Background
Cardiac dysfunction is a well-recognized complication of light chain amyloidosis (AL). Autologous stem cell transplant (auto-SCT) has emerged as a successful treatment modality for AL patients. In this study, we examined the effect of clonal immunoglobulin light chain genes (VL), which encodes the immunoglobulin light chain protein that ultimately forms amyloid, on cardiac function, in the context of auto-SCT and its impact on overall survival.
Methods
Longitudinal Doppler myocardial imaging parameters along with cardiac biomarkers were used to assess for cardiac function pre and post auto-SCT.
Results
VL gene analysis revealed that Vl genes, in particular VlVI, were associated with worse cardiac function parameters than Vk genes. Clonal VL genes appeared to have an impact on left ventricular (LV) function post-transplant and also influenced mortality, with specific VL gene families associated with lower survival. Another key predictor of mortality in this report was change in tricuspid regurgitant flow velocity following auto-SCT. Correlations were also observed between systolic strain rate, systolic strain and VL genes associated with amyloid formation.
Conclusions
Clonal VL gene usage influences global cardiac function in AL, with patients having VlVI and VlII-III-associated amyloid more severely affected than those having Vk or VlI amyloid. Pulsed wave tissue Doppler imaging along with immunoglobulin gene analysis offers novel insights into prediction of mortality and cardiac dysfunction in AL after auto-SCT.
Immunoglobulin light chain amyloid (AL) amyloidosis is the most common systemic amyloidosis, with an age-adjusted incidence of 5 to 13 per million patients per year in the United States. The traditional low-dose oral melphalan treatment regimen is generally associated with a poor prognosis (median survival, 13 months). The recent introduction of autologous peripheral blood stem cell transplantation (auto-SCT) has dramatically improved median survival in a select group of patients with AL amyloidosis. Both hematologic response at day 100 and cardiac function are key determinants of survival after auto-SCT.
In earlier studies, we reported the high sensitivity of longitudinal Doppler myocardial imaging (DMI) myocardial velocity and strain and strain rate imaging in detecting left ventricular (LV) impairment in both early and advanced AL amyloidosis. Because an association among particular clonal VL genes, organ tropism of amyloid deposition, and outcomes has been observed, this study had a twofold aim: (1) to evaluate whether clonal immunoglobulin light chain variable gene (VL) gene usage influences changes in LV function after SCT, and its impact on long-term mortality, and (2) to test whether serial measurement of cardiac biomarkers and longitudinal DMI measures are useful for monitoring cardiac function and for risk stratification.
Methods
This study was approved by the institutional review board of the Mayo Clinic (Rochester, MN). Fifty-three patients with AL systemic amyloidosis, consecutively selected from patients undergoing evaluation in the Division of Cardiovascular Diseases and the Division of Hematology at the Mayo Clinic from January 1 2004, to April 30, 2007 and referred to auto-SCT were enrolled in a prospective manner. Patients received either a standard-dose conditioning regimen (melphalan) at 200 mg/m 2 or a reduced-dose regimen (<200 mg/m 2 ), depending on age, renal function, the presence of cardiomyopathy, or triple-organ involvement. Of the 53 patients who underwent immunoglobulin (Ig) gene analysis, 28 received the standard dose and 25 received the lower dose (see Supplementary Table 1 ). Follow-up ended June 30, 2009. The diagnosis of AL amyloidosis was made by either subcutaneous fat biopsy or an involved organ biopsy study that demonstrated typical Congo red birefringence under polarized light. Endomyocardial biopsy was performed in four patients, for clinical purposes, and was positive for amyloid infiltration in all the cases. AL amyloidosis was further confirmed by the presence of a monoclonal protein in the serum or urine specimen and/or a monoclonal population of plasma cells in the bone marrow. Clinical, biomarker, and echocardiographic examinations were accomplished at two different time points (in a subset of 39 patients): the first assessment was performed <1 month before auto-SCT and the second assessment on day 100 after SCT.
