Readers’ Forum
The amount of vancomycin in the syringes prepared by the nurses before the protocol was revised was significantly lower than the theoretical one (mean SD, 33.83 4.58 mg vs. 40 mg; Student’s test, p < 0.001). When it came to the method of reconstitution, we observed that the amount of vancomycin was significantly different between water and saline, with or without stirring (Kruskal– Wallis test; p < 0.001), especially between water with stirring and saline without stirring [median (min-max): 34.5 mg (34.2–35.1) vs. 27.6 mg (25.5–33.0); Conover and Iman, p < 0.0001]. The drug transfer method and dilution process were also associated with a significant difference between the amounts of vancomycin (p = 0.043). After revising the protocol, there was still a significant difference between the observed and theoretical amounts (35.80 0.88 mg vs. 40 mg; p < 0.001). The relative standard deviation (Fig. 1) was significantly lower before we revised the protocol (2.5% vs. 13.0%; Fisher’s test, p < 0.001). Our main hypothesis is that the dosing variability of vancomycin syringes is mainly due to the solvent used to reconstitute the solution and the nonsystematic practice of stirring to ensure that the powder is completely dissolved. Another way to reduce these risks and errors is to standardize and centralize preparation and reconstitution in the hospital pharmacy (1). The authors wish to thank the members of the NICU care team, University Hospital of Lille and Dr Damien Lannoy for their dedication and commitment to this study and the manufacturers, Safic Alcan and ACS Dobfar, for providing free vancomycin powder samples for our research.
References 1. Hecq JD. Centralized intravenous additive services (CIVAS): the state of the art in 2010. Ann Pharm Fr 2011; 69: 30–7. DOI:10.1111/apa.12484
Aurelie Foinard1, Bertrand Decaudin1,2, Nicolas Simon ([email protected])1,2, Christine Barthelemy1, Laurent Storme3,4, Pascal Odou1,2 1.Laboratoire de Biopharmacie, Pharmacie nique et Hospitalie re, EA4481, Universite Lille Gale Nord de France, Lille, France 2.Institut de Pharmacie, CHRU Lille, Lille, France decine Ne onatale, CHRU Lille, Lille, 3.Clinique de Me France rinatal et Croissance, 4.EA4489, Environnement Pe Lille Nord de France, Lille, France Universite
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Readers’ Forum
caudin, Faculte de Correspondence: Bertrand De Pharmacie, Laboratoire de Biopharmacie, Pharmanique et Hospitalie re, 3 rue du Professeur cie Gale Laguesse, BP 83, 59006 Lille Cedex, France. Tel: +33 (0)3 20 96 40 29 | Fax: +33 (0)3 20 95 90 09 | Email: [email protected]
Malnutrition screening tools need to be applied properly before they can be compared Sir, We read with interest the article by Moeeni et al. (1) in Acta Paediatrica which examines the prevalence of undernutrition and in the process compares the performance of a range of paediatric nutrition screening tools. We could take issue with a number of their conclusions that do not seem to be well supported by their own evidence, but our main concern is that the PYMS tool has been miscalculated. The authors conclude that STRONGkids (2) is a better tool for identifying children with moderate and severe malnutrition, defined here using the WHO criteria of weight-for-height and height-for-age < 2 SD or a BMI z-score < 2 SD and that STAMP tool and our own PYMS (3) failed to identify all such children. This is implausible as the PYMS protocol states that all children with BMI < 2 SD should be scored high risk (3), which should give PYMS 100% sensitivity for detecting BMI < 2 SD. In fact, the supplementary file (http://onlin elibrary.wiley.com/doi/10.1111/apa.12299/ suppinfo, Figure 2c and Figure 3c) reveals that some children scored at low risk of malnutrition with PYMS apparently had a BMI z-score below 2 SD, which demonstrates that it has been miscalculated for at least some subjects. Also we question the authors claim that STRONGkids identified all children with high risk of malnutrition, when several children in the medium risk category have a BMI or weight-for-height < 2 SD, and all children in the high risk category appear to have a BMI z-score within the normal range (Figure 2a and Figure 3a). We are disturbed to find these errors which must mean that at least some of the authors conclusions are fallacious. We hope you will pursue this with the authors and issue a correction.
