The research team, led by Youjia Hao and colleagues in the Department of Critical Care Medicine at Beijing Jishuitan Hospital, Capital Medical University, systematically searched PubMed, EMBASE, Web of Science, and the Cochrane Library from inception to January 2025. They included prospective studies reporting resistin levels in relation to mortality or disease severity in sepsis. After rigorous screening, eighteen studies encompassing 2,197 sepsis patients made it into the final analysis. The review was registered with PROSPERO under CRD42025639277, ensuring methodological transparency from the outset.

Resistin itself has an intriguing biology. Originally named for its proposed role in insulin resistance, the molecule is now recognized as a potent driver of inflammation. Unlike adipose-derived resistin in rodents, human resistin circulates largely from immune cells, and it amplifies the release of tumor necrosis factor and interleukin-6 while promoting endothelial dysfunction. In the context of sepsis, where a dysregulated host response to infection cascades into organ failure, resistin’s rise seems to mirror the intensity of that inflammatory storm.

The meta-analysis quantified this relationship using standardized mean differences, a statistical measure that allows comparison across studies employing different laboratory assays. Resistin levels were significantly higher in non-survivors than in survivors, with a pooled standardized mean difference of 0.83 and a 95 percent confidence interval spanning 0.31 to 1.36. Patients with septic shock, the most severe form of sepsis characterized by profound circulatory collapse, showed even more striking elevations compared to those without shock, with a standardized mean difference of 1.34 and a confidence interval of 0.62 to 2.05. Compared with healthy controls, sepsis patients overall displayed substantially elevated resistin, yielding a standardized mean difference of 1.99 with a confidence interval of 1.63 to 2.35.

When the researchers arranged these findings along the spectrum of disease, a stepwise gradient emerged. Healthy controls occupied the lowest rung, followed by patients with non-shock sepsis, then those with septic shock, and finally non-survivors at the top. This ordered pattern suggests that resistin is not merely a binary flag of infection but a quantitative readout of inflammatory burden, potentially offering clinicians a way to gauge how far along the severity curve a patient sits at the moment of admission.

The team also assessed resistin’s diagnostic accuracy using areas under the receiver operating characteristic curve, a metric that ranges from 0.5, equivalent to random guessing, to 1.0, representing perfect discrimination. The pooled AUC for predicting mortality was 0.68 with a confidence interval of 0.64 to 0.73. In adult patients specifically, the pooled AUC rose to 0.70 with a confidence interval of 0.65 to 0.75. These values indicate moderate discriminatory power, meaning resistin alone cannot reliably sort survivors from non-survivors but may contribute meaningful prognostic information when combined with clinical scoring systems.

However, the analysis was not without caveats. Substantial heterogeneity pervaded the main pooled analyses, reaching an I-squared value of 89 percent, a statistical signal that the included studies varied considerably in their populations, assays, and timing of measurement. The 95 percent prediction intervals for sepsis-related mortality, 28-day mortality, and septic shock all included zero, indicating that the direction of the effect in future studies remains uncertain. Subgroup and meta-regression analyses were conducted to explore potential effect modifiers, but the authors acknowledge that these exploratory tools cannot fully resolve the underlying variability.

The authors conclude that admission resistin levels may be associated with disease severity and adverse outcomes in sepsis, but they are careful to emphasize that clinical utility remains unproven. Their recommendation is unambiguous: large, multicenter prospective studies are needed before resistin can be integrated into routine prognostic assessment. In the interim, the molecule joins a growing list of inflammatory biomarkers, including procalcitonin and interleukin-6, whose prognostic value in sepsis is promising but not yet definitive.

For a condition that kills swiftly and often silently, any tool that sharpens early risk stratification carries enormous clinical weight. Resistin’s stepwise rise across the sepsis spectrum offers a compelling biological narrative, one that aligns with the broader understanding of sepsis as a crescendo of immune dysregulation. Whether this cytokine will earn a place beside lactate and procalcitonin in the emergency department or intensive care unit remains to be seen, but this meta-analysis provides the strongest synthesis to date of its prognostic signal.

