TEDD Analysis



Table 1


AD
(N=8)		 DLB
(N=11)		 P-value
Daily activity counts
Mean (SD) 1620000 (232000) 1240000 (473000) 0.035
Median [Min, Max] 1620000 [1290000, 1950000] 1370000 [407000, 1860000]
Day activity
Mean (SD) 868000 (160000) 649000 (264000) 0.039
Median [Min, Max] 876000 [657000, 1100000] 740000 [238000, 931000]
Night activity
Mean (SD) 153000 (73300) 122000 (84400) 0.407
Median [Min, Max] 134000 [71700, 305000] 95500 [29900, 262000]
Drowsy
No 5 (62.5%) 2 (18.2%) 0.135
Yes 3 (37.5%) 9 (81.8%)
Nap
No 7 (87.5%) 5 (45.5%) 0.163
Yes 1 (12.5%) 6 (54.5%)
Illogical
No 3 (37.5%) 0 (0%) 0.115
Yes 5 (62.5%) 11 (100%)
Stare
No 6 (75.0%) 4 (36.4%) 0.23
Yes 2 (25.0%) 7 (63.6%)
Fluctuator
No 6 (75.0%) 2 (18.2%) 0.045
Yes 2 (25.0%) 9 (81.8%)
Hallucinations
No 8 (100%) 2 (18.2%) 0.002
Yes 0 (0%) 9 (81.8%)
Delusions
No 8 (100%) 5 (45.5%) 0.043
Yes 0 (0%) 6 (54.5%) 


## 
##  Welch Two Sample t-test
## 
## data:  act_fluc$daily_counts by act_fluc$Status
## t = 2.3105, df = 15.309, p-value = 0.03518
## alternative hypothesis: true difference in means between group AD and group DLB is not equal to 0
## 95 percent confidence interval:
##   30043.74 729443.23
## sample estimates:
##  mean in group AD mean in group DLB 
##           1617650           1237907

Exploratory figures








Other activity measures


High intradaily variability may indicate daytime napping and/or nighttime arousals




Values range from 0 to 1, with higher values indicating greater stability






UPDRS



MoCA



NPI


##          
##           H: No H: Yes
##   MF: No      8      0
##   MF: Yes     2      9
##          
##           D: No D: Yes
##   MF: No      8      0
##   MF: Yes     5      6



AAI


## # A tibble: 15 × 3
##    newID AA_Over Status
##    <chr>   <dbl> <chr> 
##  1 001     65.6  AD    
##  2 003      8.2  DLB   
##  3 005     80.1  AD    
##  4 006      0    AD    
##  5 007     18.3  DLB   
##  6 008      3.2  DLB   
##  7 011     32.3  AD    
##  8 012      3.30 DLB   
##  9 014     34.9  DLB   
## 10 016      8.4  AD    
## 11 017     20.9  AD    
## 12 018     17.1  AD    
## 13 019     22.1  DLB   
## 14 020      4.62 DLB   
## 15 022      6.19 DLB








Cleaveland Clinic Analysis



Overall
(N=171)
Baseline age
Mean (SD) 70.3 (6.51)
Median [Min, Max] 70.0 [55.0, 89.0]
Missing 1 (0.6%)
Gender
1 146 (85.4%)
2 24 (14.0%)
Missing 1 (0.6%)
Baseline MoCA
Mean (SD) 19.7 (5.69)
Median [Min, Max] 21.0 [6.00, 30.0]
Missing 6 (3.5%)
Baseline question 1
0 44 (25.7%)
1 91 (53.2%)
9 3 (1.8%)
Missing 33 (19.3%)
Baseline question 2
0 67 (39.2%)
1 66 (38.6%)
9 5 (2.9%)
Missing 33 (19.3%)
Baseline question 3
0 28 (16.4%)
1 108 (63.2%)
9 2 (1.2%)
Missing 33 (19.3%)
Baseline question 4
0 63 (36.8%)
1 70 (40.9%)
9 5 (2.9%)
Missing 33 (19.3%)
Fluctuator (baseline)
No 66 (38.6%)
Yes 71 (41.5%)
Missing 34 (19.9%)
Fluctuator (month 12)
No 26 (15.2%)
Yes 53 (31.0%)
Missing 92 (53.8%)
Fluctuator (month 24)
No 20 (11.7%)
Yes 35 (20.5%)
Missing 116 (67.8%)
Fluctuator (month 36)
No 14 (8.2%)
Yes 17 (9.9%)
Missing 140 (81.9%)
Baseline UPDRS score
Mean (SD) 28.9 (15.7)
Median [Min, Max] 27.0 [0, 80.0]
Missing 12 (7.0%)
Month 12 UPDRS score
Mean (SD) 30.2 (17.6)
Median [Min, Max] 28.0 [2.00, 87.0]
Missing 80 (46.8%)
Month 24 UPDRS score
Mean (SD) 33.4 (19.3)
Median [Min, Max] 31.0 [1.00, 83.0]
Missing 116 (67.8%)
Month 36 UPDRS score
Mean (SD) 33.3 (17.7)
Median [Min, Max] 32.5 [2.00, 71.0]
Missing 141 (82.5%)


