\[\newcommand{\eq}[1]{\begin{align*}#1\end{align*}}\]
bds.info = f.read.bdsinfo()
bds.info$Fall = ifelse(bds.info$Falls12m > 0, 1, 0)
spectral = f.read.spectral()
dynamics = f.read.dynamics()The following table is intended to develop feasible hypotheses by providing
. frequency for each disease
. disease frequency associatd with age groups
. number of falls associated with age groups
. subject id
| Disease | Dis.Freq | Group | AgeG.Fall | Subjects |
|---|---|---|---|---|
| No | 56 | Old:8 You:48 | Old: 3 You: 12 | 162, 160, 144, 142, 141, 139, 138, 136, 135, 133, 128, 122, 119, 118, 117, 115, 114, 102, 101, 97, 90, 89, 71, 69, 66, 62, 61, 60, 53, 43, 41, 40, 39, 37, 36, 35, 34, 33, 32, 30, 28, 27, 25, 22, 21, 20, 19, 18, 16, 10, 9, 7, 6, 4, 3, 2 |
| Hypertension | 29 | Old:28 You:1 | Old: 3 You: 0 | 157, 156, 155, 154, 153, 150, 148, 146, 145, 131, 112, 105, 104, 100, 93, 91, 86, 84, 82, 79, 78, 76, 73, 72, 65, 59, 56, 52, 45 |
| Hypercholesterolemia | 20 | Old:17 You:3 | Old: 4 You: 1 | 154, 151, 145, 143, 131, 111, 103, 99, 95, 94, 92, 91, 86, 84, 77, 70, 64, 56, 52, 44 |
| Osteopenia | 14 | Old:12 You:2 | Old: 4 You: 0 | 157, 151, 150, 145, 131, 124, 113, 111, 110, 92, 56, 52, 49, 44 |
| Hypothyroidism | 13 | Old:10 You:3 | Old: 2 You: 1 | 161, 157, 151, 134, 127, 111, 107, 91, 72, 67, 52, 49, 1 |
| Arthrosis | 12 | Old:11 You:1 | Old: 3 You: 1 | 132, 108, 96, 87, 86, 85, 82, 77, 74, 70, 58, 55 |
| Diabetes mellitus | 12 | Old:12 You:0 | Old: 2 You: 0 | 157, 112, 111, 110, 88, 85, 83, 82, 75, 59, 50, 14 |
| Labyrinthitis | 12 | Old:10 You:2 | Old: 3 You: 2 | 158, 157, 154, 134, 123, 121, 110, 93, 84, 79, 73, 55 |
| Osteoporosis | 11 | Old:10 You:1 | Old: 3 You: 0 | 134, 109, 106, 105, 100, 88, 82, 81, 79, 77, 52 |
| Rhinitis | 11 | Old:0 You:11 | Old: 0 You: 4 | 127, 99, 80, 57, 38, 26, 24, 23, 15, 12, 11 |
| Asthma | 9 | Old:2 You:7 | Old: 0 You: 0 | 163, 159, 154, 148, 140, 63, 31, 8, 5 |
| Sinusitis | 5 | Old:1 You:4 | Old: 0 You: 1 | 150, 99, 57, 24, 12 |
| Hyperthyroidism | 3 | Old:1 You:2 | Old: 1 You: 1 | 152, 126, 105 |
| Hypoglycemia | 3 | Old:2 You:1 | Old: 0 You: 0 | 130, 77, 42 |
| Tendinitis | 3 | Old:0 You:3 | Old: 0 You: 0 | 159, 152, 13 |
| Allergy | 2 | Old:1 You:1 | Old: 0 You: 0 | 129, 106 |
| Anxiety | 2 | Old:1 You:1 | Old: 0 You: 0 | 116, 49 |
| Arrhythmia | 2 | Old:2 You:0 | Old: 0 You: 0 | 153, 87 |
| Arthritis | 2 | Old:2 You:0 | Old: 0 You: 0 | 150, 145 |
| Bronchitis | 2 | Old:1 You:1 | Old: 0 You: 1 | 52, 15 |
| Chodromalacia of the knees | 2 | Old:0 You:2 | Old: 0 You: 0 | 147, 99 |
| Depression | 2 | Old:1 You:1 | Old: 0 You: 1 | 70, 55 |
| Endometriosis | 2 | Old:0 You:2 | Old: 0 You: 1 | 137, 125 |
| Gastritis | 2 | Old:1 You:1 | Old: 1 You: 1 | 56, 15 |
| Gastroesophageal reflux | 2 | Old:1 You:1 | Old: 0 You: 1 | 49, 15 |
| Heart problem | 2 | Old:2 You:0 | Old: 0 You: 0 | 155, 74 |
| Heel spurs | 2 | Old:2 You:0 | Old: 0 You: 0 | 98, 74 |
| Migraine | 2 | Old:1 You:1 | Old: 0 You: 0 | 65, 26 |
| Spine problem | 2 | Old:1 You:1 | Old: 0 You: 0 | 159, 156 |
| Tendinitis of the knees | 2 | Old:0 You:2 | Old: 0 You: 0 | 159, 152 |
| Anemia | 1 | Old:1 You:0 | Old: 0 You: 0 | 156 |
| Arthrosis of the feet/hands | 1 | Old:1 You:0 | Old: 1 You: 0 | 85 |
| Arthrosis of the hands | 1 | Old:1 You:0 | Old: 0 You: 0 | 74 |
| Arthrosis of the knees | 1 | Old:1 You:0 | Old: 1 You: 0 | 108 |
| Arthrosis of the left knee | 1 | Old:0 You:1 | Old: 0 You: 1 | 55 |
| Arthrosis of the spine/knees/toes | 1 | Old:1 You:0 | Old: 1 You: 0 | 132 |
| Ascending colon cancer | 1 | Old:1 You:0 | Old: 0 You: 0 | 47 |
| Breathlessness | 1 | Old:1 You:0 | Old: 0 You: 0 | 67 |
| Bursitis | 1 | Old:1 You:0 | Old: 0 You: 0 | 145 |
| Conjunctivitis | 1 | Old:1 You:0 | Old: 0 You: 0 | 106 |
| Deep vein thrombosis | 1 | Old:1 You:0 | Old: 0 You: 0 | 120 |
| Dermatitis | 1 | Old:0 You:1 | Old: 0 You: 0 | 5 |
| Esophagitis | 1 | Old:1 You:0 | Old: 1 You: 0 | 56 |
| Essential tremor | 1 | Old:1 You:0 | Old: 1 You: 0 | 56 |
| Familial Hypercholesterolemia | 1 | Old:0 You:1 | Old: 0 You: 0 | 99 |
| Fatty liver | 1 | Old:1 You:0 | Old: 0 You: 0 | 151 |
| Fibromyalgia | 1 | Old:0 You:1 | Old: 0 You: 0 | 109 |
| Glaucoma | 1 | Old:1 You:0 | Old: 0 You: 0 | 86 |
| Hashimoto disease | 1 | Old:0 You:1 | Old: 0 You: 1 | 80 |
| Heart disease | 1 | Old:1 You:0 | Old: 1 You: 0 | 51 |
| Hepatitis B | 1 | Old:0 You:1 | Old: 0 You: 0 | 54 |
| Herniated lumbar disc | 1 | Old:1 You:0 | Old: 0 You: 0 | 79 |
| Herniated lumbar of the L4-L5 discs | 1 | Old:0 You:1 | Old: 0 You: 0 | 48 |
| Hypertriglyceridemia | 1 | Old:1 You:0 | Old: 0 You: 0 | 151 |
| Inflammation of the tibial nerve | 1 | Old:1 You:0 | Old: 0 You: 0 | 98 |
| Intestine disorder | 1 | Old:0 You:1 | Old: 0 You: 1 | 29 |
| Keratoconus | 1 | Old:0 You:1 | Old: 0 You: 0 | 5 |
| Kidney stones | 1 | Old:0 You:1 | Old: 0 You: 0 | 24 |
| Ligament problems | 1 | Old:0 You:1 | Old: 0 You: 0 | 159 |
| Lumbar tumor | 1 | Old:1 You:0 | Old: 0 You: 0 | 100 |
| Lymphedema of the lower members | 1 | Old:1 You:0 | Old: 1 You: 0 | 51 |
| Melanoma | 1 | Old:1 You:0 | Old: 0 You: 0 | 46 |
| Parkinson’s disease | 1 | Old:1 You:0 | Old: 0 You: 0 | 68 |
| Poliomyelitis | 1 | Old:1 You:0 | Old: 0 You: 0 | 59 |
| Progressive breast cancer | 1 | Old:1 You:0 | Old: 0 You: 0 | 47 |
| Prostate disease | 1 | Old:1 You:0 | Old: 0 You: 0 | 93 |
| Prostatitis | 1 | Old:1 You:0 | Old: 0 You: 0 | 98 |
| Rheumatism | 1 | Old:1 You:0 | Old: 0 You: 0 | 49 |
| Scoliosis | 1 | Old:0 You:1 | Old: 0 You: 1 | 143 |
| Sickle cell anemia | 1 | Old:0 You:1 | Old: 0 You: 0 | 38 |
| Sjogren’s syndrome | 1 | Old:1 You:0 | Old: 1 You: 0 | 149 |
| Skin cancer | 1 | Old:1 You:0 | Old: 0 You: 0 | 98 |
| Skin disease | 1 | Old:1 You:0 | Old: 0 You: 0 | 93 |
| Stroke | 1 | Old:1 You:0 | Old: 0 You: 0 | 52 |
| Tendinitis of the knees/feet | 1 | Old:0 You:1 | Old: 0 You: 0 | 159 |
| Urinary tract infection | 1 | Old:1 You:0 | Old: 1 You: 0 | 113 |
| Varicose veins of the legs | 1 | Old:1 You:0 | Old: 0 You: 0 | 154 |
| Vascular leakage of the eyes | 1 | Old:1 You:0 | Old: 1 You: 0 | 85 |
| Vasovagal syncope | 1 | Old:0 You:1 | Old: 0 You: 1 | 15 |
| Vitiligo | 1 | Old:0 You:1 | Old: 0 You: 1 | 17 |
HC = Healthy Controls, IL = Illness
c(“Hypercholesterolemia”, “Rhinitis”, “Labyrinthitis”, “Arthrosis”,“Sinusitis”)
93 Falls, no illness 7 Falls, 20 Hypercholesterolemia 4 Falls, 3 Hyperthoyroidsism
4 Falls, 13 Osteopenia 4 Falls 11 Osteoporosis
21 Falls, 11 Rhinits, Nose 7 Falls, 12 Labyrinthitis 5 Falls, 5 Sinusities
# readin
df = f.read.bdsinfo()
dis = c("Hypercholesterolemia", "Hyperthoyroidsism",
"Rhinitis", "Labyrinthitis", "Sinusitis",