The study, published open access under a Creative Commons license, received no specific funding and involved no competing interests. As sepsis continues to challenge clinicians worldwide, biomarkers like resistin represent a frontier where laboratory science meets bedside decision-making, and the coming years of multicenter validation will determine whether this inflammatory messenger becomes a standard component of the sepsis prognostic toolkit.

Subject of Research: The prognostic value of resistin in patients with sepsis: a systematic review and meta-analysis

Article Title: The prognostic value of resistin in patients with sepsis: a systematic review and meta-analysis

Article References: Hao, Y., Bai, Y., Zhang, L., Cui, Z., Liu, C., & Wang, H. (2026). The prognostic value of resistin in patients with sepsis: a systematic review and meta-analysis. BMC Infectious Diseases. https://doi.org/10.1186/s12879-026-14293-4

Image Credits: AI Generated

DOI: 10.1186/s12879-026-14293-4

Keywords: resistin, sepsis, biomarker, meta-analysis, septic shock, mortality, inflammation, BMC Infectious Diseases, prognostic, value, patients, systematic

The clinical logic behind the search is compelling. Gestational diabetes mellitus, or GDM, is one of the most common metabolic complications of pregnancy, and current screening depends on venous blood sampling, most notably the oral glucose tolerance test, which requires fasting, repeated blood draws over several hours, and a glucose load that many women find unpleasant. Timely detection matters because untreated hyperglycemia in pregnancy raises risks of macrosomia, birth injury, and later metabolic disease for both mother and child. Saliva offers an attractive alternative sampling matrix: it can be collected non-invasively, repeatedly, and even at home, which would allow far more frequent monitoring than blood-based testing. The catch, as the review makes clear, is that saliva is a complex fluid whose composition reflects not only systemic metabolism but also oral health, hydration, circadian rhythm, and collection technique, all of which can confound comparisons between patient groups.

The most consistent findings emerged for salivary glucose itself. Both studies included in the review that measured glucose in saliva found higher postprandial or post-load values in women with GDM compared with normoglycemic controls, and both reported positive correlations between blood and saliva glucose concentrations, supporting the physiological premise that salivary glucose tracks circulating glucose. One study reported an area under the receiver operating characteristic curve, or AUC, of 0.865 (95% confidence interval 0.765 to 0.966) for two-hour postprandial unstimulated saliva, a discriminatory performance that, if replicated, would approach the range considered useful for clinical screening. The technical appeal is obvious: a marker that mirrors blood glucose but can be sampled without needles would transform the logistics of glucose monitoring during pregnancy, particularly for repeated postprandial assessment.

Oxidative stress markers formed the second major domain of evidence. Hyperglycemia generates reactive oxygen species, and malondialdehyde, or MDA, a lipid peroxidation product that serves as a readout of oxidative damage, emerged as the leading candidate in this category. One study reported an AUC of 0.812 (95% confidence interval 0.694 to 0.929) for salivary MDA, though the review notes that oxidative stress findings were not uniform across studies, with other measures of antioxidant capacity and oxidant status showing more variable results. The biological rationale is sound, since pregnancy already imposes oxidative load and hyperglycemia amplifies it, but the heterogeneity of assays, from ferric reducing ability of plasma to oxygen radical absorbance capacity, makes cross-study comparison difficult and underscores the need for standardized methodology.

Adipokines, the hormone-like signaling molecules secreted by fat tissue, provided a third and more modest signal. Selected adipokines showed study-specific discriminatory performance, with reported AUCs of 0.705 (95% confidence interval 0.574 to 0.836) for visfatin and 0.641 (95% confidence interval 0.520 to 0.761) for resistin. These values fall into the range that might support a screening aid but would not suffice as stand-alone diagnostic tests. Adipokines are biologically plausible candidates because insulin resistance is central to GDM pathophysiology and adipose-derived signaling is altered in metabolic disease, yet the review found that individual studies often examined different panels of molecules, limiting the ability to build a coherent picture across the literature.

