Blood glucose monitoring in stable small-for-gestational-age infants below 3rd percentile versus 3rd–10th percentiles on INTERGROWTH-21st charts: A quasi-randomized controlled trial

Abstract

Purpose

Small-for-gestational-age (SGA) infants (birth weight <10^th percentile) routinely undergo blood glucose monitoring (BGM) to detect hypoglycaemia. However, application of the INTERGROWTH-21st 10^th percentile cut-off may increase SGA classification in certain populations, potentially leading to unnecessary monitoring. This study aimed to compare the safety and effectiveness of a 3^rd centile-based BGM strategy with the conventional 10^th centile approach in stable SGA infants.

Methods

In this quasi-randomized controlled trial conducted at a tertiary-care centre in India (July 2024–April 2025), inborn, hemodynamically stable infants of 35⁺⁰ to 42⁺⁰ weeks’ gestation classified as SGA by INTERGROWTH-21st charts were enrolled within 1 hour of birth. Eligible infants were allocated to either a restricted monitoring strategy (<3^rd percentile) or a conventional monitoring strategy (3^rd–10^th percentile) using a predefined quasi-randomization method. Blood glucose was measured at predefined intervals during the first 72 h. The primary outcome was incidence of hypoglycaemia (<47 mg/dL) within 72 h. Secondary outcomes included time to full feeds, intravenous fluid requirement, sepsis, length of stay, and mortality.

Results

Among 324 enrolled infants (162 per group), hypoglycaemia occurred in 10.5% in the 3^rd centile group and 13% in the 10^th centile group (p = 0.49). The absolute risk difference was 2.5% (95% CI 8.8% to 3.8%), confirming non-inferiority. No significant differences were observed in secondary outcomes.

Conclusion

A 3^rd centile-based BGM strategy was non-inferior to the conventional 10^th centile approach in stable SGA infants. Targeted monitoring based on severity of growth restriction may reduce unnecessary interventions without compromising short-term safety.

Keywords

blood glucose monitoring INTERGROWTH-21st neonatal hypoglycaemia small for gestational age

Introduction

The WHO Expert Committee and the American College of Obstetricians and Gynecologists define small-for-gestational-age (SGA) infants as those whose birth weight falls under the 10th percentile for sex at a specific gestational age, relative to a standardized reference population.^1,2 In 2010, approximately 32.4 million infants (27% of all live births) were born SGA in low- and middle-income countries.³ India contributed the highest absolute number of SGA births globally, with an estimated 12.8 million in 2010.⁴

Small-for-gestational-age infants are at increased risk of mortality and long-term neurodevelopmental and cardiometabolic morbidity.^5,6 Among immediate complications, hypoglycaemia is an important concern in SGA infants. Small-for-gestational-age infants have limited metabolic reserves, including reduced glycogen and fat stores, impaired gluconeogenesis, and altered hormonal regulation, which together compromise postnatal glucose homeostasis. In addition, reduced ketone body production limits the availability of alternative cerebral fuel during hypoglycaemia, which may lead to brain injury, and adverse long-term neurodevelopmental and visual outcomes when episodes are recurrent or prolonged.⁷ Therefore, close blood glucose monitoring (BGM) in the first 72 h of life is considered essential for the timely recognition and management of hypoglycaemia in SGA infants.

The INTERGROWTH-21st newborn size standards were derived from a multicentre, multiethnic, population-based study conducted across eight geographical regions and were designed as prescriptive standards to define optimal foetal growth and enable global comparability.⁸ These standards are based on selected low-risk populations with optimal maternal health and nutrition. These charts are intended as standards rather than descriptive references. While this approach enhances standardization across settings, it may not fully account for population-specific variations in foetal growth influenced by genetic, environmental, and socioeconomic factors. Consequently, application of the INTERGROWTH-21st standards in certain populations, including South Asian settings, may classify a higher proportion of infants as SGA despite them being constitutionally small but physiologically normal.^9,10 This potential overestimation may lead to routine blood glucose monitoring of a large number of otherwise well infants during the first 72 h of life, exposing them to unnecessary painful procedures and increasing the risk of nosocomial infection. It also places a substantial burden on nursing staff and leads to considerable consumption of consumables, which is an important concern in resource-limited settings.

