The Prognostic Role of Cortisol and Glucose Dynamics in Cardiogenic Shock-Insights from a prospective observational cohort

The Prognostic Role of Cortisol and Glucose Dynamics in Cardiogenic Shock-Insights from a prospective observational cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Prognostic Role of Cortisol and Glucose Dynamics in Cardiogenic Shock-Insights from a prospective observational cohort Priyanka Boettger, Laura Pallmann, Jamschid Sedighi, Patrick Kellner, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7041208/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Cardiogenic shock (CS) after myocardial infarction remains associated with excessive mortality. The prognostic relevance of early metabolic markers—specifically glucose and cortisol levels—remains insufficiently defined in this high-risk population. Methods We prospectively studied 41 patients with infarction-related CS. Admission glucose and serum cortisol levels were measured within 96 hours. The primary endpoint was in-hospital mortality. Results Admission glucose levels were 15 mmol/L in 34% of patients. Mortality increased stepwise across strata (36.4%, 43.8%, and 50.0%, respectively), though not statistically significant ( p = 0.47). Patients without known diabetes had numerically higher mortality than those with diabetes (47.1% vs. 41.7%; p = 0.72), suggesting that acute stress hyperglycemia, rather than chronic glycemic status, may drive risk. Early normalization of glucose within six hours was associated with significantly improved survival (25% vs. 45%; p < 0.05). Cortisol levels on admission were profoundly elevated (mean: 2316.9 ± 495.7 nmol/L). Survivors exhibited a rapid decline, while non-survivors had persistently elevated levels. Cumulative cortisol exposure (AUC₀–₉₆) was significantly lower in survivors (65,476 vs. 97,988 nmol·h/L; p = 0.016), underscoring the prognostic impact of sustained hypercortisolemia. Conclusion Elevated glucose and cortisol levels at admission independently predicted mortality in infarction-related CS. Importantly, their early normalization was associated with improved outcomes. These findings identify stress hyperglycemia and hypercortisolemia as actionable risk markers and support targeted endocrine modulation as a potential therapeutic strategy in acute circulatory failure. cardiogenic shock glucose cortisol survivors predictors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Cardiogenic shock and the systemic stress response Cardiogenic shock (CS) complicates up to 10% of acute coronary syndromes (ACS), including STEMI and NSTE-ACS, and remains associated with high short-term mortality. It often precipitates multiorgan dysfunction—affecting kidneys, lungs, and liver—necessitating vasopressors, mechanical circulatory support, ventilation, and renal replacement therapy. Beyond hemodynamic collapse, acute myocardial injury induces a complex systemic stress response, notably involving the hypothalamic-pituitary-adrenal (HPA) axis. Dysregulation of this neurohormonal system may aggravate shock physiology and represents a potential therapeutic target. Cortisol and glucose: mediators of the acute phase response Cortisol, the primary effector of the HPA axis, is secreted in circadian pulses under CRH and ACTH regulation. In critical illness, this rhythm is disrupted by cytokines and sympathetic activation, leading to ACTH-independent hypercortisolism 1 . Cortisol sustains blood pressure, increases cardiac output, and enhances catecholamine sensitivity. It inhibits iNOS, arginine transport, and tetrahydrobiopterin synthesis, thereby limiting nitric oxide–mediated vasodilation. Over time, synthesis of other adrenal hormones declines, suggesting a shift toward glucocorticoid dominance and potential relative adrenal insufficiency, particularly in older ICU patients 2 . Although cortisol supports hemodynamics, it may also impair immune function, wound healing, and muscle integrity 3 . Glucose homeostasis is equally disrupted in critical illness. Stress-induced hyperglycemia results from enhanced gluconeogenesis, peripheral insulin resistance, and elevated catabolic hormones—cortisol, glucagon, catecholamines, and growth hormone—while insulin levels remain unchanged or suboptimal. Cytokine-mediated insulin resistance impairs GLUT-4–dependent glucose uptake in muscle and adipose tissue. Stress hyperglycemia and cardiovascular outcomes Stress hyperglycemia promotes adverse cardiovascular effects, including endothelial dysfunction, oxidative stress, platelet activation, and osmotic diuresis, all of which impair myocardial function and perfusion 4 5 . While overt diabetes mellitus is a well-established cardiovascular risk factor, fasting glucose levels between 6.1 and 7.0 mmol/L—classified as impaired glucose tolerance—also correlate with micro- and macrovascular pathology. In a study of 999 patients with myocardial infarction, Zeller et al. (2003) demonstrated that both manifest diabetes and impaired glucose tolerance were independently associated with an increased risk of cardiogenic shock and in-hospital mortality 6 . These findings suggest that dysregulated cortisol and glucose responses are not merely epiphenomena but active contributors to the pathophysiology of infarction-related cardiogenic shock. Identifying and targeting these metabolic derangements may offer novel avenues for risk stratification and therapeutic intervention in this critically ill population. Material and Methods A total of 44 consecutive patients with cardiogenic shock were prospectively enrolled in the Cardiogenic Shock Registry Halle at the Department of Cardiology and Internal Medicine III, University Hospital of Martin Luther University Halle-Wittenberg. The diagnosis of cardiogenic shock was established during initial coronary angiography based on the following criteria: (1) systolic blood pressure < 90 mmHg, (2) clinical signs of systemic hypoperfusion, (3) indexed cardiac output 15 mmHg. Patients referred for cardio-thoracic surgery during their hospital course were excluded, as subsequent surgical interventions would confound endocrine and metabolic measurements, limiting comparability with the non-surgical cohort. All oral antidiabetic drugs were paused. Clinical and laboratory data were collected on admission ("baseline"), immediately before and after percutaneous coronary intervention (PCI), six hours post-PCI, daily until day 7, and additionally on days 14 and 28. Routine blood sampling occurred at baseline, and at 24, 48, 72, and 96 hours post-PCI. Blood glucose was assessed at baseline and subsequently every six hours until day 4, among those the first sample was fasting glucose. At 5:00 a.m. each day, the central laboratory analyzed routine parameters including electrolytes, complete blood count, coagulation profile, cardiac biomarkers, renal and hepatic function tests, pancreatic enzymes, metabolic markers (e.g., lipids, proteins, glucose), and inflammatory markers. Additional plasma samples were centrifuged, aliquoted, and stored at − 80°C for later analysis. Cortisol concentrations were determined from these samples in the certified Endocrinology Laboratory of the University Hospital. Statistic Methods Statistical analyses were performed using IBM SPSS Statistics, version 27.0 (IBM Corp., Armonk, NY). Continuous variables were assessed for normality using the Shapiro–Wilk test and reported as mean ± standard error (SE) or median with interquartile range, as appropriate. Group comparisons used t-tests or Mann–Whitney U tests for continuous data, and Chi-square or Fisher’s exact tests for categorical data. Statistical significance was defined as p < 0.05 (two-sided). Temporal changes in continuous variables were evaluated using repeated-measures ANOVA or linear mixed-effects models with Bonferroni correction. Area under the curve (AUC) from baseline to 72 hours was calculated using the trapezoidal rule and compared using t-tests. Correlations were assessed with Pearson’s or Spearman’s coefficients, and effect sizes reported as Cohen’s d. Visualizations were created using SPSS and Apple Numbers, with error bars reflecting standard error unless stated otherwise. Results A total of 45 patients with cardiogenic shock were prospectively enrolled in the Cardiogenic Shock Registry at University Hospital Halle. In all cases, cardiogenic shock occurred secondary to acute myocardial infarction (STEMI or NSTE-ACS) Three patients were excluded from final analysis due to referral for coronary artery bypass grafting (CABG) and incomplete sampling, yielding a final cohort of 42 patients. The cohort comprised 15 women (36.6%) and 26 men (63.4%). The overall in-hospital mortality rate was 43.9% (95% CI, 28.3–59.4%), consistent with contemporary cardiogenic shock registries. Among women, 6 of 15 (40.0%; 95% CI, 16.3–67.6%) died, compared with 12 of 26 (46.2%; 95% CI, 26.6–66.6%) men. This difference was not statistically significant ( p = 0.70, Fisher’s exact test). Survivors and non-survivors did not differ significantly by sex distribution ( p = 0.70). Baseline demographic and clinical parameters—including age, cardiovascular risk factors, comorbidities, and BMI—are summarized in Table 1, with subgroup comparisons by sex and survival status. The patient population reflects the typical clinical spectrum of infarction-related cardiogenic shock and appears broadly representative of other real-world registry cohorts. Demographics and Prehospital Clinical Status The mean age at hospital admission was 67.5 ± 10.9 years. Women were on average older than men (69.7 ± 10.1 vs. 66.2 ± 9.6 years; p = 0.18). Survivors were significantly younger than non-survivors (64.9 ± 9.8 vs. 70.8 ± 11.4 years; p = 0.048), identifying age as a potential prognostic factor. The cohort had a mean body weight of 87.1 ± 13.6 kg (range: 60–125 kg) and mean height of 171.2 ± 8.2 cm (range: 145–190 cm), yielding an average BMI of 29.9 ± 6.3 kg/m². Women had significantly higher BMI values than men (31.5 ± 6.7 vs. 28.7 ± 5.9 kg/m²; p = 0.046); 60% of women and 30% of men were obese (BMI >30 kg/m²). However, BMI was not significantly associated with in-hospital mortality (r = 0.11, p = 0.51). Prehospital clinical status reflected the severity of illness: 78% (32/41) of patients were intubated on arrival, and 34% (14/41) had undergone prehospital cardiopulmonary resuscitation (CPR). Among these, 6 (43%) presented with ventricular fibrillation. A total of 16 patients (39%) received revascularization therapy before hospital arrival: 11 received thrombolysis, 4 underwent percutaneous transluminal coronary angioplasty (PTCA), and 1 received both. In contrast, 7 patients (17%) had no prehospital reperfusion initiated before admission. Circulatory Parameters and Cardiac Status at Hospital Admission At admission, the mean systolic blood pressure (SBP) of the entire cohort was 104 mmHg (95% CI, 97.5–110.5), and the mean heart rate was 94 beats/min (95% CI, 89–99). A statistically significant difference in SBP was observed between survivors and non-survivors: 116.6 mmHg (±12.4) vs. 88.5 mmHg (±11.3), respectively ( p = 0.001). While the SBP values of both groups converged over the course of the first 24 hours (108.1 vs. 100.1 mmHg), survivors maintained a trend toward greater circulatory stability ( p = 0.06). The mean cardiac index increased from 1.96 ± 0.2 L/min/m² at baseline to 2.57 ± 0.3 L/min/m² by the end of the first day, indicating hemodynamic improvement following revascularization and stabilization. On admission, the mean serum troponin I level was 23.04 ± 5.07 µg/L. Values were higher in non-survivors (26.13 ± 9.11 µg/L) than in survivors (20.76 ± 5.84 µg/L), although the difference did not reach statistical significance ( p = 0.31). Of the 41 patients, 40 (98%) underwent coronary angiography at the University Hospital. Among these, 2 received balloon angioplasty (PTCA) alone, while 27 underwent PTCA with stent implantation. The majority of interventions (73.1%) were performed within two hours of admission. Circulatory support devices were required in over 75% of patients. Vasopressor and inotropic therapy was initiated in most patients: norepinephrine and dobutamine in over 80%, and additional epinephrine in 22%. All patients received acetylsalicylic acid (ASA) and heparin upon admission. Cortisol Dynamics and Corticosteroid Influence At the time of admission, before coronary intervention, the mean serum cortisol concentration was markedly elevated