References 1. Moeeni V, Walls T, Day AS. Nutritional status and nutrition risk screening in hospitalized children in New Zealand. Acta Paediatr 2013; 102: e419–23. 2. Hulst JM, Zwart H, Hop WC, Joosten KF. Dutch national survey to test the STRONGkids nutritional risk screening tool in hospitalized children. Clin Nutr 2010; 29: 106–11. 3. Gerasimidis K, Keane O, Macleod I, Flynn DM, Wright CM. A four-stage evaluation of the Paediatric Yorkhill Malnutrition Score in a tertiary paediatric hospital and a district general hospital. Br J Nutr 2010; 104: 751–6. DOI:10.1111/apa.12506
Konstantinos Gerasimidis ([email protected])1, Anne Maclean2, Charlotte Wright3 1.Human Nutrition, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK 2.Department of Dietetics, Royal Hospital for Sick Children, National Health Service Greater Glasgow & Clyde, Glasgow, UK 3.Paediatric Epidemiology and Child Health Unit, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK Correspondence: Konstantinos Gerasimidis, Human Nutrition, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow G3 8SJ, UK. Tel: +44 (0) 141 2016969 | Fax: +44 (0) 141 2019275 | Email: [email protected]
Malnutrition screening tools need to be applied properly before they can be compared – Response to Letter to Editors by Gerasimidis et al. Sir, We write in reply to the letter authored by Gerasimidis et al. (1). We thank the authors for their letter regarding our manuscript published in Acta Paediatrica (2). We agree that nutrition risk screening tools should be applied correctly. We have carefully reviewed the original data for the patients included in this report. The manuscript reported that three children with moderate/severe malnutrition were not identified to be at nutritional risk according to the
ª2013 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd 2014 103, pp. e93–e94
Readers’ Forum
PYMS NRS tool. Two of these children had Height for age (HFA) measurements greater than 2 standard deviations below the mean, whilst their body mass index (BMI) z scores were 0.23 and 0.71. Consequently, although these two children were malnourished according to the WHO criteria, they were not identified to be at nutritional risk by PYMS (which classifies this risk on BMI z score rather than HFA z score). Unfortunately, however, we have realised that the third child with moderate/severe malnutrition was classified incorrectly. As this child had a BMI z score of 2.66, she should be classified as high risk by PYMS. We apologise for this error and wish to submit a corrected Supplementary Figure 3c. Figure 2c is unaffected by this error. In addition, we have reviewed the consequent analyses relating to this error. The re-classification of this child means that four consequent statements also require correction, as follows: 1 On page e419 (line 3, Results section, Abstract): This text should read NRS tools were able to identify between 87.5% and 100% of the malnourished patients…. 2 Page e421: In the first paragraph of the section entitled Outcomes of NRS tools,
Readers’ Forum
the text should read …classified by the PYMS tool, 62% of the group was low risk, 13% medium and 25% high risk. 3 Page e421: In the paragraph entitled The relationship between NRS tools and anthropometry, the fifth line should read PYMS (14/16). 4 Page e422: In the Discussion, the text should read: In contrast, PYMS classified the fewest children in this way: two undernourished children were not detected. We have taken the opportunity to reanalyse all the data in this work and are certain that there are no other errors. In regards the second issue raised by Gerasimidis et al. (1), in the Discussion section of this report, it was stated that STRONGkids detected all children with moderate/severe malnutrition in its medium and high risk groups. We did not state that all these children were all in the high risk group for this NRS tool. We thank the authors for the opportunity to correct this error and to clarify aspects of our work.
they can be compared. Acta Paediatr, In press; doi: 10.1111/apa.12506 2. Moeeni V, Walls T, Day AS. Nutritional status and nutrition risk screening in hospitalized children in New Zealand. Acta Paediatr 2013; 102: e419–23.
SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article: Figure S3c Relationship between the 3 NRS tools and BMI z-scores. DOI:10.1111/apa.12522
Andrew S Day ([email protected]), Vesal Moeeni, Tony Walls Department of Paediatrics, University of Otago, Christchurch, New Zealand Correspondence: A Day, MB, ChB, MD, FRACP, Department of Paediatrics, University of Otago, Christchurch, P.O. Box 4345, Christchurch, New Zealand. Tel: +64 3 3640747 | Fax: +64 3 3640919 | Email: [email protected]
References 1. Gerasimidis K, Maclean A, Wright C. Malnutrition screening tools need to be applied properly before
ª2013 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd 2014 103, pp. e93–e95
e95
The amount of vancomycin in the syringes prepared by the nurses before the protocol was revised was significantly lower than the theoretical one (mean SD, 33.83 4.58 mg vs. 40 mg; Student’s test, p < 0.001). When it came to the method of reconstitution, we observed that the amount of vancomycin was significantly different between water and saline, with or without stirring (Kruskal– Wallis test; p < 0.001), especially between water with stirring and saline without stirring [median (min-max): 34.5 mg (34.2–35.1) vs. 27.6 mg (25.5–33.0); Conover and Iman, p < 0.0001]. The drug transfer method and dilution process were also associated with a significant difference between the amounts of vancomycin (p = 0.043). After revising the protocol, there was still a significant difference between the observed and theoretical amounts (35.80 0.88 mg vs. 40 mg; p < 0.001). The relative standard deviation (Fig. 1) was significantly lower before we revised the protocol (2.5% vs. 13.0%; Fisher’s test, p < 0.001). Our main hypothesis is that the dosing variability of vancomycin syringes is mainly due to the solvent used to reconstitute the solution and the nonsystematic practice of stirring to ensure that the powder is completely dissolved. Another way to reduce these risks and errors is to standardize and centralize preparation and reconstitution in the hospital pharmacy (1). The authors wish to thank the members of the NICU care team, University Hospital of Lille and Dr Damien Lannoy for their dedication and commitment to this study and the manufacturers, Safic Alcan and ACS Dobfar, for providing free vancomycin powder samples for our research.
References 1. Hecq JD. Centralized intravenous additive services (CIVAS): the state of the art in 2010. Ann Pharm Fr 2011; 69: 30–7. DOI:10.1111/apa.12484
Aurelie Foinard1, Bertrand Decaudin1,2, Nicolas Simon ([email protected])1,2, Christine Barthelemy1, Laurent Storme3,4, Pascal Odou1,2 1.Laboratoire de Biopharmacie, Pharmacie nique et Hospitalie re, EA4481, Universite Lille Gale Nord de France, Lille, France 2.Institut de Pharmacie, CHRU Lille, Lille, France decine Ne onatale, CHRU Lille, Lille, 3.Clinique de Me France rinatal et Croissance, 4.EA4489, Environnement Pe Lille Nord de France, Lille, France Universite
e94
Readers’ Forum
caudin, Faculte de Correspondence: Bertrand De Pharmacie, Laboratoire de Biopharmacie, Pharmanique et Hospitalie re, 3 rue du Professeur cie Gale Laguesse, BP 83, 59006 Lille Cedex, France. Tel: +33 (0)3 20 96 40 29 | Fax: +33 (0)3 20 95 90 09 | Email: [email protected]
Malnutrition screening tools need to be applied properly before they can be compared Sir, We read with interest the article by Moeeni et al. (1) in Acta Paediatrica which examines the prevalence of undernutrition and in the process compares the performance of a range of paediatric nutrition screening tools. We could take issue with a number of their conclusions that do not seem to be well supported by their own evidence, but our main concern is that the PYMS tool has been miscalculated. The authors conclude that STRONGkids (2) is a better tool for identifying children with moderate and severe malnutrition, defined here using the WHO criteria of weight-for-height and height-for-age < 2 SD or a BMI z-score < 2 SD and that STAMP tool and our own PYMS (3) failed to identify all such children. This is implausible as the PYMS protocol states that all children with BMI < 2 SD should be scored high risk (3), which should give PYMS 100% sensitivity for detecting BMI < 2 SD. In fact, the supplementary file (http://onlin elibrary.wiley.com/doi/10.1111/apa.12299/ suppinfo, Figure 2c and Figure 3c) reveals that some children scored at low risk of malnutrition with PYMS apparently had a BMI z-score below 2 SD, which demonstrates that it has been miscalculated for at least some subjects. Also we question the authors claim that STRONGkids identified all children with high risk of malnutrition, when several children in the medium risk category have a BMI or weight-for-height < 2 SD, and all children in the high risk category appear to have a BMI z-score within the normal range (Figure 2a and Figure 3a). We are disturbed to find these errors which must mean that at least some of the authors conclusions are fallacious. We hope you will pursue this with the authors and issue a correction.