Current clinical practice guidelines advise routine blood glucose monitoring for infants whose birth weight is below the 10th percentile for gestational age.¹¹ However, application of the INTERGROWTH-21st standards using this cut-off may overestimate the prevalence of SGA, and infants between the 3rd and 10th percentiles represent a heterogeneous group. Universal glucose screening in this subgroup may therefore result in over-screening of otherwise well infants. Evaluating a lower threshold, such as restricting routine monitoring to infants below the 3rd percentile, may help more accurately identify those at greatest risk of hypoglycaemia. Such an approach could potentially reduce unnecessary screening and associated burdens without compromising safety. Given the high burden of SGA births in low- and middle-income countries, a large number of infants require postnatal glucose monitoring, which can substantially increase healthcare workload and resource utilization.

Therefore, this quasi-randomized controlled trial aimed to compare the safety and effectiveness of a 3^rd centile-based blood glucose monitoring strategy with the 3^rd−10^th centile approach in stable SGA infants.

Materials and methods

Trial design, setting, and participants

This quasi-randomized, parallel-group study was conducted in the Department of Neonatology at a tertiary-care hospital in Kolkata, India, from July 2024 to April 2025. Eligible participants were inborn, hemodynamically stable infants born during the study period with a gestational age of 35⁺⁰ to 42⁺⁰ weeks who were established on full enteral feeds from day one of life. Hemodynamically stable infants were defined as those with no signs of respiratory distress (no retractions, grunting, or tachypnea) and normal peripheral perfusion (warm extremities with capillary refill time <3 s). Exclusion criteria included major congenital anomalies, absent or reverse end-diastolic flow on umbilical artery Doppler, parental refusal, and the requirement for vasopressor support or mechanical ventilation at the time of enrolment. Infants with perinatal asphyxia were also excluded (umbilical cord or first-hour postnatal blood gas pH <7.2 and/or base excess ≤ −10 mmol/L; in the absence of blood gas data, exclusion was based on a 5-min Apgar score ≤5 and need for advanced resuscitation).

The study was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Ethical approval was granted by the Institutional Ethics Committee of the Institute of Post Graduate Medical Education & Research, Kolkata (IPGME&R/IEC/2022/694). The study was registered under the Clinical Trial Registry of India.

Enrolment and treatment

The study objectives and procedures were explained to the parents or legal guardians of eligible infants in their native language shortly after birth, and written informed consent was obtained. Relevant prenatal, antenatal, and perinatal information was collected from maternal interviews and medical records. Gestational age was assessed postnatally with priority given to first-trimester ultrasound findings. In the absence of such data, gestational age was estimated using the last menstrual period (LMP) or the Expanded New Ballard Score (NBS),¹² with the latter applied when first-trimester ultrasound was unavailable or when a discrepancy of 2 weeks or more was noted. Birth weight was measured using a calibrated infant weighing scale with an accuracy of ±5 g. Sex-specific INTERGROWTH-21st growth charts were then used to identify SGA infants, defined as those with a birth weight below the 10th percentile for gestational age and sex.⁸

Eligible SGA infants were enrolled within 1 h of birth in the operating theatre or labour room. Infants were allocated in a 1:1 ratio to the two groups using a predefined quasi-randomization method (alternate assignment), whereby consecutive eligible infants were assigned sequentially to either the restricted monitoring group or the conventional monitoring group. As allocation followed a predictable sequence, formal allocation concealment was not feasible. However, enrolment was performed consecutively to minimize selection bias.

After delivery and initial resuscitation (if required), the attending neonatologist assigned the infant to the respective group according to the predefined allocation sequence. Due to the nature of the intervention, the nursing staff performing blood glucose measurements could not be blinded. However, outcome assessors responsible for evaluating the primary and secondary outcomes were blinded to group allocation.

Feeding protocol

Following baseline assessment, feeding was initiated in all infants according to the unit’s standard feeding protocol. Depending on clinical condition, infants were fed by direct breastfeeding, katori spoon (KS) feeding in cases of breastfeeding difficulty, or orogastric (OG) feeding if receiving respiratory support. Feeding was administered by mothers in the postnatal ward or by on-duty nursing staff in the neonatal care unit, as appropriate. Lactation counselling was provided daily by the milk bank lactation counsellor, beginning in the antenatal period. Mother’s own milk (MOM) was the preferred feed; pasteurized donor human milk (PDHM) was used when MOM was unavailable, and formula milk was provided when donor milk was not available.

Infants managed in the postnatal ward were exclusively breastfed on demand. Among admitted infants, those with a birth weight <1.5 kg were started on feeds at 80 mL/kg/day, while infants with a birth weight ≥1.5 kg received 60 mL/kg/day on day one. Feed volumes were advanced by 30 mL/kg/day according to a standardized unit protocol until a target enteral intake of 150 mL/kg/day was achieved.