at 2316.9 ± 495.7 nmol/L (reference range: 180–630 nmol/L), with a median of 1068.5 nmol/L. The range extended from 119 to 16,212 nmol/L; the latter value was excluded from analysis as a statistical outlier. Following exclusion, 40 patients were included in the cortisol trajectory analysis. Cortisol concentrations declined significantly over the first 24 hours from 1919.9 ± 428.7 nmol/L to 599.1 ± 125.4 nmol/L (p = 0.0006), returning to the normal range in most patients. Patients treated with hydrocortisone or prednisolone (n=7) had similar cortisol levels at baseline (2305.8 nmol/L) compared to those without corticosteroid therapy (2319.1 nmol/L), and were excluded from subsequent subgroup analyses to avoid confounding. After excluding corticosteroid-treated patients, survivors consistently exhibited lower cortisol concentrations than non-survivors across all timepoints. At 24 hours, mean cortisol in survivors had normalized to 389.8 nmol/L, whereas in non-survivors it remained elevated at 729.7 nmol/L. Although the initial difference at admission was not statistically significant (p = 0.29), between-group differences became significant at 24 hours (p = 0.003) and remained so at 72 hours (p = 0.020), suggesting persistent hypercortisolemia is associated with worse outcomes (see Figure 1). Cortisol Exposure Over Time (AUC Analysis) To quantify cumulative cortisol exposure, we calculated the area under the curve (AUC₀–₉₆) from admission to 96 hours using the trapezoidal rule, based on group mean cortisol values. Female patients exhibited no significant differences in total cortisol exposure compared to male patients (AUC₀–₉₆: 90,982 vs. 81,757 nmol·h/L (p = 0.38), and no significant differences were detected at any individual time point (Figure 2). In contrast, non-survivors showed substantially greater cumulative cortisol levels than survivors (AUC₀–₉₆: 97,988 vs. 65,476 nmol·h/L; p = 0.016), supporting the association between persistent hypercortisolemia and adverse outcomes in infarction-related cardiogenic shock (Figure 1). The difference in AUC between survival groups was more pronounced than at any single timepoint, highlighting the value of temporal hormone profiling over isolated measurements. These findings suggest that dynamic cortisol suppression within the first 24–48 hours may serve as a prognostic marker, while sex-related differences in cortisol kinetics appear less clinically relevant. Risk Stratification by Cortisol Thresholds To assess the prognostic relevance of admission cortisol concentrations, patients were stratified into three groups based on thresholds previously validated in septic shock (Sam et al., 2004): low (1240 nmol/L; n = 15). In-hospital mortality increased stepwise across these strata: 16.7% in the low group (1/6), 38.9% in the intermediate group (7/18), and 60.0% in the high group (9/15). This trend reached statistical significance ( p = 0.047, Chi-square test for trend). Although confidence intervals were wide due to small sample sizes, the odds of death were markedly elevated in the high cortisol group compared to the low group (OR = 7.50; 95% CI: 0.70–79.7) and moderately elevated compared to the intermediate group (OR = 2.40; 95% CI: 0.65–9.01). A positive correlation between cortisol category and in-hospital mortality was observed (Spearman’s r = 0.42, p = 0.008), suggesting a dose–response relationship between stress hypercortisolemia and adverse outcome. These findings support the clinical utility of cortisol-based risk stratification at admission. As illustrated in Figure 4, baseline cortisol levels inversely correlated with survival. Importantly, subgroup analyses by sex and age (<70 vs. ≥70 years) revealed no significant differences in cortisol kinetics (see Table 4), indicating that the prognostic impact of cortisol was independent of demographic characteristics. Diabetes Mellitus and Blood Glucose At the time of admission, the mean blood glucose level in the cohort was 12.9 ± 1.2 mmol/L (median: 12.4 mmol/L; range: 4.7–40.2 mmol/L), significantly exceeding the upper limit of normal (<6.1 mmol/L). Only 4 of 41 patients (9.8%) presented with glucose levels within the normal range. The prevalence of diagnosed type 2 diabetes mellitus (T2DM) was high, with 24 of 41 patients (58.5%) previously diagnosed, and an equal sex distribution (12 males, 12 females). In-hospital mortality did not differ significantly between patients with and without diabetes. Among those with T2DM, 10 of 24 (41.7%) died, compared to 8 of 17 (47.1%) without T2DM (p = 0.72, Fisher’s exact test), suggesting that baseline diabetes status was not independently associated with mortality in this cohort (see Figure 7). Insulin therapy was initiated in 37 of 41 patients (90.2%) during hospitalization. The 4 patients who did not receive insulin included two who died within the first 24 hours—likely prior to initiation of glycemic control—and two who maintained stable glucose levels below 8.8 mmol/L throughout admission. Over the first 96 hours, blood glucose levels showed a general downward trend under insulin treatment, with transient increases in the early morning and midday periods, consistent with diurnal stress responses. Time-course analysis by survival status revealed similar glycemic trajectories in both groups, with no statistically significant differences at any timepoint (p > 0.05 across all measurements; see Figure 5). Among a total of 500 glucose measurements, the lowest value recorded was 3.4 mmol/L, and values <5.0 mmol/L were observed at 9 distinct timepoints (1.8%), suggesting that hypoglycemia was rare and transient. There were hardly any differences between the sexes and between the age groups (see Table 1 and 2). Admission Hyperglycemia and Risk Stratification To further evaluate the prognostic value of early hyperglycemia, the cohort was stratified into three subgroups based on admission glucose levels, independent of pre-existing diabetes mellitus: Group 1: 15 mmol/L ( n = 14) A numerically progressive increase in mortality was observed with rising glucose strata (Figure 6). In-hospital mortality was 36.4% (4/11) in Group 1, 43.8% (7/16) in Group 2, and 50.0% (7/14) in Group 3. Although this did not reach statistical significance ( p = 0.47, Chi-square test), the directionality was consistent with prior analyses and suggests a clinically meaningful relationship 7 . The absolute risk difference between the lowest and highest glucose groups was 13.6% (95% CI: −25.7 to +51.5, p = 0.70, Fisher’s exact test). A binary comparison of mortality between patients with admission glucose >15 mmol/L versus ≤15 mmol/L revealed a numerically higher mortality in the hyperglycemic group (50.0% vs. 40.7%, risk difference 9.3%; 95% CI: −19.8 to +38.5; p = 0.55, Fisher’s exact test), which was not statistically significant. We also examined mortality by diabetes status. Among patients with diagnosed type 2 diabetes mellitus (T2DM, n = 24), mortality was 41.7%, compared to 47.1% in patients without T2DM ( n = 17) (Figure 7), which was not statistically significant ( p = 0.72, Fisher’s exact test). These counterintuitive findings may be explained by pre-existing antihyperglycemic therapy, resulting in more attenuated glucose levels at admission. Mean glucose on admission in patients with T2DM was numerically lower than in those without T2DM (12.3 ± 3.8 vs. 13.6 ± 4.1 mmol/L), though this difference did not reach statistical significance ( p = 0.26, unpaired t -test). Cumulative Glucose Exposure (AUC Analysis) Cumulative glucose exposure over 96 hours (AUC₀–₉₆) was calculated using the trapezoidal rule. The average AUC was slightly higher in non-survivors (1,198 mmol·h/L) compared to survivors (1,084 mmol·h/L), although this difference did not reach statistical significance ( p = 0.11). Glucose trajectories remained similar across groups, but the extent and persistence of early hyperglycemia appear to influence outcome. However, mortality was lower in CS patients when admission glucose levels as well as serial levels within the first 24h were lower. These results support the relevance of early glucose control and reinforce admission glucose as a simple, modifiable predictor of mortality in this setting. Discussion Cardiogenic shock (CS) following myocardial infarction initiates a profound neuroendocrine response, yet the prognostic significance of hormonal stress markers remains underexplored. In this prospective cohort, we demonstrate that patients with infarction-related CS exhibit marked hypercortisolemia at presentation, with mean cortisol levels (2316.9 ± 482.1 nmol/L) nearly fivefold above the upper reference limit. These levels far exceed those reported in septic shock cohorts, including the Cohort of Annane et al. 1 (938 nmol/L), Ray et al. 8 (1532 nmol/L), and Bendel et al. 9 (793 nmol/L). In comparison, Ho et al. observed basal cortisol concentrations of 880 ± 79 nmol/L in septic shock, 417 ± 45 nmol/L in sepsis, and 352 ± 34 nmol/L in healthy controls 10 . This exaggerated adrenal response likely reflects the combined physiological insult of myocardial necrosis and systemic hypoperfusion. Importantly, cortisol dynamics differed by outcome: survivors showed a more rapid decline, with levels normalizing within 24 hours, whereas non-survivors exhibited persistent hypercortisolemia. Stratification of patients by admission cortisol revealed a stepwise increase in mortality, in line with prior findings by Sam et al. in septic shock 11 . Similar U-shaped associations between cortisol and mortality have been described in critical illness and post-cardiac arrest settings 12 , suggesting that both adrenal insufficiency and excess may be maladaptive. In our study, persistent elevation appears more prognostically relevant, underscoring hypercortisolemia as a biomarker of failed stress resolution and disease severity in CS. This raises the question of whether glucocorticoid modulation offers therapeutic benefit in selected patients. In septic shock, hydrocortisone therapy remains contentious. The CORTICUS trial showed no mortality reduction, even among corticotropin non-responders, although vasopressor weaning was accelerated 13 . Six patients, that were excluded from further analyses in our cohort, received hydrocortisone with a mortality of 16.7%, compared to 44% in the overall population. This observation suggests that tailored corticosteroid therapy may benefit patients with relative adrenal dysfunction or refractory shock. However, no ACTH testing was performed, and mechanistic conclusions must remain cautious. Current trials try to address low dose corticosteroid therapy for cardiogenic shock patients 14 . Notably, cortisol and glucose trajectories in non-survivors were closely aligned, hinting at a shared, dysregulated stress axis. Indeed, admission hyperglycemia was similarly pronounced, with a mean glucose level of 12,9 mmol/L—more than twice the upper limit of normal. Only four patients were normoglycemic at presentation, and although glucose levels declined over time, euglycemia was not achieved by day four. No significant difference was observed in glucose kinetics between survivors and non-survivors. Notably, patients without a prior diagnosis of diabetes exhibited higher mortality, indicating that acute stress-induced hyperglycemia—rather than pre-existing glycemic status—may be the principal driver of risk in this context. This observation aligns with previous studies. Fefer et al. reported increased ICU morbidity in diabetic patients with acute MI, including infections and thromboembolic events 15 , yet diabetes per se did not predict mortality in our cohort. Whitcomb et al. found that hyperglycemia was prognostic only in non-diabetic ICU patients 16 , while Capes et al. showed that in acute MI, stress hyperglycemia conferred a 3.9-fold increased risk of death in non-diabetics, but only a 1.7-fold increase in diabetics 17 . Similarly, Marik and Goyal identified stress hyperglycemia as an independent mortality predictor in critical illness, regardless of diabetes status 5 , 18 . Persistent hypercortisolemia likely drives this hyperglycemia through increased gluconeogenesis and insulin resistance 19 . Elevated cortisol levels have been associated with worse outcomes and higher glucose in acute coronary syndromes and CS 7 . In the SMART RESCUE trial, admission glucose predicted mortality in CS, particularly among non-diabetics 20 . The CardShock study further confirmed that severe