PediTools Electronic Growth Chart Calculators: Applications in Clinical Care, Research, and Quality Improvement

Background Parameterization of pediatric growth charts allows precise quantitation of growth metrics that would be difficult or impossible with traditional paper charts. However, limited availability of growth chart calculators for use by clinicians and clinical researchers currently restricts broader application. Objective The aim of this study was to assess the deployment of electronic calculators for growth charts using the lambda-mu-sigma (LMS) parameterization method, with examples of their utilization for patient care delivery, clinical research, and quality improvement projects. Methods The publicly accessible PediTools website of clinical calculators was developed to allow LMS-based calculations on anthropometric measurements of individual patients. Similar calculations were applied in a retrospective study of a population of patients from 7 Massachusetts neonatal intensive care units (NICUs) to compare interhospital growth outcomes (change in weight Z-score from birth to discharge [∆Z weight]) and their association with gestational age at birth. At 1 hospital, a bundle of quality improvement interventions targeting improved growth was implemented, and the outcomes were assessed prospectively via monitoring of ∆Z weight pre- and postintervention. Results The PediTools website was launched in January 2012, and as of June 2019, it received over 500,000 page views per month, with users from over 21 countries. A retrospective analysis of 7975 patients at 7 Massachusetts NICUs, born between 2006 and 2011, at 23 to 34 completed weeks gestation identified an overall ∆Z weight from birth to discharge of –0.81 (P<.001). However, the degree of ∆Z weight differed significantly by hospital, ranging from –0.56 to –1.05 (P<.001). Also identified was the association between inferior growth outcomes and lower gestational age at birth, as well as that the degree of association between ∆Z weight and gestation at birth also differed by hospital. At 1 hospital, implementing a bundle of interventions targeting growth resulted in a significant and sustained reduction in loss of weight Z-score from birth to discharge. Conclusions LMS-based anthropometric measurement calculation tools on a public website have been widely utilized. Application in a retrospective clinical study on a large dataset demonstrated inferior growth at lower gestational age and interhospital variation in growth outcomes. Change in weight Z-score has potential utility as an outcome measure for monitoring clinical quality improvement. We also announce the release of open-source computer code written in R to allow other clinicians and clinical researchers to easily perform similar analyses.

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PediTools Electronic Growth Chart Calculators: Applications in Clinical Care, Research, and Quality Improvement (Preprint)

10.2196/preprints.16204 ◽

2019 ◽

Author(s):

Joseph H Chou ◽

Sergei Roumiantsev ◽

Rachana Singh

Keyword(s):

Quality Improvement ◽

Gestational Age ◽

Anthropometric Measurement ◽

Growth Chart ◽

Growth Charts ◽

Z Score ◽

Growth Outcomes ◽

Retrospective Clinical Study ◽

Gestational Age At Birth ◽

Age At Birth

BACKGROUND Parameterization of pediatric growth charts allows precise quantitation of growth metrics that would be difficult or impossible with traditional paper charts. However, limited availability of growth chart calculators for use by clinicians and clinical researchers currently restricts broader application. OBJECTIVE The aim of this study was to assess the deployment of electronic calculators for growth charts using the lambda-mu-sigma (LMS) parameterization method, with examples of their utilization for patient care delivery, clinical research, and quality improvement projects. METHODS The publicly accessible PediTools website of clinical calculators was developed to allow LMS-based calculations on anthropometric measurements of individual patients. Similar calculations were applied in a retrospective study of a population of patients from 7 Massachusetts neonatal intensive care units (NICUs) to compare interhospital growth outcomes (change in weight Z-score from birth to discharge [∆Z weight]) and their association with gestational age at birth. At 1 hospital, a bundle of quality improvement interventions targeting improved growth was implemented, and the outcomes were assessed prospectively via monitoring of ∆Z weight pre- and postintervention. RESULTS The PediTools website was launched in January 2012, and as of June 2019, it received over 500,000 page views per month, with users from over 21 countries. A retrospective analysis of 7975 patients at 7 Massachusetts NICUs, born between 2006 and 2011, at 23 to 34 completed weeks gestation identified an overall ∆Z weight from birth to discharge of –0.81 (<i>P</i><.001). However, the degree of ∆Z weight differed significantly by hospital, ranging from –0.56 to –1.05 (<i>P</i><.001). Also identified was the association between inferior growth outcomes and lower gestational age at birth, as well as that the degree of association between ∆Z weight and gestation at birth also differed by hospital. At 1 hospital, implementing a bundle of interventions targeting growth resulted in a significant and sustained reduction in loss of weight Z-score from birth to discharge. CONCLUSIONS LMS-based anthropometric measurement calculation tools on a public website have been widely utilized. Application in a retrospective clinical study on a large dataset demonstrated inferior growth at lower gestational age and interhospital variation in growth outcomes. Change in weight Z-score has potential utility as an outcome measure for monitoring clinical quality improvement. We also announce the release of open-source computer code written in R to allow other clinicians and clinical researchers to easily perform similar analyses.

