Evidence map›Paper›PMID 36123560›Full record

ArticleEuropean journal of drug metabolism and pharmacokinetics2022

Development and Validation of a Length- and Habitus-Based Method of Ideal and Lean Body Weight Estimation for Adults Requiring Urgent Weight-Based Medical Intervention.

Mike Wells, Lara Nicole Goldstein, Giles Cattermole

3 registry-linked trialsAbstract read
PubMed Publisher
In one paragraph

Article in European journal of drug metabolism and pharmacokinetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06645548 nawithdrawnnot on this mapstarted 2029, after this paper: background citation

Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 3 - Measure the Accuracy of Weight Estimations by The 3D Camera System in Acutely Ill or Injured Emergency Department Patients and Compare This Accuracy Against That of Standard Care.

TypeinterventionalSponsorFlorida Atlantic UniversityRan2029 to 2030Enrolled0ConditionsBody Weights and Measures, Body Weight in the Overweight and Obese Class - I Population, Drug Dose, Weight EstimateArmsWeight estimation using 3D camera
NCT06646120 withdrawnnot on this mapstarted 2025, after this paper: background citation

Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care. Study 1 - Establish a Model Using a Single 3D Camera Image of a Supine Patient to Accurately Estimate TBW, IBW And LBW.

TypeobservationalSponsorFlorida Atlantic UniversityRan2025 to 2026Enrolled0ConditionsBody Weights and Measures, Body Weight in the Overweight and Obese Class - I Population
NCT06646133 withdrawnnot on this mapstarted 2027, after this paper: background citation

Machine Learning and 3D Image-Based Modeling for Real-Time Body Weight and Body Composition Estimation During Emergency Medical Care: Study 2 - Measure the Accuracy and Speed of Weight Estimations Using a 3D Camera System During Simulated Medical Emergencies

TypeobservationalSponsorFlorida Atlantic UniversityRan2027 to 2028Enrolled0ConditionsBody Weights and Measures, Body Weight in the Overweight and Obese Class - I Population, Weight Estimation, Emergency Drug DosingArms3D camera weight estimate, Standard methods of weight estimation
3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 3 countries.

Mike WellsDepartment of Emergency Medicine, Florida Atlantic University, Charles E. Schmidt College of Medicine, Boca Raton, FL, USA. profmikewells@gmail.com.ORCID http://orcid.org/0000-0002-4520-2007
Lara Nicole GoldsteinDivision of Emergency Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.ORCID http://orcid.org/0000-0002-9427-8710
Giles CattermoleEmergency Department, Princess Royal University Hospital, King's College Hospital NHS Trust, London, UK.ORCID http://orcid.org/0000-0002-8910-2307
Florida Atlantic University · USPrincess Royal University Hospital · GBUniversity of the Witwatersrand · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveAccurate drug dosing in obese patients requires an estimation of ideal body weight (IBW) or lean body weight (LBW) for dosing hydrophilic medications. Erroneous weight estimates during the management of adults requiring weight-based treatment may contribute to poor outcomes. Existing methods of IBW and LBW estimation or measurement are very difficult to use during emergency care. A new point-of-care model would be useful to provide rapid estimates of IBW and LBW for this purpose.

methodsA model was derived based on the PAWPER XL-MAC tape, a pediatric weight estimation system which uses recumbent length and mid-arm circumference to estimate IBW and LBW. The new adult model was used to generate IBW and LBW estimations for a derivation sample (n = 33155) and a validation sample (n = 5926) from National Health and Nutrition Examination Survey (NHANES) datasets. The model was developed in two steps, with calibration at each step, before being validated on an unused dataset. The outcome measure was to achieve >95% of IBW and LBW estimations within 20% of recognized reference standards (P20 > 95%) and >70% of estimations within 10% of these standards (P10 > 70%).

resultsThe new model achieved a P20 of 100% and a P10 of 99.9% for IBW and a P20 of 98.3% and a P10 of 78.3% for LBW. This accuracy was maintained in both sexes, all ages, all ethnic groups, all lengths, and in all habitus types, except for the severely obese female subgroup.

conclusionsThe modified PAWPER XL-MAC model proved to be an accurate method of IBW and LBW estimation. It could, therefore, have an important role in facilitating emergency drug dose calculations in obese adult patients.

Indexed as

ObesityAdultBody WeightChildFemaleHumansMaleNutrition Surveys

Identifiers

PMID36123560
OpenAlexW4296299186

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.