BackgroundThe improvement in sickle cell anemia (SCA) care resulted in the emergence of a large population of adults living with this disease. The mechanisms of lung injury in this new population are largely unknown. The forced oscillation technique (FOT) represents the current state-of-the-art in the assessment of lung function. The present work uses the FOT to improve our knowledge about the respiratory abnormalities in SCA, evaluates the associations of FOT with the functional exercise capacity and investigates the early detection of respiratory abnormalities.Methodology/Principal findingsSpirometric classification of restrictive abnormalities resulted in three categories: controls (n = 23), patients with a normal exam (n = 21) and presenting pulmonary restriction (n = 24). FOT analysis showed that, besides restrictive changes (reduced compliance; p<0.001), there is also an increase in respiratory resistance (p<0.001) and ventilation heterogeneity (p<0.01). FOT parameters are associated with functional exercise capacity (R = -0.38), pulmonary diffusion (R = 0.66), respiratory muscle performance (R = 0.41), pulmonary volumes (R = 0.56) and airway obstruction (R = 0.54). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). A combination of FOT and machine learning (ML) classifiers showed adequate diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.82).ConclusionsIn this study, the use of FOT showed that adults with SCA develop a mixed pattern of respiratory disease. Changes in FOT parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FOT associated with ML methods accurately diagnosed early respiratory abnormalities. This suggested the potential utility of the FOT and ML clinical decision support systems in the identification of respiratory abnormalities in patients with SCA.

No abstract

IntroductionPatients with sickle cell disease have increased left ventricular size, which is not usually accompanied by changes in systolic function indexes. We assessed echocardiographic abnormalities present in patients with sickle cell anemia (SCA) and compared echocardiographic parameters to other sickle cell diseases (OSCD).Material and methodsA blind cross-sectional study with 60 patients with SCA and 16 patients with OSCD who underwent transthoracic echocardiography was performed.ResultsEchocardiographic findings were: left atrial volume index 47.7 ±11.5 ml/m² in SCA group and 31.7 ±8.42 ml/m² in OSCD group (p < 0.001); left ventricular diastolic diameter index 3.47 ±0.37 cm/m² in SCA group and 2.97 ±0.41 cm/m² in OSCD group (p < 0.001); left ventricular systolic diameter index 2.12 ±0.31 cm/m² in SCA group and 1.86 ±0.28 cm/m² in OSCD group (p < 0.001). There were no differences in the left ventricular ejection fraction: 68.2 ±6.69% in SCA group and 67.1 ±6.21% in OSCD group (p = 0.527). The ratio between mitral E wave and mean mitral annulus e’ wave velocities was higher in the SCA group (7.72 ±1.54 vs. 6.70 ±1.65; p = 0.047). Mitral A wave correlated significantly with hemoglobin levels (r = –0.340; p = 0.032).ConclusionsThere was an increase of left ventricular and left atrial sizes in patients with SCA, compared to patients with OSCD, without changes in systolic or diastolic function in both groups. This could be due to the hyperkinetic state due to the more severe anemia in the SCA subjects.

Sickle cell anemia (SCA) causes dysfunction of multiple organs, with pulmonary involvement as a major cause of mortality. Recently, there has been growing interest in the nitrogen single-breath washout (N2SBW) test, which is able to detect ventilation heterogeneity and small airway disease when the results of other pulmonary function tests (PFTs) are still normal. Thus, the objectives of the present study were to assess the heterogeneity in the ventilation distribution in adults with SCA and to determine the association between the ventilation distribution and the clinical, cardiovascular, and radiological findings. This cross-sectional study included 38 adults with SCA who underwent PFTs, echocardiography, computed tomography (CT), and 6-min walk test. To evaluate the ventilation heterogeneity, the patients were categorized according to the phase III slope of the N2SBW (SIIIN2). Compared with adults with lower SIIIN2 values, adults with higher SIIIN2 values showed lower hemoglobin levels (P=0.048), a history of acute chest syndrome (P=0.001), an elevated tricuspid regurgitation velocity (P=0.039), predominance of a reticular pattern in the CT (P=0.002), a shorter 6-min walking distance (6MWD) (P=0.002), and lower peripheral oxygen saturation (SpO2) after exercise (P=0.03). SIIIN2 values correlated significantly with hemoglobin (rs=-0.344; P=0.034), forced vital capacity (rs=-0.671; P<0.0001), diffusing capacity for carbon monoxide (rs=-0.376; P=0.019), 6MWD (rs=-0.554; P=0.0003), and SpO2 after exercise (P=0.040). Heterogeneity in the ventilation distribution is one of the most common pulmonary dysfunctions in adults with SCA. Moreover, relationships exist between ventilation heterogeneity, worsening of pulmonary structural damage, and reduced tolerance for exercise.

Background A better understanding of sickle cell anemia (SCA) and improvements in drug therapy and health policy have contributed to the emergence of a large population of adults living with this disease. The mechanisms by which SCA produces adverse effects on the respiratory system of these patients are largely unknown. Fractional-order (FrOr) models have a high potential to improve pulmonary clinical science and could be useful for diagnostic purposes, offering accurate models with an improved ability to mimic nature. Part 2 of this two-part study examines the changes in respiratory mechanics in patients with SCA using the new perspective of the FrOr models. These results are compared with those obtained in traditional forced oscillation (FOT) parameters, investigated in Part 1 of the present study, complementing this first analysis. Methodology/Principal findings The data consisted of three categories of subjects: controls (n = 23), patients with a normal spirometric exam (n = 21) and those presenting restriction (n = 24). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Initially, it was observed that biomechanical changes in SCA included increased values of fractional inertance, as well as damping and hysteresivity (p<0.001). The correlation analysis showed that FrOr parameters are associated with functional exercise capacity (R = -0.57), pulmonary diffusion (R = -0.71), respiratory muscle performance (R = 0.50), pulmonary flows (R = -0.62) and airway obstruction (R = 0.60). Fractional-order modeling showed high diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.93), outperforming spirometry (p<0.03) and standard FOT analysis (p<0.01) used in Part 1 of this study. A combination of machine learning methods with fractional-order modeling further improved diagnostic accuracy (AUC = 0.97). Conclusions FrOr modeling improved our knowledge about the biomechanical abnormalities in adults with SCA. Changes in FrOr parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FrOr modeling outperformed spirometric and traditional forced oscillation analyses, showing a high diagnostic accuracy in the diagnosis of early respiratory abnormalities that was further improved by an automatic clinical decision support system. This finding suggested the potential utility of this combination to help identify early respiratory changes in patients with SCA.