Inflammatory markers told a more complicated story, one that illustrates why the oral environment cannot be ignored. Inflammatory findings varied with periodontal context, meaning that gum disease, which is itself common in pregnancy and independently alters salivary inflammatory profiles, appears to act as a confounder for markers such as interleukins, matrix metalloproteinases, and related mediators. A woman with periodontitis may show salivary inflammation patterns that mimic or mask those attributable to hyperglycemia. The review’s authors highlight this as a critical methodological gap: few studies adequately assessed or controlled for periodontal status, which means that some reported differences between GDM and control groups could reflect oral health rather than glucose metabolism. Future studies, they argue, must document and adjust for periodontal conditions as a matter of course.

Perhaps the most forward-looking portion of the review concerns the oral microbiome. Rather than measuring single molecules, some studies examined the composition of the salivary microbial community, identifying taxon-specific differences between hyperglycemic and normoglycemic pregnancies. One study went further and internally validated saliva-only classification models, machine-learning style classifiers built from microbial profiles, while another examined early-pregnancy microbial patterns in a separate cohort, probing whether the microbiome might flag risk before overt hyperglycemia develops. The idea that a bacterial fingerprint in spit could predict metabolic disease is undeniably viral in its appeal, but the review tempers the enthusiasm: internal validation is not external validation, and models trained on one cohort frequently lose performance when applied to another population with different demographics, diets, and oral hygiene practices.

Methodological caveats run throughout the review and shape its conclusions. Most of the thirty-one reports used cross-sectional or case-control designs rather than prospective cohorts, and several arose from the same or potentially overlapping study populations, which raises the possibility of double-counting evidence. Critical appraisal using design-specific JBI tools revealed limited control of confounding in many studies, and the collection and processing of saliva varied widely, from stimulated to unstimulated samples and differing timing relative to meals or glucose loads. The absence of external validation for reported diagnostic-performance estimates was identified as the central constraint on interpretation. In plain terms, an AUC reported in a single study tells you how well a marker performed in that dataset, not how it will perform in your clinic tomorrow.

What the review does establish is a roadmap. The findings for salivary glucose, MDA, and selected adipokines support further investigation in hyperglycemia in pregnancy, particularly GDM, but the authors are careful to state that their diagnostic utility remains unestablished. They call for prospective studies with standardized collection and assay methods, appropriate consideration of periodontal status, and validation in independent cohorts, the sequence of steps that any biomarker must clear before regulatory approval and clinical adoption. Multi-center prospective designs would also allow researchers to test whether combining markers, for example glucose with MDA or microbial features, improves discrimination beyond any single analyte, an approach that has proven fruitful in other diagnostic fields.

For pregnant women and their clinicians, the practical takeaway is patience. The needle-based oral glucose tolerance test remains the standard of care, and no salivary test currently exists that can replace or supplement it. But the direction of travel is clear: the review demonstrates a growing, if uneven, evidence base and identifies exactly which molecules and study designs deserve investment. If salivary glucose or MDA can replicate their reported performance in large, well-controlled prospective cohorts, the familiar scenario of a pregnant woman sitting in a clinic for hours after a sugary drink, having blood drawn repeatedly, could eventually give way to something as simple as spitting into a tube. That future is not here yet, but the scientific groundwork for it is now, for the first time, systematically mapped.

Subject of Research: Salivary biomarkers for detecting hyperglycemia in pregnancy and gestational diabetes mellitus

Article Title: Salivary biomarkers in hyperglycemia in pregnancy: a scoping review

Article References: Wu, Z., Huang, Y., Lyu, L., Huang, Y., Chen, Y., Hang, Q., Zhang, Q., & Ping, F. (2026). Salivary biomarkers in hyperglycemia in pregnancy: a scoping review. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02647-7

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02647-7

Keywords: salivary biomarkers, hyperglycemia in pregnancy, gestational diabetes mellitus, salivary glucose, malondialdehyde, oxidative stress, adipokines, visfatin, resistin, oral microbiome, scoping review, non-invasive diagnostics

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