Exclusion criteria were familial, secondary, or senile amyloidosis ( n = 2); all other causes of cardiomyopathy (including other forms of restrictive cardiomyopathy, hypertrophic cardiomyopathy, or any cause of LV hypertrophy other than AL amyloidosis); diabetes mellitus ( n = 0); a history of moderate or greater systemic or pulmonary hypertension ( n = 1); more than mild valvular heart disease ( n = 0); and coronary artery disease or previous myocardial infarction ( n = 0). Atrial fibrillation ( n = 3) was not an exclusion criterion.
Clinical Classification of Patients
Patients with AL amyloidosis were evaluated for the extent of amyloid-related organ involvement and for dominant organ involvement, integrating standard criteria described elsewhere with information provided by the assessment of cardiac biomarkers and diastolic function. Patients were categorized according to clinical presentation as having renal, cardiac, hepatic, neurologic, or other dominant organ involvement. This clinical classification was performed independently blind to clonal VL gene usage. Patients with more than one organ involved were categorized according to the most prominent and symptomatic affected organ. Because several patients had both cardiac and renal dysfunction due to amyloid deposition, information on dominant or codominant involvement was collected for these patients. Dominant gastrointestinal, pulmonary, or soft tissue AL amyloidosis (excluding cardiac, renal, hepatic, or neurologic dominant involvement) were all classified in the category “other” to simplify analysis.
Dominant cardiac involvement was defined as having positive results on endomyocardial biopsy or abnormally elevated cardiac biomarkers, including brain natriuretic peptide (BNP), and cardiac troponin T (cTnT), on the basis of our previous observations. Additionally, echocardiographic parameters, such as mean LV wall thickness (half the sum of the anteroseptal and posterior wall thickness in the parasternal long-axis view) >12 mm and diastolic dysfunction with a grade of 3 or 4 (restrictive pattern), were also used to define dominant cardiac involvement. Dominant renal involvement was defined as having positive results on kidney biopsy and proteinuria >0.5 g/dL, dialysis dependence, or creatinine clearance <10 mL/min.
Classification of enrolled patients followed a three-step algorithm. First, patients were categorized on the basis of clonal VL germline gene usage, and thus two groups were generated: group Vκ, including patients using Vκ I family genes, and group Vλ, including patients using Vλ I, Vλ II, Vλ III, and Vλ VI families. Second, group Vλ patients were further subdivided on the basis of cardiac function by standard echocardiography (LV wall thickness, mass index, and ejection fraction) at baseline (before auto-SCT): group Vλ I-II-III and group Vλ VI. Third, patients in group Vλ I-II-III were subdivided on the basis of hematologic response ; all group Vλ I patients ( n = 7) had either partial or complete response at day 100 and were therefore considered independently from those in group Vλ II-III, who had heterogeneous hematologic responses. In summary, four different groups were used in the analysis for comparison: groups Vκ, Vλ I, Vλ II-III, and Vλ VI.
Specimen Preparation and Cloning of Ig VL Genes
Bone marrow samples from all 53 patients with AL amyloidosis were processed to collect plasma cells and clonal Ig gene analysis was performed as per protocol (see the online Appendix for methodologic details).
Definition of Clonal Ig Gene Usage
The term “Ig gene usage” refers to the concept that antibodies or Ig molecules are generated in the immune system as a result of selection and molecular combining of three or four individual gene segments (three for Ig light chain and four for Ig heavy chain, light and heavy chain being essential for the formation of a complete antibody molecule). This process of selection and molecular recombination is a stochastic event whereby individual gene segments are apparently randomly “chosen” or “used” out of a larger array of such gene “families.” In a normal immune response, the diversity of antibody molecules produced by a terminally differentiated B cell (plasma cell) is large (polyclonal response) in contrast to what is observed during a neoplastic process, such as in AL amyloidosis, in which a single plasma cell undergoes expansion to produce a population of plasma cells (monoclonal or clonal), all secreting exactly the same antibody (Ig), from which the light chain forms amyloid fibrils and undergoes tissue deposition.
Biomarkers
BNP, N-terminal pro-BNP, cTnT, creatinine, and glomerular filtration rate were measured and collected at the time of the echocardiographic examination, as previously described. Hematologic assessment included percentage of bone marrow clonal plasma cells, level of clonal serum free light chain (FLC), and serum and urine protein electrophoresis (monoclonal protein quantitation) with immunofixation (monoclonal protein identification).
