The Lancet Diabetes and Endocrinology Commission, in its 2025 report, proposed a fundamental reframing of obesity. Rather than treating a high BMI as a diagnosis in itself, the Commission distinguished between clinical obesity, in which excess body fat is accompanied by measurable organ dysfunction or limitations in daily activities, and preclinical obesity, in which excess fat has not yet caused observable harm. The distinction matters because BMI is an imperfect proxy: it overestimates adiposity in muscular individuals and underestimates it in people with central fat accumulation but normal weight. By requiring evidence of organ dysfunction, the new framework aims to identify people whose excess fat is actively damaging their health.

Applying this framework at population scale required an unprecedented collaborative effort. No single cohort had collected all the anthropometric measures, body composition data, and clinical and laboratory markers the Commission’s criteria demand. So the research consortium, known as ECOS, integrated cross-sectional data from 11 population-based cohorts in Australia, Canada, Estonia, Finland, the Netherlands, the United Kingdom, and the United States, covering 44 assessment waves collected between 1996 and 2023. In total, 786,557 participants aged four and above were classified, making this the largest clinical obesity prevalence study conducted to date.

The results reveal a striking age-dependent divergence between BMI-defined and clinical obesity. In early childhood, clinical obesity affected just 3.7 percent of children aged four to five, well below the 8.8 percent prevalence of BMI-defined obesity in the same group. Throughout childhood, adolescence, and early and mid-adulthood, BMI-defined obesity consistently overestimated the burden of clinically significant disease. At ages 35 to 44, for example, 26.3 percent of participants met BMI criteria for obesity, but only 15.1 percent met the Commission’s criteria for clinical obesity. Then the pattern inverts: from age 55 onward, clinical obesity becomes more common than BMI-defined obesity, climbing to 52.0 percent among adults aged 65 to 74.

The organ dysfunction criteria driving these classifications varied systematically with age. Among children with clinical obesity, elevated systolic blood pressure was overwhelmingly the most common finding, present in 87.3 percent of affected four- to nine-year-olds. Renal dysfunction, detected through microalbuminuria, was also most prevalent in childhood, affecting 44.2 percent of young children with clinical obesity. In early and mid-adulthood, liver dysfunction took center stage, with elevated alanine aminotransferase found in 56.3 percent of affected adults aged 20 to 34 and elevated gamma-glutamyl transferase in 48.8 percent of those aged 35 to 54. In later life, musculoskeletal dysfunction dominated, affecting 55.1 percent of people aged 75 and older with clinical obesity.

Sex emerged as a powerful modifier of these patterns. From adolescence through mid-adulthood, males carried a higher prevalence of clinical obesity than females; at ages 35 to 44, 18.6 percent of men versus 13.9 percent of women met the criteria. But from age 55 onward the relationship reversed, with women showing markedly higher prevalence. At ages 65 to 74, 57.1 percent of women had clinical obesity compared with 44.1 percent of men, and female prevalence peaked at 58.5 percent at ages 75 to 84. Preclinical obesity followed a different trajectory: in women it rose through early adulthood, peaked in the mid-thirties to mid-forties, and then declined, whereas in men it remained relatively constant across the life course. The authors suggest these divergences may partly reflect survival bias and differences in how excess adiposity manifests between the sexes, though the underlying biology remains to be fully explored.

Socioeconomic position, measured through education level, showed a more modest influence. Across all age groups, clinical obesity prevalence was slightly lower among people with high education compared with those in the middle and low education categories; at ages 65 to 74, prevalence was 46.8 percent in the high education group versus 53.9 and 55.0 percent in the middle and low groups respectively. The age-dependent patterns of both clinical and preclinical obesity were broadly similar across all three education strata, suggesting that while education shapes obesity risk, the relationship between excess fat and organ dysfunction follows a comparable life course architecture regardless of socioeconomic background.

The study also exposed how sensitive prevalence estimates are to the specific measures chosen to define excess adiposity. In a subgroup of cohorts with complete anthropometric and body composition data, waist-to-height ratio was met by virtually all participants classified with clinical or preclinical obesity, between 95.4 and 100 percent depending on the cohort, while body fat percentage was the least commonly satisfied criterion, met by as few as 9.6 percent of UK Biobank participants with clinical obesity. When excess adiposity was defined by any two anthropometric criteria, clinical obesity prevalence in adults ranged from 5.2 percent at ages 20 to 24 to 51.2 percent at ages 65 to 74, substantially higher than estimates based on BMI plus one anthropometric measure or body fat percentage alone. These differences carry real consequences for diagnosis, risk prediction, and treatment eligibility.