Table 1 by baseline fluctuation status


No
(N=66)		 Yes
(N=71)		 Overall
(N=137)
Baseline age
Mean (SD) 69.8 (6.35) 70.5 (6.38) 70.2 (6.35)
Median [Min, Max] 70.0 [57.0, 84.0] 70.0 [55.0, 86.0] 70.0 [55.0, 86.0]
Gender
1 57 (86.4%) 60 (84.5%) 117 (85.4%)
2 9 (13.6%) 11 (15.5%) 20 (14.6%)
Baseline MoCA
Mean (SD) 21.3 (5.15) 19.2 (5.80) 20.2 (5.58)
Median [Min, Max] 22.0 [10.0, 30.0] 20.0 [7.00, 29.0] 21.0 [7.00, 30.0]
Missing 2 (3.0%) 1 (1.4%) 3 (2.2%)
Baseline question 1
0 42 (63.6%) 2 (2.8%) 44 (32.1%)
1 22 (33.3%) 69 (97.2%) 91 (66.4%)
9 1 (1.5%) 0 (0%) 1 (0.7%)
Missing 1 (1.5%) 0 (0%) 1 (0.7%)
Baseline question 2
0 49 (74.2%) 18 (25.4%) 67 (48.9%)
1 13 (19.7%) 53 (74.6%) 66 (48.2%)
9 3 (4.5%) 0 (0%) 3 (2.2%)
Missing 1 (1.5%) 0 (0%) 1 (0.7%)
Baseline question 3
0 28 (42.4%) 0 (0%) 28 (20.4%)
1 37 (56.1%) 71 (100%) 108 (78.8%)
9 0 (0%) 0 (0%) 0 (0%)
Missing 1 (1.5%) 0 (0%) 1 (0.7%)
Baseline question 4
0 48 (72.7%) 15 (21.1%) 63 (46.0%)
1 16 (24.2%) 54 (76.1%) 70 (51.1%)
9 1 (1.5%) 2 (2.8%) 3 (2.2%)
Missing 1 (1.5%) 0 (0%) 1 (0.7%)
Fluctuator (baseline)
No 66 (100%) 0 (0%) 66 (48.2%)
Yes 0 (0%) 71 (100%) 71 (51.8%)
Fluctuator (month 12)
No 16 (24.2%) 9 (12.7%) 25 (18.2%)
Yes 17 (25.8%) 32 (45.1%) 49 (35.8%)
Missing 33 (50.0%) 30 (42.3%) 63 (46.0%)
Fluctuator (month 24)
No 14 (21.2%) 5 (7.0%) 19 (13.9%)
Yes 13 (19.7%) 19 (26.8%) 32 (23.4%)
Missing 39 (59.1%) 47 (66.2%) 86 (62.8%)
Fluctuator (month 36)
No 6 (9.1%) 4 (5.6%) 10 (7.3%)
Yes 8 (12.1%) 9 (12.7%) 17 (12.4%)
Missing 52 (78.8%) 58 (81.7%) 110 (80.3%)
Baseline UPDRS score
Mean (SD) 27.0 (18.0) 29.0 (13.6) 28.1 (15.8)
Median [Min, Max] 25.0 [0, 80.0] 28.5 [2.00, 68.0] 27.0 [0, 80.0]
Missing 5 (7.6%) 1 (1.4%) 6 (4.4%)
Month 12 UPDRS score
Mean (SD) 29.0 (22.1) 29.7 (13.5) 29.4 (18.1)
Median [Min, Max] 26.0 [2.00, 87.0] 30.5 [5.00, 60.0] 28.0 [2.00, 87.0]
Missing 33 (50.0%) 37 (52.1%) 70 (51.1%)
Month 24 UPDRS score
Mean (SD) 29.3 (20.1) 36.1 (18.5) 32.6 (19.4)
Median [Min, Max] 29.0 [1.00, 83.0] 33.0 [3.00, 75.0] 31.0 [1.00, 83.0]
Missing 45 (68.2%) 51 (71.8%) 96 (70.1%)
Month 36 UPDRS score
Mean (SD) 26.0 (16.7) 38.2 (15.1) 31.5 (16.8)
Median [Min, Max] 28.0 [2.00, 54.0] 39.0 [7.00, 57.0] 34.0 [2.00, 57.0]
Missing 55 (83.3%) 62 (87.3%) 117 (85.4%)



