Publications by Ismael calandri
covid_draft
##############################Data wrangling section########################################## ##Data tidy library(tidyverse) base<-base %>% rename( Diagnosis = dx, Symptomatic = covid_sint, Hospitalization = hospitalizacion, ICU =terapia, ICU_days = dias_terapia, s_Anosmia = covid_symptoms___0, s_Ageus...
1855 sym R (31414 sym/27 pcs) 7 img 7 tbl
CogVid casos y controles2
Table 1. Demographics Esta tabla, y la siguiente, las pense para mostrar la poblacion. Ya que es en definitiva una serie de casos, es muy importante mostrar como son los casos por eso la tabla 2 Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%)...
1825 sym 4 img 7 tbl
Document
Delay to consultation Survival analysis Time to death ## Warning in .pvalue(fit, data = data, method = method, pval = pval, pval.coord = pval.coord, : There are no survival curves to be compared. ## This is a null model. Time to death by diagnosis Time to nursing home admission ## Warning in .pvalue(fit, data = data, method = method, pval ...
186 sym R (338 sym/2 pcs) 8 img
CogVid casos y controles
Table 1. Demographics Esta tabla, y la siguiente, las pense para mostrar la poblacion. Ya que es en definitiva una serie de casos, es muy importante mostrar como son los casos por eso la tabla 2 Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%)...
1756 sym 4 img 7 tbl
CogVid
Demographics Characteristic Healthy control, N = 361 Covid, N = 361 p-value2 Age (y) 58 (48, 64) 51 (44, 65) 0.7 sex >0.9 Male 18 (50%) 18 (50%) Female 18 (50%) 18 (50%) escolaridad 18.00 (15.00, 18.00) 18.00 (15.00, 18.00) 0.9 total_caide 6.00 (5.00, 7.00) 5.00 (3.00, 7.00) 0.2 1 Median (IQR); n (%) 2 Wilcoxon ra...
203 sym 3 tbl
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