NCT05515211

Diagnostic Accuracy of Foot Length in Predicting Preterm and Low Birth Weight Using Ultrasound Dating as The Gold Standard in a Rural District of Pakistan

Completed Last updated 14 July 2023

What this trial tests

trial testing Foot length in Preterm Birth in 336 participants. Completed in 13 July 2023.

Timeline

7 November 2022

Primary endpoint
30 June 2023

13 July 2023

Quick facts

Lead sponsor	Aga Khan University
Status	Completed
Study type	OBSERVATIONAL
Enrollment	336
Start date	7 November 2022
Primary completion	30 June 2023
Estimated completion	13 July 2023
Sites	1 location across Pakistan

Drugs / interventions tested

• Foot length

Conditions studied

• Preterm Birth — all drugs for Preterm Birth →
• Low Birth Weight — all drugs for Low Birth Weight →

Sponsor

Aga Khan University

Who can join

Adults 0 Hours to 48 Hours, any sex, with Preterm Birth or Low Birth Weight. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Background:

The burden of preterm and low birth weight babies (LBW) is high in low- and middle-income countries (LMICs). Therefore, assessment of gestational age (GA) and birth weight is important. The GA is assessed using a reliable last menstrual period (LMP), measuring fundal height, using ultrasound for dating, or postnatally using Ballard, Dubowitz, or Eregie scores. However, each method has some limitations. Pregnant women in LMIC are not able to recall LMP and are also unreliable when menstrual cycles are irregular, fundal height is often imprecise and subject to variation due to observer bias, uterine pathologies, abdominal obesity, amniotic fluid volume, fetal position, and ultrasound in a rural setting is often unreliable because lack of trained sonologist, power failures, and maintenance of ultrasound machine. Post-natal GA scoring is also lengthy, subjective, and time-consuming. Similarly, determining birth weight has many challenges. In Thatta, weighing scales are only available in health facilities, therefore, birth weight is available for babies born in the health facilities. Furthermore, even where weighing scales are available, the calibration and maintenance are not without challenges, especially in the extremely hot climate. In the majority of studies, foot length has been validated for determining GA and birth weight, with LMP serving as the gold standard, which has limitations in our population. In a meta-analysis on the diagnostic accuracy of foot length to identify preterm and LBW, researchers emphasized the need for studies using high-quality ultrasound as a reference standard for early dating. Hence, there is a need to develop a simple and effective method of GA and birth weight that healthcare providers of all levels including mid-level healthcare workers in remote areas can use with reasonable accuracy.

Objectives of the study The primary objectives of the study are to determine the diagnostic accuracy of foot length in predicting GA and low birth weight using ultrasound conducted between 6-20 weeks for the predicted estimated date of delivery (EDD) as the gold standard.

Secondary objectives of the study are, 1) to develop the regression equations that predict gestational age and low birth weight using foot length, 2) to assess the use of foot length measurement as a screening tool to identify LBW or preterm infants in a community-based setting, and 3) to develop percentile charts of foot length for gestational age and low birth weight

Methods:

This test validation study will be conducted in Global Network's Maternal and Newborn Health Registry catchment area. All live birth singleton babies who have a first-trimester ultrasound for gestational age and birth weight within 48 hours of birth will be included in this study. Stillbirths, multiple pregnancies, gross congenital malformations such as neural tube defects, omphalocele, etc., club foot, and babies with chromosomal abnormalities such as Down syndrome that make measuring foot length difficult, will be excluded from the study. Gestational age will be assessed using ultrasound between 6-20 weeks of gestation by a trained sonographer working in the registry. Neonatal assessment having neuromuscular, and physical signs will be conducted by the research assistants (RA). RA will be taking anthropometric measurements such as birth weight using calibrated weighing scales, foot length, mid-upper arm circumference, and fronto-occipital circumference.

The data will be entered in Epicollect data five. Sensitivity, specificity, positive \& negative predictive value, likelihood ratios, and diagnostic accuracy will be done using different cut-offs of foot length against ultrasound estimated gestational age and birth weight. Receivers operating characteristics (ROC) curves will be generated to identify the optimal cut-off point for foot length taken within 24 hours of birth for identification of prematurity and LBW (based on first-trimester ultrasound) with ≥80% sensitivity. Linear regression will be done for estimating predictive values of foot length by GA. Pentile charts for foot length (FL) against GA will be derived. Bland Altman's analyses will identify and quantify any biases inherent to the tool.

Public health implications:

If these equations predict gestational age and birth weight with accuracy, an android-based application can be developed for health care providers (HCP) who simply measure foot length and enter it into the application to identify preterm \&/or low birth weight along with referred guidelines for early treatment. This is one step closer to Every Newborn Action Plan's goal of lowering neonatal mortality to 12/1000 LB by 2030.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

1. Diagnostic accuracy of foot length measurement for identification of preterm newborn in rural Sindh, Pakistan.
   Tikmani SS, Brown N, Inayat A, Mårtensson A, et al · · 2024 · cited 2× · PMID 38267220 · DOI 10.1136/bmjpo-2023-002316
2. Postnatal foot length measurement as a proxy to identify low birth weight for frontline health workers in rural Sindh Province, Pakistan: a diagnostic accuracy study.
   Tikmani SS, Brown N, Inayat Ali A, Martensson A, et al · · 2024 · cited 1× · PMID 39730154 · DOI 10.1136/bmjopen-2024-089153