UPDRS scores vs. Fluctuation status


## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$updrs_base by cc_fluc$fluc_base
## t = -0.68672, df = 110.94, p-value = 0.4937
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -7.524567  3.651499
## sample estimates:
##  mean in group No mean in group Yes 
##          27.04918          28.98571
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$updrs_m12 by cc_fluc$fluc_m12
## t = 0.42765, df = 22.416, p-value = 0.673
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -9.434806 14.343378
## sample estimates:
##  mean in group No mean in group Yes 
##          28.21429          25.76000
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$updrs_m24 by cc_fluc$fluc_m24
## t = -1.2797, df = 19.449, p-value = 0.2157
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -23.512377   5.652237
## sample estimates:
##  mean in group No mean in group Yes 
##          28.45455          37.38462
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$updrs_m36 by cc_fluc$fluc_m36
## t = -0.91326, df = 2.241, p-value = 0.4485
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -74.48349  46.15016
## sample estimates:
##  mean in group No mean in group Yes 
##          27.33333          41.50000



MoCA scores vs. Fluctuation status


## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$moca_base by cc_fluc$fluc_base
## t = 2.2136, df = 131.89, p-value = 0.02858
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  0.2227708 3.9656221
## sample estimates:
##  mean in group No mean in group Yes 
##          21.26562          19.17143
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$moca_m12 by cc_fluc$fluc_m12
## t = 0.20603, df = 28.385, p-value = 0.8382
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -3.887147  4.757147
## sample estimates:
##  mean in group No mean in group Yes 
##            18.875            18.440
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$moca_m24 by cc_fluc$fluc_m24
## t = 0.322, df = 20.042, p-value = 0.7508
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -5.394339  7.364036
## sample estimates:
##  mean in group No mean in group Yes 
##          18.16667          17.18182


CDR vs. Fluctuation status


## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$cdr_base by cc_fluc$fluc_base
## t = -0.6546, df = 70.037, p-value = 0.5149
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -1.8129261  0.9169433
## sample estimates:
##  mean in group No mean in group Yes 
##          4.661765          5.109756
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$cdr_m12 by cc_fluc$fluc_m12
## t = 0.30801, df = 15.122, p-value = 0.7623
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -2.419817  3.237999
## sample estimates:
##  mean in group No mean in group Yes 
##          5.909091          5.500000
## 
##  Welch Two Sample t-test
## 
## data:  cc_fluc$cdr_m24 by cc_fluc$fluc_m24
## t = -0.88223, df = 14.638, p-value = 0.3919
## alternative hypothesis: true difference in means between group No and group Yes is not equal to 0
## 95 percent confidence interval:
##  -4.884696  2.029140
## sample estimates:
##  mean in group No mean in group Yes 
##          5.350000          6.777778