The authors are candid about the limitations inherent in retrofitting a new diagnostic framework onto data collected before it existed. No cohort captured all 13 diagnostic domains specified by the Commission, meaning clinical obesity prevalence was likely underestimated in some groups. Data on central nervous system, respiratory, lymphatic, and reproductive criteria were sparse or absent, and the researchers could not always verify that observed organ dysfunction was genuinely attributable to excess adiposity rather than to other common conditions of later life. Laboratory thresholds varied across jurisdictions, and the treatment of medicated conditions, such as hypertension controlled by antihypertensive drugs, required pragmatic decisions that the Commission’s guidelines do not address. The cohorts were also predominantly from high-income, majority-White populations, limiting generalizability to more diverse settings where the burden of obesity is growing fastest.

Despite these caveats, the consistency of the life course pattern across cohorts from different countries, recruitment epochs, and measurement protocols lends weight to the central conclusion: clinical obesity is rarer than BMI-defined obesity in childhood and early adulthood, but substantially more common in later life. The findings underscore an urgent need for prospective longitudinal studies with standardized collection of all diagnostic criteria, which would allow researchers to track how individuals transition from preclinical to clinical obesity and to determine whether early identification and intervention in childhood, a critical window for prevention, can alter that trajectory. For now, the study provides the most comprehensive picture yet of what the new definition of obesity means for real populations, and it suggests that the number on the scale, and even the ratio of weight to height, may be far less informative than the quiet damage that excess fat does to organs over decades of exposure.

Subject of Research: Life course prevalence of clinical and preclinical obesity using the Lancet Commission diagnostic criteria

Article Title: The lancet commission definition of clinical obesity: a multi-cohort cross-sectional analysis from early childhood to older age in seven high-income countries

Article References: Longmore, D. K., MacKechnie, G. P., Huntington, P. A., Chen, Z. H., de Groot, J., Mikkonen, S., Mykkänen, J., Pätsi, S., Puusepp, T., Fischer, K., Jaddoe, V., Kerr, J. A., Lakka, T. A., Lehtimäki, T., Miliku, K., Nedelec, R., Ponsonby, A.-L., Sebert, S., Vuillermin, P., … Viikari, J. (2026). The lancet commission definition of clinical obesity: a multi-cohort cross-sectional analysis from early childhood to older age in seven high-income countries. eClinicalMedicine, Article 104231. https://doi.org/10.1016/j.eclinm.2026.104231

Image Credits: AI Generated

DOI: 10.1016/j.eclinm.2026.104231

Keywords: clinical obesity, preclinical obesity, Lancet Commission, body mass index, organ dysfunction, life course epidemiology, adiposity, pediatric obesity, cohort study, prevalence, metabolic health, public health

Adipokines have long been the province of metabolic research rather than emergency medicine. These molecules, secreted by white adipose tissue, act as chemical messengers that influence appetite, insulin sensitivity, and immune activity throughout the body. Among the most studied are adiponectin, which generally exerts anti-inflammatory and protective effects on blood vessels and kidneys, and resistin, which in humans is produced largely by immune cells and is strongly associated with inflammatory activation. Leptin and retinol-binding protein 4 round out the panel, each carrying its own metabolic and immunological signatures. What has remained unclear is how this hormonal ensemble behaves in the acute chaos of major trauma, and whether its behavior carries any clinical meaning for patients fighting for their lives in intensive care.

To find out, the Ulm team, led by Lena Schütte and Rebecca Halbgebauer, conducted a secondary retrospective analysis of a longitudinal observational cohort, drawing on prospectively collected plasma samples and clinical data from 67 patients with an Injury Severity Score of at least 16, a threshold defining severe polytrauma. They compared these patients with 31 healthy volunteers. Blood was drawn at four time points: on admission to hospital, and then on days one, five, and ten. At each point, the researchers measured circulating levels of resistin, adiponectin, leptin, and retinol-binding protein 4, alongside a battery of inflammatory markers and clinical indicators of organ function.