"Arthrosis", "Osteopenia")
# select trial with patient with specific disease
dl = data.frame(sapply(dis, function(x) (grepl(x, df$Illness2))))
df$select = apply(dl, 1, any)
# Allocate disease
dl$disease = 0
for (i in 1:length(dis)){
dl$disease[dl[,i]] = rep(colnames(dl)[i], dim(dl)[1])[dl[,i]]
}
df$Disease = dl$disease
vrb = c("Trial", "Subject", "Gender", "AgeGroup", "Falls12m", "Illness2", "Disease", "Ortho-Prosthesis2")
chrt = subset(df[!duplicated(df$Subject), ], select = vrb)
t.kable(chrt)| Trial | Subject | Gender | AgeGroup | Falls12m | Illness2 | Disease | Ortho-Prosthesis2 | |
|---|---|---|---|---|---|---|---|---|
| 1 | BDS00001 | 1 | F | Young | 0 | Hypothyroidism | 0 | Corrective lens |
| 13 | BDS00013 | 2 | F | Young | 0 | No | 0 | No |
| 25 | BDS00025 | 3 | M | Young | 0 | No | 0 | Bridge teeh |
| 37 | BDS00037 | 4 | M | Old | 1 | No | 0 | Denture |
| 49 | BDS00049 | 5 | F | Young | 0 | Asthma, Dermatitis, Keratoconus | 0 | No |
| 61 | BDS00061 | 6 | M | Young | 1 | No | 0 | Corrective lens, Denture |
| 73 | BDS00073 | 7 | M | Young | 0 | No | 0 | Corrective lens, Dental braces |
| 85 | BDS00085 | 8 | F | Young | 0 | Asthma | 0 | Corrective lens |
| 97 | BDS00097 | 9 | F | Young | 0 | No | 0 | Corrective lens |
| 109 | BDS00109 | 10 | F | Young | 1 | No | 0 | Corrective lens |
| 121 | BDS00121 | 11 | M | Young | 0 | Rhinitis | Rhinitis | No |
| 133 | BDS00133 | 12 | M | Young | 0 | Rhinitis, Sinusitis | Sinusitis | Corrective lens |
| 145 | BDS00145 | 13 | M | Young | 0 | Tendinitis | 0 | Corrective lens |
| 157 | BDS00157 | 14 | M | Old | 0 | Diabetes mellitus | 0 | Corrective lens |
| 169 | BDS00169 | 15 | F | Young | 1 | Vasovagal syncope, Gastritis, Bronchitis, Rhinitis, Gastroesophageal reflux | Rhinitis | No |
| 181 | BDS00181 | 16 | M | Young | 0 | No | 0 | Corrective lens |
| 193 | BDS00193 | 17 | F | Young | 3 | Vitiligo | 0 | No |
| 205 | BDS00205 | 18 | M | Young | 0 | No | 0 | No |
| 217 | BDS00217 | 19 | M | Young | 1 | No | 0 | No |
| 229 | BDS00229 | 20 | M | Young | 1 | No | 0 | Corrective lens, Dental braces |
| 241 | BDS00241 | 21 | F | Young | 0 | No | 0 | Corrective lens |
| 253 | BDS00253 | 22 | F | Young | 0 | No | 0 | Corrective lens |
| 265 | BDS00265 | 23 | F | Young | 0 | Rhinitis | Rhinitis | No |
| 277 | BDS00277 | 24 | F | Young | 0 | Rhinitis, Sinusitis, Kidney stones | Sinusitis | Corrective lens |
| 289 | BDS00289 | 25 | F | Young | 0 | No | 0 | Corrective lens |
| 301 | BDS00301 | 26 | F | Young | 0 | Rhinitis, Migraine | Rhinitis | Corrective lens |
| 313 | BDS00313 | 27 | F | Young | 0 | No | 0 | Dental retention |
| 325 | BDS00325 | 28 | M | Young | 0 | No | 0 | Corrective lens |
| 337 | BDS00337 | 29 | F | Young | 1 | Intestine disorder | 0 | No |
| 349 | BDS00349 | 30 | F | Young | 0 | No | 0 | Corrective lens |
| 361 | BDS00361 | 31 | F | Young | 0 | Asthma | 0 | Corrective lens |
| 373 | BDS00373 | 32 | M | Young | 0 | No | 0 | No |
| 385 | BDS00385 | 33 | M | Young | 0 | No | 0 | Corrective lens |
| 397 | BDS00397 | 34 | F | Young | 0 | No | 0 | Corrective lens |
| 409 | BDS00409 | 35 | M | Young | 0 | No | 0 | No |
| 421 | BDS00421 | 36 | M | Young | 0 | No | 0 | No |
| 433 | BDS00433 | 37 | M | Young | 0 | No | 0 | Corrective lens |
| 445 | BDS00445 | 38 | M | Young | 0 | Rhinitis, Sickle cell anemia | Rhinitis | No |
| 457 | BDS00457 | 39 | F | Young | 0 | No | 0 | No |
| 469 | BDS00469 | 40 | F | Young | 0 | No | 0 | Corrective lens |
| 481 | BDS00481 | 41 | M | Old | 0 | No | 0 | Corrective lens, Bridge teeh |
| 493 | BDS00493 | 42 | F | Old | 0 | Hypoglycemia | 0 | Corrective lens |
| 505 | BDS00505 | 43 | F | Old | 0 | No | 0 | No |
| 517 | BDS00517 | 44 | F | Old | 0 | Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
| 529 | BDS00529 | 45 | M | Old | 0 | Hypertension | 0 | Corrective lens |
| 541 | BDS00541 | 46 | M | Old | 0 | Melanoma | 0 | Corrective lens |
| 553 | BDS00553 | 47 | F | Old | 0 | Ascending colon cancer, Progressive breast cancer | 0 | Corrective lens |
| 565 | BDS00565 | 48 | F | Young | 0 | Herniated lumbar of the L4-L5 discs | 0 | Corrective lens, Dental braces |
| 577 | BDS00577 | 49 | F | Old | 0 | Hypothyroidism, Rheumatism, Anxiety, Osteopenia, Gastroesophageal reflux | Osteopenia | Corrective lens, Hearing aid, Dental implant |
| 589 | BDS00589 | 50 | F | Old | 0 | Diabetes mellitus | 0 | Corrective lens |
| 601 | BDS00601 | 51 | F | Old | 1 | Heart disease, Lymphedema of the lower members | 0 | Corrective lens |
| 613 | BDS00613 | 52 | F | Old | 0 | Osteoporosis, Osteopenia, Hypothyroidism, Stroke, Hypertension, Hypercholesterolemia, Bronchitis | Osteopenia | Corrective lens |
| 625 | BDS00625 | 53 | F | Young | 1 | No | 0 | Corrective lens |
| 637 | BDS00637 | 54 | M | Young | 0 | Hepatitis B | 0 | No |
| 649 | BDS00649 | 55 | F | Young | 3 | Depression, Arthrosis of the left knee, Labyrinthitis | Arthrosis | Corrective lens |
| 661 | BDS00661 | 56 | F | Old | 1 | Hypertension, Hypercholesterolemia, Essential tremor, Osteopenia, Gastritis, Esophagitis | Osteopenia | Corrective lens |
| 673 | BDS00673 | 57 | F | Young | 5 | Rhinitis, Sinusitis | Sinusitis | Corrective lens, Dental retention |
| 685 | BDS00685 | 58 | F | Old | 0 | Arthrosis | Arthrosis | Corrective lens, PaceMaker |
| 697 | BDS00697 | 59 | M | Old | 0 | Hypertension, Diabetes mellitus, Poliomyelitis | 0 | Corrective lens |
| 703 | BDS00709 | 60 | M | Young | 6 | No | 0 | Crutch |
| 712 | BDS00721 | 61 | F | Young | 1 | No | 0 | Corrective lens |
| 724 | BDS00733 | 62 | M | Young | 0 | No | 0 | Corrective lens, Dental braces |
| 736 | BDS00745 | 63 | F | Young | 0 | Asthma | 0 | Corrective lens, Dental retention |
| 748 | BDS00757 | 64 | F | Old | 2 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Bridge teeh |
| 760 | BDS00769 | 65 | F | Old | 0 | Hypertension, Migraine | 0 | Corrective lens, Denture |
| 772 | BDS00781 | 66 | M | Young | 0 | No | 0 | Corrective lens |
| 784 | BDS00793 | 67 | M | Old | 0 | Hypothyroidism, Breathlessness | 0 | Corrective lens, Denture |
| 796 | BDS00805 | 68 | M | Old | 0 | Parkinson’s disease | 0 | Corrective lens, Denture |
| 808 | BDS00817 | 69 | F | Old | 0 | No | 0 | Corrective lens |
| 820 | BDS00829 | 70 | F | Old | 0 | Depression, Hypercholesterolemia, Arthrosis | Arthrosis | Corrective lens, Dental prosthesis |
| 832 | BDS00841 | 71 | F | Old | 0 | No | 0 | Bridge teeh |
| 844 | BDS00853 | 72 | F | Old | 1 | Hypothyroidism, Hypertension | 0 | Corrective lens, Denture |
| 856 | BDS00865 | 73 | F | Old | 0 | Hypertension, Labyrinthitis | Labyrinthitis | Corrective lens, Denture |