Standard Ultrasound Examination
All ultrasound examinations were performed using a commercially available echocardiographic instrument (Vivid 7; GE Vingmed Ultrasound AS, Horten, Norway). The thickness of the ventricular septum and LV posterior wall, the end-systolic and end-diastolic LV diameters, and the left atrial anteroposterior diameter were determined from M-mode or two-dimensional imaging, while LV mass and ejection fraction were calculated. Left atrial volume measurement was carried out as previously described. Both LV mass and LA volume were indexed to body surface area. Pulsed-wave Doppler of mitral inflow, the pulmonary veins, and LV outflow was performed as previously described. Pulsed-wave Doppler tissue imaging was performed using a sample volume gate length of 0.17 cm. The sample volume was placed on the medial mitral annulus in the apical four-chamber view, and the early (E′) and peak diastolic velocity were measured. The right index of myocardial performance was measured as previously described. Right ventricular systolic pressure was calculated by inserting the tricuspid regurgitation velocity obtained with continuous-wave Doppler into the simplified Bernoulli equation.
Offline analysis of standard echocardiographic variables was performed using dedicated software (ProSolv CV Analyzer version 3.0; ProSolv, Indianapolis, IN); three consecutive beats were measured and averaged for each measurement. All standard and DMI echocardiographic measures were collected with the two investigators obtaining the data (D.B. and G.B.A.) blind to the patients’ clinical status and the time point (before or after SCT) at which the images undergoing analysis were acquired.
Strain Imaging Data Acquisition and Analysis
For DMI, apical four-chamber, long-axis, and two-chamber views were acquired. DMI was used to measure longitudinal LV myocardial strain and strain rate in two separate echocardiographic examinations, as mentioned above. In addition, narrow-sector views were acquired for each LV wall from apical views. Color tissue recordings were collected with a frame rate ≥200 frames/sec during a brief breath hold. Three consecutive cardiac cycles were recorded as cine loops, and the acquired raw data were saved on magneto-optical disks for offline analysis (EchoPAC BT06; GE Vingmed Ultrasound AS).
Sample volumes were placed on basal, middle, and apical LV segments of the anterolateral, inferoseptal, posterior, anteroseptal, inferior, and anterior walls to assess longitudinal DMI. Longitudinal systolic peak values were determined for systolic strain rate (sSR) and systolic strain (sS). Analysis was performed for all 16 LV segments individually (data not shown) and in clusters according to the LV level (basal, middle, and apical). Specifically, the DMI values (sSR and sS) were averaged for the six basal segments (basal mean), the six middle segments (middle mean), and the four apical segments (apical mean).
Statistical Analysis
Statistical analyses were performed using a commercially available software program (Stata 10, MP version; StataCorp LP, College Station, TX). Comparisons between groups were made using either the Kruskal-Wallis test or Fisher’s exact test to determine differences among groups at baseline (before auto-SCT). Wilcoxon’s matched-pairs signed rank-sum test was used to compare post-auto-SCT biomarkers and DMI measures to the pre-SCT values. The natural logarithms of BNP and FLC were used in the analysis to meet the assumptions of a normal distribution.
Follow-up of the patients included a median follow-up time of 34 months (range, 0.9–64 months). The primary endpoint was all-cause mortality, and this was ascertained in all patients ( n = 53), either while they were under medical management, through the review of death certificates, or by querying the Social Security Death Index.
Because many of the patients in the study were first referred to the Mayo Clinic several months after their initial diagnoses, left truncation was used for the Kaplan-Meier and Cox regression analyses; that is, no subject was considered to be in the risk set until the time of echocardiography. Kaplan-Meier survival curves for the four groups were constructed, after which a log-rank test of uniform survival distribution among groups was performed. By definition, transplantation-related mortality was excluded in the analysis of this subset. Univariate analysis of the time to events was performed with use of Cox proportional-hazards models, considering the differences between before and after SCT of biomarkers and standard echocardiographic and longitudinal DMI measurements as predictors of primary outcomes. Differences were computed for all collected variables as the post-SCT value minus the pre-SCT value.
Data are presented as mean ± SD, as median (interquartile range) for biomarkers, or as count (percentage). A difference was considered statistically significant when the P value was <.05.