The statistical approach was deliberately rigorous. Because adipokine levels are known to vary with body composition, age, and sex, the team used linear mixed-effects models adjusted for age, sex, body mass index, and waist-to-hip ratio, the latter derived from computed tomography scans as a measure of body-fat distribution. Associations with inflammatory markers and organ dysfunction were assessed using partial Spearman correlations, and the researchers applied false discovery rate correction to guard against spurious findings that arise when many comparisons are made simultaneously. Exploratory receiver-operating characteristic analyses were then used to ask whether adipokine measurements could classify clinically meaningful outcomes, including length of hospital stay, length of intensive care stay, shock severity, and 30-day mortality.

The results were striking from the very first blood draw. Compared with healthy volunteers, trauma patients arrived at the hospital with a fundamentally altered adipokine profile: resistin was significantly elevated, while adiponectin was significantly reduced. This reciprocal shift, an increase in a pro-inflammatory signal paired with a decrease in a protective one, suggests that severe injury rapidly reprograms the endocrine output of fat tissue and the immune cells that produce these hormones. The changes were not subtle statistical whispers but robust differences detectable at admission, before most clinical interventions had time to exert their own effects on the circulating hormone landscape.

Perhaps the most compelling finding was the strength of the relationship between resistin and interleukin-6, one of the central cytokines driving the post-traumatic inflammatory response. At admission, resistin levels correlated with IL-6 at approximately 0.75, a correlation strong enough to survive false discovery rate correction. In biological terms, this means that patients whose blood carried the highest resistin concentrations were also mounting the most intense inflammatory responses. Resistin, in this context, appears less as a bystander and more as a potential readout of the immune system’s overall state of activation in the hours following injury.

When the researchers combined the two opposing signals into a single metric, the resistin-to-adiponectin ratio, they found the most consistent pattern of associations across the entire study. This ratio tracked with both inflammatory parameters and markers of renal dysfunction, including measures of kidney function such as estimated glomerular filtration. The kidney connection is particularly intriguing, because adiponectin has well-documented protective effects on renal tissue, and acute kidney injury is one of the most common and dangerous complications of severe trauma. A falling adiponectin level paired with rising resistin may therefore reflect, or even contribute to, the vulnerability of the kidneys during the critical early days after injury.

The exploratory outcome analyses offered cautious grounds for optimism, tempered by important limitations. Several adipokine measures showed moderate ability to classify selected clinical outcomes, such as length of hospital or intensive care stay and shock severity, in receiver-operating characteristic analyses. However, the mortality analyses were hampered by the small number of death events available at the later time points, making any conclusion about predicting survival statistically fragile. The authors are explicit that these outcome associations are exploratory and require prospective, multicenter validation before any claim of added clinical value beyond conventional parameters, such as the Sequential Organ Failure Assessment score, can be made.

One of the study’s secondary questions concerned whether body-fat distribution shapes the adipokine response to trauma. Using CT-derived waist-to-hip ratios, the researchers stratified patients and looked for differences in hormone profiles. For the most part, the stratified comparisons showed no clear separation across groups, suggesting that the dramatic adipokine shifts triggered by severe injury may override the more gradual influence of body composition, at least within the first ten days. This is a useful negative finding, because it implies that the trauma-induced adipokine signature could potentially serve as a standardized marker across patients of varying body types, though the authors note that most WHR-stratified differences were limited.

The broader significance of this work lies in its reframing of fat tissue as an active participant in the response to injury rather than a passive energy depot. The concept of immunometabolism, the interplay between immune signaling and metabolic regulation, has gained momentum across critical care research, and this study provides some of the most detailed longitudinal human data on adipokines in polytrauma to date. If future multicenter studies confirm that the resistin-to-adiponectin ratio adds predictive power for organ dysfunction beyond existing clinical scores, it could eventually help clinicians identify, within hours of admission, which patients are most likely to develop kidney injury or multi-organ dysfunction, opening a window for earlier and more targeted interventions. For now, the message is one of careful promise: the body’s fat-derived hormones respond to trauma with remarkable speed and specificity, and their story is only beginning to be told.