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WHICH GROWTH CHARTS TO USE TO CLASSIFY NEONATES AS SMALL-FOR-GESTATIONAL AGE AT BIRTH?

Indian Journal of Child Health ◽

10.32677/ijch.2019.v06.i12.001 ◽

2019 ◽

Vol 06 (12) ◽

pp. 636-642

Author(s):

Pratima Anand ◽

Tanushree Sahoo ◽

Krishna Mohan Gulla

Keyword(s):

Gestational Age ◽

Small For Gestational Age ◽

Growth Charts ◽

Gestational Age At Birth ◽

Age At Birth

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Prolonged ventilation and postnatal growth of preterm infants

Journal of Perinatal Medicine ◽

10.1515/jpm-2019-0278 ◽

2019 ◽

Vol 48 (1) ◽

pp. 82-86 ◽

Cited By ~ 2

Author(s):

Emma Williams ◽

Theodore Dassios ◽

Kate Arnold ◽

Ann Hickey ◽

Anne Greenough

Keyword(s):

Mechanical Ventilation ◽

Gestational Age ◽

Head Circumference ◽

Invasive Mechanical Ventilation ◽

Postnatal Growth ◽

Z Score ◽

Prolonged Ventilation ◽

Gestational Age At Birth ◽

Age At Birth ◽

Prematurely Born Infants

AbstractBackgroundExtremely premature infants often need invasive respiratory support from birth, but have low nutritional reserves and high metabolic demands. Our aim was to determine if there was a relationship between prolonged ventilation and reduced postnatal growth in such infants.MethodsA retrospective, observational study was undertaken. Data from infants born at less than 28 weeks of gestational age and ventilated for 7 days or more were collected and analysed including gestational age, gender, birth and discharge weight, birth and discharge head circumference, days of invasive mechanical ventilation and use of postnatal corticosteroids. The duration of invasive mechanical ventilation and the differences in weight (ΔWz) and head circumference (ΔHz) z-score from birth to discharge were calculated.ResultsFifty-five infants were studied with a median [interquartile range (IQR)] gestational age at birth of 25.3 (24.3–26.7) weeks and birth weight of 0.73 (0.65–0.87) kg. The median duration of mechanical ventilation was 45 (33–68) days. Both ΔWz and ΔHz were significantly negatively correlated to the number of invasive mechanical ventilation days (P = 0.01 and P = 0.03, respectively), but not to the use of postnatal corticosteroids.ConclusionPoor postnatal growth is significantly negatively associated with a longer duration of mechanical ventilation in extremely prematurely born infants.