Intraobserver and Interobserver Variability
To examine intraobserver variability (repeatability), a sample of 10 echocardiographic examinations was randomly selected for masked review by the same investigator (D.B.). To examine interobserver variability, a second investigator (G.B.A.), blinded to the clinical information and to the results of the first investigator, examined 10 randomly selected echocardiographic exams. Intraclass correlation coefficients for the same observer and different observers were calculated using previously described formulas for single segments and for the global mean of each DMI modality.
Results
Ig Germline Gene Usage and Clinical Characteristics
Baseline
The frequency distribution of clonal VL gene usage and dominant organ involvement are shown in Table 1 . The Vλ VI 6a gene was the most frequently used ( n = 13 [25%]), followed by the Vλ I genes ( n = 11 [21%]), Vλ III genes ( n = 11 [21%]), and Vκ genes ( n =11 [21%]); Vλ II genes were used the least frequently in this cohort ( n = 7 [13%]). The time between diagnosis and enrollment in the study was not significantly different among the groups ( P = .51).
| VL gene subtype | Gene | Number of patients | Dominant organ involvement | Number involved ≥3 | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Cardiac | Renal | PNS | Hepatic | Other | ||||||
| Primary | Secondary | Primary | Secondary | |||||||
| Vλ I | 1b | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| 1c | 6 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | |
| 1e | 2 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | |
| 1g | 2 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | |
| Vλ II | 2a2 | 4 | 1 | 0 | 3 | 0 | 0 | 0 | 0 | 0 |
| 2b2 | 2 | 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | |
| 2c | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
| Vλ III | 3h | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
| 3r | 10 | 5 | 1 | 3 | 3 | 1 | 0 | 0 | 1 | |
| Vλ VI | 6a | 13 | 6 | 0 | 4 | 1 | 1 | 0 | 1 | 5 |
| Vκ | L1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 |
| L12 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | |
| L2 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | |
| O12/O2 | 2 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | |
| O18/O8 | 6 | 0 | 2 | 3 | 0 | 0 | 0 | 1 | 0 | |
| Total | 53 | 17 | 5 | 21 | 9 | 3 | 1 | 3 | 7 | |
Amyloid deposition most frequently involved the heart and kidneys, and in particular, the heart was the dominant organ affected in patients using the Vλ VI 6a gene (46%), with the Vλ III family genes close behind (45%). Dominant renal involvement was observed in 31% of Vλ VI, 36% of Vλ I, 57% of Vλ II, 27% of Vλ III, and 54% of Vκ patients. The Vλ I, Vλ III, and Vλ VI genes all had at least one patient with dominant peripheral nervous system involvement. Only one patient in the Vλ I group had hepatic involvement ( Table 1 ).
There were no significant differences among the three V λ subgroups and the Vκ group patients with regard to age, gender, and baseline clinical parameters ( Table 2 ). At baseline, FLC levels were significantly lower in the Vλ VI group compared to the other patients. Furthermore, specific trends could be identified: patients using the Vλ VI gene appeared to have a higher prevalence of advanced New York Heart Association functional class, and BNP and cTnT levels had a tendency to be lower in patients using the Vκ gene family and higher in patients using the Vλ VI family.
