Dear Editor,
We read with great interest the recent publication by Gao et al. [1], which investigated at the nonlinear association between the stress hyperglycemic ratio (SHR) and prognosis in patients with cardiac surgery-associated acute kidney injury (CS-AKI). The authors demonstrated a U-shaped relationship between SHR and all-cause mortality. The lowest risk was observed at an SHR = 1.39. They also showed high SHR (≥1.61) is an independent prognostic factor for poor outcomes in CS-AKI patients, which is important for the field. The study also found adding SHR to common prognostic models (APACHE III, SAPS II, SOFA) improved prediction. This was shown by higher AUC, NRI and IDI values. This means that SHR could be useful in clinical work to assess patient risk. We agree with the main conclusions of the study. There are some points to consider. They are about the biological explanation of the findings, general use of the results, and how to use SHR in clinical practice. However, these points require further discussion.
First, while the study attributes the link between elevated SHR and poor CS-AKI prognosis to oxidative stress and inflammatory pathways, recent mechanistic research has identified additional biological mechanisms that may underlie this relationship [2–3]. Furthermore, elevated SHR induce renal tubular cell apoptosis through activation of the unfolded protein response [4], a pathway known to exacerbate AKI and progression to severe AKI stages, which is consistent with the higher proportion of AKI stage 3 patients in the highest SHR quartile observed by Gao et al.’. Integrating these mechanistic insights would further strengthen the rationale for SHR as a reliable prognostic biomarker beyond conventional absolute glucose measurements.
This study suggests that oxidative stress and inflammation cause a link between high SHR and poor CS-AKI outcomes. Recent studies has identified several biological reasons for this link. SHR are associated with endothelial dysfunction in critically ill patients [2]. Endothelial dysfunction is key pathophysiological contributor of CS-AKI [3]. This is happens because the body has less usable nitric oxide, and blood vessels allow more substances to pass through. High SHR also cause kidney tubular cell death [4]. This was achieved by turning on the unfolded protein response. This pathway aggravates acute kidney injury and promotes progression to advanced AKI. More patients with AKI stage 3 were in the group with the highest SHR in Gao et al. This matches the above findings. Knowing these biological reasons clarifies why SHR is a good prognostic marker. This is better than directly measuring blood glucose levels.
Secondly, the subgroup analysis demonstrating a significantly stronger association between SHR and mortality in CS-AKI patients with comorbid chronic obstructive pulmonary disease (COPD) (HR = 7.18 vs. 2.53 in non-COPD patients) aligns with well-characterized systemic features of COPD [5]. COPD is associated with chronic low-grade inflammation and impaired glucose metabolism, which may synergize with stress hyperglycemia to amplify renal oxidative stress and injury. This finding underscores the need for tailored-SHR-guided glycemic management in this high-risk subgroup, a clinical implication that deserves further emphasis to optimize perioperative management.
Third, despite its large sample size (n = 3,249), raises important considerations regarding external validity [6]. Electronic health record-derived prediction models are often limited by regional variations in clinical practice, including cardiac surgical strategies, perioperative glycemic management protocols and patient comorbidity profiles. Validating the optimal SHR threshold of 1.39 identified in this study in diverse, multi-center cohorts, including non-Western populations, is therefore essential to confirm its universal applicability in clinical practice.
The authors noted key problems in using SHR in clinical practice. The biggest is the need for baseline HbA1c tests [1]. These tests will only be conducted on patients with a confirmed diabetes diagnosis to monitor their recent blood sugar levels and further evaluate surgical wound prognosis, and are not routinely administered to all non-diabetic patients during surgery or recovery. This makes it difficult to calculate SHR quickly in some places. Recent advances in point-of-care HbA1c testing have addressed this problem [7]. The test can be performed in less than 15 min. It can also be used in intensive care units. The use of SHR for risk stratification may improve the cost-effectiveness of care in CS-AKI patients [7]. This reduces unnecessary renal replacement therapy. It also helps improve patient survival. However, this result was not examined in the current study, this result requires further research.
Gao et al. demonstrated a U-shaped link between SHR and mortality. This raises important questions regarding the best blood sugar targets for CS-AKI patients. Recent clinical guidelines suggest personalized blood sugar control [8]. This finding is consistent with the guidelines. A recent study tested various glycemic targets in patients [9]. It sets an SHR target between 1.2 and 1.4. This range encompasses the optimal low-risk SHR threshold identified by Gao et al.’. This was compared to the common target of blood glucose below 180 mg/dL. The study found the SHR target reduced 30-day death rate by 27%. This proves the SHR level from Gao et al.’ is useful in clinical practice. This also provides early proof. Using SHR to guide specific blood sugar treatment is effective for this high-risk group of patients.
In conclusion, this study Gao et al.’ offers substantial evidence for the prognostic value of SHR in CS-AKI patients and highlights its potential in enhancing existing risk prediction models. However, its findings should be interpreted in conjunction with the mechanistic pathways mediated by SHR-induced renal injury, and the external validity of the determined SHR threshold needs to be confirmed in diverse populations. Taking these factors into account, evaluating the cost-effectiveness of SHR-guided glycemic management simultaneously is crucial for translating this promising biomarker into routine perioperative clinical practice to improve the prognosis of patients with CS-AKI.
Acknowledgements
The authors sincerely thank the researchers and clinicians who commented on and cited the articles. We are grateful to Shanghai Seventh People’s Hospital for providing an excellent platform. I also thank my master’s supervisor for her guidance. We would also like to thank the editors and reviewers for their constructive suggestions, which have significantly improved the quality of this manuscript. The conception and design were jointly handled by Fan Yena and Hu Jing. YeNan Fan was responsible for drafting the paper. Hu Jing was responsible for the strict revision of the content and for finalizing the version to be published. All the authors were collectively responsible for all aspects of the work.
Funding Statement
This article has not been funded by any fund.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
Data availability is not applicable to this article as no new data were created or analyzed in this study.
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Data Availability Statement
Data availability is not applicable to this article as no new data were created or analyzed in this study.