="bibr" rid="B18">McInnis et al., 1998</xref>). However, no association between running speed and hematuria was observed in the present study.</p>
<p>As for cylindruria, hyaline casts can be found in normal cases of paraphysiological conditions such as after strenuous exercise, and in non-renal disorders such as dehydration. During intense physical activity, renal blood flow can decrease markedly&#x2014;from approximately 1,000 mL/min at rest to as low as 200 mL/min (<xref ref-type="bibr" rid="B4">Bellinghieri et al., 2008</xref>). In addition, a reduction in urine output below 25 mL/h was associated with a significant increase in urinary casts (<xref ref-type="bibr" rid="B12">Haugen et al., 1980</xref>). Notably, 2/20 (10%) finishers presented hyaline casts after the race. One of the finishers who exhibited hyaline casts &#x3e;25/LPF also exhibited granular casts. The presence of granular casts is commonly associated with renal tubular damage (<xref ref-type="bibr" rid="B6">Caleffi and Lippi, 2015</xref>; <xref ref-type="bibr" rid="B7">Chawla et al., 2008</xref>). Taken together, these results might imply that acute adverse effects on glomerular function occur in response to long-distance running.</p>
<p>Morteza-Khodaee&#x2019;s study showed that 30% of runners had proteinuria (&#x2265;1&#x2b;) after completing a 161-km ultra-marathon (<xref ref-type="bibr" rid="B16">Khodaee et al., 2021</xref>). In the present study, 45% of the included finishers exhibited proteinuria (spot urine PCR &#x3e;0.2 mg/mg), based on the most reported cutoff for detecting proteinuria (<xref ref-type="bibr" rid="B15">Kami&#x144;ska et al., 2020</xref>). Albuminuria is an early and sensitive marker of kidney risk (<xref ref-type="bibr" rid="B10">de Zeeuw, 2004</xref>) and albumin is the main protein lost during exercise (<xref ref-type="bibr" rid="B13">Heathcote et al., 2009</xref>; <xref ref-type="bibr" rid="B20">Poortmans et al., 1989</xref>). After running, albuminuria can reach a 10 to 25-fold increase in healthy individuals (<xref ref-type="bibr" rid="B21">Poortmans et al., 1997</xref>; <xref ref-type="bibr" rid="B20">Poortmans et al., 1989</xref>). Wo&#x142;yniec and colleagues have reported that ACR increased from 5.37 to 49.64 mg/g after a 100 km ultra-marathon (<xref ref-type="bibr" rid="B32">Wo&#x142;yniec et al., 2020</xref>). The ACR of the finishers included in the present study increased from 0 to 31.8 mg/g after the 100 km cross-country run. This data, although far from conclusive, provides additional insights into urine ACR and PCR&#x2014;important biomarkers of kidney damage&#x2014;in long-distance running sports.</p>
<p>In the literature discussing during very long runs, the post-exercise proteinuria is said to be related to the duration but not the intensity of exercise (<xref ref-type="bibr" rid="B32">Wo&#x142;yniec et al., 2020</xref>). The data of the present study showed no correlation between running speed and the degree of proteinuria and myoglobinuria. Notably, 13 (65%) of the finishers observed in the present study presented with urinary myoglobin levels above 5 ng/mL after the run. The wide variability in post-race myoglobin levels suggests inter-individual differences that may be influenced by factors such as hydration status, muscle mass, or baseline conditioning. However, myoglobinuria may be asymptomatic, transient, and reversible, and visible myoglobinuria (tea colored or brown colored urine) only occurs when urinary myoglobin exceeds 250 &#x3bc;g/mL (<xref ref-type="bibr" rid="B25">Scalco et al., 2016</xref>; <xref ref-type="bibr" rid="B31">Warren et al., 2002</xref>). Ultra-marathoners frequently compete in endurance events, where repeated myoglobin overflow may contribute to renal injury through renal vasoconstriction, proximal tubular necrosis, and distal tubular obstruction (<xref ref-type="bibr" rid="B5">Bosch et al., 2009</xref>).</p>
<p>As measurements during CCUMs are challenging, the time course of urinary data during ultra-endurance is limited. The strength of our study is that it presents acute urinary changes among finishers of a 100 km CCUM event. The present study has some limitations. First, the small sample size resulted in decreased power to detect significant post-race changes in the evaluated parameters. As CCUM is an extreme sport, it is difficult to enroll many individuals. Second, only male runners were included in the final analysis, which may account for sex differences in the urine data. Therefore, the data presented might not be representative of potential urinary parameter changes in female runners. Third, follow-up urinary tests on participants beyond the immediately post-race period were not performed. Hence, future studies measuring the long-term effects of CCUM races are necessary.</p>
<p>To date, no prior literature has explored acute urinary changes of athletic pseudonephritis in Asian ultra-marathoners during a CCUM. Although our study focuses on immediate post-race changes, it highlights important questions about the potential long-term consequences of repeated episodes of exertional hematuria and proteinuria. Incorporating longitudinal studies and post-race follow-ups would position this work within a broader clinical and research context. Such future investigations could shed light on whether these acute urinary changes fully resolve or contribute to cumulative renal stress over time. We anticipate that further data on ultra-marathons could provide additional insights into this issue.</p>
<sec id="s4-1">
<title>4.1 Conclusion</title>
<p>Athletic pseudonephritis was observed in participants after a 100 km CCUM. The development of exercise-related hematuria and proteinuria was frequently observed among these runners. A faster average running speed had no significant effect on exercise-induced hematuria, proteinuria or myoglobinuria in the included finishers. These results are potentially relevant to coaches, athletic trainers, and race organizers, who might apply them to hydration planning, post-race screening, or athlete education.</p>
</sec>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s5">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="ethics-statement" id="s6">
<title>Ethics statement</title>
<p>The studies involving humans were approved by MacKay Memorial Hospital Institutional Review Board. 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 sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>K-HC: Writing &#x2013; original draft, Writing &#x2013; review and editing, Data curation. C-HL: Data curation, Writing &#x2013; original draft. P-YC: Formal Analysis, Writing &#x2013; review and editing. L-HL: Writing &#x2013; review and editing, Formal Analysis. C-KH: Writing &#x2013; review and editing. Y-KL: Formal Analysis, Writing &#x2013; review and editing. Y-HC: Methodology, Conceptualization, Writing &#x2013; original draft, Data curation, Formal Analysis, Writing &#x2013; review and editing, Funding acquisition. F-LW: Writing &#x2013; review and editing. W-FK: Writing &#x2013; review and editing, Data curation, Supervision. M-KH: Writing &#x2013; review and editing. D-KC: Supervision, Writing &#x2013; review and editing. W-HC: Writing &#x2013; review and editing, Supervision.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was supported by MacKay Memorial Hospital, Taiwan (MMH10997/114131).</p>
</sec>
<ack>
<p>We thank all the CCUM runners who participated in this study and all the doctors, and nurses who provided professional care at this CCUM race. We also express gratitude to the Chinese Taipei Association of Ultra Runners, all of which assisted at the CCUM event.</p>
</ack>
<sec sec-type="COI-statement" id="s9">
<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 sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="s11">
<title>Publisher&#x2019;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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