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Gestational Age at Birth, 1994 and 2004

PsycEXTRA Dataset ◽

10.1037/e411542008-001 ◽

2006 ◽

Keyword(s):

Gestational Age ◽

Gestational Age At Birth ◽

Age At Birth

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Faculty Opinions recommendation of Effects of gestational age at birth on health outcomes at 3 and 5 years of age: population based cohort study.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.14264188.15777343 ◽

2012 ◽

Author(s):

Mark Sullivan

Keyword(s):

Cohort Study ◽

Health Outcomes ◽

Gestational Age ◽

Population Based ◽

Gestational Age At Birth ◽

Age At Birth

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Prenatal household air pollutant exposure is associated with reduced size and gestational age at birth among a cohort of Ghanaian infants

Environment International ◽

10.1016/j.envint.2021.106659 ◽

2021 ◽

Vol 155 ◽

pp. 106659

Author(s):

Ashlinn K. Quinn ◽

Irene Apewe Adjei ◽

Kenneth Ayuurebobi Ae-Ngibise ◽

Oscar Agyei ◽

Ellen Abrafi Boamah-Kaali ◽

...

Keyword(s):

Gestational Age ◽

Air Pollutant ◽

Gestational Age At Birth ◽

Age At Birth

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Coeliac disease presenting atypically: A much wider spectrum

Tropical Doctor ◽

10.1177/0049475521991348 ◽

2021 ◽

pp. 004947552199134

Author(s):

Avinash Lomash ◽

Abhinaya Venkatakrishnan ◽

Meenakshi Bothra ◽

Bhavna Dhingra ◽

Praveen Kumar ◽

...

Keyword(s):

Coeliac Disease ◽

Gestational Age ◽

Dermatitis Herpetiformis ◽

Mode Of Delivery ◽

Gastrointestinal Symptoms ◽

Stunted Growth ◽

Significant Difference ◽

High Index Of Suspicion ◽

Gestational Age At Birth ◽

Age At Birth

Atypical coeliac disease in young children is frequently missed when it presents atypically as non-gastrointestinal presentations to different specialties. There was a greater delay (54 months) in establishing the diagnosis in those with atypical coeliac disease (p < 0.001). No difference was observed in the mode of delivery or duration of breast feeding, but significant difference was observed between gestational age at birth (p < 0.001). Most cases showed stunted growth and underweight. Irritability, anaemia, rickets, dermatitis herpetiformis, alopecia and intussusception were other common predictors of atypical coeliac disease. Because of a myriad spectrum of non-gastrointestinal symptoms, at any age with diverse presentation, a high index of suspicion is therefore required.

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Maternal biological age assessed in early pregnancy is associated with gestational age at birth

Scientific Reports ◽

10.1038/s41598-021-94281-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Eva E. Lancaster ◽

Dana M. Lapato ◽

Colleen Jackson-Cook ◽

Jerome F. Strauss ◽

Roxann Roberson-Nay ◽

...

Keyword(s):

Risk Factors ◽

Preterm Birth ◽

Early Pregnancy ◽

Gestational Age ◽

Cellular Aging ◽

Biological Age ◽

Potential Candidate ◽

A Genome ◽

Gestational Age At Birth ◽

Age At Birth

AbstractMaternal age is an established predictor of preterm birth independent of other recognized risk factors. The use of chronological age makes the assumption that individuals age at a similar rate. Therefore, it does not capture interindividual differences that may exist due to genetic background and environmental exposures. As a result, there is a need to identify biomarkers that more closely index the rate of cellular aging. One potential candidate is biological age (BA) estimated by the DNA methylome. This study investigated whether maternal BA, estimated in either early and/or late pregnancy, predicts gestational age at birth. BA was estimated from a genome-wide DNA methylation platform using the Horvath algorithm. Linear regression methods assessed the relationship between BA and pregnancy outcomes, including gestational age at birth and prenatal perceived stress, in a primary and replication cohort. Prenatal BA estimates from early pregnancy explained variance in gestational age at birth above and beyond the influence of other recognized preterm birth risk factors. Sensitivity analyses indicated that this signal was driven primarily by self-identified African American participants. This predictive relationship was sensitive to small variations in the BA estimation algorithm. Benefits and limitations of using BA in translational research and clinical applications for preterm birth are considered.

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