| 868 | BDS00877 | 74 | F | Old | 0 | Heel spurs, Heart problem, Arthrosis of the hands | Arthrosis | Corrective lens, By pass |
| 880 | BDS00889 | 75 | F | Old | 0 | Diabetes mellitus | 0 | Corrective lens |
| 892 | BDS00901 | 76 | M | Old | 0 | Hypertension | 0 | Corrective lens |
| 904 | BDS00913 | 77 | F | Old | 0 | Osteoporosis, Arthrosis, Hypercholesterolemia, Hypoglycemia | Arthrosis | Corrective lens, Bridge teeh |
| 916 | BDS00925 | 78 | F | Old | 0 | Hypertension | 0 | Corrective lens, Denture |
| 928 | BDS00937 | 79 | F | Old | 0 | Hypertension, Osteoporosis, Herniated lumbar disc, Labyrinthitis | Labyrinthitis | Corrective lens, Denture |
| 940 | BDS00949 | 80 | F | Young | 12 | Hashimoto disease, Rhinitis | Rhinitis | Corrective lens, Extensor left knee orthosis |
| 952 | BDS00961 | 81 | F | Old | 2 | Osteoporosis | 0 | Corrective lens, Denture |
| 964 | BDS00973 | 82 | F | Old | 0 | Diabetes mellitus, Hypertension, Osteoporosis, Arthrosis | Arthrosis | Corrective lens, Dental implant, Denture |
| 976 | BDS00985 | 83 | M | Old | 0 | Diabetes mellitus | 0 | Dental implant |
| 988 | BDS00997 | 84 | F | Old | 0 | Labyrinthitis, Hypertension, Hypercholesterolemia | Labyrinthitis | Corrective lens, Dental prosthesis |
| 1000 | BDS01009 | 85 | F | Old | 1 | Diabetes mellitus, Arthrosis of the feet/hands, Vascular leakage of the eyes | Arthrosis | Corrective lens, Protese dentaria |
| 1012 | BDS01021 | 86 | F | Old | 0 | Hypertension, Hypercholesterolemia, Glaucoma, Arthrosis | Arthrosis | Corrective lens, Hearing aid, Dental prosthesis |
| 1018 | BDS01033 | 87 | F | Old | 0 | Arrhythmia, Arthrosis | Arthrosis | Corrective lens, Hearing aid, Denture |
| 1030 | BDS01045 | 88 | F | Old | 0 | Diabetes mellitus, Osteoporosis | 0 | Corrective lens, Dental implant |
| 1042 | BDS01057 | 89 | M | Young | 0 | No | 0 | No |
| 1054 | BDS01069 | 90 | M | Young | 1 | No | 0 | Corrective lens |
| 1066 | BDS01081 | 91 | F | Old | 0 | Hypothyroidism, Hypertension, Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental prosthesis |
| 1078 | BDS01093 | 92 | F | Old | 1 | Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens, Dental prosthesis |
| 1090 | BDS01105 | 93 | M | Old | 0 | Hypertension, Labyrinthitis, Prostate disease, Skin disease | Labyrinthitis | Corrective lens, Dental prosthesis, Denture |
| 1102 | BDS01117 | 94 | F | Old | 0 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental implant |
| 1114 | BDS01129 | 95 | F | Old | 1 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental prosthesis |
| 1126 | BDS01141 | 96 | M | Old | 0 | Arthrosis | Arthrosis | Corrective lens, Dental prosthesis |
| 1138 | BDS01153 | 97 | M | Young | 1 | No | 0 | Corrective lens |
| 1150 | BDS01165 | 98 | M | Old | 0 | Heel spurs, Inflammation of the tibial nerve, Prostatitis, Skin cancer | 0 | Corrective lens, Denture |
| 1162 | BDS01177 | 99 | F | Young | 0 | Familial Hypercholesterolemia, Chodromalacia of the knees, Sinusitis, Rhinitis | Sinusitis | Dental retention |
| 1174 | BDS01189 | 100 | F | Old | 0 | Hypertension, Lumbar tumor, Osteoporosis | 0 | Corrective lens |
| 1186 | BDS01201 | 101 | F | Young | 4 | No | 0 | No |
| 1198 | BDS01213 | 102 | F | Old | 1 | No | 0 | Corrective lens, Denture, Bridge teeh |
| 1210 | BDS01225 | 103 | F | Old | 0 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Denture |
| 1222 | BDS01237 | 104 | F | Old | 0 | Hypertension | 0 | Corrective lens |
| 1234 | BDS01249 | 105 | F | Old | 1 | Osteoporosis, Hypertension, Hyperthyroidism | 0 | Corrective lens, Dental prosthesis |
| 1246 | BDS01261 | 106 | F | Old | 0 | Allergy, Osteoporosis, Conjunctivitis | 0 | Corrective lens, Denture |
| 1258 | BDS01273 | 107 | F | Old | 0 | Hypothyroidism | 0 | Corrective lens, Hearing aid |
| 1270 | BDS01285 | 108 | F | Old | 1 | Arthrosis of the knees | Arthrosis | Corrective lens, Denture, Dental implant |
| 1282 | BDS01297 | 109 | F | Young | 0 | Osteoporosis, Fibromyalgia | 0 | Corrective lens |
| 1294 | BDS01309 | 110 | F | Old | 1 | Diabetes mellitus, Osteopenia, Labyrinthitis | Osteopenia | Corrective lens |
| 1306 | BDS01321 | 111 | F | Old | 0 | Diabetes mellitus, Hypothyroidism, Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
| 1318 | BDS01333 | 112 | F | Old | 0 | Diabetes mellitus, Hypertension | 0 | Corrective lens, Dental prosthesis |
| 1330 | BDS01345 | 113 | F | Old | 1 | Urinary tract infection, Osteopenia | Osteopenia | Corrective lens, Dental prosthesis |
| 1342 | BDS01357 | 114 | F | Young | 0 | No | 0 | No |
| 1354 | BDS01369 | 115 | F | Young | 1 | No | 0 | Corrective lens, Dental retention |
| 1366 | BDS01381 | 116 | F | Young | 0 | Anxiety | 0 | No |
| 1378 | BDS01393 | 117 | F | Young | 0 | No | 0 | No |
| 1390 | BDS01405 | 118 | F | Young | 0 | No | 0 | No |
| 1402 | BDS01417 | 119 | F | Young | 0 | No | 0 | Corrective lens |
| 1414 | BDS01429 | 120 | F | Old | 0 | Deep vein thrombosis | 0 | No |
| 1426 | BDS01441 | 121 | F | Old | 1 | Labyrinthitis | Labyrinthitis | Corrective lens |
| 1438 | BDS01453 | 122 | M | Old | 52 | No | 0 | Corrective lens, Denture, Crutch |
| 1442 | BDS01465 | 123 | F | Young | 1 | Labyrinthitis | Labyrinthitis | Corrective lens |
| 1454 | BDS01477 | 124 | F | Young | 0 | Osteopenia | Osteopenia | Corrective lens |
| 1466 | BDS01489 | 125 | F | Young | 0 | Endometriosis | 0 | Corrective lens |
| 1478 | BDS01501 | 126 | F | Young | 3 | Hyperthyroidism | 0 | Corrective lens |
| 1490 | BDS01513 | 127 | F | Young | 3 | Hypothyroidism, Rhinitis | Rhinitis | Corrective lens |
| 1502 | BDS01525 | 128 | F | Young | 0 | No | 0 | Corrective lens |
| 1514 | BDS01537 | 129 | F | Young | 0 | Allergy | 0 | Corrective lens |
| 1526 | BDS01549 | 130 | F | Young | 0 | Hypoglycemia | 0 | Corrective lens, Dental retention |
| 1538 | BDS01561 | 131 | F | Young | 0 | Hypertension, Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
| 1550 | BDS01573 | 132 | F | Old | 1 | Arthrosis of the spine/knees/toes | Arthrosis | Corrective lens, Denture |
| 1562 | BDS01585 | 133 | F | Old | 0 | No | 0 | Corrective lens, Dental prosthesis, Denture |
| 1574 | BDS01597 | 134 | F | Old | 1 | Labyrinthitis, Osteoporosis, Hypothyroidism | Labyrinthitis | Corrective lens, Dental prosthesis |
| 1583 | BDS01609 | 135 | M | Young | 0 | No | 0 | Corrective lens |
| 1595 | BDS01621 | 136 | F | Young | 0 | No | 0 | Corrective lens |
| 1607 | BDS01633 | 137 | F | Young | 3 | Endometriosis | 0 | No |
| 1619 | BDS01645 | 138 | M | Young | 0 | No | 0 | 1 intramedullary rod and 3 screws in the left leg |
| 1631 | BDS01657 | 139 | F | Young | 20 | No | 0 | Corrective lens |