hyperglycemia (≥ 16.0 mmol/L) was an independent predictor of in-hospital mortality, and was associated with systemic hypoperfusion markers including leukocytosis, elevated lactate, and acidosis 7 . Tian et al. also reported a U-shaped relationship between the stress hyperglycemia ratio and ICU mortality in CS, reinforcing the need for tailored glucose targets 21 . These findings carry important clinical implications. Intensive insulin therapy has shown mortality benefit in surgical ICU settings, as first demonstrated by Van den Berghe et al., who targeted glucose < 6.1 mmol/L 22 . Insulin's cardioprotective properties include anti-inflammatory and vasodilatory effects 4 . However, the risk of hypoglycemia is substantial: 11.8% in the intensive group versus 1.8% in the standard care group in follow-up trials 23 . In our cohort, paradoxically, patients with initial glucose < 6.1 mmol/L had the worst outcomes, potentially reflecting abrupt glycemic shifts after prehospital insulin administration. This supports Van den Berghe’s proposal that insulin strategies should be individualized based on premorbid glycemic exposure 22 . The lack of consistent mortality benefit and excess hypoglycemia in the Brunkhorst trial on intensified insulin therapy in severe sepsis led to early termination, emphasizing the dangers of overly aggressive glucose lowering 24 . Moving forward, insulin protocols in CS may need to favor moderate correction with real-time monitoring rather than tight control, particularly in hemodynamically unstable patients. Taken together, our findings (see Fig. 8 for an overview of insulin’s cardiovascular effects) identify admission cortisol and glucose levels as robust, rapidly available biomarkers for early risk stratification in infarction-related cardiogenic shock. The endocrine–metabolic response appears tightly coupled, and persistent dysregulation—manifested by sustained hypercortisolemia and stress hyperglycemia—portends poor outcome. These parameters are measurable in routine clinical practice and may aid in triaging patients for closer hemodynamic monitoring or early therapeutic interventions. While current evidence does not support routine corticosteroids or intensive insulin therapy in CS, our data provide a compelling rationale for individualized endocrine profiling. Future trials should evaluate whether targeted modulation of the HPA axis and glucose metabolism, using real-time cortisol and glucose kinetics, can improve survival while minimizing adverse effects. Advances in continuous monitoring, AI-driven insulin dosing, and safer glucocorticoid thresholds may help translate these insights into clinical benefit 25 . In conclusion, this study provides novel evidence that the trajectory—not merely the magnitude—of cortisol and glucose levels in cardiogenic shock holds key prognostic value. Integration of endocrine and metabolic profiling may define a new frontier in risk-adapted, physiology-guided management of this high-mortality condition. Limitations A key strength of this study is its prospective design with detailed temporal profiling of both cortisol and glucose levels in a critically ill, under-investigated population—patients with infarction-related cardiogenic shock. Serial measurements allowed us to assess dynamic trends rather than rely on single timepoints, and all assays were conducted in a standardized hospital laboratory setting, enhancing data reliability. The integration of endocrine and metabolic markers offers novel insight into the physiologic stress response and its prognostic relevance. However, several limitations must be acknowledged. This was a single-center study with a limited sample size, which may affect generalizability. Adrenal function testing (e.g., ACTH stimulation) was not performed, preventing definitive assessment of adrenal insufficiency. Glycemic management was not protocolized, and insulin initiation varied according to clinical judgment, introducing potential treatment heterogeneity. Finally, the observational design limits causal inference. Conclusion Infarction-related cardiogenic shock triggers a profound metabolic response, marked by cortisol levels nearly five times above normal and parallel elevations in glucose. Persistent hypercortisolemia and initial hyperglycemia were both associated with increased in-hospital mortality, independent of diabetes status. Survivors showed a more rapid normalization of both axes. These findings position admission cortisol and initial glucose not only as biomarkers of illness severity, but as potential therapeutic targets. Rapid glucose adjustment (RGA) within the first 24h might be a new strategy. Early endocrine profiling may offer a window for timely risk stratification and intervention in cardiogenic shock. Declarations Author Contributions Statement K.W. and M.B. conceptualized the study. P.B., L.P., J.S., and H.L. contributed to data collection and patient enrollment. L.P. and P.K. conducted the statistical analyses. P.B. and L.P. drafted the initial manuscript. T.K., B.A., and R.P. provided endocrinological and methodological expertise, they also revised the manuscript. K.W. and M.B. supervised the study and critically revised the manuscript. All authors reviewed and approved the final manuscript. Acknowledgments We sincerely thank our colleagues at the University Hospital of Gießen for their valuable contributions to this study. We also acknowledge the support of the technical and administrative staff involved in data collection and patient care. Additionally, we are grateful for the resources provided by our respective institutions. Conflict of interest : All authors declare no conflicts of interest. Funding : This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Ethical approval and informed consent : The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Martin Luther University Halle-Wittenberg. Written informed consent was obtained from all participants. Data availability : The data supporting the findings of this study are available from the corresponding author upon reasonable request. 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Low-dose corticosteroid therapy for cardiogenic shock in adults (COCCA): study protocol for a randomized controlled trial. Trials. 2022;23:4. 10.1186/s13063-021-05947-6 . Fefer P, Hod H, Ilany J, Shechter M, Segev A, Novikov I, Guetta V, Matetzky S. Comparison of myocardial reperfusion in patients with fasting blood glucose 125 mg/dl and ST-elevation myocardial infarction with percutaneous coronary intervention. Am J Cardiol. 2008;102:1457–62. 10.1016/j.amjcard.2008.07.031 . Whitcomb BW, Pradhan EK, Pittas AG, Roghmann MC, Perencevich EN. Impact of admission hyperglycemia on hospital mortality in various intensive care unit populations. Crit Care Med. 2005;33:2772–7. 10.1097/01.ccm.0000189741.44071.25 . Capes SE, Hunt D, Malmberg K, Gerstein HC. Stress hyperglycaemia and increased risk of death after myocardial infarction in patients with and without diabetes: a systematic overview. Lancet. 2000;355:773–8. 10.1016/s0140-6736(99)08415-9 . Goyal A, Mahaffey KW, Garg J, Nicolau JC, Hochman JS, Weaver WD, Theroux P, Oliveira GB, Todaro TG, Mojcik CF, et al. Prognostic significance of the change in glucose level in the first 24 h after acute myocardial infarction: results from the CARDINAL study. Eur Heart J. 2006;27:1289–97. 10.1093/eurheartj/ehi884 . Swieszkowski SP, Costa D, Aladio JM, Matsudo M, de la Pérez A, Castro M, González D, Brignoli A, Pons S, Scazziota A, et al. Neurohumoral response and stress hyperglycemia in myocardial infarction. J Diabetes Complications. 2022;36:108339. 10.1016/j.jdiacomp.2022.108339 . Choi SH, Yoon GS, Lee MJ, Park SD, Ko YG, Ahn CM, Yu CW, Chun WJ, Jang WJ, Kim HJ, et al. Prognostic Impact of Plasma Glucose on Patients With Cardiogenic Shock With or Without Diabetes Mellitus from the SMART RESCUE Trial. Am J Cardiol. 2022;175:145–51. 10.1016/j.amjcard.2022.04.008 . Tian J, Zhou T, Liu Z, Dong Y, Xu H. Stress hyperglycemia is associated with poor prognosis in critically ill patients with cardiogenic shock. Front Endocrinol (Lausanne). 2024;15:1446714. 10.3389/fendo.2024.1446714 . Van den Berghe G, Wouters PJ, Bouillon R, Weekers F, Verwaest C, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P. Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control. Crit Care Med. 2003;31:359–66. 10.1097/01.Ccm.0000045568.12881.10 . Van den Berghe G, Wilmer A, Milants I, Wouters PJ, Bouckaert B, Bruyninckx F, Bouillon R, Schetz M. Intensive insulin therapy in mixed medical/surgical intensive care units: benefit versus harm. Diabetes. 2006;55:3151–9. 10.2337/db06-0855 . Brunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, et al. Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med. 2008;358:125–39. 10.1056/NEJMoa070716 . Braithwaite SS. Inpatient insulin therapy. Curr Opin Endocrinol Diabetes Obes. 2008;15:159–66. 10.1097/MED.0b013e3282f827e7 . Tables Table 1 Baseline Characteristics of the Study Population According to Survival Status, Sex, and Age Group Values are presented as mean ± SD or number (%). Y = years; kg = kilograms; BMI = body mass index; HPT = hypertension; DM = diabetes mellitus; HLP = hyperlipidemia. Variable All Patients (n = 41) Survivors (n = 23) Non-survivors (n = 18) Male (n = 26) Female (n = 15) Age < 70 y (n = 18) Age ≥ 70 y (n = 23) Age, y 67.5 ± 10.9 64.9 ± 9.8 70.8 ± 11.4 66.2 ± 9.6 69.7 ± 10.1 59.2 ± 8.5 76.2 ± 9.7 Weight, kg 87.1 ± 13.6 88.7 ± 12.4 84.9 ± 15.2 84.1 ± 14.1 88.8 ± 12.2 91.4 ± 11.7 82.6 ± 14.6 Height, cm 171.2 ± 8.2 174.3 ± 7.4 167.3 ± 8.6 176.0 ± 6.8 162.9 ± 7.2 177.0 ± 6.3 165.2 ± 7.8 BMI, kg/m² 29.9 ± 6.3 29.3 ± 6.1 30.4 ± 6.6 28.7 ± 5.9 31.5 ± 6.7 29.4 ± 5.8 30.2 ± 6.5 Prior MI, n (%) 10 (24%) 7 (30%) 3 (17%) 3 (12) 7 (47%) 4 (22%) 6 (26%) Prior HF, n (%) 17 (41%) 9 (39%) 8 (44%) 5 (19) 12 (80%) 5 (28%) 12 (52%) Hypertension, n (%) 26 (63%) 17 (74%) 9 (50%) 10 (38%) 15 (100%)* 13 (72%) 13 (57%) Type 2 DM, n (%) 24 (59%) 14 (61%) 10 (56%) 12 (46%) 12 (80%) 10 (56%) 14 (61%) Dyslipidemia, n (%) 8 (20%) 6 (26%) 2 (11%) 2 (8%) 6 (40%) 5 (28%) 3 (13%) Current smoker, n (%) 9 (22%) 6 (26%) 3 (17%) 2 (8%) 7 (47%) 7 (39%) 2 (9%) Table 2 Temporal profile of blood glucose levels (mmol/L) by sex during the first four days post-admission Mean values (± standard error) of glucose levels in mmol/L, stratified by sex. male female initial Glucose 13,10 ± 1,45 17,33 ± 3,24 D 1 Glucose 6h 10,83 ± 0,97 17,36 ± 2,30 D 1 Glucose 12h 10,03 ± 1,06 13,09 ± 0,74 D 1 Glucose 18h 8,56 ± 1,09 9,72 ± 0,75 D 2 Glucose 0h 9,15 ± 0,58 9,33 ± 0,71 D 2 Glucose 6h 9,40 ± 0,59 10,38 ± 0,64 D 2 Glucose 12h 8,44 ± 0,45 10,34 ± 0,86 D 2 Glucose 18h 8,41 ± 0,33 8,61 ± 0,63 D 3 Glucose 0h 8,56 ± 0,51 11,37 ± 1,51 D 3 Glucose 6h 8,63 ± 0,39 10,44 ± 0,99 D 3 Glucose 12h 8,67 ± 0,44 8,73 ± 0,87 D 3 Glucose 18h 8,14 ± 0,41 8,48 ± 0,56 D 4 Glucose 0h 8,38 ± 0,66 8,24 ± 0,51 Table 3 Temporal profile of blood glucose Levels (mmol/L) by age group during the first Four days post-admission Mean values (± standard error) of blood glucose levels in mmol/L, stratified by age < 70 years and ≥ 70 years. < 70 years ≥ 70 years initial Glucose 16,17 ± 4,51 14,32 ± 1,43 D 1 Glucose 6h 12,89 ± 2,40 13,95 ± 1,27 D 1 Glucose 12h 9,89 ± 1,17 12,46 ± 0,87 D 1 Glucose 18h 6,66 ± 0,64 11,12 ± 1,05 D 2 Glucose 0h 8.08 ± 0,40 10,18 ± 0,67 D 2 Glucose 6h 8,97 ± 0,58 10,44 ± 0,61 D 2 Glucose 12h 8,77 ± 0,59 9,49 ± 0,67 D 2 Glucose 18h 7,79 ± 0,34 9,12 ± 0,47 D 3 Glucose 0h 9,83 ± 1,45 9,61 ± 0,63 D 3 Glucose 6h 9,87 ± 1,04 9,04 ± 0,39 D 3 Glucose 12h 9,57 ± 0,80 8,11 ± 0,48 D 3 Glucose 18h 8,79 ± 0,47 7,91 ± 0,45 D 4 Glucose 0h 8,69 ± 0,39 7,51 ± 0,53 Table 4 Temporal Profile of Serum Cortisol Concentrations (nmol/L) by Sex and Age Group Mean values (± standard error) of cortisol concentrations in nmol/L, stratified by sex and age < 70 vs. ≥70 years over the first 96 hours of hospitalization. initial 24 hours 48 hours 72 hours 96 hours female 2345,00 ± 520,59 690,39 ± 111,61 727,00 ± 86,98 829,83 ± 128,44 742,42 ± 114,16 male 2299,00 ± 750,56 597,48 ± 114,05 818 ± 156,87 517,00 ± 87,26 649,1 ± 78,88 < 70 years 2776,63 ± 1010,25 583,11 ± 128,58 753,44 ± 171,56 638,36 ± 124,12 715,71 ± 97,65 ≥ 70 years 1949,10 ± 392,59 678,94 ± 106,26 806,05 ± 117,17 654,00 ± 100,75 660,81 ± 89,66 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7041208","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":484424631,"identity":"2be9cce5-f196-42b4-8a9c-b038d6057309","order_by":0,"name":"Priyanka