Subject of Research: Adipokine dynamics and their association with inflammation and acute organ dysfunction after severe polytrauma

Article Title: Inflammation-linked adipokine profiles associate with acute organ dysfunction after severe trauma

Article References: Schütte, L., Oßwald, K., Mannes, M., Wohlgemuth, L., Kumral, E., Mayer, B., Bülow, J. M., Bergmann, C. B., Relja, B., Gebhard, F., Huber-Lang, M., Fischer-Posovszky, P., Rayatdoost, F., & Halbgebauer, R. (2026). Inflammation-linked adipokine profiles associate with acute organ dysfunction after severe trauma. Journal of Translational Medicine, 24(1), Article 1176. https://doi.org/10.1186/s12967-026-08968-4

Image Credits: AI Generated

DOI: 10.1186/s12967-026-08968-4

Keywords: adipokines, polytrauma, resistin, adiponectin, inflammation, organ dysfunction, acute kidney injury, interleukin-6, biomarkers, immunometabolism, intensive care, trauma surgery

The research team, led by investigators at Children’s Hospital, Zhejiang University School of Medicine, together with collaborators spanning thirteen pediatric intensive care units across China, assembled a retrospective cohort of 2,374 children under eighteen years of age who were admitted to intensive care with suspected infections between 2023 and 2025. Rather than treating this population as a single undifferentiated group, the investigators prespecified two clinically distinct sub-cohorts for focused analysis: a neonatal group of 576 infants aged twenty-eight days or younger, and a hematology group of 494 children, a population in which underlying malignancies, immunosuppression, and hematologic abnormalities complicate both the diagnosis of sepsis and the interpretation of laboratory-based severity scores. This design choice reflects a growing recognition in the field that a scoring system validated in a general pediatric intensive care population may not transfer cleanly to the extremes of age or to immunocompromised patients.

Methodologically, the study followed a disciplined approach to score calculation. For each child, both the Phoenix sepsis score and the pSOFA score were computed using the worst available physiological and laboratory values recorded within the first twenty-four hours of intensive care unit admission. This window matters: early severity assessment is precisely what clinicians need when deciding how aggressively to resuscitate, monitor, and escalate care. The primary outcome was in-hospital mortality, and the principal metric of prognostic accuracy was the adjusted area under the receiver operating characteristic curve, or AUROC, a statistic that captures how well a score discriminates between children who died and those who survived, with 0.5 representing chance-level performance and 1.0 representing perfect discrimination. By adjusting the AUROC, the researchers accounted for confounding structure in the data, strengthening the comparability of the two scores.

The headline finding is statistically clear. Across the full cohort of 2,374 critically ill children, the Phoenix sepsis score achieved an adjusted AUROC of 0.840, significantly outperforming the pSOFA score’s 0.817, with a P value below 0.001. In absolute terms the difference may appear modest, but in the world of mortality prediction models, where incremental gains in discrimination can translate into earlier recognition and redirected resources for the sickest patients, such a difference across a cohort of this size carries weight. The result provides external validation, on a scale and in a healthcare context distinct from the original derivation studies, that the Phoenix framework’s emphasis on four organ systems, respiratory, cardiovascular, coagulation, and neurologic, captures lethal trajectories in infected children at least as well as, and slightly better than, the older pSOFA construct.

The picture grows more complicated in the predefined sub-cohorts. In the hematology group, the Phoenix score again outperformed pSOFA, with adjusted AUROCs of 0.718 versus 0.682, a difference that reached statistical significance at P equal to 0.006. Yet the investigators were careful to characterize discriminative ability in this subgroup as limited for both tools. Children with hematologic disease present a notoriously difficult prediction problem: baseline cytopenias, chemotherapy-related organ toxicity, and altered inflammatory responses can all inflate or deflate organ dysfunction scores independent of sepsis severity. A score of 0.718, while better than chance, leaves substantial room for misclassification, and the authors’ framing suggests that neither score should be treated as a reliable standalone prognostic instrument in this vulnerable population.

In neonates, the story changes again. Among the 576 infants aged twenty-eight days or younger, the Phoenix score posted a strikingly high adjusted AUROC of 0.915 compared with 0.850 for pSOFA, but the difference did not reach statistical significance, with P equal to 0.222. The absence of a significant gap does not mean either score performed poorly; indeed, both achieved excellent discrimination in this low-event-rate setting. Rather, the finding suggests that in newborns the two instruments are statistically interchangeable for mortality prediction, an important practical conclusion given that the Phoenix criteria were designed to span pediatric and neonatal populations and that neonatal sepsis has long posed unique challenges, from nonspecific clinical presentation to the scarcity of neonate-specific validation data for adult-derived scoring frameworks.