| 1643 | BDS01669 | 140 | M | Young | 0 | Asthma | 0 | Corrective lens |
| 1655 | BDS01681 | 141 | F | Young | 0 | No | 0 | No |
| 1667 | BDS01693 | 142 | F | Young | 0 | No | 0 | Corrective lens |
| 1679 | BDS01705 | 143 | F | Young | 2 | Scoliosis, Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental retention |
| 1691 | BDS01717 | 144 | M | Young | 0 | No | 0 | No |
| 1703 | BDS01729 | 145 | F | Old | 0 | Hypertension, Hypercholesterolemia, Osteopenia, Arthritis, Bursitis | Osteopenia | Prosthesis aortic valve, Corrective lens, Dental implant |
| 1715 | BDS01741 | 146 | M | Old | 0 | Hypertension | 0 | Corrective lens, Dental prosthesis |
| 1727 | BDS01753 | 147 | F | Young | 0 | Chodromalacia of the knees | 0 | Corrective lens, Dental retention |
| 1739 | BDS01765 | 148 | F | Old | 0 | Asthma, Hypertension | 0 | Corrective lens |
| 1751 | BDS01777 | 149 | F | Old | 1 | Sjogren’s syndrome | 0 | Corrective lens, Denture |
| 1763 | BDS01789 | 150 | F | Old | 0 | Hypertension, Osteopenia, Arthritis, Sinusitis | Osteopenia | Corrective lens, Denture |
| 1775 | BDS01801 | 151 | F | Old | 0 | Hypothyroidism, Hypercholesterolemia, Hypertriglyceridemia, Osteopenia, Fatty liver | Osteopenia | Corrective lens, Dental implant |
| 1787 | BDS01813 | 152 | M | Young | 0 | Hyperthyroidism, Tendinitis of the knees | 0 | Corrective lens |
| 1799 | BDS01825 | 153 | F | Old | 0 | Arrhythmia, Hypertension | 0 | Corrective lens, Dental implant, 1 screw in the right toe |
| 1811 | BDS01837 | 154 | M | Old | 0 | Hypertension, Hypercholesterolemia, Labyrinthitis, Asthma, Varicose veins of the legs | Labyrinthitis | Hearing aid, Corrective lens, Dental implant, Dental prosthesis |
| 1823 | BDS01849 | 155 | F | Old | 0 | Hypertension, Heart problem | 0 | Corrective lens, Denture |
| 1835 | BDS01861 | 156 | F | Old | 0 | Anemia, Hypertension, Spine problem | 0 | Dental implant |
| 1847 | BDS01873 | 157 | F | Old | 0 | Hypertension, Diabetes mellitus, Osteopenia, Labyrinthitis, Hypothyroidism | Osteopenia | Corrective lens, Denture |
| 1859 | BDS01885 | 158 | F | Old | 0 | Labyrinthitis | Labyrinthitis | Corrective lens, Dental prosthesis |
| 1871 | BDS01897 | 159 | F | Young | 0 | Tendinitis of the knees/feet, Ligament problems, Spine problem, Asthma | 0 | No |
| 1883 | BDS01909 | 160 | F | Young | 0 | No | 0 | Corrective lens |
| 1895 | BDS01921 | 161 | F | Young | 0 | Hypothyroidism | 0 | No |
| 1907 | BDS01933 | 162 | M | Young | 0 | No | 0 | Corrective lens |
| 1919 | BDS01945 | 163 | M | Young | 0 | Asthma | 0 | Corrective lens |
# AgeGroup
df.old = chrt[chrt$AgeGroup == "Old" ,]
t.kable(do.call(rbind,
apply(df.old[,-c(1,2,6)], 2,
as.data.frame(table))
)
)| value.Var1 | value.Freq | |
|---|---|---|
| Gender.1 | F | 60 |
| Gender.2 | M | 16 |
| AgeGroup | Old | 76 |
| Falls12m.1 | 0 | 57 |
| Falls12m.2 | 1 | 16 |
| Falls12m.3 | 2 | 2 |
| Falls12m.4 | 52 | 1 |
| Disease.1 | 0 | 40 |
| Disease.2 | Arthrosis | 11 |
| Disease.3 | Hypercholesterolemia | 5 |
| Disease.4 | Labyrinthitis | 8 |
| Disease.5 | Osteopenia | 12 |
| Ortho-Prosthesis2.1 | Bridge teeh | 1 |
| Ortho-Prosthesis2.2 | Corrective lens | 20 |
| Ortho-Prosthesis2.3 | Corrective lens, Bridge teeh | 3 |
| Ortho-Prosthesis2.4 | Corrective lens, By pass | 1 |
| Ortho-Prosthesis2.5 | Corrective lens, Dental implant | 3 |
| Ortho-Prosthesis2.6 | Corrective lens, Dental implant, 1 screw in the right toe | 1 |
| Ortho-Prosthesis2.7 | Corrective lens, Dental implant, Denture | 1 |
| Ortho-Prosthesis2.8 | Corrective lens, Dental prosthesis | 12 |
| Ortho-Prosthesis2.9 | Corrective lens, Dental prosthesis, Denture | 2 |
| Ortho-Prosthesis2.10 | Corrective lens, Denture | 16 |
| Ortho-Prosthesis2.11 | Corrective lens, Denture, Bridge teeh | 1 |
| Ortho-Prosthesis2.12 | Corrective lens, Denture, Crutch | 1 |
| Ortho-Prosthesis2.13 | Corrective lens, Denture, Dental implant | 1 |
| Ortho-Prosthesis2.14 | Corrective lens, Hearing aid | 1 |
| Ortho-Prosthesis2.15 | Corrective lens, Hearing aid, Dental implant | 1 |
| Ortho-Prosthesis2.16 | Corrective lens, Hearing aid, Dental prosthesis | 1 |
| Ortho-Prosthesis2.17 | Corrective lens, Hearing aid, Denture | 1 |
| Ortho-Prosthesis2.18 | Corrective lens, PaceMaker | 1 |
| Ortho-Prosthesis2.19 | Corrective lens, Protese dentaria | 1 |
| Ortho-Prosthesis2.20 | Dental implant | 2 |
| Ortho-Prosthesis2.21 | Denture | 1 |
| Ortho-Prosthesis2.22 | Hearing aid, Corrective lens, Dental implant, Dental prosthesis | 1 |
| Ortho-Prosthesis2.23 | No | 2 |
| Ortho-Prosthesis2.24 | Prosthesis aortic valve, Corrective lens, Dental implant | 1 |
dis = c("Hypercholesterolemia", "Hyperthoyroidsism",
"Rhinitis", "Labyrinthitis", "Sinusitis",
"Arthrosis", "Osteopenia")
l = lapply(dis, function(x)
subset(df.old, Disease == x)
)
t.kable(do.call(rbind, l))| Trial | Subject | Gender | AgeGroup | Falls12m | Illness2 | Disease | Ortho-Prosthesis2 | |
|---|---|---|---|---|---|---|---|---|
| 748 | BDS00757 | 64 | F | Old | 2 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Bridge teeh |
| 1066 | BDS01081 | 91 | F | Old | 0 | Hypothyroidism, Hypertension, Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental prosthesis |
| 1102 | BDS01117 | 94 | F | Old | 0 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental implant |
| 1114 | BDS01129 | 95 | F | Old | 1 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental prosthesis |
| 1210 | BDS01225 | 103 | F | Old | 0 | Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Denture |
| 856 | BDS00865 | 73 | F | Old | 0 | Hypertension, Labyrinthitis | Labyrinthitis | Corrective lens, Denture |
| 928 | BDS00937 | 79 | F | Old | 0 | Hypertension, Osteoporosis, Herniated lumbar disc, Labyrinthitis | Labyrinthitis | Corrective lens, Denture |
| 988 | BDS00997 | 84 | F | Old | 0 | Labyrinthitis, Hypertension, Hypercholesterolemia | Labyrinthitis | Corrective lens, Dental prosthesis |
| 1090 | BDS01105 | 93 | M | Old | 0 | Hypertension, Labyrinthitis, Prostate disease, Skin disease | Labyrinthitis | Corrective lens, Dental prosthesis, Denture |
| 1426 | BDS01441 | 121 | F | Old | 1 | Labyrinthitis | Labyrinthitis | Corrective lens |
| 1574 | BDS01597 | 134 | F | Old | 1 | Labyrinthitis, Osteoporosis, Hypothyroidism | Labyrinthitis | Corrective lens, Dental prosthesis |
| 1811 | BDS01837 | 154 | M | Old | 0 | Hypertension, Hypercholesterolemia, Labyrinthitis, Asthma, Varicose veins of the legs | Labyrinthitis | Hearing aid, Corrective lens, Dental implant, Dental prosthesis |
| 1859 | BDS01885 | 158 | F | Old | 0 | Labyrinthitis | Labyrinthitis | Corrective lens, Dental prosthesis |