Boettger","email":"data:image/png;base64,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","orcid":"","institution":"University of Giessen","correspondingAuthor":true,"prefix":"","firstName":"Priyanka","middleName":"","lastName":"Boettger","suffix":""},{"id":484424632,"identity":"7d7a49fc-8b37-4a9b-8223-f0579285ccc9","order_by":1,"name":"Laura Pallmann","email":"","orcid":"","institution":"University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Pallmann","suffix":""},{"id":484424633,"identity":"ee55012e-7a36-4996-9be3-c1d8cb888aca","order_by":2,"name":"Jamschid Sedighi","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Jamschid","middleName":"","lastName":"Sedighi","suffix":""},{"id":484424634,"identity":"09937c25-a58a-4e74-99fc-88d34e68f4fa","order_by":3,"name":"Patrick Kellner","email":"","orcid":"","institution":"Regio Kliniken","correspondingAuthor":false,"prefix":"","firstName":"Patrick","middleName":"","lastName":"Kellner","suffix":""},{"id":484424635,"identity":"f3e091dc-63b0-4302-b4f3-5de8d1f80f8d","order_by":4,"name":"Henning Lemm","email":"","orcid":"","institution":"Marien Kliniken Siegen","correspondingAuthor":false,"prefix":"","firstName":"Henning","middleName":"","lastName":"Lemm","suffix":""},{"id":484424637,"identity":"37ada376-69a6-4367-b0a8-1224489d5581","order_by":5,"name":"Roland Prondzinsky","email":"","orcid":"","institution":"University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg","correspondingAuthor":false,"prefix":"","firstName":"Roland","middleName":"","lastName":"Prondzinsky","suffix":""},{"id":484424639,"identity":"74d30cd2-15dd-49e0-8e05-623c303382f9","order_by":6,"name":"Thomas Karrasch","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Karrasch","suffix":""},{"id":484424642,"identity":"6d32cb73-8ed0-4d2d-a600-c3bf026c7632","order_by":7,"name":"Birgit Assmus","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Birgit","middleName":"","lastName":"Assmus","suffix":""},{"id":484424645,"identity":"c1484840-17dc-431e-b318-95211704529b","order_by":8,"name":"Karl Werdan","email":"","orcid":"","institution":"University Hospital Halle (Saale), Martin-Luther-University Halle-Wittenberg","correspondingAuthor":false,"prefix":"","firstName":"Karl","middleName":"","lastName":"Werdan","suffix":""},{"id":484424648,"identity":"d6c34a8b-9cbe-45f4-8edc-a87be2d382e5","order_by":9,"name":"Michael Buerke","email":"","orcid":"","institution":"Marien Kliniken Siegen","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Buerke","suffix":""}],"badges":[],"createdAt":"2025-07-03 20:23:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7041208/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7041208/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86764953,"identity":"2bd8ff21-9e47-4bfe-8fb2-a6c741c95aba","added_by":"auto","created_at":"2025-07-15 10:56:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":111012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTemporal Changes in Serum Cortisol Levels in Survivors and Non-Survivors With Infarction-Related Cardiogenic Shock \u003c/strong\u003eMean serum cortisol concentrations (± standard error) are shown at admission and at 24, 48, 72, and 96 hours post-admission, stratified by in-hospital survival status. Survivors (blue triangles, dashed line) exhibited a rapid decline in cortisol levels, reaching near-normal range within 24 hours (389.8 nmol/L). In contrast, non-survivors (green circles, solid line) showed persistently elevated cortisol throughout the observation period, with levels at 24 and 48 hours remaining significantly higher (\u003cstrong\u003ep = 0.003\u003c/strong\u003e and \u003cstrong\u003ep = 0.020\u003c/strong\u003e, respectively). The difference in cumulative cortisol exposure (AUC₀–₉₆) between groups was also significant (\u003cstrong\u003ep = 0.016\u003c/strong\u003e), underscoring persistent hypercortisolemia as a marker of poor prognosis.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/112c0e21373ec7242a17ff12.png"},{"id":86765918,"identity":"d6429d88-e713-4279-99e3-2f450c33d386","added_by":"auto","created_at":"2025-07-15 11:04:10","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":103367,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex-Specific Cortisol Kinetics Following Rescue PCI in Cardiogenic Shock \u003c/strong\u003eMean serum cortisol concentrations (± standard error) are shown at admission and through 96 hours post–rescue PCI, stratified by sex: males (blue triangles, solid line) and females (green circles, solid line). Both sexes demonstrated a steep decline in cortisol levels during the first 24 hours, from supraphysiologic concentrations to near the upper limit of the normal range (UNL = 630 nmol/L, dashed line). No statistically significant differences were observed between males and females at any timepoint (p \u0026gt; 0.05 for all comparisons), and cumulative cortisol exposure over 96 hours (AUC₀–₉₆) was comparable (p = 0.38), suggesting cortisol kinetics were independent of sex in this cohort.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/36bebf52fbafcfb95881a91f.png"},{"id":86764955,"identity":"5dcdfa99-8be3-48b4-bf06-911cd3ada7d1","added_by":"auto","created_at":"2025-07-15 10:56:10","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":111488,"visible":true,"origin":"","legend":"\u003cp\u003eCortisol Kinetics Following Rescue PCI in Cardiogenic Shock, Stratified by Age Group Mean serum cortisol concentrations (± standard error) are shown at admission and up to 96 hours post–rescue PCI, stratified by age ≤70 years (blue triangles) and \u0026gt;70 years (green circles). Both age groups exhibited a sharp decline in cortisol levels within the first 24 hours. Although patients ≤70 years had higher initial cortisol levels, this difference did not persist beyond the first day. Cortisol levels stabilized near the upper limit of the normal range (UNL = 630 nmol/L, dashed line) across timepoints. No statistically significant differences were observed between age groups at individual timepoints (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05 for all comparisons). LNL = lower normal limit (180 nmol/L).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/7929a10ea8f82339b597fddb.png"},{"id":86765919,"identity":"a18d8fb7-53c0-4438-ad50-4f8df4515dec","added_by":"auto","created_at":"2025-07-15 11:04:10","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":82066,"visible":true,"origin":"","legend":"\u003cp\u003eIn-hospital mortality by admission cortisol levels in infarction-related cardiogenic shock\u003c/p\u003e\n\u003cp\u003eStacked bar chart depicting the proportion of survivors (blue) and non-survivors (green) stratified by admission serum cortisol concentration:\u003c/p\u003e\n\u003cp\u003e• Low (\u0026lt;552 nmol/L, n = 6)\u003c/p\u003e\n\u003cp\u003e• Intermediate (552–1240 nmol/L, n = 18)\u003c/p\u003e\n\u003cp\u003e• High (\u0026gt;1240 nmol/L, n = 15)\u003c/p\u003e\n\u003cp\u003eA significant stepwise increase in in-hospital mortality was observed with rising cortisol levels: 16.7% in the low group, 38.9% in the intermediate group, and 60.0% in the high group (p = 0.047, Chi-square test for trend). The odds of death in the high cortisol group were 7.5 times higher than in the low group (OR = 7.50, 95% CI: 0.70–79.7), supporting a dose–response relationship between admission hypercortisolemia and adverse outcomes. These findings underscore the prognostic relevance of early endocrine profiling in infarction-related cardiogenic shock.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/1081bd0eaf089645f7064856.png"},{"id":86764957,"identity":"3be41fab-e186-4463-baab-14ae9722ea16","added_by":"auto","created_at":"2025-07-15 10:56:10","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":105837,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal Blood Glucose Profiles in Survivors and Non-Survivors with Cardiogenic Shock Mean blood glucose concentrations (± standard error) are shown over 96 hours in survivors (blue triangles) and non-survivors (green circles) following admission for infarction-related cardiogenic shock. Both groups exhibited an initial decline in glucose levels, with non-survivors starting from significantly higher values at admission. Despite similar glycemic trajectories thereafter, glucose levels remained moderately elevated in non-survivors throughout the observation period. However, no statistically significant differences were observed at individual timepoints (\u003cem\u003ep\u003c/em\u003e \u0026gt; 0.05 across all comparisons). These findings suggest that the extent of initial hyperglycemia may carry more prognostic weight than subsequent glycemic fluctuations.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/bc6591514fa9a041a5c6a418.png"},{"id":86765922,"identity":"983b8c8e-9fb4-4f92-bc7c-785acc3f0270","added_by":"auto","created_at":"2025-07-15 11:04:10","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":83334,"visible":true,"origin":"","legend":"\u003cp\u003eIn-Hospital Mortality by Admission Glucose Range in Cardiogenic Shock Patients Stacked bar chart showing proportions of survivors (blue) and non-survivors (green) according to admission blood glucose levels: \u0026lt;10 mmol/L (\u003cem\u003en\u003c/em\u003e = 11), 10–15 mmol/L (\u003cem\u003en\u003c/em\u003e = 16), and \u0026gt;15 mmol/L (\u003cem\u003en\u003c/em\u003e = 14). A trend toward increased mortality was observed with rising glucose levels: survival decreased from 64.6% in the \u0026lt;10 mmol/L group to 50.0% in the \u0026gt;15 mmol/L group. While the differences were not statistically significant (\u003cem\u003ep\u003c/em\u003e = 0.19), the findings support the clinical relevance of admission hyperglycemia as a potential risk marker in infarction-related cardiogenic shock.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/ec1c78b0f45c496ff2c1064e.png"},{"id":86764959,"identity":"ae55b90c-7ff3-498b-a4b5-161146fc3d77","added_by":"auto","created_at":"2025-07-15 10:56:10","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":68896,"visible":true,"origin":"","legend":"\u003cp\u003eIn-Hospital Mortality in Patients With and Without Type 2 Diabetes Mellitus Stacked bar chart displaying survival (blue) and mortality (green) proportions in patients with known type 2 diabetes mellitus (T2DM) versus those without diabetes at admission. Among patients with T2DM (\u003cem\u003en\u003c/em\u003e = 24), 58.3% survived and 41.7% died. In patients without T2DM (\u003cem\u003en\u003c/em\u003e = 17), the survival rate was 52.9%, with 47.1% mortality. The difference in outcome between groups was not statistically significant (\u003cem\u003ep\u003c/em\u003e = 0.72, Fisher’s exact test), suggesting that pre-existing diabetes was not an independent predictor of in-hospital mortality in this cohort of infarction-related cardiogenic shock patients.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/aca39b7f626e6b11928c1c91.png"},{"id":86764964,"identity":"88a45a4d-b4fe-4364-8af7-4f9eb46ca905","added_by":"auto","created_at":"2025-07-15 10:56:11","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":31094,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCardiovascular Effects of Insulin in Critical Illness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInsulin exerts multiple cardioprotective actions, including attenuation of inflammatory responses, enhancement of endothelial function, inhibition of oxidative stress, and improvement of myocardial glucose uptake. These effects collectively support cardiac output and hemodynamic stability in acute settings such as cardiogenic shock.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/9104bce26551f4f5e85cb45f.png"},{"id":87281880,"identity":"53f56e09-c705-4dd8-b578-9854b8fc7331","added_by":"auto","created_at":"2025-07-22 09:53:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2065442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7041208/v1/0058defa-b4b7-4def-bf52-9d41e991ab86.