| Baseline ∗ | Vκ ( n = 11) | Vλ I ( n = 11) | Vλ II-III ( n = 18) | Vλ VI ( n = 13) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variable | P | Pre-auto-SCT | Post-auto-SCT | P | Pre-auto-SCT | Post-auto-SCT | P | Pre-auto-SCT | Post-auto-SCT | P | Pre-auto-SCT | Post-auto-SCT | P |
| Women | .18 | 3 (28%) | 8 (73%) | 8 (45%) | 5 (38%) | ||||||||
| Age (y) | .33 | 60 ± 5 | 55 ± 11 | 58 ± 11 | 59 ± 9 | ||||||||
| NYHA class III/IV | .81 | 0 | 1 (12%) | 0 | 3 (30%) | ||||||||
| BMI (kg/m 2 ) | .64 | 26.21 ± 3.9 | 27.48 ± 4.6 | 25.8 ± 6 | 25 ± 3.6 | ||||||||
| Creatinine (mg/dL) | .69 | 1.20 (1.3) | 1.05 (1.1) | 1.0 (0.3) | 1.10 (0.4) | ||||||||
| GFR (mL/min/m 2 ) | .57 | 59 (56) | 65.5 (47) | 70 (18) | 72 (30) | ||||||||
| 24-h proteinuria (mg/24 h) | .37 | 5,516 (7,469) | 4,859 (3,055) | 1,865 (4,178) | 3,538 (4,575) | ||||||||
| FLC κ | .003 | 14.1 (63) | 1.03 (4.8) | .04 | 1.24 (0.3) | 1.18 (1.5) | .70 | 0.88 (1.5) | 0.94 (2.4) | .33 | 1.41 (0.2) | 0.94 (1.4) | .78 |
| FLC λ | .004 | 1.64 (0.8) | 1.95 (1.9) | .90 | 13.55 (28.2) | 2.03 (5.2) | .02 | 20.95 (44.5) | 4.58 (12.6) | .01 | 5.68 (4.4) | 2.31 (3.9) | .71 |
| FLC κ/λ | .003 | 4.6 (6.1) | 1.94 (2.4) | .14 | 0.12 (0.2) | 0.2 (0.4) | .13 | 0.06 (0.1) | 0.48 (0.7) | .01 | 0.28 (0.2) | 0.36 (0.7) | .16 |
| BNP (pg/mL) | .59 | 79 (1,158) | 80 (818) | .17 | 137 (290) | 198 (718) | .05 | 239 (262) | 154 (781) | .78 | 315 (480) | 293 (313) | .68 |
| cTnT (ng/mL) | .95 | 0.01 (0.02) | 0.02 (0.02) | .67 | 0.01 (0.04) | 0.01 (0.19) | .42 | 0.01 (0.02) | 0.02 (0.06) | .12 | 0.02 (0.02) | 0.02 (0.02) | .23 |
| LV thickness (mm) | .02 | 10.6 ± 2 | 11.9 ± 3 | .12 | 12.4 ± 2 | 14.3 ± 2 | .01 | 12.7 ± 3 | 13.5 ± 3 | .26 | 15.0 ± 4 | 15.7 ± 3 | .04 |
| LVMI (g/m 2 ) | .04 | 95 ± 34 | 107 ± 49 | .26 | 80 ± 21 | 71 ± 22 | .01 | 92 ± 30 | 92 ± 33 | .38 | 157 ± 65 | 152 ± 35 | .62 |
| LVEDV (mm) | .65 | 86 ± 48 | 83 ± 34 | .23 | 37 ± 11 | 30 ± 9 | .34 | 41 ± 16 | 41 ± 19 | .95 | 73 ± 33 | 72 ± 35 | .04 |
| LVESV (mm) | .97 | 37.5 ± 17.4 | 33 ± 13.8 | .41 | 106 ± 18 | 132 ± 30 | .14 | 117 ± 46 | 122 ± 63 | .92 | 38.86 ± 19.8 | 33.25 ± 17 | .67 |
| LAV (mL/m 2 ) | .68 | 47.7 ± 14.1 | 38.1 ± 10.9 | .02 | 37 ± 12 | 37 ± 9 | .25 | 40 ± 13 | 39 ± 19 | .86 | 41.8 ± 7.0 | 45.6 ± 9.6 | .31 |
| E (m/sec) | .48 | 0.8 ± 0.1 | 0.6 ± 0.1 | .08 | 0.9 ± 0.2 | 0.9 ± 0.2 | .44 | 0.8 ± 0.3 | 0.9 ± 0.3 | .69 | 0.8 ± 0.1 | 0.9 ± 0.2 | .27 |
| A (m/sec) | .87 | 0.65 ± 0.2 | 0.75 ± 0.2 | .15 | 0.8 ± 0.3 | 0.7 ± 0.3 | .58 | 0.8 ± 0.4 | 0.7 ± 0.3 | .78 | 0.65 ± 0.2 | 0.63 ± 0.3 | .72 |