| 685 | BDS00685 | 58 | F | Old | 0 | Arthrosis | Arthrosis | Corrective lens, PaceMaker |
| 820 | BDS00829 | 70 | F | Old | 0 | Depression, Hypercholesterolemia, Arthrosis | Arthrosis | Corrective lens, Dental prosthesis |
| 868 | BDS00877 | 74 | F | Old | 0 | Heel spurs, Heart problem, Arthrosis of the hands | Arthrosis | Corrective lens, By pass |
| 904 | BDS00913 | 77 | F | Old | 0 | Osteoporosis, Arthrosis, Hypercholesterolemia, Hypoglycemia | Arthrosis | Corrective lens, Bridge teeh |
| 964 | BDS00973 | 82 | F | Old | 0 | Diabetes mellitus, Hypertension, Osteoporosis, Arthrosis | Arthrosis | Corrective lens, Dental implant, Denture |
| 1000 | BDS01009 | 85 | F | Old | 1 | Diabetes mellitus, Arthrosis of the feet/hands, Vascular leakage of the eyes | Arthrosis | Corrective lens, Protese dentaria |
| 1012 | BDS01021 | 86 | F | Old | 0 | Hypertension, Hypercholesterolemia, Glaucoma, Arthrosis | Arthrosis | Corrective lens, Hearing aid, Dental prosthesis |
| 1018 | BDS01033 | 87 | F | Old | 0 | Arrhythmia, Arthrosis | Arthrosis | Corrective lens, Hearing aid, Denture |
| 1126 | BDS01141 | 96 | M | Old | 0 | Arthrosis | Arthrosis | Corrective lens, Dental prosthesis |
| 1270 | BDS01285 | 108 | F | Old | 1 | Arthrosis of the knees | Arthrosis | Corrective lens, Denture, Dental implant |
| 1550 | BDS01573 | 132 | F | Old | 1 | Arthrosis of the spine/knees/toes | Arthrosis | Corrective lens, Denture |
| 517 | BDS00517 | 44 | F | Old | 0 | Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
| 577 | BDS00577 | 49 | F | Old | 0 | Hypothyroidism, Rheumatism, Anxiety, Osteopenia, Gastroesophageal reflux | Osteopenia | Corrective lens, Hearing aid, Dental implant |
| 613 | BDS00613 | 52 | F | Old | 0 | Osteoporosis, Osteopenia, Hypothyroidism, Stroke, Hypertension, Hypercholesterolemia, Bronchitis | Osteopenia | Corrective lens |
| 661 | BDS00661 | 56 | F | Old | 1 | Hypertension, Hypercholesterolemia, Essential tremor, Osteopenia, Gastritis, Esophagitis | Osteopenia | Corrective lens |
| 1078 | BDS01093 | 92 | F | Old | 1 | Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens, Dental prosthesis |
| 1294 | BDS01309 | 110 | F | Old | 1 | Diabetes mellitus, Osteopenia, Labyrinthitis | Osteopenia | Corrective lens |
| 1306 | BDS01321 | 111 | F | Old | 0 | Diabetes mellitus, Hypothyroidism, Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
| 1330 | BDS01345 | 113 | F | Old | 1 | Urinary tract infection, Osteopenia | Osteopenia | Corrective lens, Dental prosthesis |
| 1703 | BDS01729 | 145 | F | Old | 0 | Hypertension, Hypercholesterolemia, Osteopenia, Arthritis, Bursitis | Osteopenia | Prosthesis aortic valve, Corrective lens, Dental implant |
| 1763 | BDS01789 | 150 | F | Old | 0 | Hypertension, Osteopenia, Arthritis, Sinusitis | Osteopenia | Corrective lens, Denture |
| 1775 | BDS01801 | 151 | F | Old | 0 | Hypothyroidism, Hypercholesterolemia, Hypertriglyceridemia, Osteopenia, Fatty liver | Osteopenia | Corrective lens, Dental implant |
| 1847 | BDS01873 | 157 | F | Old | 0 | Hypertension, Diabetes mellitus, Osteopenia, Labyrinthitis, Hypothyroidism | Osteopenia | Corrective lens, Denture |
t = data.frame()
for (i in dis){
temp = subset(df.old, Disease == i)
tmp = do.call(rbind,
apply(temp[,-c(1,2,6)], 2,
as.data.frame(table))
)
if (dim(tmp)[2] == 2) t = rbind(tmp, t)
}
t.kable(t)| value.Var1 | value.Freq | |
|---|---|---|
| Gender | F | 12 |
| AgeGroup | Old | 12 |
| Falls12m.1 | 0 | 8 |
| Falls12m.2 | 1 | 4 |
| Disease | Osteopenia | 12 |
| Ortho-Prosthesis2.1 | Corrective lens | 5 |
| Ortho-Prosthesis2.2 | Corrective lens, Dental implant | 1 |
| Ortho-Prosthesis2.3 | Corrective lens, Dental prosthesis | 2 |
| Ortho-Prosthesis2.4 | Corrective lens, Denture | 2 |
| Ortho-Prosthesis2.5 | Corrective lens, Hearing aid, Dental implant | 1 |
| Ortho-Prosthesis2.6 | Prosthesis aortic valve, Corrective lens, Dental implant | 1 |
| Gender.1 | F | 10 |
| Gender.2 | M | 1 |
| AgeGroup3 | Old | 11 |
| Falls12m.13 | 0 | 8 |
| Falls12m.23 | 1 | 3 |
| Disease3 | Arthrosis | 11 |
| Ortho-Prosthesis2.13 | Corrective lens, Bridge teeh | 1 |
| Ortho-Prosthesis2.23 | Corrective lens, By pass | 1 |
| Ortho-Prosthesis2.33 | Corrective lens, Dental implant, Denture | 1 |
| Ortho-Prosthesis2.43 | Corrective lens, Dental prosthesis | 2 |
| Ortho-Prosthesis2.52 | Corrective lens, Denture | 1 |
| Ortho-Prosthesis2.61 | Corrective lens, Denture, Dental implant | 1 |
| Ortho-Prosthesis2.7 | Corrective lens, Hearing aid, Dental prosthesis | 1 |
| Ortho-Prosthesis2.8 | Corrective lens, Hearing aid, Denture | 1 |
| Ortho-Prosthesis2.9 | Corrective lens, PaceMaker | 1 |
| Ortho-Prosthesis2.10 | Corrective lens, Protese dentaria | 1 |
| Gender.11 | F | 6 |
| Gender.21 | M | 2 |
| AgeGroup2 | Old | 8 |
| Falls12m.12 | 0 | 6 |
| Falls12m.22 | 1 | 2 |
| Disease2 | Labyrinthitis | 8 |
| Ortho-Prosthesis2.12 | Corrective lens | 1 |
| Ortho-Prosthesis2.22 | Corrective lens, Dental prosthesis | 3 |
| Ortho-Prosthesis2.32 | Corrective lens, Dental prosthesis, Denture | 1 |
| Ortho-Prosthesis2.42 | Corrective lens, Denture | 2 |
| Ortho-Prosthesis2.51 | Hearing aid, Corrective lens, Dental implant, Dental prosthesis | 1 |
| Gender1 | F | 5 |
| AgeGroup1 | Old | 5 |
| Falls12m.11 | 0 | 3 |
| Falls12m.21 | 1 | 1 |
| Falls12m.3 | 2 | 1 |
| Disease1 | Hypercholesterolemia | 5 |
| Ortho-Prosthesis2.11 | Corrective lens, Bridge teeh | 1 |
| Ortho-Prosthesis2.21 | Corrective lens, Dental implant | 1 |
| Ortho-Prosthesis2.31 | Corrective lens, Dental prosthesis | 2 |
| Ortho-Prosthesis2.41 | Corrective lens, Denture | 1 |
# AgeGroup
df.young = chrt[chrt$AgeGroup == "Young" ,]
t.kable(
do.call(rbind,
apply(df.young[,-c(1,2,6)], 2,
as.data.frame(table))
)
)| value.Var1 | value.Freq | |
|---|---|---|
| Gender.1 | F | 56 |
| Gender.2 | M | 31 |
| AgeGroup | Young | 87 |
| Falls12m.1 | 0 | 64 |
| Falls12m.2 | 1 | 12 |
| Falls12m.3 | 2 | 1 |
| Falls12m.4 | 3 | 5 |
| Falls12m.5 | 4 | 1 |
| Falls12m.6 | 5 | 1 |
| Falls12m.7 | 6 | 1 |
| Falls12m.8 | 12 | 1 |
| Falls12m.9 | 20 | 1 |
| Disease.1 | 0 | 71 |
| Disease.2 | Arthrosis | 1 |
| Disease.3 | Hypercholesterolemia | 1 |
| Disease.4 | Labyrinthitis | 1 |
| Disease.5 | Osteopenia | 2 |
| Disease.6 | Rhinitis | 7 |
| Disease.7 | Sinusitis | 4 |
| Ortho-Prosthesis2.1 | 1 intramedullary rod and 3 screws in the left leg | 1 |
| Ortho-Prosthesis2.2 | Bridge teeh | 1 |
| Ortho-Prosthesis2.3 | Corrective lens | 44 |
| Ortho-Prosthesis2.4 | Corrective lens, Dental braces | 4 |
| Ortho-Prosthesis2.5 | Corrective lens, Dental retention | 6 |
| Ortho-Prosthesis2.6 | Corrective lens, Denture | 1 |
| Ortho-Prosthesis2.7 | Corrective lens, Extensor left knee orthosis | 1 |