Human milk fortifier (HMF) was added to breast milk for infants with a birth weight <1.5 kg once enteral feeds reached 100 mL/kg/day to ensure adequate caloric intake. All other feeding-related practices in both groups followed unit standard protocols, including feeding intervals, advancement criteria, and management of feed intolerance.

Blood glucose monitoring and management protocols

Blood glucose levels were measured at 2, 6, 12, 24, 48, and 72 h of life using a point-of-care glucometer (Accu-Chek Instant-S; Roche Diabetes Care India Pvt. Ltd).¹³ Hypoglycaemia was defined as a blood glucose level <47 mg/dL.¹⁴ Operational thresholds for intervention were 25–40 mg/dL in the first 4 h of life, 35–45 mg/dL between 4 and 24 h, and <45 mg/dL beyond 24 h.¹⁴ Blood glucose values suggestive of hypoglycaemia were confirmed using a blood gas analyser or standard laboratory methods before initiating intervention.

Outcome measures

Primary outcome.

• Incidence of symptomatic or asymptomatic hypoglycaemia (blood glucose <47 mg/dL) within the first 72 h of life.¹⁴

Secondary outcomes.

• Time to achieve full enteral feeds (defined as sustained intake ≥150 mL/kg/day for 24 h).

• Requirement for intravenous fluids before reaching full enteral feeds.

• Incidence of necrotizing enterocolitis (NEC), defined as Modified Bell staging ≥ Stage II.¹⁵

• Incidence of culture-positive sepsis.

• Length of hospital stay (in days).

• Mortality prior to discharge.

Sample size calculation

The sample size was estimated to evaluate whether a selective blood glucose monitoring (BGM) strategy based on the 3rd percentile was not clinically inferior to the conventional 10th percentile strategy in detecting hypoglycaemia. A previous study reported a hypoglycaemia incidence of 19.42% among term and late preterm SGA infants.¹⁶ Given the absence of prior studies directly comparing these two BGM strategies in stable SGA infants, a pilot study was conducted involving 20 infants (10 in each group), in which one hypoglycaemia event occurred in each group within the first 72 h of life. Based on these findings and the expectation of lower event rates in stable, early-fed cohorts, a conservative event rate of 15% was assumed for both groups.

A non-inferiority margin of 10% was pre-specified, informed by the HypoEXIT trial, which demonstrated that, among otherwise healthy newborns with asymptomatic moderate hypoglycaemia, a lower glucose treatment threshold (36 mg/dL) was non-inferior to the traditional threshold (47 mg/dL) with respect to psychomotor development, despite a higher frequency of hypoglycaemic episodes in the lower-threshold group (57% vs 47%).¹⁷ Therefore, a 10% margin was considered to represent the maximum clinically acceptable difference in hypoglycaemia detection that would justify adoption of a less intensive monitoring strategy. This margin was balanced against the potential clinical benefits of reducing iatrogenic harm, including neonatal pain from repeated heel pricks, risk of nosocomial infections, and optimization of healthcare resources in a high-volume setting.^18,19

Assuming a one-sided alpha of 0.025 and 80% power, the minimum required sample size was calculated as 162 infants per group using G*Power software (version 3.1.9.7; Heinrich Heine University, Düsseldorf, Germany, 2024).

Statistical analysis

All data were entered into an Excel spreadsheet, coded, and statistically analysed using SPSS Statistics version 20 (IBM Corp, Armonk, NY, USA). Data were assessed for normality using the Shapiro-Wilk test. Continuous data with a normal distribution were expressed as mean and standard deviation (SD), while non-normally distributed data were expressed as median with interquartile range (IQR). Categorical data were presented as percentages. Differences in continuous variables between the two groups were analysed using the Student's t-test (for parametric data) or the Mann–Whitney U test (for non-parametric data). Differences in categorical variables were analysed using the chi-square test or Fisher’s exact test, as appropriate. A p-value of <0.05 was considered statistically significant. All analyses were performed according to the intention-to-treat (ITT) principle.

