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Background <p>Continuous glucose monitoring (CGM) captures dysglycaemia and glycaemic variability after acute coronary syndrome (ACS), but patient-level trajectories from early recovery to mid-term follow-up—particularly in people without diabetes—remain insufficiently characterized.</p> Methods <p>In this prospective multicenter observational study (ORACLE program), consecutive high-risk ACS patients wore a FreeStyle Libre 3/3 Plus sensor for 14–15 days near discharge and again at ~ 4 months. We quantified CGM time-in-range metrics (70–180&#xa0;mg/dL and tight range 70–140&#xa0;mg/dL), time above/below range, and variability/risk indices, including within-day profiles. Clinically relevant changes were categorized using pre-specified thresholds, and predictors of worsening were explored using multivariable models.</p> Results <p>Among all patients, 213 patients had analyzable baseline CGM recordings meeting quality criteria. In the early post-ACS period, median [IQR] time in range 70–180&#xa0;mg/dL was 96.57% [86.91–98.92], time in tight range 70–140&#xa0;mg/dL was 85.00% [62.16–93.24], time above range &gt; 180&#xa0;mg/dL was 1.12% [0.18–9.82], and time below range &lt; 70&#xa0;mg/dL was 0.43% [0.00–1.84], with a mean glucose of 114.26&#xa0;mg/dL [106.26–133.96] and a median glucose management indicator of 6.04% [5.85–6.51]. CGM demonstrated marked inter-individual heterogeneity and a reproducible late-morning (10:00–12:00) vulnerability window with lower range time and higher hyperglycaemic exposure, consistent across diabetes status and similar on weekdays and weekends; adverse CGM profiles were more prominent in patients with diabetes, older individuals, and women. Although CGM parameters improved modestly during the initial monitoring period, glycaemic control showed a slight but consistent deterioration from baseline to ~ 4 months after ACS, including in patients without diabetes. Tight-range time decreased by 4.5% (<i>p</i> = 0.008) and mean glucose increased by 4.67&#xa0;mg/dL (<i>p</i> = 0.03), accompanied by a parallel worsening of variability and glycaemic risk indices. In contrast, HbA1c remained stable over follow-up. Across CGM endpoints, ~ 20–40% of patients showed a worsening trajectory (20.2% by broad time-in-range thresholds); higher comorbidity burden clustered with deterioration, with hypertension and COPD independently associated with tight-range worsening.</p> Conclusions <p>After ACS, CGM reveals substantial inter-individual heterogeneity and a reproducible late-morning vulnerability window. From discharge to mid-term follow-up, deterioration—also affecting patients without diabetes—may be preferentially detected by tight-range and variability/risk metrics that traditional monitoring of blood glucose and static measures such as HbA1c may overlook, supporting CGM-informed phenotyping to refine post-ACS metabolic surveillance.</p> Graphical Abstract <p></p>

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Continuous glucose monitoring trajectories in patients with acute coronary syndrome

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月20日

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  • Arancha Díaz-Expósito,
  • Victoria García-Ruiz,
  • Diego Castillo-Barnes,
  • Andrés Ortiz,
  • Jose Ignacio Larrubia-Valle,
  • Agustín Molinero,
  • Fernando Puyol-Ruiz,
  • Oscar Barquero-Alegre,
  • Nelsa González-Aguado,
  • Laura Martín-Chaves,
  • Jorge Segovia-Reyes,
  • Cristobal Urbano-Carrillo,
  • Juan José Gómez Doblas,
  • Manuel Jiménez-Navarro,
  • Jorge García-Alemán,
  • Jorge Rodríguez-Capitán,
  • Fernando Gómez Peralta,
  • Francesco Costa

摘要

Background

Continuous glucose monitoring (CGM) captures dysglycaemia and glycaemic variability after acute coronary syndrome (ACS), but patient-level trajectories from early recovery to mid-term follow-up—particularly in people without diabetes—remain insufficiently characterized.

Methods

In this prospective multicenter observational study (ORACLE program), consecutive high-risk ACS patients wore a FreeStyle Libre 3/3 Plus sensor for 14–15 days near discharge and again at ~ 4 months. We quantified CGM time-in-range metrics (70–180 mg/dL and tight range 70–140 mg/dL), time above/below range, and variability/risk indices, including within-day profiles. Clinically relevant changes were categorized using pre-specified thresholds, and predictors of worsening were explored using multivariable models.

Results

Among all patients, 213 patients had analyzable baseline CGM recordings meeting quality criteria. In the early post-ACS period, median [IQR] time in range 70–180 mg/dL was 96.57% [86.91–98.92], time in tight range 70–140 mg/dL was 85.00% [62.16–93.24], time above range > 180 mg/dL was 1.12% [0.18–9.82], and time below range < 70 mg/dL was 0.43% [0.00–1.84], with a mean glucose of 114.26 mg/dL [106.26–133.96] and a median glucose management indicator of 6.04% [5.85–6.51]. CGM demonstrated marked inter-individual heterogeneity and a reproducible late-morning (10:00–12:00) vulnerability window with lower range time and higher hyperglycaemic exposure, consistent across diabetes status and similar on weekdays and weekends; adverse CGM profiles were more prominent in patients with diabetes, older individuals, and women. Although CGM parameters improved modestly during the initial monitoring period, glycaemic control showed a slight but consistent deterioration from baseline to ~ 4 months after ACS, including in patients without diabetes. Tight-range time decreased by 4.5% (p = 0.008) and mean glucose increased by 4.67 mg/dL (p = 0.03), accompanied by a parallel worsening of variability and glycaemic risk indices. In contrast, HbA1c remained stable over follow-up. Across CGM endpoints, ~ 20–40% of patients showed a worsening trajectory (20.2% by broad time-in-range thresholds); higher comorbidity burden clustered with deterioration, with hypertension and COPD independently associated with tight-range worsening.

Conclusions

After ACS, CGM reveals substantial inter-individual heterogeneity and a reproducible late-morning vulnerability window. From discharge to mid-term follow-up, deterioration—also affecting patients without diabetes—may be preferentially detected by tight-range and variability/risk metrics that traditional monitoring of blood glucose and static measures such as HbA1c may overlook, supporting CGM-informed phenotyping to refine post-ACS metabolic surveillance.

Graphical Abstract