| E/A | .42 | 1.4 ± 0.7 | 0.9 ± 0.5 | .03 | 1.4 ± 0.9 | 1.4 ± 0.7 | .14 | 1.3 ± 0.9 | 1.3 ± 0.6 | .37 | 1.5 ± 0.8 | 2.2 ± 1.9 | .41 |
| E-wave DT (msec) | .48 | 232 ± 52 | 248 ± 79 | .93 | 188 ± 36 | 203 ± 52 | .25 | 204 ± 48 | 195 ± 51 | .68 | 191 ± 43 | 194 ± 49 | .77 |
| E′ (m/sec) | .51 | 0.06 ± 0.02 | 0.06 ± 0.03 | .22 | 0.06 ± 0.01 | 0.06 ± 0.03 | .67 | 0.06 ± 0.02 | 0.05 ± 0.02 | .11 | 0.05 ± 0.02 | 0.04 ± 0.01 | .04 |
| E/E′ | .37 | 15.5 ± 8.9 | 13.9 ± 7.9 | .44 | 15.8 ± 6.7 | 13.3 ± 8.6 | .79 | 15.5 ± 11.6 | 19.0 ± 10.6 | .04 | 17.79 ± 7.5 | 22.79 ± 10.9 | .08 |
| EF (%) | .37 | 65 ± 9 | 62 ± 8.4 | .67 | 56 ± 9 | 56 ± 10 | .89 | 57 ± 7 | 57 ± 10 | .53 | 59 ± 12 | 60 ± 10 | .41 |
| Cardiac index (L/min/m 2 ) | .45 | 3.9 ± 0.7 | 3.2 ± 1.2 | .32 | 3.3 ± 1.1 | 3.1 ± 1 | .32 | 3.3 ± 0.9 | 2.9 ± 0.7 | 1.0 | 2.8 ± 1.2 | 3.0 ± 0.75 | .65 |
| RV tricuspid regurgitation velocity (m/s) | .57 | 2.6 ± 0.5 | 2.3 ± 0.3 | .05 | 2.7 ± 0.1 | 2.9 ± 0.3 | .14 | 2.5 ± 0.2 | 2.5 ± 0.4 | .80 | 2.6 ± 0.3 | 2.6 ± 0.5 | .91 |
| RVSP (mm Hg) | .69 | 34.5 ± 11.6 | 25.67 ± 3.9 | .05 | 34.2 ± 3.5 | 42.4 ± 11 | .14 | 30.7 ± 7.3 | 36.4 ± 10.1 | .19 | 34.7 ± 8.4 | 35.2 ± 12 | .91 |
| RIMP | .54 | 0.36 ± 0.2 | 0.34 ± 0.2 | .67 | 0.32 ± 0.2 | 0.55 ± 0.3 | .15 | 0.26 ± 0.1 | 0.38 ± 0.1 | .03 | 0.38 ± 0.1 | 0.43 ± 0.2 | .41 |
∗ Comparisons of baseline values among groups were made using the Kruskal-Wallis test or Fisher’s exact test; comparisons between pre-auto-SCT and post-auto-SCT values per variable were made using Wilcoxon’s signed-rank paired sum test.
After SCT
The changes in BNP, cTnT, and FLC κ levels following auto-SCT were not significant in any of the four groups, but FLC λ was significantly reduced in both Vλ I and Vλ II-III groups, while the FLC κ/λ ratio was reduced in only the Vλ II-III group.
Standard Echocardiography
Baseline
LV thickness and mass index at baseline were significantly different among the groups ( Table 2 ), with the highest value being seen in Vλ VI patients. LV and left atrial volumes, ejection fraction, and cardiac index, along with parameters of diastolic function (E-wave and A-wave velocities, E/A ratio, pulsed-wave tissue Doppler E′ velocity of the medial mitral annulus, and E/E′ ratio) were similar among all gene groups. Tricuspid regurgitant flow velocity, estimated right ventricular systolic pressure, and right index of myocardial performance were also similar among the groups.
