Publications by Ismael calandri
FTD survival
Summary table ## Warning: The `.dots` argument of `group_by()` is deprecated as of dplyr 1.0.0. Characteristic bvFTD, N = 561 PPA Agm, N = 121 PPA Sem, N = 91 p-value2 Age_onset 66 (58, 71) 65 (60, 72) 71 (70, 77) 0.2 Sex 0.5 Female 25 (45%) 7 (58%) 3 (33%) Male 31 (55%) 5 (42%) 6 (67%) Follow time (months) 23 (11, 34) 18 (13, 34) 49 (17, ...
239 sym R (717 sym/5 pcs) 9 img 2 tbl
Hoteles
Population description ## Warning: The `.dots` argument of `group_by()` is deprecated as of dplyr 1.0.0. Variable N N = 4401 AMBA inhabitant 243 181 (74%) non-Argentinian_residency 244 27 (11%) Age 361 18 (12, 40) Education 90 Universitary level 55 (61%) High school level 31 (34%) Elementary level 4 (4.4%) Symptoms_grade 240 Mild 18...
289 sym R (1635 sym/6 pcs) 2 img 7 tbl
Document
Table 1. Demographics Characteristic Healthy control, N = 451 Covid, N = 451 p-value2 Age (y) 57 (46, 64) 50 (43, 63) 0.4 sex 0.7 Male 25 (56%) 23 (51%) Female 20 (44%) 22 (49%) Education (y) 17.00 (15.00, 18.00) 17.00 (15.00, 18.00) >0.9 CAIDE dementia score 6.00 (3.00, 7.00) 5.00 (2.00, 7.00) 0.3 1 Median (IQR); n (%) 2 ...
964 sym R (4668 sym/1 pcs) 6 img 9 tbl
SVCR
Predictores de HSA Characteristic 0, N = 311 1, N = 201 p-value2 Edad 41 (11) 51 (12) 0.003 Sexo 19 / 31 (61%) 16 / 20 (80%) 0.2 Antecedentes_Depresion_Ansiedad >0.9 No 26 / 31 (84%) 17 / 20 (85%) Si 5 / 31 (16%) 3 / 20 (15%) Antecedentes_Hipertension 0.071 No 30 / 31 (97%) 16 / 20 (80%) Si 1 / 31 (3.2%) 4 / 20 (20%) Antecedentes_Taba...
39 sym 1 img 1 tbl
CJD survival
Estadísticos descriptivos Characteristic Afectiva, N = 41 Clásica, N = 181 Cognitiva, N = 171 Heidenhain, N = 141 Oppenheimer, N = 111 p-value2 Demográficos Edad 62 (60, 66) 64 (63, 73) 64 (55, 72) 64 (60, 69) 63 (57, 68) 0.8 Nacionalidad >0.9 No 0 (0%) 1 (5.6%) 0 (0%) 0 (0%) 0 (0%) Si 4 (100%) 17 (94%) 17 (100%) 14 (100%) 11 (100%) De...
461 sym R (3752 sym/9 pcs) 7 img 2 tbl
TGA meta v2
###data tidy#### data$`Recurrence as a main outcome`<-factor(data$`Recurrence as a main outcome`, levels = c(0,1), labels = c("No", "Yes")) library(expss) ## ## Attaching package: 'expss' ## The following objects are masked from 'package:dplyr': ## ## between, compute, contains, first...
820 sym R (99459 sym/115 pcs) 27 img
Enfermería
Características de los ingresos a ambas sedes Characteristic Belgrano, N = 1461 Escobar, N = 101 age 44 (13, 69) 47 (22, 67) sex Hombre 82 (56%) 5 (50%) Mujer 64 (44%) 5 (50%) Otro 0 (0%) 0 (0%) unidad_ingreso_belgrano Guardia 18 (12%) 0 (NA%) Piso/UIT 72 (49%) 0 (NA%) UTI ad 5 (3.4%) 0 (NA%) UTI Ped 15 (10%) 0 (NA%) UCO 18 (12%) 0 (...
439 sym 10 img 3 tbl
TGA metanalisys extended
###data tidy#### data$`Recurrence as a main outcome`<-factor(data$`Recurrence as a main outcome`, levels = c(0,1), labels = c("No", "Yes")) library(expss) ## ## Use 'expss_output_rnotebook()' to display tables inside R Notebooks. ## To return to the console output, use 'expss_output_defaul...
346 sym R (49814 sym/79 pcs) 24 img
TGA2
## ## Use 'expss_output_rnotebook()' to display tables inside R Notebooks. ## To return to the console output, use 'expss_output_default()'. ## ## Attaching package: 'expss' ## The following objects are masked from 'package:dplyr': ## ## between, compute, contains, first, last, na_if, recode, vars Prevalence metanalysis Outliers an...
275 sym R (5270 sym/8 pcs) 24 img
Epilepsy
data$N_daes<-as.numeric(data$N_daes) data$EEG_pre<-as.factor(data$IctalEEG_pre) data %>% select(Edad_InicioEPI, Duracion_epi, N_daes, CTCG_2ria, Crisis_febriles, Complic_perinatales, TEC, Infeccion_cerebral, Status_ep, frec_c...
7 sym R (1198 sym/1 pcs) 1 tbl