The primary outcome of hypoglycemia incidence underwent non-inferiority testing. The absolute risk difference (ARD) with 95% confidence intervals (CI) was calculated using Newcombe’s hybrid score method (PropCIs package, R 4.4.2), the reference standard for binary proportion comparisons.²⁰ Non-inferiority was confirmed if the one-sided upper 95% CI limit excluded the pre-specified 10% margin.¹⁸

Results

A total of 512 SGA infants born between 35 and 42 weeks of gestation were initially screened during the study period. Of these, 324 infants met the inclusion criteria and were prospectively enrolled, while 188 were excluded based on predefined criteria, as shown in the participant flow diagram (Figure 1). Based on the predefined blood glucose monitoring protocol, infants were categorized into two groups: Group A (n = 162), comprising of infants with birth weight below the 3rd percentile on the INTERGROWTH-21st growth chart who underwent selective BGM, and Group B (n = 162), comprising of infants with birth weight between the 3rd and 10th percentiles who underwent conventional BGM according to the 10th percentile threshold.

Figure 1.

Participants flow diagram.

Baseline characteristics

The baseline demographic and clinical characteristics of the infants in the two groups are summarized in Table 1 and were overall comparable. Although the frequency of consanguinity differed significantly between the groups, no meaningful association between consanguinity and hypoglycaemia was observed. Mean blood glucose levels at 2 h of life did not differ significantly between the two groups.

Table 1.

Baseline characteristics of enrolled infants.

Variables	Group A (n = 162) BGM <3^rd percentile	Group B (n = 162) BGM <3^rd–10^th percentile	p-value
Demographic
Birth weight (gm)	1959.3 ± 407.4	1974.3 ± 374.7	0.730
Gestational age (weeks)	37 [36–39]	37 [36–39]	0.750
Maternal data
Maternal age (years)	25 [23–30]	26 [23–30.2]	0.541
Consanguinity	1 (0.6%)	8 (4.9%)	0.036
Gravida (1)	96 (59.3%)	100 (61.7%)	0.649
Gravida (2)	45 (27.8%)	35 (21.6%)	0.198
Gravida (3 or more)	21 (12.9%)	27 (16.6%)	0.348
Major obstetric complication	47 (29.2%)	58 (36%)	0.191
Chorioamnionitis	3 (1.9%)	6 (3.7%)	0.502
GDM	4 (2.5%)	5 (3.1%)	0.735
Unbooked case	2 (1.2%)	1 (0.6%)	0.562
Received beta blockers	12 (7.4%)	15 (9.3%)	0.546
Neonatal data
Male sex	85 (52.5%)	82 (50.6%)	0.739
Multi-foetal	15 (9.3%)	17 (10.5%)	0.710
LUCS	106 (65.4%)	117 (72.2)	0.187
Malformation	5 (3.1%)	7 (4.4%)	0.534
Respiratory support	26 (16%)	31 (19.1%)	0.466
Neonatal morbidities (any one)	34 (21%)	39 (24.1%)	0.506
Antibiotics	19 (11.7%)	16 (9.9%)	0.591
Mean blood glucose at 2 h (mg/dl)	49 ± 3.5	50.5 ± 4.6	0.312

*p-values significant at <0.05; p-values not significant at >0.05; Continuous data presented as mean ± standard deviation or median [interquartile range]; categorical data presented as n (%).

Abbreviations: BGM, blood glucose monitoring; GDM, gestational diabetes mellitus; LUCS, lower uterine caesarean section.

Primary and secondary outcomes

The outcome measures are summarized in Table 2. The incidence of hypoglycemia in the first 72 h of life was 10.5% (17/162) in group A versus 13% (21/162) in group B (p = 0.485). The absolute risk difference was −2.5% (95% CI −8.8% to 3.8%). As the upper bound of the confidence interval remained below the pre-specified non-inferiority margin of 10 percentage points (absolute difference), the restricted BGM strategy met the criterion for non-inferiority.

Table 2.

Primary and secondary outcome measure.

	Group A (n = 162) BGM <3^rd percentile	Group B (n = 162) BGM <3^rd–10^th percentile	p-value
Primary outcome
Hypoglycemia in first 72 hrs^a	17 (10.5%)	21 (13 %)	0.490
Secondary outcomes
Time to reach full feed (@150 ml/kg/day)^b	6 [5–7]	6 [6–7]	0.100
Intravenous fluid requirement^a	27 (16.7%)	30 (18.5%)	0.662
Length of hospital stay (days)^b	8 [7–10]	8 [7–10]	0.546
Culture-positive sepsis^a	4 (2.46%)	6 (3.7%)	0.750

^aCategorical data presented as n (%).

^bContinuous data presented as median [interquartile range].

Abbreviations: BGM, blood glucose monitoring.

