• Indian J Anaesth · Mar 2014

    A prospective observational study of skin to subarachnoid space depth in the Indian population.

    • Smita Prakash, Parul Mullick, Pooja Chopra, Santosh Kumar, Rajvir Singh, and Anoop R Gogia.
    • Department of Anaesthesia and Intensive Care, Vardhman Mahavir Medical College and Safdarjang Hospital, New Delhi, India.
    • Indian J Anaesth. 2014 Mar 1;58(2):165-70.

    Background And AimsA pre-puncture estimate of skin to subarachnoid space depth (SSD) may guide spinal needle placement and reduce complications associated with lumbar puncture. Our aim was to determine (1) The SSD in Indian males, females, parturients and the overall population; (2) To derive formulae for predicting SSD and (3) To determine which previously suggested formula best suited our population.MethodsIn this prospective, observational study, 800 adult Indian patients undergoing surgery under spinal anaesthesia were divided into three groups: Males (Group M), females (Group F) and parturients (Group PF). SSD was measured after lumbar puncture. The relationship between SSD and patient characteristics was studied and statistical models were used to derive formula for predicting SSD. Statistical analysis included One-way ANOVA with post hoc analysis, forward stepwise multivariate regression analysis and paired t-tests.ResultsMean SSD was 4.71 ± 0.70 cm in the overall population. SSD in adult males (4.81 ± 0.68 cm) was significantly longer than that observed in females (4.55 ± 0.66 cm) but was comparable with SSD in parturients (4.73 ± 0.73 cm). Formula for predicting SSD in the overall population was 2.71 + 0.09 × Body Mass Index (BMI). Stocker's formula when applied correlated best with the observed SSD. Formulae were derived for the three groups.ConclusionsWe found gender-based differences in SSD, with SSD in males being significantly greater than that observed in the female population. SSD correlated with BMI in the parturient and the overall population. Amongst the previously proposed formulae, Stocker's formula was most accurate in predicting SSD in our population.

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