After SCT
Post-SCT LV thickness was significantly increased in Vλ I and Vλ VI patients, while LV mass index was increased in Vλ I patients only ( Figure 1 A). LV end-diastolic and end-systolic volumes were not significantly changed following auto-SCT in any of the four groups. Left atrial volume was significantly reduced following auto-SCT in patients using the Vκ family ( Figure 1 B). Among diastolic measures, post-SCT transmitral E/A ratio was reduced in the Vκ group, while the difference after auto-SCT was not significant in patients using any of the Vλ families. E′ was reduced in Vλ VI patients, and E/E′ ratio was increased in Vλ II-III patients. There were no significant variations in the other groups ( Figure 1 C), although post-auto-SCT E/E′ ratio was marginally reduced in Vκ and in Vλ I patients. There was no variation in ejection fraction or cardiac index among groups. Both tricuspid regurgitant flow velocity and right ventricular systolic pressure showed a tendency to decrease only in patients using the Vκ family. At the same time, right index of myocardial performance was unchanged in the Vκ group, while it increased in Vλ II-III patients.
DMI
Baseline
The longitudinal sSR mean of the six middle segments and the mean of the four apical segments, as well as the mean of 16 LV segments, were significantly different among all groups, with the highest values in patients using the Vκ gene family, intermediate values in Vλ II-III groups, and the lowest values in patients using the Vλ VI and Vλ I gene families ( Table 3 ).
| Baseline ∗ | Vκ ( n = 11) | Vλ I (n = 11) | Vλ II-III (n = 18) | Vλ VI (n = 13) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Variable | P | Pre-auto-SCT | Post-auto-SCT | P | Pre-auto-SCT | Post-auto-SCT | P | Pre-auto-SCT | Post-Auto-SCT | P | Pre-Auto-SCT | Post-auto-SCT | P |
| Strain rate imaging (s −1 ) | |||||||||||||
| Basal mean | .22 | −0.9 ± 0.5 | −0.9 ± 0.3 | .4 | −0.8 ± 0.3 | −0.7 ± 0.3 | .88 | −0.8 ± 0.3 | −0.7 ± 0.3 | .01 | −0.6 ± 0.4 | −0.5 ± 0.2 | .37 |
| Middle mean | .009 | −1.2 ± 0.3 | −1.0 ± 0.2 | .26 | −0.9 ± 0.2 | −0.8 ± 0.3 | .4 | −1.1 ± 0.3 | −0.8 ± 0.3 | .001 | −0.7 ± 0.3 | −0.7 ± 0.3 | .53 |
| Apical mean | .02 | −1.2 ± 0.2 | −1.1 ± 0.3 | .16 | −0.9 ± 0.3 | −0.8 ± 0.2 | .12 | −1.2 ± 0.4 | −0.9 ± 0.3 | .001 | −0.8 ± 0.2 | −0.7 ± 0.2 | .03 |
| Global average | .02 | −1.1 ± 0.3 | −0.1 ± 0.3 | .26 | −0.9 ± 0.2 | −0.8 ± 0.3 | .78 | −1.0 ± 0.3 | −0.8 ± 0.2 | .001 | −0.7 ± 0.3 | −0.6 ± 0.2 | .11 |
| Strain imaging (%) | |||||||||||||
| Basal mean | .06 | −15.6 ± 5.7 | −12.63 ± 5.9 | .09 | −10.2 ± 3.2 | −9.3 ± 6.4 | .78 | −11.3 ± 4.3 | −9.9 ± 4.8 | .48 | −8.7 ± 6.9 | −8.2 ± 5.3 | .72 |
| Middle mean | .08 | −17.1 ± 4.6 | −16.11 ± 3 | .33 | −13.0 ± 4.7 | −12.5 ± 5.5 | 1 | −15.7 ± 3.3 | −14.1 ± 5.7 | .18 | −11.5 ± 5.4 | −9.8 ± 4.3 | .04 |
| Apical mean | .009 | −17.1 ± 2.9 | −14.51 ± 3.6 | .09 | −12.5 ± 3.7 | −12.1 ± 3.9 | .41 | −17.3 ± 4.7 | −13.8 ± 4.3 | .009 | −12.2 ± 3.9 | −9.6 ± 3.3 | .04 |
| Global average | .02 | −16.6 ± 4.2 | −14.41 ± 4.1 | .09 | −11.8 ± 2.6 | −11.2 ± 4.9 | .78 | −14.5 ± 3.3 | −12.5 ± 4.3 | .02 | −10.6 ± 5.2 | −9.2 ± 4.1 | .06 |
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