{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T06:04:29Z","timestamp":1789452269584,"version":"build-2803163510"},"reference-count":31,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Pediatr."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      To characterize non-linear associations between inflammatory biomarkers and\n                      <jats:italic>Mycoplasma pneumoniae<\/jats:italic>\n                      \u2013associated necrotizing pneumonia (MPNP) in children using restricted cubic spline (RCS) analysis, and to develop a predictive nomogram.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We retrospectively analyzed 319 children hospitalized for\n                      <jats:italic>Mycoplasma pneumoniae<\/jats:italic>\n                      pneumonia (MPP) at Tianjin Children's Hospital (2020\u20132025), comprising an MPNP group (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009146) and\n                      <jats:italic>Mycoplasma pneumoniae<\/jats:italic>\n                      non-necrotizing pneumonia (MPNNP) group (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009173). MPNP was defined on contrast-enhanced chest CT according to established pediatric criteria. Thirty-three pre-treatment variables were extracted. Candidate predictors were screened by least absolute shrinkage and selection operator (LASSO) logistic regression with 10-fold cross-validation. RCS analysis with non-linearity testing was applied to evaluate dose\u2013response relationships, and a multivariable logistic regression nomogram was constructed. Model performance was assessed by ROC analysis, calibration plots, and decision curve analysis (DCA), with internal validation using 1,000 bootstrap resamples.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      LASSO regression identified three independent predictors: white blood cell (WBC) count, C-reactive protein (CRP), and fever duration. RCS analysis revealed a significant non-linear, threshold-like association for WBC (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&amp;lt;\u20090.001;\n                      <jats:italic>P<\/jats:italic>\n                      -non-linearity\u2009=\u20090.014) and a significant non-linear, inverted U-shaped association for CRP (\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&amp;lt;\u20090.001;\n                      <jats:italic>P<\/jats:italic>\n                      -non-linearity &amp;lt; 0.001), with risk peaking at intermediate concentrations and attenuating at very high levels, whereas fever duration showed an approximately linear positive relationship. The nomogram demonstrated strong discrimination in internal validation, with an apparent AUC of 0.941 (95% CI, 0.908\u20130.975) and a bootstrap bias-corrected AUC of 0.920 (95% CI, 0.877\u20130.962). Calibration curves closely approximated the 45\u00b0 reference line, and DCA confirmed net clinical benefit across a broad range of threshold probabilities.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>WBC count, CRP, and fever duration independently predict MPNP, with WBC and CRP exhibiting distinct non-linear dose\u2013response patterns. The RCS-based nomogram integrating these readily available predictors shows promising predictive performance, though external validation is required before clinical implementation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fped.2026.1915170","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T05:33:48Z","timestamp":1789450428000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Non-linear associations between inflammatory biomarkers and Mycoplasma pneumoniae\u2013associated necrotizing pneumonia in children: a restricted cubic spline analysis and nomogram development"],"prefix":"10.3389","volume":"14","author":[{"given":"Jiafeng","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Pediatric Respiratory Medicine, Children\u2019s Hospital, Tianjin University\/Tianjin Children\u2019s Hospital","place":["Tianjin, 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China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongsheng","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Pediatric Respiratory Medicine, Children\u2019s Hospital, Tianjin University\/Tianjin Children\u2019s Hospital","place":["Tianjin, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1128\/CMR.00114-16","article-title":"Mycoplasma pneumoniae from the respiratory tract and beyond","volume":"30","author":"Waites","year":"2017","journal-title":"Clin Microbiol Rev"},{"key":"B2","doi-asserted-by":"publisher","first-page":"23","DOI":"10.4103\/ijmr.IJMR_1582_16","article-title":"Mycoplasma pneumoniae: a significant but underrated pathogen in paediatric community-acquired lower respiratory tract infections","volume":"147","author":"Kumar","year":"2018","journal-title":"Indian J Med 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