| Ortho-Prosthesis2.8 | Crutch | 1 |
| Ortho-Prosthesis2.9 | Dental retention | 2 |
| Ortho-Prosthesis2.10 | No | 26 |
dis = c("Hypercholesterolemia", "Hyperthoyroidsism",
"Rhinitis", "Labyrinthitis", "Sinusitis",
"Arthrosis", "Osteopenia")
l = lapply(dis, function(x)
subset(df.young, Disease == x)
)
t.kable(do.call(rbind, l))| Trial | Subject | Gender | AgeGroup | Falls12m | Illness2 | Disease | Ortho-Prosthesis2 | |
|---|---|---|---|---|---|---|---|---|
| 1679 | BDS01705 | 143 | F | Young | 2 | Scoliosis, Hypercholesterolemia | Hypercholesterolemia | Corrective lens, Dental retention |
| 121 | BDS00121 | 11 | M | Young | 0 | Rhinitis | Rhinitis | No |
| 169 | BDS00169 | 15 | F | Young | 1 | Vasovagal syncope, Gastritis, Bronchitis, Rhinitis, Gastroesophageal reflux | Rhinitis | No |
| 265 | BDS00265 | 23 | F | Young | 0 | Rhinitis | Rhinitis | No |
| 301 | BDS00301 | 26 | F | Young | 0 | Rhinitis, Migraine | Rhinitis | Corrective lens |
| 445 | BDS00445 | 38 | M | Young | 0 | Rhinitis, Sickle cell anemia | Rhinitis | No |
| 940 | BDS00949 | 80 | F | Young | 12 | Hashimoto disease, Rhinitis | Rhinitis | Corrective lens, Extensor left knee orthosis |
| 1490 | BDS01513 | 127 | F | Young | 3 | Hypothyroidism, Rhinitis | Rhinitis | Corrective lens |
| 1442 | BDS01465 | 123 | F | Young | 1 | Labyrinthitis | Labyrinthitis | Corrective lens |
| 133 | BDS00133 | 12 | M | Young | 0 | Rhinitis, Sinusitis | Sinusitis | Corrective lens |
| 277 | BDS00277 | 24 | F | Young | 0 | Rhinitis, Sinusitis, Kidney stones | Sinusitis | Corrective lens |
| 673 | BDS00673 | 57 | F | Young | 5 | Rhinitis, Sinusitis | Sinusitis | Corrective lens, Dental retention |
| 1162 | BDS01177 | 99 | F | Young | 0 | Familial Hypercholesterolemia, Chodromalacia of the knees, Sinusitis, Rhinitis | Sinusitis | Dental retention |
| 649 | BDS00649 | 55 | F | Young | 3 | Depression, Arthrosis of the left knee, Labyrinthitis | Arthrosis | Corrective lens |
| 1454 | BDS01477 | 124 | F | Young | 0 | Osteopenia | Osteopenia | Corrective lens |
| 1538 | BDS01561 | 131 | F | Young | 0 | Hypertension, Hypercholesterolemia, Osteopenia | Osteopenia | Corrective lens |
t = data.frame()
for (i in dis){
temp = subset(df.young, Disease == i)
tmp = do.call(rbind,
apply(temp[,-c(1,2,6)], 2,
as.data.frame(table))
)
if (dim(tmp)[2] == 2) t = rbind(tmp, t)
}
t.kable(t)| value.Var1 | value.Freq | |
|---|---|---|
| Gender | F | 2 |
| AgeGroup | Young | 2 |
| Falls12m | 0 | 2 |
| Disease | Osteopenia | 2 |
| Ortho-Prosthesis2 | Corrective lens | 2 |
| Gender3 | F | 1 |
| AgeGroup5 | Young | 1 |
| Falls12m3 | 3 | 1 |
| Disease5 | Arthrosis | 1 |
| Ortho-Prosthesis23 | Corrective lens | 1 |
| Gender.1 | F | 3 |
| Gender.2 | M | 1 |
| AgeGroup4 | Young | 4 |
| Falls12m.1 | 0 | 3 |
| Falls12m.2 | 5 | 1 |
| Disease4 | Sinusitis | 4 |
| Ortho-Prosthesis2.1 | Corrective lens | 2 |
| Ortho-Prosthesis2.2 | Corrective lens, Dental retention | 1 |
| Ortho-Prosthesis2.3 | Dental retention | 1 |
| Gender2 | F | 1 |
| AgeGroup3 | Young | 1 |
| Falls12m2 | 1 | 1 |
| Disease3 | Labyrinthitis | 1 |
| Ortho-Prosthesis22 | Corrective lens | 1 |
| Gender.11 | F | 5 |
| Gender.21 | M | 2 |
| AgeGroup2 | Young | 7 |
| Falls12m.11 | 0 | 4 |
| Falls12m.21 | 1 | 1 |
| Falls12m.3 | 3 | 1 |
| Falls12m.4 | 12 | 1 |
| Disease2 | Rhinitis | 7 |
| Ortho-Prosthesis2.11 | Corrective lens | 2 |
| Ortho-Prosthesis2.21 | Corrective lens, Extensor left knee orthosis | 1 |
| Ortho-Prosthesis2.31 | No | 4 |
| Gender1 | F | 1 |
| AgeGroup1 | Young | 1 |
| Falls12m1 | 2 | 1 |
| Disease1 | Hypercholesterolemia | 1 |
| Ortho-Prosthesis21 | Corrective lens, Dental retention | 1 |
Table with subjects > 0 falls.
df = f.read.bdsinfo()
df.falls = subset(df, Falls12m > 0 & !duplicated(df$Subject), select =c("Subject", "Falls12m", "Disability2", "Illness2", "Ortho-Prosthesis2", "AgeGroup", "BMI", "Medication" ))
t.kable(df.falls)| Subject | Falls12m | Disability2 | Illness2 | Ortho-Prosthesis2 | AgeGroup | BMI | Medication | |
|---|---|---|---|---|---|---|---|---|
| 37 | 4 | 1 | No | No | Denture | Old | 25.413 | No |
| 61 | 6 | 1 | No | No | Corrective lens, Denture | Young | 26.429 | Beta-blocker |
| 109 | 10 | 1 | No | No | Corrective lens | Young | 18.548 | No |
| 169 | 15 | 1 | No | Vasovagal syncope, Gastritis, Bronchitis, Rhinitis, Gastroesophageal reflux | No | Young | 19.742 | Oral contraceptive |
| 193 | 17 | 3 | No | Vitiligo | No | Young | 29.496 | Essential amino acid |
| 217 | 19 | 1 | No | No | No | Young | 22.043 | No |
| 229 | 20 | 1 | No | No | Corrective lens, Dental braces | Young | 17.943 | No |
| 337 | 29 | 1 | No | Intestine disorder | No | Young | 21.043 | No |
| 601 | 51 | 1 | No | Heart disease, Lymphedema of the lower members | Corrective lens | Old | 29.815 | Vasodilator, Calcium-channel blocker, Beta blocker, Nonsteroidal antiinflammatory, HMG coenzyme A reductase inhibitor, Proton pump inhibitor |
| 625 | 53 | 1 | No | No | Corrective lens | Young | 22.740 | No |
| 649 | 55 | 3 | No | Depression, Arthrosis of the left knee, Labyrinthitis | Corrective lens | Young | 27.293 | Calcium channel blocker |
| 661 | 56 | 1 | No | Hypertension, Hypercholesterolemia, Essential tremor, Osteopenia, Gastritis, Esophagitis | Corrective lens | Old | 28.670 | Angiotensin II receptor antagonist, Beta blocker, HMG coenzyme A reductase inhibitor, Sedative, Muscle relaxant |
| 673 | 57 | 5 | No | Rhinitis, Sinusitis | Corrective lens, Dental retention | Young | 21.842 | Oral contraceptive |
| 703 | 60 | 6 | Physical (Cerebral Palsy) | No | Crutch | Young | 23.918 | No |
| 712 | 61 | 1 | No | No | Corrective lens | Young | 20.094 | No |
| 748 | 64 | 2 | No | Hypercholesterolemia | Corrective lens, Bridge teeh | Old | 29.159 | HMG coenzyme A reductase inhibitor, Antibiotic |
| 844 | 72 | 1 | No | Hypothyroidism, Hypertension | Corrective lens, Denture | Old | 22.422 | Synthetic thyroid hormone, Diuretic, Proton pump inhibitor |
| 940 | 80 | 12 | Physical (Cerebral Palsy) | Hashimoto disease, Rhinitis | Corrective lens, Extensor left knee orthosis | Young | 20.061 | No |
| 952 | 81 | 2 | No | Osteoporosis | Corrective lens, Denture | Old | 28.043 | Bisphosphonate |
| 1000 | 85 | 1 | Visual (Left eye and Right eye) | Diabetes mellitus, Arthrosis of the feet/hands, Vascular leakage of the eyes | Corrective lens, Protese dentaria | Old | 23.942 | Sulfonylurea |
| 1054 | 90 | 1 | No | No | Corrective lens | Young | 23.771 | No |
| 1078 | 92 | 1 | No | Hypercholesterolemia, Osteopenia | Corrective lens, Dental prosthesis | Old | 25.400 | HMG coenzyme A reductase inhibitor |