On exploratory univariate analysis, no statistically significant associations were identified between hypoglycaemia and baseline clinical or demographic variables, including gestational age, birth weight, sex, SGA category, or feeding pattern (Table 3).

Table 3.

Univariate analysis of factors associated with hypoglycaemia.

Variable	Hypoglycaemia (n = 38)	No hypoglycaemia (n = 286)	p-value
Birth weight (g)	1910 ± 380	1975 ± 395	0.210
Gestational age (weeks)	36.5 [36–38]	37 [36–39]	0.180
<3rd percentile	17 (44.7%)	145 (50.7%)	0.480
Male sex	21 (55.3%)	146 (51.0%)	0.640
GDM	3 (7.9%)	6 (2.1%)	0.090
LSCS delivery	26 (68.4%)	197 (68.9%)	0.950
Multiple gestation	5 (13.2%)	27 (9.4%)	0.520
Exclusive mother’s milk	28 (73.7%)	230 (80.4%)	0.330

The type of milk received during the first 72 h of life did not differ significantly between the groups (Table 4). The majority of infants in both groups received exclusive mother’s own milk (78.4% in Group A vs 80.9% in Group B; p = 0.82).

Table 4.

Type of milk received during the first 72 h.

Type of milk	Group A (n = 162)	Group B (n = 162)	p-value
Exclusive mother’s own milk	127 (78.4%)	131 (80.9%)	0.82
Predominantly donor human milk	5 (3.1%)	4 (2.5%)
Predominantly formula supplementation	30 (18.5%)	27 (16.7%)

(Predominantly donor human milk: infants who received >50% of their total enteral intake as donor human milk during the first 72 h of life. Predominantly formula supplementation: infants who received >50% of their total enteral intake as formula during the first 72 h of life).

There were no statistically or clinically significant differences between the groups in secondary outcomes. The median time to achieve full enteral feeds was similar (6 [IQR 5–7] days vs 6 [IQR 6–7] days; p = 0.100), as were the requirement for intravenous fluids before full feeds (16.7% vs 18.5%; p = 0.662), median length of hospital stay (8 [IQR 7–10] days in both groups; p = 0.546), and incidence of culture-positive sepsis (2.46% vs 3.7%; p = 0.750). No cases of necrotizing enterocolitis or mortality were observed in either group.

Discussion

In this quasi-randomized controlled study of stable, early-fed SGA infants born between 35 and 42 weeks of gestation, blood glucose monitoring (BGM) strategy based on the 3^rd percentile of the INTERGROWTH-21st growth chart was not associated with a clinically significant increase in hypoglycaemia compared with the 3^rd−10^th percentile-based strategy. Furthermore, no significant differences were observed between the groups in secondary clinical outcomes.

The INTERGROWTH-21st standards were developed as prescriptive international growth standards derived from healthy, low-risk pregnancies across diverse geographical settings.⁸ Unlike population-based reference charts, they are intended to define optimal growth rather than describe observed growth patterns within a specific population. Although this approach allows global comparability, the populations used to construct the INTERGROWTH-21st charts may not fully represent the ethnic and genetic diversity of the Indian population.¹⁹ Consequently, application of these standards without prior local validation may increase the risk of misclassification of infant growth status. Anand et al. reported that INTERGROWTH-21st classified 19.6% of neonates as SGA compared with only 4.5% using the AIIMS chart, while the ‘additional SGA’ identified by INTERGROWTH-21^st had significantly lower risk of adverse outcomes.²¹

A recent systematic review of clinical practice guidelines on neonatal hypoglycaemia screening highlighted considerable variation in screening definitions and a lack of consensus regarding which infants are truly at risk of clinically significant hypoglycaemia.²² Large cohort studies have also shown ethnic differences in screening eligibility, with infants of Indian and other non-European mothers more frequently classified as at risk due to variations in maternal anthropometry and the application of growth charts.²²

The use of country-specific growth charts remains debated.^23,24 In India, applying international standards may increase SGA classification, whereas relying solely on local references may mask true pathological growth restriction if the reference population reflects underlying nutritional or socioeconomic constraints.²¹ Our findings do not argue against the use of the INTERGROWTH-21st standards but suggest that additional clinical risk stratification within SGA categories such as focusing on more severe centile thresholds may offer a balanced and context-sensitive approach.