References 1. Moeeni V, Walls T, Day AS. Nutritional status and nutrition risk screening in hospitalized children in New Zealand. Acta Paediatr 2013; 102: e419–23. 2. Hulst JM, Zwart H, Hop WC, Joosten KF. Dutch national survey to test the STRONGkids nutritional risk screening tool in hospitalized children. Clin Nutr 2010; 29: 106–11. 3. Gerasimidis K, Keane O, Macleod I, Flynn DM, Wright CM. A four-stage evaluation of the Paediatric Yorkhill Malnutrition Score in a tertiary paediatric hospital and a district general hospital. Br J Nutr 2010; 104: 751–6. DOI:10.1111/apa.12506
Konstantinos Gerasimidis ([email protected])1, Anne Maclean2, Charlotte Wright3 1.Human Nutrition, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK 2.Department of Dietetics, Royal Hospital for Sick Children, National Health Service Greater Glasgow & Clyde, Glasgow, UK 3.Paediatric Epidemiology and Child Health Unit, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK Correspondence: Konstantinos Gerasimidis, Human Nutrition, School of Medicine, College of Medicine, Veterinary & Life Sciences, University of Glasgow, Glasgow G3 8SJ, UK. Tel: +44 (0) 141 2016969 | Fax: +44 (0) 141 2019275 | Email: [email protected]
Malnutrition screening tools need to be applied properly before they can be compared – Response to Letter to Editors by Gerasimidis et al. Sir, We write in reply to the letter authored by Gerasimidis et al. (1). We thank the authors for their letter regarding our manuscript published in Acta Paediatrica (2). We agree that nutrition risk screening tools should be applied correctly. We have carefully reviewed the original data for the patients included in this report. The manuscript reported that three children with moderate/severe malnutrition were not identified to be at nutritional risk according to the
ª2013 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd 2014 103, pp. e93–e94
Readers’ Forum
PYMS NRS tool. Two of these children had Height for age (HFA) measurements greater than 2 standard deviations below the mean, whilst their body mass index (BMI) z scores were 0.23 and 0.71. Consequently, although these two children were malnourished according to the WHO criteria, they were not identified to be at nutritional risk by PYMS (which classifies this risk on BMI z score rather than HFA z score). Unfortunately, however, we have realised that the third child with moderate/severe malnutrition was classified incorrectly. As this child had a BMI z score of 2.66, she should be classified as high risk by PYMS. We apologise for this error and wish to submit a corrected Supplementary Figure 3c. Figure 2c is unaffected by this error. In addition, we have reviewed the consequent analyses relating to this error. The re-classification of this child means that four consequent statements also require correction, as follows: 1 On page e419 (line 3, Results section, Abstract): This text should read NRS tools were able to identify between 87.5% and 100% of the malnourished patients…. 2 Page e421: In the first paragraph of the section entitled Outcomes of NRS tools,
Readers’ Forum
the text should read …classified by the PYMS tool, 62% of the group was low risk, 13% medium and 25% high risk. 3 Page e421: In the paragraph entitled The relationship between NRS tools and anthropometry, the fifth line should read PYMS (14/16). 4 Page e422: In the Discussion, the text should read: In contrast, PYMS classified the fewest children in this way: two undernourished children were not detected. We have taken the opportunity to reanalyse all the data in this work and are certain that there are no other errors. In regards the second issue raised by Gerasimidis et al. (1), in the Discussion section of this report, it was stated that STRONGkids detected all children with moderate/severe malnutrition in its medium and high risk groups. We did not state that all these children were all in the high risk group for this NRS tool. We thank the authors for the opportunity to correct this error and to clarify aspects of our work.
they can be compared. Acta Paediatr, In press; doi: 10.1111/apa.12506 2. Moeeni V, Walls T, Day AS. Nutritional status and nutrition risk screening in hospitalized children in New Zealand. Acta Paediatr 2013; 102: e419–23.
SUPPORTING INFORMATION Additional Supporting Information may be found in the online version of this article: Figure S3c Relationship between the 3 NRS tools and BMI z-scores. DOI:10.1111/apa.12522
Andrew S Day ([email protected]), Vesal Moeeni, Tony Walls Department of Paediatrics, University of Otago, Christchurch, New Zealand Correspondence: A Day, MB, ChB, MD, FRACP, Department of Paediatrics, University of Otago, Christchurch, P.O. Box 4345, Christchurch, New Zealand. Tel: +64 3 3640747 | Fax: +64 3 3640919 | Email: [email protected]
References 1. Gerasimidis K, Maclean A, Wright C. Malnutrition screening tools need to be applied properly before
ª2013 Foundation Acta Pædiatrica. Published by John Wiley & Sons Ltd 2014 103, pp. e93–e95
e95