| 1114 | 95 | 1 | No | Hypercholesterolemia | Corrective lens, Dental prosthesis | Old | 21.426 | HMG coenzyme A reductase inhibitor |
| 1138 | 97 | 1 | No | No | Corrective lens | Young | 17.256 | No |
| 1186 | 101 | 4 | No | No | No | Young | 23.202 | Oral contraceptive |
| 1198 | 102 | 1 | No | No | Corrective lens, Denture, Bridge teeh | Old | 20.677 | No |
| 1234 | 105 | 1 | No | Osteoporosis, Hypertension, Hyperthyroidism | Corrective lens, Dental prosthesis | Old | 24.569 | Synthetic thyroid hormone, Beta-blocker, Diuretic, Bisphosphonate |
| 1270 | 108 | 1 | No | Arthrosis of the knees | Corrective lens, Denture, Dental implant | Old | 23.528 | Salicylate, Beta blocker, Selective serotonin reuptake inhibitor |
| 1294 | 110 | 1 | Hearing (Right ear) | Diabetes mellitus, Osteopenia, Labyrinthitis | Corrective lens | Old | 22.481 | Biguanide |
| 1330 | 113 | 1 | No | Urinary tract infection, Osteopenia | Corrective lens, Dental prosthesis | Old | 25.502 | Antibiotic |
| 1354 | 115 | 1 | No | No | Corrective lens, Dental retention | Young | 21.055 | Oral contraceptive |
| 1426 | 121 | 1 | No | Labyrinthitis | Corrective lens | Old | 22.512 | No |
| 1438 | 122 | 52 | Visual (Left eye and Right eye), Physical (Tumor in the head surgery) | No | Corrective lens, Denture, Crutch | Old | 27.087 | No |
| 1442 | 123 | 1 | Intellectual | Labyrinthitis | Corrective lens | Young | 22.065 | Phenothiazine (2), Anticonvulsant |
| 1478 | 126 | 3 | No | Hyperthyroidism | Corrective lens | Young | 17.924 | Antithyroid |
| 1490 | 127 | 3 | No | Hypothyroidism, Rhinitis | Corrective lens | Young | 18.816 | Synthetic thyroid hormone |
| 1550 | 132 | 1 | No | Arthrosis of the spine/knees/toes | Corrective lens, Denture | Old | 22.231 | Calcium channel blocker, Selective serotonin reuptake inhibitor, HMG coenzyme A reductase inhibitor |
| 1574 | 134 | 1 | No | Labyrinthitis, Osteoporosis, Hypothyroidism | Corrective lens, Dental prosthesis | Old | 28.278 | Bisphosphonate, HMG coenzyme A reductase inhibitor, Synthetic thyroid hormone |
| 1607 | 137 | 3 | No | Endometriosis | No | Young | 20.241 | Oral contraceptive |
| 1631 | 139 | 20 | No | No | Corrective lens | Young | 23.178 | No |
| 1679 | 143 | 2 | No | Scoliosis, Hypercholesterolemia | Corrective lens, Dental retention | Young | 20.114 | HMG coenzyme A reductase inhibitor, Homeopathic |
| 1751 | 149 | 1 | No | Sjogren’s syndrome | Corrective lens, Denture | Old | 23.855 | Antimalarial, Benzodiazepine, Nonsteroidal antiinflammatory |
diseases = unlist(strsplit(df.falls$Illness2, ','))
diseases = gsub("^ ", "", diseases)
diseases = diseases[!duplicated(diseases)]
falls.disease= sapply(diseases, function(x) {
sum(grepl(x, df.falls$Illness2))
})
class(falls.disease)## [1] "integer"falls.disease = data.frame(Diseases = names(falls.disease), Frequency = falls.disease, row.names = NULL)
falls.disease = falls.disease[order(falls.disease$Frequency, decreasing = TRUE),]
t.kable(falls.disease)| Diseases | Frequency | |
|---|---|---|
| 1 | No | 15 |
| 13 | Labyrinthitis | 5 |
| 15 | Hypercholesterolemia | 5 |
| 5 | Rhinitis | 4 |
| 17 | Osteopenia | 4 |
| 14 | Hypertension | 3 |
| 20 | Hypothyroidism | 3 |
| 22 | Osteoporosis | 3 |
| 3 | Gastritis | 2 |
| 23 | Diabetes mellitus | 2 |
| 26 | Hyperthyroidism | 2 |
| 2 | Vasovagal syncope | 1 |
| 4 | Bronchitis | 1 |
| 6 | Gastroesophageal reflux | 1 |
| 7 | Vitiligo | 1 |
| 8 | Intestine disorder | 1 |
| 9 | Heart disease | 1 |
| 10 | Lymphedema of the lower members | 1 |
| 11 | Depression | 1 |
| 12 | Arthrosis of the left knee | 1 |
| 16 | Essential tremor | 1 |
| 18 | Esophagitis | 1 |
| 19 | Sinusitis | 1 |
| 21 | Hashimoto disease | 1 |
| 24 | Arthrosis of the feet/hands | 1 |
| 25 | Vascular leakage of the eyes | 1 |
| 27 | Arthrosis of the knees | 1 |
| 28 | Urinary tract infection | 1 |
| 29 | Arthrosis of the spine/knees/toes | 1 |
| 30 | Endometriosis | 1 |
| 31 | Scoliosis | 1 |
| 32 | Sjogren’s syndrome | 1 |
meds = unlist(strsplit(df.falls$Medication, ','))
meds = gsub("^ ", "", meds)
meds = meds[!duplicated(meds)]
falls.meds= sapply(meds, function(x) {
sum(grepl(x, df.falls$Medication))
})
falls.meds = data.frame(meds = names(falls.meds), Frequency = falls.meds, row.names = NULL)
falls.meds = falls.meds[order(falls.meds$Frequency, decreasing = TRUE),]
t.kable(falls.meds)| meds | Frequency | |
|---|---|---|
| 1 | No | 17 |
| 9 | HMG coenzyme A reductase inhibitor | 8 |
| 3 | Oral contraceptive | 5 |
| 16 | Synthetic thyroid hormone | 4 |
| 7 | Beta blocker | 3 |
| 18 | Bisphosphonate | 3 |
| 2 | Beta-blocker | 2 |
| 8 | Nonsteroidal antiinflammatory | 2 |
| 10 | Proton pump inhibitor | 2 |
| 11 | Calcium channel blocker | 2 |
| 15 | Antibiotic | 2 |
| 17 | Diuretic | 2 |
| 21 | Selective serotonin reuptake inhibitor | 2 |
| 4 | Essential amino acid | 1 |
| 5 | Vasodilator | 1 |
| 6 | Calcium-channel blocker | 1 |
| 12 | Angiotensin II receptor antagonist | 1 |
| 13 | Sedative | 1 |
| 14 | Muscle relaxant | 1 |
| 19 | Sulfonylurea | 1 |
| 20 | Salicylate | 1 |
| 22 | Biguanide | 1 |
| 24 | Anticonvulsant | 1 |
| 25 | Antithyroid | 1 |
| 26 | Homeopathic | 1 |
| 27 | Antimalarial | 1 |
| 28 | Benzodiazepine | 1 |
| 23 | Phenothiazine (2) | 0 |
prosth = unlist(strsplit(df.falls$`Ortho-Prosthesis2`, ','))
prosth = gsub("^ ", "", prosth)
prosth = prosth[!duplicated(prosth)]
falls.prosth= sapply(prosth, function(x) {
sum(grepl(x, df.falls$`Ortho-Prosthesis2`))
})
falls.prosth = data.frame(meds = names(falls.prosth), Frequency = falls.prosth, row.names = NULL)
falls.prosth = falls.prosth[order(falls.prosth$Frequency, decreasing = TRUE),]
t.kable(falls.prosth)| meds | Frequency | |
|---|---|---|
| 2 | Corrective lens | 34 |
| 1 | Denture | 9 |
| 3 | No | 6 |
| 10 | Dental prosthesis | 5 |
| 5 | Dental retention | 3 |
| 6 | Crutch | 2 |
| 7 | Bridge teeh | 2 |
| 4 | Dental braces | 1 |
| 8 | Extensor left knee orthosis | 1 |
| 9 | Protese dentaria | 1 |
| 11 | Dental implant | 1 |
df.rh.flls = df[!duplicated(df$Subject), ]
df.rh.flls = df.rh.flls[grepl("Rhinitis", df.rh.flls$Illness2 ), ]
df.rh.flls = subset(df.rh.flls, select = c("Subject", "Falls12m", "Disability2", "Illness2", "Ortho-Prosthesis2", "AgeGroup", "BMI", "Medication" ))
t.kable(df.rh.flls)| Subject | Falls12m | Disability2 | Illness2 | Ortho-Prosthesis2 | AgeGroup | BMI | Medication | |
|---|---|---|---|---|---|---|---|---|
| 121 | 11 | 0 | No | Rhinitis | No | Young | 25.196 | No |
| 133 | 12 | 0 | No | Rhinitis, Sinusitis | Corrective lens | Young | 20.581 | Proton pump inhibitor, Corticosteroid |
| 169 | 15 | 1 | No | Vasovagal syncope, Gastritis, Bronchitis, Rhinitis, Gastroesophageal reflux | No | Young | 19.742 | Oral contraceptive |