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Prognostic Role of Cortisol and Glucose Dynamics in Cardiogenic Shock-Insights from a prospective observational cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cb\u003eCardiogenic shock and the systemic stress response\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCardiogenic shock (CS) complicates up to 10% of acute coronary syndromes (ACS), including STEMI and NSTE-ACS, and remains associated with high short-term mortality. It often precipitates multiorgan dysfunction\u0026mdash;affecting kidneys, lungs, and liver\u0026mdash;necessitating vasopressors, mechanical circulatory support, ventilation, and renal replacement therapy. Beyond hemodynamic collapse, acute myocardial injury induces a complex systemic stress response, notably involving the hypothalamic-pituitary-adrenal (HPA) axis. Dysregulation of this neurohormonal system may aggravate shock physiology and represents a potential therapeutic target.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCortisol and glucose: mediators of the acute phase response\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCortisol, the primary effector of the HPA axis, is secreted in circadian pulses under CRH and ACTH regulation. In critical illness, this rhythm is disrupted by cytokines and sympathetic activation, leading to ACTH-independent hypercortisolism \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Cortisol sustains blood pressure, increases cardiac output, and enhances catecholamine sensitivity. It inhibits iNOS, arginine transport, and tetrahydrobiopterin synthesis, thereby limiting nitric oxide\u0026ndash;mediated vasodilation. Over time, synthesis of other adrenal hormones declines, suggesting a shift toward glucocorticoid dominance and potential relative adrenal insufficiency, particularly in older ICU patients \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Although cortisol supports hemodynamics, it may also impair immune function, wound healing, and muscle integrity \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGlucose homeostasis is equally disrupted in critical illness. Stress-induced hyperglycemia results from enhanced gluconeogenesis, peripheral insulin resistance, and elevated catabolic hormones\u0026mdash;cortisol, glucagon, catecholamines, and growth hormone\u0026mdash;while insulin levels remain unchanged or suboptimal. Cytokine-mediated insulin resistance impairs GLUT-4\u0026ndash;dependent glucose uptake in muscle and adipose tissue.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStress hyperglycemia and cardiovascular outcomes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStress hyperglycemia promotes adverse cardiovascular effects, including endothelial dysfunction, oxidative stress, platelet activation, and osmotic diuresis, all of which impair myocardial function and perfusion \u003csup\u003e4 5\u003c/sup\u003e. While overt diabetes mellitus is a well-established cardiovascular risk factor, fasting glucose levels between 6.1 and 7.0 mmol/L\u0026mdash;classified as impaired glucose tolerance\u0026mdash;also correlate with micro- and macrovascular pathology. In a study of 999 patients with myocardial infarction, Zeller et al. (2003) demonstrated that both manifest diabetes and impaired glucose tolerance were independently associated with an increased risk of cardiogenic shock and in-hospital mortality \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThese findings suggest that dysregulated cortisol and glucose responses are not merely epiphenomena but active contributors to the pathophysiology of infarction-related cardiogenic shock. Identifying and targeting these metabolic derangements may offer novel avenues for risk stratification and therapeutic intervention in this critically ill population.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eA total of 44 consecutive patients with cardiogenic shock were prospectively enrolled in the Cardiogenic Shock Registry Halle at the Department of Cardiology and Internal Medicine III, University Hospital of Martin Luther University Halle-Wittenberg. The diagnosis of cardiogenic shock was established during initial coronary angiography based on the following criteria: (1) systolic blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;90 mmHg, (2) clinical signs of systemic hypoperfusion, (3) indexed cardiac output\u0026thinsp;\u0026lt;\u0026thinsp;2.2 L/min/m\u0026sup2;, and (4) pulmonary capillary wedge pressure\u0026thinsp;\u0026gt;\u0026thinsp;15 mmHg.\u003c/p\u003e\u003cp\u003ePatients referred for cardio-thoracic surgery during their hospital course were excluded, as subsequent surgical interventions would confound endocrine and metabolic measurements, limiting comparability with the non-surgical cohort. All oral antidiabetic drugs were paused.\u003c/p\u003e\u003cp\u003eClinical and laboratory data were collected on admission (\"baseline\"), immediately before and after percutaneous coronary intervention (PCI), six hours post-PCI, daily until day 7, and additionally on days 14 and 28. Routine blood sampling occurred at baseline, and at 24, 48, 72, and 96 hours post-PCI. Blood glucose was assessed at baseline and subsequently every six hours until day 4, among those the first sample was fasting glucose.\u003c/p\u003e\u003cp\u003eAt 5:00 a.m. each day, the central laboratory analyzed routine parameters including electrolytes, complete blood count, coagulation profile, cardiac biomarkers, renal and hepatic function tests, pancreatic enzymes, metabolic markers (e.g., lipids, proteins, glucose), and inflammatory markers. Additional plasma samples were centrifuged, aliquoted, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for later analysis. Cortisol concentrations were determined from these samples in the certified Endocrinology Laboratory of the University Hospital.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistic Methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics, version 27.0 (IBM Corp., Armonk, NY). Continuous variables were assessed for normality using the Shapiro\u0026ndash;Wilk test and reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE) or median with interquartile range, as appropriate. Group comparisons used t-tests or Mann\u0026ndash;Whitney U tests for continuous data, and Chi-square or Fisher\u0026rsquo;s exact tests for categorical data. Statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (two-sided). Temporal changes in continuous variables were evaluated using repeated-measures ANOVA or linear mixed-effects models with Bonferroni correction. Area under the curve (AUC) from baseline to 72 hours was calculated using the trapezoidal rule and compared using t-tests. Correlations were assessed with Pearson\u0026rsquo;s or Spearman\u0026rsquo;s coefficients, and effect sizes reported as Cohen\u0026rsquo;s d.\u003c/p\u003e\u003cp\u003eVisualizations were created using SPSS and Apple Numbers, with error bars reflecting standard error unless stated otherwise.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 45 patients with cardiogenic shock were prospectively enrolled in the \u003cem\u003eCardiogenic Shock Registry\u003c/em\u003e at University Hospital Halle. In all cases, cardiogenic shock occurred secondary to acute myocardial infarction (STEMI or NSTE-ACS) Three patients were excluded from final analysis due to referral for coronary artery bypass grafting (CABG) and incomplete sampling, yielding a final cohort of 42 patients.\u003c/p\u003e\n\u003cp\u003eThe cohort comprised 15 women (36.6%) and 26 men (63.4%). The overall in-hospital mortality rate was 43.9% (95% CI, 28.3\u0026ndash;59.4%), consistent with contemporary cardiogenic shock registries. Among women, 6 of 15 (40.0%; 95% CI, 16.3\u0026ndash;67.6%) died, compared with 12 of 26 (46.2%; 95% CI, 26.6\u0026ndash;66.6%) men. This difference was not statistically significant (\u003cem\u003ep\u003c/em\u003e = 0.70, Fisher\u0026rsquo;s exact test). Survivors and non-survivors did not differ significantly by sex distribution (\u003cem\u003ep\u003c/em\u003e = 0.70).\u003c/p\u003e\n\u003cp\u003eBaseline demographic and clinical parameters\u0026mdash;including age, cardiovascular risk factors, comorbidities, and BMI\u0026mdash;are summarized in Table 1, with subgroup comparisons by sex and survival status. The patient population reflects the typical clinical spectrum of infarction-related cardiogenic shock and appears broadly representative of other real-world registry cohorts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographics and Prehospital Clinical Status\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age at hospital admission was 67.5 \u0026plusmn; 10.9 years. Women were on average older than men (69.7 \u0026plusmn; 10.1 vs. 66.2 \u0026plusmn; 9.6 years; p = 0.18). Survivors were significantly younger than non-survivors (64.9 \u0026plusmn; 9.8 vs. 70.8 \u0026plusmn; 11.4 years; p = 0.048), identifying age as a potential prognostic factor. The cohort had a mean body weight of 87.1 \u0026plusmn; 13.6 kg (range: 60\u0026ndash;125 kg) and mean height of 171.2 \u0026plusmn; 8.2 cm (range: 145\u0026ndash;190 cm), yielding an average BMI of 29.9 \u0026plusmn; 6.3 kg/m\u0026sup2;. Women had significantly higher BMI values than men (31.5 \u0026plusmn; 6.7 vs. 28.7 \u0026plusmn; 5.9 kg/m\u0026sup2;; p = 0.046); 60% of women and 30% of men were obese (BMI \u0026gt;30 kg/m\u0026sup2;). However, BMI was not significantly associated with in-hospital mortality (r = 0.11, p = 0.51).\u003c/p\u003e\n\u003cp\u003ePrehospital clinical status reflected the severity of illness: 78% (32/41) of patients were intubated on arrival, and 34% (14/41) had undergone prehospital cardiopulmonary resuscitation (CPR). Among these, 6 (43%) presented with ventricular fibrillation. A total of 16 patients (39%) received revascularization therapy before hospital arrival: 11 received thrombolysis, 4 underwent percutaneous transluminal coronary angioplasty (PTCA), and 1 received both. In contrast, 7 patients (17%) had no prehospital reperfusion initiated before admission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCirculatory Parameters and Cardiac Status at Hospital Admission\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt admission, the mean systolic blood pressure (SBP) of the entire cohort was 104 mmHg (95% CI, 97.5\u0026ndash;110.5), and the mean heart rate was 94 beats/min (95% CI, 89\u0026ndash;99). A statistically significant difference in SBP was observed between survivors and non-survivors: 116.6 mmHg (\u0026plusmn;12.4) vs. 88.5 mmHg (\u0026plusmn;11.3), respectively (\u003cem\u003ep\u003c/em\u003e = 0.001). While the SBP values of both groups converged over the course of the first 24 hours (108.1 vs. 100.1 mmHg), survivors maintained a trend toward greater circulatory stability (\u003cem\u003ep\u003c/em\u003e = 0.06). The mean cardiac index increased from 1.96 \u0026plusmn; 0.2 L/min/m\u0026sup2; at baseline to 2.57 \u0026plusmn; 0.3 L/min/m\u0026sup2; by the end of the first day, indicating hemodynamic improvement following revascularization and stabilization. On admission, the mean serum troponin I level was 23.04 \u0026plusmn; 5.07 \u0026micro;g/L. Values were higher in non-survivors (26.13 \u0026plusmn; 9.11 \u0026micro;g/L) than in survivors (20.76 \u0026plusmn; 5.84 \u0026micro;g/L), although the difference did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.31).\u003c/p\u003e\n\u003cp\u003eOf the 41 patients, 40 (98%) underwent coronary angiography at the University Hospital. Among these, 2 received balloon angioplasty (PTCA) alone, while 27 underwent PTCA with stent implantation. The majority of interventions (73.1%) were performed within two hours of admission. Circulatory support devices were required in over 75% of patients. Vasopressor and inotropic therapy was initiated in most patients: norepinephrine and dobutamine in over 80%, and additional epinephrine in 22%. All patients received acetylsalicylic acid (ASA) and heparin upon admission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCortisol Dynamics and Corticosteroid Influence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the time of admission, before coronary intervention, the mean serum cortisol concentration was markedly elevated at 2316.9 \u0026plusmn; 495.7 nmol/L (reference range: 180\u0026ndash;630 nmol/L), with a median of 1068.5 nmol/L. The range extended from 119 to 16,212 nmol/L; the latter value was excluded from analysis as a statistical outlier. Following exclusion, 40 patients were included in the cortisol trajectory analysis. Cortisol concentrations declined significantly over the first 24 hours from 1919.9 \u0026plusmn; 428.7 nmol/L to 599.1 \u0026plusmn; 125.4 nmol/L (p = 0.0006), returning to the normal range in most patients. Patients treated with hydrocortisone or prednisolone (n=7) had similar cortisol levels at baseline (2305.8 nmol/L) compared to those without corticosteroid therapy (2319.1 nmol/L), and were excluded from subsequent subgroup analyses to avoid confounding. After excluding corticosteroid-treated patients, survivors consistently exhibited lower cortisol concentrations than non-survivors across all timepoints. At 24 hours, mean cortisol in survivors had normalized to 389.8 nmol/L, whereas in non-survivors it remained elevated at 729.7 nmol/L. Although the initial difference at admission was not statistically significant (p = 0.29), between-group differences became significant at 24 hours (p = 0.003) and remained so at 72 hours (p = 0.020), suggesting persistent hypercortisolemia is associated with worse outcomes (see Figure 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCortisol Exposure Over Time (AUC Analysis)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo quantify cumulative cortisol exposure, we calculated the area under the curve (AUC₀\u0026ndash;₉₆) from admission to 96 hours using the trapezoidal rule, based on group mean cortisol values.