Predictors of Acute Chest Syndrome in Patients With Sickle Cell Disease: A Cross-Sectional Observational Study

镰状细胞病患者急性胸痛综合征的预测因素:一项横断面观察研究

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Abstract

Background Acute chest syndrome (ACS) is a major cause of mortality and hospitalization in patients with sickle cell disease (SCD). While clinical features often overlap with uncomplicated vaso-occlusive crises (VOC), early differentiation is critical for survival. Data regarding specific predictors of ACS in the Indian population remains limited. The objective of this study was to identify clinical and laboratory factors associated with the diagnosis of ACS in hospitalized patients with sickle cell disease. Methods This cross-sectional analytical study was conducted at a tertiary care teaching hospital in Eastern India between March 2023 and February 2025 and included 90 hospitalized patients with homozygous sickle cell anemia (HbSS). Patients were stratified into two groups: those diagnosed with ACS (n=33) and a control group of patients with uncomplicated VOC (n=57). Detailed clinical, hematological, and biochemical parameters were compared. Clinical and laboratory variables, including respiratory rate and lactate dehydrogenase (LDH), were analysed as early markers recorded at initial clinical presentation, prior to radiographic confirmation of ACS. Multivariate logistic regression and receiver operating characteristic (ROC) curve analysis were performed to identify independent predictors. Results The prevalence of ACS among hospitalized SCD patients was 36.67%. On univariate analysis, patients with ACS had significantly higher respiratory rates, heart rates, and inflammatory markers, total leukocyte count, C-reactive protein, and lactate dehydrogenase, along with lower hemoglobin levels compared to the non-ACS group (p < 0.05). Platelet counts did not differ significantly between groups. On multivariate logistic regression, respiratory rate showed an independent association with ACS (p = 0.001). ROC analysis demonstrated that a respiratory rate >21 breaths/minute had a sensitivity of 93.9% and specificity of 93% (area under the curve (AUC) = 0.944) for identifying ACS. LDH levels >389 U/L also demonstrated significant diagnostic discrimination (AUC = 0.769). Conclusion An elevated respiratory rate is a robust, accessible clinical parameter strongly associated with ACS in patients with SCD. Close monitoring of vital signs, particularly tachypnea, along with lactate dehydrogenase levels, may aid in early identification and risk stratification of ACS in resource-limited settings.

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