Beyond discrimination, the study examined how the scores behave at their operational threshold, the cutoff clinicians actually use to flag sepsis. At the standard threshold of two or more points, both the Phoenix score and pSOFA maintained high sensitivity, exceeding 80 percent across all cohorts, meaning they rarely missed a child who went on to die. The trade-off came in specificity: positive predictive values were low, at or below 50 percent everywhere, and in the neonatal sub-cohort they fell below 8 percent. This asymmetry is not a flaw unique to these scores but a mathematical consequence of applying screening thresholds in settings where deaths are, thankfully, uncommon. A highly sensitive tool catches nearly everyone at risk, but in a population where most children survive, most flagged children will nonetheless survive, producing many false alarms.

The trade-off between sensitivity and positive predictive value took on a different character in the hematology sub-cohort, where the event rate was high enough to make predictive values more meaningful. There, the Phoenix score traded approximately five percentage points of sensitivity for a meaningfully higher positive predictive value than pSOFA. In practical terms, the Phoenix score was somewhat more likely to miss a child who died, but when it flagged a child, that flag was more often correct. Which trade-off a clinician or unit should prefer depends on context: in settings where missing a death is the dominant concern, sensitivity may reign; where flagged patients trigger resource-intensive interventions, a higher positive predictive value reduces unnecessary escalations. The study does not prescribe a choice but equips decision-makers with the quantitative texture needed to make one.

The findings land amid an active international debate about the Phoenix criteria, which were developed and validated by a global consensus effort published in JAMA in 2024 and have since undergone external validation in cohorts from the United States, Bolivia, Australia, and beyond, with mixed results in low-resource settings and emergency departments. The new Chinese multicenter analysis adds a critical piece: evidence from a large, geographically diverse, non-Western cohort, with dedicated attention to neonates and hematology patients, two groups underrepresented in earlier validation work. It also complements the research group’s own prior multicenter study of the Phoenix score, pSOFA, and SIRS criteria in non-intensive care settings, extending the comparison to the sickest children in intensive care.

For the field, the message is one of calibrated confidence. The Phoenix sepsis score can now claim superior discrimination for in-hospital mortality in the general population of critically ill children with suspected infection, supporting its adoption in pediatric intensive care contexts. But the study simultaneously cautions against universal enthusiasm: in neonates, the older pSOFA remains an equally defensible choice, and in children with hematologic disease, both scores fall short of what clinicians would want from a decision-support tool, underscoring the need for population-specific approaches, whether through recalibration, integration of novel biomarkers, or entirely new models tailored to immunocompromised hosts. As sepsis mortality prediction moves from one-size-fits-all scores toward precision risk stratification, this study provides both a benchmark and a reminder that the sickest children often defy the averages on which general scores are built.

Subject of Research: External validation comparing the Phoenix sepsis score and pSOFA for predicting in-hospital mortality in critically ill children with suspected infection.

Article Title: Discrimination performance of the Phoenix sepsis score versus pediatric sequential organ failure assessment for predicting in-hospital mortality in critically ill children: a multicenter external validation study

Article References: Ru, X.-W., Liu, R.-Y., Yang, Z.-H., Huang, C.-Z., Zhang, C., Li, T.-W., Yang, J.-M., Liu, Y., Cui, X.-Y., Chen, H.-B., Zhou, X., Tang, F., Gong, X.-Y., Ling, P., Lv, X., Zeng, Q., Ma, Z., Yuan, B.-Y., Zhu, H., … Ye, Q. (2026). Discrimination performance of the Phoenix sepsis score versus pediatric sequential organ failure assessment for predicting in-hospital mortality in critically ill children: a multicenter external validation study. World Journal of Pediatrics. https://doi.org/10.1007/s12519-026-01073-y

Image Credits: AI Generated

DOI: 10.1007/s12519-026-01073-y

Keywords: Phoenix sepsis score, pSOFA, pediatric sepsis, in-hospital mortality, critical care, neonatal sepsis, hematology, AUROC, external validation, organ dysfunction, predictive scoring, intensive care unit