\u003c/p\u003e\n\u003cp\u003eFemale patients exhibited no significant differences in total cortisol exposure compared to male patients (AUC₀\u0026ndash;₉₆: 90,982 vs. 81,757 nmol\u0026middot;h/L (p = 0.38), and no significant differences were detected at any individual time point (Figure 2). In contrast, non-survivors showed substantially greater cumulative cortisol levels than survivors (AUC₀\u0026ndash;₉₆: 97,988 vs. 65,476 nmol\u0026middot;h/L; p = 0.016), supporting the association between persistent hypercortisolemia and adverse outcomes in infarction-related cardiogenic shock (Figure 1). The difference in AUC between survival groups was more pronounced than at any single timepoint, highlighting the value of temporal hormone profiling over isolated measurements.\u003c/p\u003e\n\u003cp\u003eThese findings suggest that dynamic cortisol suppression within the first 24\u0026ndash;48 hours may serve as a prognostic marker, while sex-related differences in cortisol kinetics appear less clinically relevant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk Stratification by Cortisol Thresholds\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the prognostic relevance of admission cortisol concentrations, patients were stratified into three groups based on thresholds previously validated in septic shock (Sam et al., 2004): low (\u0026lt;552 nmol/L; n = 6), intermediate (552\u0026ndash;1240 nmol/L; n = 18), and high (\u0026gt;1240 nmol/L; n = 15). In-hospital mortality increased stepwise across these strata: 16.7% in the low group (1/6), 38.9% in the intermediate group (7/18), and 60.0% in the high group (9/15). This trend reached statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.047, Chi-square test for trend).\u003c/p\u003e\n\u003cp\u003eAlthough confidence intervals were wide due to small sample sizes, the odds of death were markedly elevated in the high cortisol group compared to the low group (OR = 7.50; 95% CI: 0.70\u0026ndash;79.7) and moderately elevated compared to the intermediate group (OR = 2.40; 95% CI: 0.65\u0026ndash;9.01). A positive correlation between cortisol category and in-hospital mortality was observed (Spearman\u0026rsquo;s r = 0.42, \u003cem\u003ep\u003c/em\u003e = 0.008), suggesting a dose\u0026ndash;response relationship between stress hypercortisolemia and adverse outcome.\u003c/p\u003e\n\u003cp\u003eThese findings support the clinical utility of cortisol-based risk stratification at admission. As illustrated in Figure 4, baseline cortisol levels inversely correlated with survival. Importantly, subgroup analyses by sex and age (\u0026lt;70 vs. \u0026ge;70 years) revealed no significant differences in cortisol kinetics (see Table 4), indicating that the prognostic impact of cortisol was independent of demographic characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiabetes Mellitus and Blood Glucose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt the time of admission, the mean blood glucose level in the cohort was 12.9 \u0026plusmn; 1.2 mmol/L (median: 12.4 mmol/L; range: 4.7\u0026ndash;40.2 mmol/L), significantly exceeding the upper limit of normal (\u0026lt;6.1 mmol/L). Only 4 of 41 patients (9.8%) presented with glucose levels within the normal range. The prevalence of diagnosed type 2 diabetes mellitus (T2DM) was high, with 24 of 41 patients (58.5%) previously diagnosed, and an equal sex distribution (12 males, 12 females). In-hospital mortality did not differ significantly between patients with and without diabetes. Among those with T2DM, 10 of 24 (41.7%) died, compared to 8 of 17 (47.1%) without T2DM (p = 0.72, Fisher\u0026rsquo;s exact test), suggesting that baseline diabetes status was not independently associated with mortality in this cohort (see Figure 7). Insulin therapy was initiated in 37 of 41 patients (90.2%) during hospitalization. The 4 patients who did not receive insulin included two who died within the first 24 hours\u0026mdash;likely prior to initiation of glycemic control\u0026mdash;and two who maintained stable glucose levels below 8.8 mmol/L throughout admission.\u003c/p\u003e\n\u003cp\u003eOver the first 96 hours, blood glucose levels showed a general downward trend under insulin treatment, with transient increases in the early morning and midday periods, consistent with diurnal stress responses. Time-course analysis by survival status revealed similar glycemic trajectories in both groups, with no statistically significant differences at any timepoint (p \u0026gt; 0.05 across all measurements; see Figure 5). Among a total of 500 glucose measurements, the lowest value recorded was 3.4 mmol/L, and values \u0026lt;5.0 mmol/L were observed at 9 distinct timepoints (1.8%), suggesting that hypoglycemia was rare and transient. There were hardly any differences between the sexes and between the age groups (see Table 1 and 2).\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eAdmission Hyperglycemia and Risk Stratification\u003c/h3\u003e\n\u003cp\u003eTo further evaluate the prognostic value of early hyperglycemia, the cohort was stratified into three subgroups based on admission glucose levels, independent of pre-existing diabetes mellitus:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 1:\u003c/strong\u003e \u0026lt;10 mmol/L (\u003cem\u003en\u003c/em\u003e = 11)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 2:\u003c/strong\u003e 10\u0026ndash;15 mmol/L (\u003cem\u003en\u003c/em\u003e = 16)\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eGroup 3:\u003c/strong\u003e \u0026gt;15 mmol/L (\u003cem\u003en\u003c/em\u003e = 14)\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eA numerically progressive increase in mortality was observed with rising glucose strata (Figure 6). In-hospital mortality was 36.4% (4/11) in Group 1, 43.8% (7/16) in Group 2, and 50.0% (7/14) in Group 3. Although this did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.47, Chi-square test), the directionality was consistent with prior analyses and suggests a clinically meaningful relationship\u0026nbsp;\u003csup\u003e7\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe absolute risk difference between the lowest and highest glucose groups was 13.6% (95% CI: \u0026minus;25.7 to +51.5, \u003cem\u003ep\u003c/em\u003e = 0.70, Fisher\u0026rsquo;s exact test). A binary comparison of mortality between patients with admission glucose \u0026gt;15 mmol/L versus \u0026le;15 mmol/L revealed a numerically higher mortality in the hyperglycemic group (50.0% vs. 40.7%, risk difference 9.3%; 95% CI: \u0026minus;19.8 to +38.5; \u003cem\u003ep\u003c/em\u003e = 0.55, Fisher\u0026rsquo;s exact test), which was not statistically significant.\u003c/p\u003e\n\u003cp\u003eWe also examined mortality by diabetes status. Among patients with diagnosed type 2 diabetes mellitus (T2DM, \u003cem\u003en\u003c/em\u003e = 24), mortality was 41.7%, compared to 47.1% in patients without T2DM (\u003cem\u003en\u003c/em\u003e = 17) (Figure 7), which was not statistically significant (\u003cem\u003ep\u003c/em\u003e = 0.72, Fisher\u0026rsquo;s exact test). These counterintuitive findings may be explained by pre-existing antihyperglycemic therapy, resulting in more attenuated glucose levels at admission. Mean glucose on admission in patients with T2DM was numerically lower than in those without T2DM (12.3 \u0026plusmn; 3.8 vs. 13.6 \u0026plusmn; 4.1 mmol/L), though this difference did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.26, unpaired \u003cem\u003et\u003c/em\u003e-test).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCumulative Glucose Exposure (AUC Analysis)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCumulative glucose exposure over 96 hours (AUC₀\u0026ndash;₉₆) was calculated using the trapezoidal rule. The average AUC was slightly higher in non-survivors (1,198 mmol\u0026middot;h/L) compared to survivors (1,084 mmol\u0026middot;h/L), although this difference did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e = 0.11). Glucose trajectories remained similar across groups, but the extent and persistence of early hyperglycemia appear to influence outcome. However, mortality was lower in CS patients when admission glucose levels as well as serial levels within the first 24h were lower. These results support the relevance of early glucose control and reinforce admission glucose as a simple, modifiable predictor of mortality in this setting.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eCardiogenic shock (CS) following myocardial infarction initiates a profound neuroendocrine response, yet the prognostic significance of hormonal stress markers remains underexplored. In this prospective cohort, we demonstrate that patients with infarction-related CS exhibit marked hypercortisolemia at presentation, with mean cortisol levels (2316.9\u0026thinsp;\u0026plusmn;\u0026thinsp;482.1 nmol/L) nearly fivefold above the upper reference limit. These levels far exceed those reported in septic shock cohorts, including the Cohort of Annane et al. \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e (938 nmol/L), Ray et al. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e (1532 nmol/L), and Bendel et al. \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e (793 nmol/L). In comparison, Ho et al. observed basal cortisol concentrations of 880\u0026thinsp;\u0026plusmn;\u0026thinsp;79 nmol/L in septic shock, 417\u0026thinsp;\u0026plusmn;\u0026thinsp;45 nmol/L in sepsis, and 352\u0026thinsp;\u0026plusmn;\u0026thinsp;34 nmol/L in healthy controls \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. This exaggerated adrenal response likely reflects the combined physiological insult of myocardial necrosis and systemic hypoperfusion.\u003c/p\u003e\u003cp\u003eImportantly, cortisol dynamics differed by outcome: survivors showed a more rapid decline, with levels normalizing within 24 hours, whereas non-survivors exhibited persistent hypercortisolemia. Stratification of patients by admission cortisol revealed a stepwise increase in mortality, in line with prior findings by Sam et al. in septic shock \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Similar U-shaped associations between cortisol and mortality have been described in critical illness and post-cardiac arrest settings\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, suggesting that both adrenal insufficiency and excess may be maladaptive. In our study, persistent elevation appears more prognostically relevant, underscoring hypercortisolemia as a biomarker of failed stress resolution and disease severity in CS. This raises the question of whether glucocorticoid modulation offers therapeutic benefit in selected patients. In septic shock, hydrocortisone therapy remains contentious. The CORTICUS trial showed no mortality reduction, even among corticotropin non-responders, although vasopressor weaning was accelerated\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Six patients, that were excluded from further analyses in our cohort, received hydrocortisone with a mortality of 16.7%, compared to 44% in the overall population. This observation suggests that tailored corticosteroid therapy may benefit patients with relative adrenal dysfunction or refractory shock. However, no ACTH testing was performed, and mechanistic conclusions must remain cautious. Current trials try to address low dose corticosteroid therapy for cardiogenic shock patients\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Notably, cortisol and glucose trajectories in non-survivors were closely aligned, hinting at a shared, dysregulated stress axis.