Prognostic significance of early platelet dynamics in Staphylococcus aureus bacteremia

Abstract

Background Platelets are recognized as key immune effectors, but they are targets of bacterial virulence factors. In the present study, we aimed to examine the relationship between early platelet dynamics and the outcome of Staphylococcus aureus bacteremia (SAB). Method Electronic medical records of adult patients hospitalized for SAB between July 2012 and November 2020 were retrospectively reviewed for relevant demographic, laboratory, and clinical data. The outcome endpoints were mortality and microbial persistence. Results Among the 811 patients evaluated, 29% experienced thrombocytopenia on Day 1. Platelet count nadir occurred on Days 2–3 following SAB onset, and Day 4 was a determining point of platelet count trajectory and mortality. Mortality risk was 6% or less for those with normal platelet count by Day 4 regardless of whether they experienced thrombocytopenia on Day 1, but the risk increased to 16–21% for those who experienced thrombocytopenia on Day 4 regardless of whether they had normal platelet count on Day 1 or sustained thrombocytopenia. The duration of bacteremia was prolonged by one day (median 3 d vs. 2 d) for those with sustained thrombocytopenia compared to those without. Conclusion Early platelet dynamics during SAB have prognostic significance and represent an early window for potential platelet-directed therapeutic interventions to improve outcome.

Predictive models for short-term mortality and length of hospital stay among adults with community-onset bacteraemia before and during the COVID-19 pandemic: application of early data dynamics

“…Consistent with the BLOOMY score [ 7 ], the clinical condition on day 0 and day 3 (as demonstrated in Model IV) had been evidenced as the crucial determinates of short-term fatality. Moreover, similar to updated reports that highlighted the importance of dynamic vital signs and laboratory data in predicting short-term mortality among septic or bacteraemic individuals [ 27 , 28 ], the changed variables form day 0 to day 3 (as the component in Model IV) were recognised as the powerful determinants of 30-day mortality, in terms of the changes in the conscious level, respiratory condition, and hemodynamic status, which can be recognised as the responses to prompt antimicrobial therapy and early resuscitation.…”

Machine Learning with Alpha Toxin Phenotype to Predict Clinical Outcome in Patients with Staphylococcus aureus Bloodstream Infection

“…We have previously shown that patients who experienced TC on day 1 of bloodstream infection may recover by day 4 while others who had normal platelet counts on day 1 may develop TC on day 4 depending on the degree of Hla production of the infecting strain and that TC on day 4 was significantly associated with mortality [ 23 ]. A total of 539 images taken with a smartphone representing growth of 229 unique isolates on SBA were employed.…”

Serial platelet count as a dynamic prediction marker of hospital mortality among septic patients

“…Septic patients often exhibit abnormal activation and over-consumption of platelets, which subsequently lead to thrombocytopenia, thereby increasing bleeding risk [ 12 ]. Results from multiple studies have described the prognostic value of early changes in platelet count in septic patients [ 11 , 13 ]. However, the relationship between trajectories of repeated measures of platelet count collected from daily clinical practice and the prognosis of septic patients is not yet clear.…”