| 265 | 23 | 0 | No | Rhinitis | No | Young | 28.334 | Antihistamine |
| 277 | 24 | 0 | No | Rhinitis, Sinusitis, Kidney stones | Corrective lens | Young | 19.249 | Oral contraceptive |
| 301 | 26 | 0 | No | Rhinitis, Migraine | Corrective lens | Young | 18.985 | Oral contraceptive |
| 445 | 38 | 0 | No | Rhinitis, Sickle cell anemia | No | Young | 22.259 | No |
| 673 | 57 | 5 | No | Rhinitis, Sinusitis | Corrective lens, Dental retention | Young | 21.842 | Oral contraceptive |
| 940 | 80 | 12 | Physical (Cerebral Palsy) | Hashimoto disease, Rhinitis | Corrective lens, Extensor left knee orthosis | Young | 20.061 | No |
| 1162 | 99 | 0 | No | Familial Hypercholesterolemia, Chodromalacia of the knees, Sinusitis, Rhinitis | Dental retention | Young | 24.168 | Oral contraceptive |
| 1490 | 127 | 3 | No | Hypothyroidism, Rhinitis | Corrective lens | Young | 18.816 | Synthetic thyroid hormone |
# Data Sets
df.bds = f.read.bdsinfo()
df.bds$BMI.Class = cut(df.bds$BMI, c(0,25,30,100), labels=c("normal","overweight","obese"))
df.bds$Fall = ifelse(df.bds$Falls12m >0, 1, 0)
df.steady = read.csv(paste0(pth, 'steadyness.measures.csv'))
df = merge(df.bds, df.steady, by = "Trial")
t.kable(head(df, 4))| Trial | Subject | Vision | Surface | Age | AgeGroup | Gender | Height | Weight | BMI | FootLen | Nationality | SkinColor | Ystudy | Footwear | Illness | Illness2 | Nmedication | Medication | Ortho-Prosthesis | Ortho-Prosthesis2 | Disability | Disability2 | Falls12m | FES_1 | FES_2 | FES_3 | FES_4 | FES_5 | FES_6 | FES_7 | FES_T | FES_S | IPAQ_1a | IPAQ_1b | IPAQ_2a | IPAQ_2b | IPAQ_3a | IPAQ_3b | IPAQ_4a | IPAQ_4b | IPAQ_S | TMT_timeA | TMT_errorsA | TMT_timeB | TMT_errorsB | Best_1 | Best_2 | Best_3l | Best_3r | Best_4 | Best_5 | Best_6l | Best_6r | Best_7 | Best_8 | Best_9 | Best_10 | Best_11 | Best_12 | Best_13 | Best_14 | Best_T | Date | BMI.Class | Fall | AP_ | ML_ | RDIST.AP | RDIST.ML | MDIST | RDIST | TOTEX | TOTEX.AP | TOTEX.ML | MVELO | MVELO.AP | MVELO.ML | AREA_CC | AREA_CE | MFREQ | POWER | POWER.ML | POWER.AP |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BDS00001 | 1 | Open | Firm | 33 | Young | F | 157.5 | 54.2 | 21.849 | 21.8 | Brazil | Yellow | 17 | Flip-Flops | Yes | Hypothyroidism | 1 | Oral contraceptive | Yes | Corrective lens | No | No | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | Low Concern | 7 | 120 | 2 | 90 | 3 | 30 | 0.208 | 0.167 | High | 14.06 | 0 | 19.69 | 0 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 25 | 42285.35 | normal | 0 | -7.994 | 0.949 | 0.300 | 0.173 | 0.308 | 0.346 | 29.924 | 27.872 | 7.565 | 0.611 | 0.569 | 0.154 | 1.011 | 0.968 | 0.315 | 1.237 | 0.339 | 3.551 |
| BDS00002 | 1 | Open | Firm | 33 | Young | F | 157.5 | 54.2 | 21.849 | 21.8 | Brazil | Yellow | 17 | Flip-Flops | Yes | Hypothyroidism | 1 | Oral contraceptive | Yes | Corrective lens | No | No | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | Low Concern | 7 | 120 | 2 | 90 | 3 | 30 | 0.208 | 0.167 | High | 14.06 | 0 | 19.69 | 0 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 25 | 42285.35 | normal | 0 | -7.734 | 0.550 | 0.383 | 0.157 | 0.335 | 0.414 | 32.398 | 29.909 | 8.562 | 0.661 | 0.610 | 0.175 | 1.697 | 1.131 | 0.314 | 2.434 | 0.731 | 7.103 |
| BDS00003 | 1 | Open | Firm | 33 | Young | F | 157.5 | 54.2 | 21.849 | 21.8 | Brazil | Yellow | 17 | Flip-Flops | Yes | Hypothyroidism | 1 | Oral contraceptive | Yes | Corrective lens | No | No | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | Low Concern | 7 | 120 | 2 | 90 | 3 | 30 | 0.208 | 0.167 | High | 14.06 | 0 | 19.69 | 0 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 25 | 42285.35 | normal | 0 | -7.890 | 0.417 | 0.208 | 0.125 | 0.216 | 0.242 | 27.971 | 26.232 | 7.064 | 0.571 | 0.535 | 0.144 | 0.498 | 0.486 | 0.421 | 0.579 | 0.429 | 1.517 |
| BDS00004 | 1 | Closed | Firm | 33 | Young | F | 157.5 | 54.2 | 21.849 | 21.8 | Brazil | Yellow | 17 | Flip-Flops | Yes | Hypothyroidism | 1 | Oral contraceptive | Yes | Corrective lens | No | No | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | Low Concern | 7 | 120 | 2 | 90 | 3 | 30 | 0.208 | 0.167 | High | 14.06 | 0 | 19.69 | 0 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 2 | 2 | 2 | 2 | 2 | 2 | 2 | 1 | 25 | 42285.35 | normal | 0 | -6.886 | 0.567 | 0.181 | 0.100 | 0.180 | 0.207 | 26.424 | 24.415 | 7.207 | 0.539 | 0.498 | 0.147 | 0.380 | 0.337 | 0.476 | 0.533 | 0.330 | 1.601 |
vrbls = c("Trial", "Subject", "Vision", "Surface", "AgeGroup", "Age", "Gender", "Illness", "Illness2", "Disability", "Disability2", "Footwear", "BMI", "Falls12m", "Nmedication")
vrbls.stead = names(df.steady)
vrb.dmgrphc = c("Subject", "AgeGroup", "Age", "Gender", "Illness", "Disability","Fall")df.lab = df[grepl("Labyrinthitis", df$Illness2), ]
df.lab.chrt = subset(df.lab, !duplicated(df.lab$Subject))
lt.old = subset(df.lab.chrt, AgeGroup == "Old",
select =c(Subject, Age, Gender, Falls12m, Illness, Illness2))
lt.old = lt.old[lt.old$Subject != "158", ]
lt.old$Grp = "LT"
hc.old = subset(df, !duplicated(df$Subject) & AgeGroup == "Old" & Illness == "No",
select =c(Subject, Age, Gender, Falls12m,Illness, Illness2))
hc.old$Grp = "HC"
lt.test = data.frame(rbind(hc.old, lt.old))
rownames(lt.test) = NULL
t.kable(lt.test)| Subject | Age | Gender | Falls12m | Illness | Illness2 | Grp |
|---|---|---|---|---|---|---|
| 4 | 61.750 | M | 1 | No | No | HC |
| 41 | 68.833 | M | 0 | No | No | HC |
| 43 | 60.667 | F | 0 | No | No | HC |
| 69 | 65.083 | F | 0 | No | No | HC |
| 71 | 61.417 | F | 0 | No | No | HC |
| 102 | 66.167 | F | 1 | No | No | HC |
| 122 | 64.917 | M | 52 | No | No | HC |
| 133 | 82.333 | F | 0 | No | No | HC |
| 158 | 72.167 | F | 0 | No | Labyrinthitis | HC |
| 73 | 79.750 | F | 0 | Yes | Hypertension, Labyrinthitis | LT |
| 79 | 72.250 | F | 0 | Yes | Hypertension, Osteoporosis, Herniated lumbar disc, Labyrinthitis | LT |
| 84 | 78.417 | F | 0 | Yes | Labyrinthitis, Hypertension, Hypercholesterolemia | LT |
| 93 | 75.583 | M | 0 | Yes | Hypertension, Labyrinthitis, Prostate disease, Skin disease | LT |
| 110 | 66.583 | F | 1 | Yes | Diabetes mellitus, Osteopenia, Labyrinthitis | LT |
| 121 | 67.000 | F | 1 | Yes | Labyrinthitis | LT |
| 134 | 79.917 | F | 1 | Yes | Labyrinthitis, Osteoporosis, Hypothyroidism | LT |
| 154 | 71.833 | M | 0 | Yes | Hypertension, Hypercholesterolemia, Labyrinthitis, Asthma, Varicose veins of the legs | LT |
| 157 | 61.833 | F | 0 | Yes | Hypertension, Diabetes mellitus, Osteopenia, Labyrinthitis, Hypothyroidism | LT |
lt = df[df$Subject %in% lt.test$Subject ,]
lt$Grp = ifelse(lt$Illness2 == "No", "HC", "LT")