\u003c/p\u003e\u003cp\u003eIndeed, admission hyperglycemia was similarly pronounced, with a mean glucose level of 12,9 mmol/L\u0026mdash;more than twice the upper limit of normal. Only four patients were normoglycemic at presentation, and although glucose levels declined over time, euglycemia was not achieved by day four. No significant difference was observed in glucose kinetics between survivors and non-survivors. Notably, patients without a prior diagnosis of diabetes exhibited higher mortality, indicating that acute stress-induced hyperglycemia\u0026mdash;rather than pre-existing glycemic status\u0026mdash;may be the principal driver of risk in this context.\u003c/p\u003e\u003cp\u003eThis observation aligns with previous studies. Fefer et al. reported increased ICU morbidity in diabetic patients with acute MI, including infections and thromboembolic events \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, yet diabetes per se did not predict mortality in our cohort. Whitcomb et al. found that hyperglycemia was prognostic only in non-diabetic ICU patients\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, while Capes et al. showed that in acute MI, stress hyperglycemia conferred a 3.9-fold increased risk of death in non-diabetics, but only a 1.7-fold increase in diabetics\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Similarly, Marik and Goyal identified stress hyperglycemia as an independent mortality predictor in critical illness, regardless of diabetes status\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePersistent hypercortisolemia likely drives this hyperglycemia through increased gluconeogenesis and insulin resistance\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Elevated cortisol levels have been associated with worse outcomes and higher glucose in acute coronary syndromes and CS \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In the SMART RESCUE trial, admission glucose predicted mortality in CS, particularly among non-diabetics\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The CardShock study further confirmed that severe hyperglycemia (\u0026ge;\u0026thinsp;16.0 mmol/L) was an independent predictor of in-hospital mortality, and was associated with systemic hypoperfusion markers including leukocytosis, elevated lactate, and acidosis\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Tian et al. also reported a U-shaped relationship between the stress hyperglycemia ratio and ICU mortality in CS, reinforcing the need for tailored glucose targets\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThese findings carry important clinical implications. Intensive insulin therapy has shown mortality benefit in surgical ICU settings, as first demonstrated by Van den Berghe et al., who targeted glucose\u0026thinsp;\u0026lt;\u0026thinsp;6.1 mmol/L\u003csup\u003e22\u003c/sup\u003e. Insulin's cardioprotective properties include anti-inflammatory and vasodilatory effects \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, the risk of hypoglycemia is substantial: 11.8% in the intensive group versus 1.8% in the standard care group in follow-up trials \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In our cohort, paradoxically, patients with initial glucose\u0026thinsp;\u0026lt;\u0026thinsp;6.1 mmol/L had the worst outcomes, potentially reflecting abrupt glycemic shifts after prehospital insulin administration. This supports Van den Berghe\u0026rsquo;s proposal that insulin strategies should be individualized based on premorbid glycemic exposure \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe lack of consistent mortality benefit and excess hypoglycemia in the Brunkhorst trial on intensified insulin therapy in severe sepsis led to early termination, emphasizing the dangers of overly aggressive glucose lowering \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Moving forward, insulin protocols in CS may need to favor moderate correction with real-time monitoring rather than tight control, particularly in hemodynamically unstable patients.\u003c/p\u003e\u003cp\u003eTaken together, our findings (see Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e for an overview of insulin\u0026rsquo;s cardiovascular effects) identify admission cortisol and glucose levels as robust, rapidly available biomarkers for early risk stratification in infarction-related cardiogenic shock. The endocrine\u0026ndash;metabolic response appears tightly coupled, and persistent dysregulation\u0026mdash;manifested by sustained hypercortisolemia and stress hyperglycemia\u0026mdash;portends poor outcome. These parameters are measurable in routine clinical practice and may aid in triaging patients for closer hemodynamic monitoring or early therapeutic interventions. While current evidence does not support routine corticosteroids or intensive insulin therapy in CS, our data provide a compelling rationale for individualized endocrine profiling. Future trials should evaluate whether targeted modulation of the HPA axis and glucose metabolism, using real-time cortisol and glucose kinetics, can improve survival while minimizing adverse effects. Advances in continuous monitoring, AI-driven insulin dosing, and safer glucocorticoid thresholds may help translate these insights into clinical benefit \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn conclusion, this study provides novel evidence that the trajectory\u0026mdash;not merely the magnitude\u0026mdash;of cortisol and glucose levels in cardiogenic shock holds key prognostic value. Integration of endocrine and metabolic profiling may define a new frontier in risk-adapted, physiology-guided management of this high-mortality condition.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA key strength of this study is its prospective design with detailed temporal profiling of both cortisol and glucose levels in a critically ill, under-investigated population\u0026mdash;patients with infarction-related cardiogenic shock. Serial measurements allowed us to assess dynamic trends rather than rely on single timepoints, and all assays were conducted in a standardized hospital laboratory setting, enhancing data reliability. The integration of endocrine and metabolic markers offers novel insight into the physiologic stress response and its prognostic relevance. However, several limitations must be acknowledged. This was a single-center study with a limited sample size, which may affect generalizability. Adrenal function testing (e.g., ACTH stimulation) was not performed, preventing definitive assessment of adrenal insufficiency. Glycemic management was not protocolized, and insulin initiation varied according to clinical judgment, introducing potential treatment heterogeneity. Finally, the observational design limits causal inference.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eInfarction-related cardiogenic shock triggers a profound metabolic response, marked by cortisol levels nearly five times above normal and parallel elevations in glucose. Persistent hypercortisolemia and initial hyperglycemia were both associated with increased in-hospital mortality, independent of diabetes status. Survivors showed a more rapid normalization of both axes. These findings position admission cortisol and initial glucose not only as biomarkers of illness severity, but as potential therapeutic targets. Rapid glucose adjustment (RGA) within the first 24h might be a new strategy. Early endocrine profiling may offer a window for timely risk stratification and intervention in cardiogenic shock.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK.W. and M.B. conceptualized the study. P.B., L.P., J.S., and H.L. contributed to data collection and patient enrollment. L.P. and P.K. conducted the statistical analyses. P.B. and L.P. drafted the initial manuscript. T.K., B.A., and R.P. provided endocrinological and methodological expertise, they also revised the manuscript. K.W. and M.B. supervised the study and critically revised the manuscript. All authors reviewed and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank our colleagues at the University Hospital of Gie\u0026szlig;en for their valuable contributions to this study. We also acknowledge the support of the technical and administrative staff involved in data collection and patient care. Additionally, we are grateful for the resources provided by our respective institutions.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/em\u003e: All authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding\u003c/strong\u003e:\u003c/em\u003e This study received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthical approval and informed consent\u003c/strong\u003e\u003c/em\u003e: The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Martin Luther University Halle-Wittenberg. 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Stress hyperglycemia is associated with poor prognosis in critically ill patients with cardiogenic shock. Front Endocrinol (Lausanne). 2024;15:1446714. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fendo.2024.1446714\u003c/span\u003e\u003cspan address=\"10.3389/fendo.2024.1446714\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan den Berghe G, Wouters PJ, Bouillon R, Weekers F, Verwaest C, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P. Outcome benefit of intensive insulin therapy in the critically ill: Insulin dose versus glycemic control. 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Diabetes. 2006;55:3151\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2337/db06-0855\u003c/span\u003e\u003cspan address=\"10.2337/db06-0855\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBrunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, et al. Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med. 2008;358:125\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1056/NEJMoa070716\u003c/span\u003e\u003cspan address=\"10.1056/NEJMoa070716\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBraithwaite SS. Inpatient insulin therapy. Curr Opin Endocrinol Diabetes Obes. 2008;15:159\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MED.0b013e3282f827e7\u003c/span\u003e\u003cspan address=\"10.1097/MED.0b013e3282f827e7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eBaseline Characteristics of the Study Population According to Survival Status, Sex, and Age Group\u003c/strong\u003e \u003cem\u003eValues are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or number (%). Y\u0026thinsp;=\u0026thinsp;years; kg\u0026thinsp;=\u0026thinsp;kilograms; BMI\u0026thinsp;=\u0026thinsp;body mass index; HPT\u0026thinsp;=\u0026thinsp;hypertension; DM\u0026thinsp;=\u0026thinsp;diabetes mellitus; HLP\u0026thinsp;=\u0026thinsp;hyperlipidemia.\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll Patients\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;41)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvivors (n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-survivors (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFemale (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;70 y\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;70 y (n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.8\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e59.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.9\u0026thinsp;\u0026plusmn;\u0026thinsp;15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e91.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeight, cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e171.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e174.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e176.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e162.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e177.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e165.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e29.