Identifying premature infant at high and low risk for motor delays using motor performance testing and MRS Patricia Coker-Bolt, PhD OTR/L, FAOTA1; Kathryn Hope2, MPH; Viswanathan Ramakrishnan, PhD3; Truman Brown, PhD4; Denise Mulvihill, MD1, and Dorothea Jenkins, MD2

1Division of Occupational Therapy, 2Department of Pediatrics, 3Public Health Sciences, 4Radiology, Medical University of South Carolina, Charleston, SC

Background:

• Premature infants with normal cranial ultrasounds remain at risk for later

motor delays, which go undetected in early infancy.2

• Of the 12-16% of children with developmental delay, only half will be

identified by the time they enter kindergarten.1

• The Test of Infant Motor Performance (TIMP) is the current gold

standard infant motor assessment, but rarely used by pediatricians

during well-child visits due to lack of time and special training required.

• A short, standardized screening test administered to infants in the first

months of life would target early intervention to those most at risk.3

• In our previous work, Rasch partial credit model was used to analyze

and select 10 TIMP items with strongest correlation to motor ability at 12

months. New scales were then developed for more sensitive scoring of

these 10 items, comprising a novel screening tool, the Specific Test of

Early Infant Motor performance (STEP) (Figure 1).

Specific aims: Evaluate the robustness of a new, shortened, screening

assessment (STEP) through factor analysis of 10 motor items, and test the

STEP against current validated infant motor skills assessments and

outcome measures of development.

Design: A secondary analysis of an existing cohort of 22 preterm infants

(24-35 weeks gestation), with video recorded motor tests at 12 weeks and

12 months corrected gestational age (CGA). (Table 1)

Measures of Outcome:

• STEP scored from existing video recordings of TIMP at 12 weeks CGA.

• Test of Infant Motor Performance (TIMP) at term and 12 weeks CGA.

• Bayley III Scales of Infant and Toddler Development (Bayley III) at

12 months CGA. Bayley subscale scores ≤8 = low/below average 4,5.

• MRS: Siemens 3T: Single voxel [15 x 15 x 15 mm] in basal ganglia (BG) and frontal lobe white matter (WM) [echo PRESS sequence128 avg,

TR=2000ms, TE 30ms, 270ms].

• Data Analysis: Pearson’s correlational coefficient was used to relate

TIMP, Bayley and STEP scores. Exploratory factor analysis (EFA) was

used to identify latent constructs of STEP. Logistic regression, using EFA

scores, was performed to predict dichotomized Bayley outcome.

Sensitivity and specificity of EFA STEP scores were evaluated using

predictive outcomes versus actual outcomes. A drop-one-predict

evaluation was used to assess external validity.

ABSTRACT

DESIGN/ METHODS

RESULTS

Table 1. Patient Demographics Total Infants (N=22)

Sex 10 Females, 12 Males

Race 11 Caucasians, 11 African Americans

GA at Birth (mean ± SD) 29.6 ± 2.9 weeks

Birth weight (mean ± SD) 1259 ± 634 grams

Intracranial lesions 4 IVH (3 grade I, 1 grade II), 0 infarcts/PVL

Risk (TIMP at 12-weeks CGA) 9 High; 13 Low

Bayley Motor Outcome (N=19) 8 Average; 11 Low/Below Average

Figure 1. Representative schematic of STEP scale for “Prone Extension”

Head Control Upper

Extremity

Lower

Extremity

Pull to sit 0.89540 -0.23615 -0.06632

Prone extension 0.89496 -0.15936 -0.21346

Supine with no vision 0.84610 0.20399 -0.16812

Supine with vision 0.76003 -0.30853 0.16172

Standing 0.69165 -0.43411 0.23230

Supine sitting 0.76553 0.36989 0.00095

Grasp 0.24003 0.72577 -0.29594

Kicking 0.38154 0.48327 0.76373

Rolling with leg 0.65745 0.11327 -0.17037

% variance explained 68% 20% 12%

Table 2. Latent constructs of STEP using Exploratory Factor Analysis (EFA)

• STEP correlated with TIMP scores at

term (r=0.062, p=0.003), 12 weeks CGA

(r=0.79, p