Measuring consistency



## # A tibble: 11 × 5
## # Groups:   fluc_base, fluc_m12, fluc_m24 [7]
##    fluc_base fluc_m12 fluc_m24 fluc_m36     n
##    <chr>     <chr>    <chr>    <chr>    <int>
##  1 No        No       No       No           1
##  2 No        No       No       Yes          3
##  3 No        No       Yes      No           1
##  4 No        Yes      No       No           1
##  5 No        Yes      Yes      No           2
##  6 No        Yes      Yes      Yes          3
##  7 Yes       No       No       No           1
##  8 Yes       No       No       Yes          1
##  9 Yes       Yes      No       No           2
## 10 Yes       Yes      Yes      No           1
## 11 Yes       Yes      Yes      Yes          4
## # A tibble: 6 × 7
##   fluc_base fluc_m12 fluc_m24 fluc_m36 initial final group         
##   <chr>     <chr>    <chr>    <chr>      <dbl> <dbl> <chr>         
## 1 Yes       Yes      No       No             1     0 Improvement   
## 2 Yes       Yes      Yes      <NA>           1     1 Consistent yes
## 3 No        No       No       <NA>           0     0 Consistent no 
## 4 No        Yes      <NA>     <NA>           0     1 Progression   
## 5 Yes       No       No       Yes            1     1 Inconsistent  
## 6 No        No       Yes      No             0     0 Inconsistent
Overall
(N=171)
Group
Consistent no 15 (8.8%)
Consistent yes 38 (22.2%)
Improvement 12 (7.0%)
Inconsistent 8 (4.7%)
Progression 18 (10.5%)
Missing 80 (46.8%)
Overall
(N=91)
Group
Consistent no 15 (16.5%)
Consistent yes 38 (41.8%)
Improvement 12 (13.2%)
Inconsistent 8 (8.8%)
Progression 18 (19.8%)




Spaghetti plots for people who “progressed”





Spaghetti plots for people who “improved”






Spaghetti plots for consistent yes




Modeling


CDR vs. visit








CDR sums of boxes









MoCA









## Linear mixed model fit by REML ['lmerMod']
## Formula: CDR ~ (1 | DLBC_ID) + time * fluc_base + AGE_BASELINE
##    Data: cc_fluc_long_cdr
## 
## REML criterion at convergence: 706.5
## 
## Scaled residuals: 
##      Min       1Q   Median       3Q      Max 
## -1.87881 -0.44007 -0.08448  0.47183  2.03230 
## 
## Random effects:
##  Groups   Name        Variance Std.Dev.
##  DLBC_ID  (Intercept) 7.477    2.734   
##  Residual             2.639    1.624   
## Number of obs: 150, groups:  DLBC_ID, 75
## 
## Fixed effects:
##                   Estimate Std. Error t value
## (Intercept)       -4.28749    4.11447  -1.042
## time               1.11245    0.23348   4.765
## fluc_baseYes       0.60111    0.88129   0.682
## AGE_BASELINE       0.11175    0.05764   1.939
## time:fluc_baseYes -0.32908    0.34054  -0.966
## 
## Correlation of Fixed Effects:
##             (Intr) time   flc_bY AGE_BA
## time        -0.150                     
## fluc_baseYs -0.058  0.425              
## AGE_BASELIN -0.988  0.059 -0.056       
## tm:flc_bsYs  0.100 -0.685 -0.602 -0.038
  Baseline fluc Grouping Grouping
Predictors Estimates CI p Estimates CI p Estimates CI p
(Intercept) -4.29 -12.42 – 3.85 0.299 -3.50 -13.36 – 6.35 0.483 -5.65 -14.91 – 3.62 0.230
time 1.11 0.65 – 1.57 <0.001 0.88 0.26 – 1.50 0.006 0.88 0.23 – 1.52 0.009
fluc_baseYes 0.60 -1.14 – 2.34 0.496
Baseline age 0.11 -0.00 – 0.23 0.055 0.10 -0.03 – 0.24 0.133 0.13 0.01 – 0.26 0.039
time:fluc_baseYes -0.33 -1.00 – 0.34 0.335
groupConsistent yes 0.28 -2.40 – 2.97 0.835
groupImprovement 1.28 -1.92 – 4.48 0.430
groupInconsistent -1.06 -5.11 – 2.99 0.606
groupProgression 1.27 -1.92 – 4.45 0.432
time:groupConsistent yes 0.04 -0.85 – 0.92 0.938
time:groupImprovement 0.66 -0.34 – 1.65 0.193
time:groupInconsistent 0.40 -0.65 – 1.46 0.451
time:groupProgression -0.87 -2.00 – 0.25 0.127
group2Consistent yes 0.21 -2.51 – 2.93 0.878
group2Inconsistent 0.68 -1.98 – 3.34 0.613
time:group2Consistent yes 0.03 -0.90 – 0.96 0.948
time:group2Inconsistent 0.17 -0.66 – 0.99 0.686
Random Effects
σ2 2.64 2.16 2.37
τ00 7.48 DLBC_ID 8.71 DLBC_ID 8.62 DLBC_ID
ICC 0.74 0.80 0.78
N 75 DLBC_ID 63 DLBC_ID 63 DLBC_ID
Observations 150 128 128
Marginal R2 / Conditional R2 0.100 / 0.765 0.175 / 0.836 0.111 / 0.808
  Baseline fluc Grouping Grouping
Predictors Estimates CI p Estimates CI p Estimates CI p
(Intercept) 28.82 17.38 – 40.26 <0.001 29.65 15.01 – 44.29 <0.001 30.80 16.18 – 45.41 <0.001
time -1.74 -2.40 – -1.09 <0.001 -1.02 -2.16 – 0.12 0.079 -1.02 -2.16 – 0.11 0.078
fluc_baseYes -2.63 -5.15 – -0.12 0.040
Baseline age -0.08 -0.24 – 0.08 0.320 -0.10 -0.30 – 0.10 0.319 -0.12 -0.31 – 0.08 0.247
time:fluc_baseYes 0.46 -0.50 – 1.42 0.348
groupConsistent yes -1.37 -5.63 – 2.89 0.526
groupImprovement -3.95 -9.33 – 1.42 0.149
groupInconsistent 0.47 -5.59 – 6.53 0.879
groupProgression 0.98 -3.88 – 5.83 0.692
time:groupConsistent yes -0.65 -2.14 – 0.84 0.389
time:groupImprovement -1.15 -2.97 – 0.66 0.212
time:groupInconsistent -1.25 -2.95 – 0.45 0.149
time:groupProgression -0.16 -1.85 – 1.53 0.852
group2Consistent yes -1.34 -5.73 – 3.04 0.546
group2Inconsistent -0.57 -4.89 – 3.74 0.793
time:group2Consistent yes -0.66 -2.15 – 0.83 0.381
time:group2Inconsistent -0.86 -2.22 – 0.50 0.214
Random Effects
σ2 9.37 9.39 9.32
τ00 29.95 DLBC_ID 27.92 DLBC_ID 30.89 DLBC_ID
ICC 0.76 0.75 0.77
N 134 DLBC_ID 90 DLBC_ID 90 DLBC_ID
Observations 254 184 184
Marginal R2 / Conditional R2 0.074 / 0.779 0.171 / 0.791 0.090 / 0.789






