摘要
Background The number of critically ill immunocompromised （CIIC） patients has increased dramatically in recent years,and they represent a high risk population for invasive pulmonary aspergillosis （IPA） infection.Host immunity should play a major role in determining the outcome and recovery of these patients.The purpose of this study was to evaluate the dynamic changes in host immune status and its potential influence on prognosis in CIIC patients with IPA.Methods We monitored the evolution of a number of key cellular and humoral parameters on days 1,3,and 10 （D1,D3 and D10） following ICU admission in sixty-two CIIC patients with microbiological evidence of IPA.We included immunoglobulins IgG,IgA and IgM,complement factors C3 and C4,and lymphocyte subgroups CD3＋,CD4＋,CD8＋,CD28＋CD4＋,and CD28＋CD8＋ T cells,CD19＋B cells,and CD3-CD16＋CD56＋ natural killer cells （NK）.Results The primary outcome was 28-day mortality.Thirty-eight （61.3％） patients died within the 28 days following ICU admission.Compared to patients who died,CD3＋,CD8＋,CD28＋CD8＋ T-cell counts on D1,D3,and D10,CD28＋CD4＋ T-cell counts on D3 and D10,and NK counts on D3 and D10 were significantly higher in survivors.Receiver operating characteristic （ROC） analysis of immune parameters predicting 28-day mortality revealed area under the curve （AUC） values of 0.82 （95％ CI 0.71-0.92）,0.94 （95％ CI 0.87-0.99）,and 0.94 （95％ CI 0.85-0.99） for CD8＋ T-cell counts for D1,D3,and D10 respectively,and 0.84 （95％ CI 0.75-0.94）,0.92 （95％ CI 0.85-0.99）,and 0.90 （95％ CI 0.79-0.99） for CD28＋CD8＋ T-cell counts for D1,D3,and D10 respectively.Kaplan-Meier survival analysis showed that CD8＋ T-cell counts ＜149.5×106 cells/L and CD28＋CD8＋ T-cell counts ＜75×106 cells/L at ICU admission were associated with lower survival probabilities in CIIC patients with IPA （both Log rank：P＜0.001）.Conclusions Low CD8＋ and CD28＋CD8＋ T-cell counts were associated with high mortality in CIIC patients with IPA.Early counts of CD8＋ and CD28＋CD8＋ T cells in CIIC patients with IPA may be valuable for predicting outcome.
Background The number of critically ill immunocompromised （CIIC） patients has increased dramatically in recent years,and they represent a high risk population for invasive pulmonary aspergillosis （IPA） infection.Host immunity should play a major role in determining the outcome and recovery of these patients.The purpose of this study was to evaluate the dynamic changes in host immune status and its potential influence on prognosis in CIIC patients with IPA.Methods We monitored the evolution of a number of key cellular and humoral parameters on days 1,3,and 10 （D1,D3 and D10） following ICU admission in sixty-two CIIC patients with microbiological evidence of IPA.We included immunoglobulins IgG,IgA and IgM,complement factors C3 and C4,and lymphocyte subgroups CD3＋,CD4＋,CD8＋,CD28＋CD4＋,and CD28＋CD8＋ T cells,CD19＋B cells,and CD3-CD16＋CD56＋ natural killer cells （NK）.Results The primary outcome was 28-day mortality.Thirty-eight （61.3％） patients died within the 28 days following ICU admission.Compared to patients who died,CD3＋,CD8＋,CD28＋CD8＋ T-cell counts on D1,D3,and D10,CD28＋CD4＋ T-cell counts on D3 and D10,and NK counts on D3 and D10 were significantly higher in survivors.Receiver operating characteristic （ROC） analysis of immune parameters predicting 28-day mortality revealed area under the curve （AUC） values of 0.82 （95％ CI 0.71-0.92）,0.94 （95％ CI 0.87-0.99）,and 0.94 （95％ CI 0.85-0.99） for CD8＋ T-cell counts for D1,D3,and D10 respectively,and 0.84 （95％ CI 0.75-0.94）,0.92 （95％ CI 0.85-0.99）,and 0.90 （95％ CI 0.79-0.99） for CD28＋CD8＋ T-cell counts for D1,D3,and D10 respectively.Kaplan-Meier survival analysis showed that CD8＋ T-cell counts ＜149.5×106 cells/L and CD28＋CD8＋ T-cell counts ＜75×106 cells/L at ICU admission were associated with lower survival probabilities in CIIC patients with IPA （both Log rank：P＜0.001）.Conclusions Low CD8＋ and CD28＋CD8＋ T-cell counts were associated with high mortality in CIIC patients with IPA.Early counts of CD8＋ and CD28＋CD8＋ T cells in CIIC patients with IPA may be valuable for predicting outcome.
