TY - JOUR
T1 - A clinical prediction of skin to subarachnoid space depth in parturients undergoing caesarean delivery in a Nigerian population
AU - Olateju, Simeon Olugbade
AU - Adetoye, Adedapo Omowonuola
AU - Aaron, Olurotimi Idowu
AU - Ameye, Sanyaolu Alani
AU - Oria, Adebose Ibukunoluwa
AU - Olomu, Patrick Nduyari
AU - Adeniyi, Olumide Adedotun
AU - Faponle, Aramide Folayemi
N1 - Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Few studies on the prediction of skin to subarachnoid space depth (SSD) in African parturients undergoing caesarean delivery are available. We undertook a prospective observational study of 402 parturients scheduled for elective caesarean delivery to determine simple and clinically applicable formulae for predicting skin to SSD. Additionally, the impact of patient characteristics and variables such as age, height, weight, body mass index (BMI), and body surface area on SSD was studied. We employed a Stepwise Multiple Linear Regression Model to predict SSD in normal weight, overweight, and obese parturients using previously described formulae and compared our derived SSDs to these previous formulae for concordance. (Craig, Abe, Stocker, Chong’s modified, Prakash, Ma, Hazarika, Taman and Celik). Mean SSD was 6.62 ± 1.07 cm in the overall population. SSD in normal weight patients was (6.19 ± 0.92 cm), overweight (6.44 ± 0.92 cm) and obese (6.97 ± 1.17 cm). There was a correlation between SSD and BMI (p = 0.001). Formulae for predicting SSD in the overall population, normal weight, overweight and obese parturients were 4.34 + weight × 0.03, 4.43 + weight × 0.03, 4.54 + weight × 0.03 and 3.56 + weight × 0.03, respectively. We also found the Prakash formula to correlate best with our observed SSD. We concluded that SSD correlated well with weight in the overall parturient population and that Prakash’s formula was the most accurate of the other previously described formulae in predicting SSD in this subset of African parturients.
AB - Few studies on the prediction of skin to subarachnoid space depth (SSD) in African parturients undergoing caesarean delivery are available. We undertook a prospective observational study of 402 parturients scheduled for elective caesarean delivery to determine simple and clinically applicable formulae for predicting skin to SSD. Additionally, the impact of patient characteristics and variables such as age, height, weight, body mass index (BMI), and body surface area on SSD was studied. We employed a Stepwise Multiple Linear Regression Model to predict SSD in normal weight, overweight, and obese parturients using previously described formulae and compared our derived SSDs to these previous formulae for concordance. (Craig, Abe, Stocker, Chong’s modified, Prakash, Ma, Hazarika, Taman and Celik). Mean SSD was 6.62 ± 1.07 cm in the overall population. SSD in normal weight patients was (6.19 ± 0.92 cm), overweight (6.44 ± 0.92 cm) and obese (6.97 ± 1.17 cm). There was a correlation between SSD and BMI (p = 0.001). Formulae for predicting SSD in the overall population, normal weight, overweight and obese parturients were 4.34 + weight × 0.03, 4.43 + weight × 0.03, 4.54 + weight × 0.03 and 3.56 + weight × 0.03, respectively. We also found the Prakash formula to correlate best with our observed SSD. We concluded that SSD correlated well with weight in the overall parturient population and that Prakash’s formula was the most accurate of the other previously described formulae in predicting SSD in this subset of African parturients.
KW - body mass index
KW - caesarean delivery
KW - depth prediction formulae
KW - parturient
KW - subarachnoid block
KW - subarachnoid space depth
UR - http://www.scopus.com/inward/record.url?scp=85144148975&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85144148975&partnerID=8YFLogxK
U2 - 10.1080/01443615.2022.2151348
DO - 10.1080/01443615.2022.2151348
M3 - Article
C2 - 36518050
AN - SCOPUS:85144148975
SN - 0144-3615
JO - Journal of Obstetrics and Gynaecology
JF - Journal of Obstetrics and Gynaecology
M1 - 2151348
ER -