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrior MI, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrior HF, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (44%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (100%)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e13 (72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eType 2 DM, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e10 (56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDyslipidemia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e5 (28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e7 (39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003e\u003cstrong\u003eTemporal profile of blood glucose levels (mmol/L) by sex during the first four days post-admission\u003c/strong\u003e \u003cem\u003eMean values (\u0026plusmn;\u0026thinsp;standard error) of glucose levels in mmol/L, stratified by sex.\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003einitial Glucose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,10\u0026thinsp;\u0026plusmn;\u0026thinsp;1,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,33\u0026thinsp;\u0026plusmn;\u0026thinsp;3,24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,83\u0026thinsp;\u0026plusmn;\u0026thinsp;0,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,36\u0026thinsp;\u0026plusmn;\u0026thinsp;2,30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,03\u0026thinsp;\u0026plusmn;\u0026thinsp;1,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,09\u0026thinsp;\u0026plusmn;\u0026thinsp;0,74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,56\u0026thinsp;\u0026plusmn;\u0026thinsp;1,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,72\u0026thinsp;\u0026plusmn;\u0026thinsp;0,75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,15\u0026thinsp;\u0026plusmn;\u0026thinsp;0,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,33\u0026thinsp;\u0026plusmn;\u0026thinsp;0,71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,40\u0026thinsp;\u0026plusmn;\u0026thinsp;0,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,38\u0026thinsp;\u0026plusmn;\u0026thinsp;0,64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,44\u0026thinsp;\u0026plusmn;\u0026thinsp;0,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,34\u0026thinsp;\u0026plusmn;\u0026thinsp;0,86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,41\u0026thinsp;\u0026plusmn;\u0026thinsp;0,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,61\u0026thinsp;\u0026plusmn;\u0026thinsp;0,63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,56\u0026thinsp;\u0026plusmn;\u0026thinsp;0,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,37\u0026thinsp;\u0026plusmn;\u0026thinsp;1,51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,63\u0026thinsp;\u0026plusmn;\u0026thinsp;0,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,44\u0026thinsp;\u0026plusmn;\u0026thinsp;0,99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,67\u0026thinsp;\u0026plusmn;\u0026thinsp;0,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,73\u0026thinsp;\u0026plusmn;\u0026thinsp;0,87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,14\u0026thinsp;\u0026plusmn;\u0026thinsp;0,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,48\u0026thinsp;\u0026plusmn;\u0026thinsp;0,56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 4 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,38\u0026thinsp;\u0026plusmn;\u0026thinsp;0,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,24\u0026thinsp;\u0026plusmn;\u0026thinsp;0,51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemporal profile of blood glucose Levels (mmol/L) by age group during the first Four days post-admission\u003c/strong\u003e \u003cem\u003eMean values (\u0026plusmn;\u0026thinsp;standard error) of blood glucose levels in mmol/L, stratified by age\u0026thinsp;\u0026lt;\u0026thinsp;70 years and \u0026ge;\u0026thinsp;70 years.\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;70 years\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;70 years\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003einitial Glucose\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,17\u0026thinsp;\u0026plusmn;\u0026thinsp;4,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,32\u0026thinsp;\u0026plusmn;\u0026thinsp;1,43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,89\u0026thinsp;\u0026plusmn;\u0026thinsp;2,40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,95\u0026thinsp;\u0026plusmn;\u0026thinsp;1,27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,89\u0026thinsp;\u0026plusmn;\u0026thinsp;1,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,46\u0026thinsp;\u0026plusmn;\u0026thinsp;0,87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 1 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,66\u0026thinsp;\u0026plusmn;\u0026thinsp;0,64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,12\u0026thinsp;\u0026plusmn;\u0026thinsp;1,05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0,40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,18\u0026thinsp;\u0026plusmn;\u0026thinsp;0,67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,97\u0026thinsp;\u0026plusmn;\u0026thinsp;0,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,44\u0026thinsp;\u0026plusmn;\u0026thinsp;0,61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,77\u0026thinsp;\u0026plusmn;\u0026thinsp;0,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,49\u0026thinsp;\u0026plusmn;\u0026thinsp;0,67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 2 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,79\u0026thinsp;\u0026plusmn;\u0026thinsp;0,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,12\u0026thinsp;\u0026plusmn;\u0026thinsp;0,47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,83\u0026thinsp;\u0026plusmn;\u0026thinsp;1,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,61\u0026thinsp;\u0026plusmn;\u0026thinsp;0,63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 6h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,87\u0026thinsp;\u0026plusmn;\u0026thinsp;1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,04\u0026thinsp;\u0026plusmn;\u0026thinsp;0,39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 12h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,57\u0026thinsp;\u0026plusmn;\u0026thinsp;0,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,11\u0026thinsp;\u0026plusmn;\u0026thinsp;0,48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 3 Glucose 18h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,79\u0026thinsp;\u0026plusmn;\u0026thinsp;0,47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,91\u0026thinsp;\u0026plusmn;\u0026thinsp;0,45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eD 4 Glucose 0h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,69\u0026thinsp;\u0026plusmn;\u0026thinsp;0,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,51\u0026thinsp;\u0026plusmn;\u0026thinsp;0,53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemporal Profile of Serum Cortisol Concentrations (nmol/L) by Sex and Age Group\u003c/strong\u003e \u003cem\u003eMean values (\u0026plusmn;\u0026thinsp;standard error) of cortisol concentrations in nmol/L, stratified by sex and age\u0026thinsp;\u0026lt;\u0026thinsp;70 vs. \u0026ge;70 years over the first 96 hours of hospitalization.\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003einitial\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e24 hours\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e48 hours\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e72 hours\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e96 hours\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2345,00\u0026thinsp;\u0026plusmn;\u0026thinsp;520,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e690,39\u0026thinsp;\u0026plusmn;\u0026thinsp;111,61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e727,00\u0026thinsp;\u0026plusmn;\u0026thinsp;86,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e829,83\u0026thinsp;\u0026plusmn;\u0026thinsp;128,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e742,42\u0026thinsp;\u0026plusmn;\u0026thinsp;114,16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2299,00\u0026thinsp;\u0026plusmn;\u0026thinsp;750,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e597,48\u0026thinsp;\u0026plusmn;\u0026thinsp;114,05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e818 \u0026plusmn; 156,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e517,00\u0026thinsp;\u0026plusmn;\u0026thinsp;87,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e649,1\u0026thinsp;\u0026plusmn;\u0026thinsp;78,88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2776,63\u0026thinsp;\u0026plusmn;\u0026thinsp;1010,25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e583,11\u0026thinsp;\u0026plusmn;\u0026thinsp;128,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e753,44\u0026thinsp;\u0026plusmn;\u0026thinsp;171,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e638,36\u0026thinsp;\u0026plusmn;\u0026thinsp;124,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e715,71\u0026thinsp;\u0026plusmn;\u0026thinsp;97,65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;70 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1949,10\u0026thinsp;\u0026plusmn;\u0026thinsp;392,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e678,94\u0026thinsp;\u0026plusmn;\u0026thinsp;106,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e806,05\u0026thinsp;\u0026plusmn;\u0026thinsp;117,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e654,00\u0026thinsp;\u0026plusmn;\u0026thinsp;100,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e660,81\u0026thinsp;\u0026plusmn;\u0026thinsp;89,66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"cardiogenic shock, glucose, cortisol, survivors, predictors","lastPublishedDoi":"10.21203/rs.3.rs-7041208/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7041208/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCardiogenic shock (CS) after myocardial infarction remains associated with excessive mortality. The prognostic relevance of early metabolic markers\u0026mdash;specifically glucose and cortisol levels\u0026mdash;remains insufficiently defined in this high-risk population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eWe prospectively studied 41 patients with infarction-related CS. Admission glucose and serum cortisol levels were measured within 96 hours. The primary endpoint was in-hospital mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eAdmission glucose levels were \u0026lt;\u0026thinsp;10 mmol/L in 27%, 10\u0026ndash;15 mmol/L in 39%, and \u0026gt;\u0026thinsp;15 mmol/L in 34% of patients. Mortality increased stepwise across strata (36.4%, 43.8%, and 50.0%, respectively), though not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.47). Patients without known diabetes had numerically higher mortality than those with diabetes (47.1% vs. 41.7%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.72), suggesting that acute stress hyperglycemia, rather than chronic glycemic status, may drive risk. Early normalization of glucose within six hours was associated with significantly improved survival (25% vs. 45%; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cortisol levels on admission were profoundly elevated (mean: 2316.9\u0026thinsp;\u0026plusmn;\u0026thinsp;495.7 nmol/L). Survivors exhibited a rapid decline, while non-survivors had persistently elevated levels. Cumulative cortisol exposure (AUC₀\u0026ndash;₉₆) was significantly lower in survivors (65,476 vs. 97,988 nmol\u0026middot;h/L; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), underscoring the prognostic impact of sustained hypercortisolemia.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eElevated glucose and cortisol levels at admission independently predicted mortality in infarction-related CS. Importantly, their early normalization was associated with improved outcomes. These findings identify stress hyperglycemia and hypercortisolemia as actionable risk markers and support targeted endocrine modulation as a potential therapeutic strategy in acute circulatory failure.\u003c/p\u003e","manuscriptTitle":"The Prognostic Role of Cortisol and Glucose Dynamics in Cardiogenic Shock-Insights from a prospective observational cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 10:56:06","doi":"10.21203/rs.3.rs-7041208/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"783e68ce-e500-4ce0-bd8b-44fded455dd2","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-22T09:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-15 10:56:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7041208","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7041208","identity":"rs-7041208","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}