**PRENATAL USE EARLY VERSUS 1-3, EXCLUDE FETAL
prenatal vs postnatal stratified, exclude fetal.
## Warning: package 'lattice' was built under R version 4.2.3** THIS IS FOR THE CG DATA **
** THIS IS FOR THE HUNG DATA **
combine data frames
df_combo <- inner_join(dfc[,c(1,2,4,11,12,13:17,18:23)],dfh[,c(1,10,11,12:16,17:22)],by="Pt..No",suffix=c(".CG",".HUNG"))
df_combo$PRE.OR.POST[df_combo$PRE.OR.POST == "prenatal "] <- "prenatal"
df_combo_avg <- df_combo[,c(1:3)]
df_combo_avg$SAS_LV <- rowMeans(df_combo[,c('Ratio.of.Ventricular.to.Subarachnoid.Space.LV.CG', 'Ratio.of.Ventricular.to.Subarachnoid.Space.LV.HUNG')])
df_combo_avg$SAS_BF <- rowMeans(df_combo[,c(9,22)])
df_combo_avg$SAS_EA <- rowMeans(df_combo[,c(10,23)])
df_combo_avg$chiari <- rowMeans(df_combo[,c(7,20)])
df_combo_avg$CP_glomus<- rowMeans(df_combo[,c(12,25)])
df_combo_avg$CP_body <- rowMeans(df_combo[,c(13,26)])
df_combo_avg$ratio_AP <- rowMeans(df_combo[,c(4,17)])
df_combo_avg$ratio_SI <- rowMeans(df_combo[,c(5,18)])early life vs 1-3 months in fetal vs postnatal repair
Prenatal repair. vs. Postnatal repair Early life and 1-3 mo Early life and 1-3 mo
looking at SAS ratio for LV, BF, EA Chiari, CP glomus and body, and ratio of AP/SI
df_combo_avg[,c(2:11)] %>%
filter(timescale == "1-3mo") %>%
tbl_summary(label = `PRE.OR.POST` ~ "Neuroradiologic Findings",by='PRE.OR.POST')%>%
bold_labels() %>%add_p()| Characteristic | postnatal, N = 131 | prenatal, N = 141 | p-value2 |
|---|---|---|---|
| timescale | |||
| 1-3mo | 13 (100%) | 14 (100%) | |
| SAS_LV | 15.9 (13.0, 17.4) | 19.8 (17.4, 23.1) | 0.008 |
| SAS_BF | 55 (42, 68) | 42 (36, 46) | 0.033 |
| SAS_EA | 4.40 (3.50, 5.55) | 3.92 (2.22, 4.64) | 0.3 |
| chiari | 9.4 (4.6, 13.4) | 0.0 (0.0, 1.7) | 0.002 |
| CP_glomus | 2.70 (2.10, 3.85) | 2.85 (2.51, 3.18) | >0.9 |
| CP_body | 1.55 (1.30, 1.65) | 1.58 (1.39, 1.78) | 0.6 |
| ratio_AP | 50 (46, 54) | 43 (38, 47) | 0.017 |
| Unknown | 1 | 0 | |
| ratio_SI | 15.2 (12.8, 16.8) | 8.6 (7.7, 12.6) | 0.006 |
| Unknown | 1 | 0 | |
| 1 n (%); Median (IQR) | |||
| 2 Wilcoxon rank sum test; Wilcoxon rank sum exact test | |||
df_combo_avg[,c(2:11)] %>%
filter(timescale == "early") %>%
tbl_summary(label = `PRE.OR.POST` ~ "Neuroradiologic Findings",by='PRE.OR.POST')%>%
bold_labels() %>%add_p()| Characteristic | postnatal, N = 171 | prenatal, N = 191 | p-value2 |
|---|---|---|---|
| timescale | |||
| early | 17 (100%) | 19 (100%) | |
| SAS_LV | 16.10 (14.80, 17.00) | 16.65 (14.28, 17.45) | 0.6 |
| SAS_BF | 42 (39, 49) | 37 (33, 45) | 0.12 |
| SAS_EA | 1.90 (1.50, 2.00) | 1.80 (1.25, 3.15) | 0.7 |
| chiari | 14 (7, 17) | 1 (0, 3) | <0.001 |
| Unknown | 0 | 1 | |
| CP_glomus | 3.00 (2.55, 3.30) | 2.50 (2.05, 3.15) | 0.2 |
| Unknown | 0 | 2 | |
| CP_body | 1.50 (1.30, 1.85) | 1.25 (1.15, 1.40) | 0.078 |
| Unknown | 0 | 2 | |
| ratio_AP | 42 (38, 44) | 38 (34, 41) | 0.2 |
| Unknown | 0 | 1 | |
| ratio_SI | 11.3 (9.9, 13.6) | 8.2 (6.7, 9.7) | 0.004 |
| Unknown | 0 | 1 | |
| 1 n (%); Median (IQR) | |||
| 2 Wilcoxon rank sum test; Wilcoxon rank sum exact test | |||
separate by postfetal repair and fetal repair dataframes
post <- df_combo %>%
filter(PRE.OR.POST == "postnatal" | PRE.OR.POST == "postnatal " | PRE.OR.POST == "post ")
pre <- df_combo %>%
filter(PRE.OR.POST == "prenatal" | PRE.OR.POST == "prenatal ")fetal vs post fetal repair
CP is different between fetal and post fatal
we suspect something is different in the CP. the subarachnoid space is the most interesting. the chiari is different between the prenatal and postnatal repair.
the CP globus seems to be involved.
the CP and SAS are different in babies that are repaired prenatally.
SAS has something to do with hydrocephalus if we can show a difference between postnatally repaired SAS
how much difference is there between the brain anatomy of a baby who was repaired prenatally and postnatally?
visually the difference between the two.
how have the fetal repair kids changed where the postnatal repair kids did not?