Background <p>Critically ill patients with acute myocardial infarction (AMI) frequently exhibit marked inflammatory and immune dysregulation, which substantially increases their risk of short-term mortality. The pan-immune-inflammation value (PIV) represents an integrated index calculated from neutrophil, monocyte, platelet, and lymphocyte counts. There is currently no systematical evaluation clarifying the link of PIV with 60-day in-hospital mortality in the critically ill patients with AMI. The primary objective of the current study was to assess PIV’s prognostic utility and to identify potential threshold effects using data derived from the MIMIC-IV database.</p> Methods <p>Three thousand two hundred twenty-four critically ill patients with AMI were included and stratified into tertiles according to log-PIV: Q1 (low, <i>n</i> = 1,075), Q2 (intermediate, <i>n</i> = 1,074), and Q3 (high, <i>n</i> = 1,075). Kaplan-Meier (KM) survival curves, together with the log-rank test, was applied to analyze differences in 60-day in-hospital mortality across tertiles. Multivariable Cox proportional hazards models were constructed to estimate the corresponding hazard ratios (HRs) for each tertile. Restricted cubic spline (RCS) analysis was carried out to investigate the potential dose-response association between log-PIV and mortality risk, and segmented Cox models were fitted for participants with log-PIV values exceeding the identified inflection point. Subgroup analyses were carried out for assessing potential effect modification.</p> Results <p>KM analysis demonstrated a stepwise decrease in 60-day in-hospital mortality with increasing PIV (<i>p</i> &lt; 0.0001). RCS curves showed a U-shaped pattern of the association between log-PIV and mortality risk, with an inflection point at log-PIV = 5.75, beyond which mortality risk increased linearly (<i>p</i> overall &lt; 0.001). Above this threshold, the unadjusted model showed a 28% higher mortality risk for patients in PIV-Q3 versus those in PIV-Q1 (HR = 1.28; 95% confidence interval [CI]: 1.09–1.51; <i>p</i> = 0.003). This risk was further elevated to 32% following adjustment for demographic variables (HR = 1.32; 95% CI: 1.11–1.55; <i>p</i> = 0.001) and remained significant at 20% after full adjustment (HR = 1.20; 95% CI: 1.01–1.44; <i>p</i> = 0.041). Subgroup analysis revealed that PIV had better predictive performance among patients not receiving anticoagulants (<i>p</i> interaction &lt; 0.05).</p> Conclusion <p>Elevated PIV was independently linked to increased 60-day in-hospital mortality among critically ill patients with AMI. The observed threshold effect warrants further validation in external cohorts. PIV may represent a convenient adjunct marker for risk stratification, although its clinical significance should be further validated in prospective studies. Routine measurement of PIV may enable early detection of high-risk individuals and guide the implementation of timely and targeted clinical management in acute care settings.</p>

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Association of the pan-immune-inflammation value with 60-day in-hospital mortality in critically ill patients with acute myocardial infarction: evidence from the MIMIC-IV database

  • Mingjie Wu,
  • Hanyu Xu,
  • Zhen Jia,
  • Ling Pan

摘要

Background

Critically ill patients with acute myocardial infarction (AMI) frequently exhibit marked inflammatory and immune dysregulation, which substantially increases their risk of short-term mortality. The pan-immune-inflammation value (PIV) represents an integrated index calculated from neutrophil, monocyte, platelet, and lymphocyte counts. There is currently no systematical evaluation clarifying the link of PIV with 60-day in-hospital mortality in the critically ill patients with AMI. The primary objective of the current study was to assess PIV’s prognostic utility and to identify potential threshold effects using data derived from the MIMIC-IV database.

Methods

Three thousand two hundred twenty-four critically ill patients with AMI were included and stratified into tertiles according to log-PIV: Q1 (low, n = 1,075), Q2 (intermediate, n = 1,074), and Q3 (high, n = 1,075). Kaplan-Meier (KM) survival curves, together with the log-rank test, was applied to analyze differences in 60-day in-hospital mortality across tertiles. Multivariable Cox proportional hazards models were constructed to estimate the corresponding hazard ratios (HRs) for each tertile. Restricted cubic spline (RCS) analysis was carried out to investigate the potential dose-response association between log-PIV and mortality risk, and segmented Cox models were fitted for participants with log-PIV values exceeding the identified inflection point. Subgroup analyses were carried out for assessing potential effect modification.

Results

KM analysis demonstrated a stepwise decrease in 60-day in-hospital mortality with increasing PIV (p < 0.0001). RCS curves showed a U-shaped pattern of the association between log-PIV and mortality risk, with an inflection point at log-PIV = 5.75, beyond which mortality risk increased linearly (p overall < 0.001). Above this threshold, the unadjusted model showed a 28% higher mortality risk for patients in PIV-Q3 versus those in PIV-Q1 (HR = 1.28; 95% confidence interval [CI]: 1.09–1.51; p = 0.003). This risk was further elevated to 32% following adjustment for demographic variables (HR = 1.32; 95% CI: 1.11–1.55; p = 0.001) and remained significant at 20% after full adjustment (HR = 1.20; 95% CI: 1.01–1.44; p = 0.041). Subgroup analysis revealed that PIV had better predictive performance among patients not receiving anticoagulants (p interaction < 0.05).

Conclusion

Elevated PIV was independently linked to increased 60-day in-hospital mortality among critically ill patients with AMI. The observed threshold effect warrants further validation in external cohorts. PIV may represent a convenient adjunct marker for risk stratification, although its clinical significance should be further validated in prospective studies. Routine measurement of PIV may enable early detection of high-risk individuals and guide the implementation of timely and targeted clinical management in acute care settings.