In our study, the lack of difference in hypoglycaemia incidence between groups may reflect the heterogeneity within the 10^th percentile definition of SGA. Infants between the 3^rd and 10^th percentiles likely include constitutionally small but metabolically appropriate infants with adequate glycogen stores and intact counter-regulatory hormonal responses. All infants in our cohort were hemodynamically stable and initiated on feeds from day one of life, a factor known to support endogenous glucose production and reduce transitional hypoglycaemia. Furthermore, metabolic vulnerability appears to increase with the severity of growth restriction. Infants below the 3rd percentile are more likely to represent true intrauterine growth restriction. This biological gradient may explain why the 3^rd percentile threshold more specifically identifies infants at highest metabolic risk, while inclusion of those between the 3rd and 10th percentiles does not increase hypoglycaemia detection in our setting.

The similar rates of intravenous fluid use, time to reach full feeds, length of hospital stay, and infectious complications further support the short-term clinical safety of the selective BGM strategy. In a prospective Indian cohort study, Anand et al. reported that the INTERGROWTH-21st chart classified a substantially higher proportion of infants as SGA compared with regional growth charts.²¹ However, the additional SGA infants identified solely by the INTERGROWTH-21st chart had a lower risk of short-term adverse outcomes. These findings suggest that use of the 10^th percentile threshold based on global standards may overestimate clinically significant growth restriction in our setting.

Overclassification of infants as SGA may increase the burden of postnatal glucose monitoring, particularly in low- and middle-income countries with limited healthcare resources. Additionally, minimizing repeated heel pricks is consistent with the principles of developmental supportive care and may reduce procedural pain and stress in newborns.^25,26

In our study, feeding patterns during the first 72 h were similar in both groups, with most infants receiving exclusive mother’s own milk. Evidence suggests that human milk and standard infant formula produce comparable postprandial glycaemic and insulinaemic responses.²⁷ Although breastfed infants may have slightly lower physiological glucose levels, this has not been shown to increase the risk of clinically significant hypoglycaemia.²⁸ Together, these findings support breastfeeding as a safe and appropriate feeding strategy, even for infants considered at risk of hypoglycaemia.

To the best of our knowledge, this is one of the first prospective quasi-randomized studies from an Indian tertiary-care centre to evaluate a centile-based risk stratification approach for blood glucose monitoring in stable SGA infants. The study was conducted using a predefined protocol with uniform feeding practices and a standardized glucose monitoring schedule.

This study has several limitations. The quasi-random allocation method (alternate assignment) is susceptible to selection bias due to the lack of allocation concealment. The study was conducted at a single tertiary-care centre, which may limit the generalizability of the findings to other settings. Outcomes were assessed only during the first 72 h of life and until hospital discharge; long-term neurodevelopmental follow-up was not performed. In addition, the study population was restricted to hemodynamically stable, early-fed infants, which may limit the applicability of the results to clinically unstable or higher-risk SGA infants. Finally, classification of SGA was based solely on the INTERGROWTH-21st standards without local validation; therefore, misclassification of constitutionally small infants as having true intrauterine growth restriction cannot be completely excluded.

Conclusion

In this quasi-randomized controlled trial of stable, early-fed SGA infants, a 3^rd percentile-based (INTERGROWTH-21st) blood glucose monitoring strategy was non-inferior to the 3^rd −10^th percentile approach for detecting hypoglycaemia. No significant differences were observed in short-term clinical outcomes. These findings should be interpreted in the context of a comparison between monitoring strategies based on different centile thresholds, rather than a direct comparison of biological risk between SGA subgroups. These findings suggest that additional risk stratification within the SGA category, focusing on more severe growth restriction, may allow a more targeted monitoring strategy without compromising short-term safety. Larger multicentre studies with long-term follow-up are needed to confirm these findings and inform screening guidelines.

Footnotes

Acknowledgements

We thank the parents, all the residents and nursing officers of the unit. We express our sincere gratitude to all the laboratory technicians for their help and whole hearted support.

ORCID iDs

Md Habibullah Sk

Bijan Saha

Consent to participate

Informed written consent was obtained from all legal guardians before enrolment in the trial.

Consent for publication

Informed written consent was obtained from parents or legal guardians of all included participants for publication of anonymous patients’ data.

Author contributions

The study protocol was designed by SD, MH, and BS. BS provided his valuable input in every stage of the study and improved the content. SD and MH collected the data under the supervision of BS. MB did the statistical analysis. SD and MH prepared the first draft. BS and MH edited the manuscript. All the authors approved the final version of the manuscript and agreed to be accountable for all aspects of the work.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data supporting the findings of this study are available from the corresponding author upon reasonable request.*

Appendix

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