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Published on: January 27, 2023
Multicentric Standardized Flow Cytometry Routine Assessment of Patients With Sepsis to Predict Clinical Worsening
Thomas Daix1, Estelle Guerin2, Elsa Tavernier3
1Réanimation Polyvalente, CHU Dupuytren, Limoges, France; Inserm CIC1435, CHU Dupuytren, Limoges, France.
Background:
In this study, we primarily sought to assess the ability of flow cytometry to predict early clinical deterioration and overall survival in patients with sepsis admitted in the ED and ICU.
Methods:
Patients admitted for community-acquired acute sepsis from 11 hospital centers were eligible. Early (day 7) and late (day 28) deaths were notified. Levels of CD64pos granulocytes, CD16pos monocytes, CD16dim immature granulocytes (IGs), and T and B lymphocytes were assessed by flow cytometry using an identical, cross-validated, robust, and simple consensus standardized protocol in each center.
Results:
Among 1,062 patients screened, 781 patients with confirmed sepsis were studied (age, 67 ± 48 years; Simplified Acute Physiology Score II, 36 ± 17; Sequential Organ Failure Assessment, 5 ± 4). Patients were divided into three groups (sepsis, severe sepsis, and septic shock) on day 0 and on day 2. On day 0, patients with sepsis exhibited increased levels of CD64pos granulocytes, CD16pos monocytes, and IGs with T-cell lymphopenia. Clinical severity was associated with higher percentages of IGs and deeper T-cell lymphopenia. IG percentages tended to be higher in patients whose clinical status worsened on day 2 (35.1 ± 35.6 vs 43.5 ± 35.2, P = .07). Increased IG percentages were also related to occurrence of new organ failures on day 2. Increased IG percentages, especially when associated with T-cell lymphopenia, were independently associated with early (P < .01) and late (P < .01) death.
Conclusions:
Increased circulating IGs at the acute phase of sepsis are linked to clinical worsening, especially when associated with T-cell lymphopenia. Early flow cytometry could help clinicians to target patients at high risk of clinical deterioration.
Trial Registry:
ClinicalTrials.gov; No.: NCT01995448; URL: www.clinicaltrials.gov.
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However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