Missingness



Missingness by attrition



Missing altogether


## # A tibble: 15 × 7
##    fluc_base fluc_m12 fluc_m24 fluc_m36 BASELINE_VISIT_DATE dod         ttd2
##    <chr>     <chr>    <chr>    <chr>    <date>              <date>     <dbl>
##  1 Yes       No       No       No       2017-08-29          2020-02-14   899
##  2 No        Yes      <NA>     <NA>     2018-03-13          2018-08-08   148
##  3 No        No       No       Yes      2018-01-09          2018-09-13   247
##  4 <NA>      <NA>     <NA>     No       2019-06-12          2021-11-28   900
##  5 <NA>      <NA>     Yes      <NA>     2020-02-25          2021-08-20   542
##  6 <NA>      <NA>     Yes      <NA>     2021-09-28          2023-06-22   632
##  7 <NA>      <NA>     No       <NA>     2022-01-24          2023-03-10   410
##  8 Yes       <NA>     Yes      Yes      2018-10-26          2020-08-25   669
##  9 Yes       Yes      <NA>     <NA>     2019-02-07          2019-07-11   154
## 10 Yes       Yes      <NA>     <NA>     2018-08-29          2019-05-02   246
## 11 Yes       <NA>     Yes      <NA>     2019-12-16          2020-10-24   313
## 12 Yes       Yes      Yes      <NA>     2017-10-12          2017-11-08    27
## 13 Yes       Yes      No       No       2019-06-12          2021-08-29   809
## 14 No        Yes      Yes      Yes      2019-10-07          2021-01-09   460
## 15 No        Yes      Yes      No       2018-05-01          2019-05-18   382



## # A tibble: 5 × 3
## # Groups:   fluc_m36 [3]
##   fluc_m36   dead_m36     n
##   <fct>      <chr>    <int>
## 1 No (n=10)  No           8
## 2 No (n=10)  Yes          2
## 3 Yes (n=13) No          13
## 4 NA (n=109) No          89
## 5 NA (n=109) Yes         20