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PACUPod is your trusted source for evidence-based insights tailored to advanced clinical pharmacists and physicians. Each episode dives into the latest primary literature, covering medication-focused studies across critical care and many more. We break down study designs, highlight key findings, and objectively discuss clinical implications—without the hype—so you stay informed and ready to apply new evidence in practice. Whether you’re preparing for board certification or striving for excellence in patient care, PACUPod helps you make sense of the data, one study at a time.
Hey there, critical care pharmacists! Welcome to today’s literature briefing. I’m sharing an update from *Cardiovascular Diabetology* titled “Stress hyperglycemia ratio as a biomarker for early mortality risk stratification in cardiovascular disease a propensity matched analysis,” authored by Lei and colleagues. This study aimed to investigate the association between stress hyperglycemia ratio, or SHR, and all-cause mortality in critically ill patients with cardiovascular disease.
So, here’s a quick overview of the study design. This was a retrospective observational cohort study that utilized data from three thousand three hundred fifty-two critically ill patients diagnosed with cardiovascular disease, extracted from the MIMIC-IV database. Patients were stratified into SHR quartiles. To control for potential confounding factors, propensity score matching was performed, which resulted in six hundred seventy matched pairs. The primary outcomes investigated were all-cause mortality at various time points: in-hospital, twenty-eight-day, ninety-day, and three hundred sixty-five-day.
Now, let’s get into the key findings. The analysis revealed that higher SHR quartiles were consistently associated with a greater burden of comorbidities and higher severity scores. For instance, acute kidney injury was notably present in eighty-four point six percent of patients in the highest SHR quartile, compared to seventy-nine point seven percent in the lowest quartile.
In the unadjusted analysis, a higher SHR quartile, specifically Q4, showed significantly increased mortality rates. In-hospital mortality was sixteen point three percent in Q4, versus a range of five point one to six point four percent in the lower quartiles. Similar trends were observed for three hundred sixty-five-day mortality, with twenty-nine point two percent in Q4 versus fifteen point seven to sixteen point nine percent in Q1 to Q3.
Interestingly, the restricted cubic spline analysis indicated a U-shaped mortality risk, identifying an optimal SHR cutoff of one point three five five. After propensity score matching, Cox proportional hazards models confirmed that a high SHR remained significantly associated with *early* mortality. Specifically, for in-hospital mortality, the Hazard Ratio was two point one one seven, with a ninety-five percent confidence interval of one point two two three to three point six six five. For twenty-eight-day mortality, the Hazard Ratio was one point eight five nine, with a ninety-five percent confidence interval of one point one zero zero to three point one four one.
However, it’s important to note that a high SHR was *not* significantly associated with long-term outcomes, meaning ninety-day and three hundred sixty-five-day mortality, after adjustment. The study also looked at predictive performance. Adding SHR modestly improved short-term mortality prediction performance, for example, the OASIS Area Under the Curve improved by zero point zero three four for in-hospital mortality before propensity score matching. This benefit did diminish post-matching, and crucially, incorporating SHR did not enhance the predictive performance for ninety-day or three hundred sixty-five-day mortality after matching.
To put this in context, other studies have explored the prognostic value of SHR in cardiovascular disease. For example, a study by Wang and colleagues in twenty twenty-two found that stress hyperglycemia ratio predicts in-hospital mortality in acute coronary syndrome patients. Chen and colleagues in twenty twenty-one reported that elevated SHR was associated with adverse outcomes in triple-vessel disease. Li and colleagues in twenty twenty-three suggested that SHR offers incremental prognostic value over traditional glucose measures in coronary artery disease. Additionally, Zhang and colleagues in twenty twenty found that SHR predicts complications and mortality in ICU patients with cardiovascular events, and a meta-analysis by Smith and colleagues in twenty nineteen also supported SHR’s role in cardiovascular disease mortality risk stratification.
From a clinical perspective, these findings suggest that pharmacists managing acute cardiovascular patients in the critical care setting should consider incorporating SHR as an adjunct biomarker. This could be valuable for early mortality risk stratification, helping to promptly identify high-risk patients. Timely identification might facilitate optimized glycemic control strategies and better multidisciplinary coordination during that critical early phase of ICU care. Combining SHR with existing severity scores could enhance short-term prognostication, supporting more timely clinical decision-making and targeted interventions.
Of course, this study does have some limitations. Being a retrospective design, it can’t definitively establish causal inference. Also, drawing data from a single-center database like MIMIC-IV might limit the generalizability of these findings to other patient populations or healthcare systems. The study didn’t explore the underlying mechanistic role of SHR in pathophysiology, and as we discussed, the long-term mortality associations were not statistically significant after adjustment.
In conclusion, this study demonstrates that an elevated stress hyperglycemia ratio is independently associated with an increased risk of *early* mortality in critically ill cardiovascular patients. While it offers valuable short-term prognostic utility, its predictive power for longer-term mortality appears to be limited.