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Height status matters for risk of mortality in critically ill children

Journal of Intensive Care volume 12, Article number: 42 (2024) Cite this article

Abstract

Background

Anthropometric measurements are crucial in pediatric critical care, but the impact of height on ICU outcomes is underexplored despite a substantial number of short-for-age children in ICUs. Previous studies suggest that short stature increases the risk of poor clinical outcomes. This study examines the relationship between short stature and ICU outcomes.

Methods

We conducted a retrospective cohort study using a Japanese nationwide database (the Japanese Intensive Care Patient Database; JIPAD), which included pediatric patients under 16 years admitted to ICUs from April 2015 to March 2020. Height standard deviation scores (SD scores) were calculated based on age and sex. Short-stature patients were defined as height SD score <  − 2. The primary outcome was all-cause ICU mortality, and the secondary outcome was the length of stay in ICU.

Results

Out of 6,377 pediatric patients, 27.2% were classified as having short stature. The ICU mortality rate was significantly higher in the short-stature group compared to the normal-height group (3.6% vs. 1.4%, p < 0.01). Multivariable logistic regression showed that short stature was independently associated with increased ICU mortality (OR = 2.73, 95% CI 1.81–4.11). Additionally, the Fine–Gray subdistribution hazards model indicated that short stature was associated with a lower chance of ICU discharge for each additional day (HR 0.85, 95% CI 0.81–0.90, p < 0.01).

Conclusions

Short stature is a significant risk factor for increased ICU mortality and prolonged ICU stay in critically ill children. Height should be considered in risk assessments and management strategies in pediatric intensive care to improve outcomes.

Introduction

Anthropometry on admission to the intensive care unit (ICU) is commonly used in evaluating children’s nutritional status and identifying those at risk of suboptimal clinical outcomes. Low height status, or short stature, is an important indicator reflecting chronic malnutrition in children [1, 2]. Notably, previous studies reported a significant prevalence of short stature ranging from 16 to 50% in children requiring intensive care [3,4,5,6,7,8,9]. Moreover, impaired height growth is a classical but important risk factor for mortality [10]. Additionally, previous studies reported that pediatric short stature was associated with various clinical outcomes including treatment failure of pneumonia [11], prolonged duration of mechanical ventilation [4, 5], and extended length of ICU stay [6] or hospital stay [7]. These findings suggest that height status impacts the prognosis of ICU children and is a sensitive predictor of clinical outcomes, particularly where short stature is prevalent. However, these previous studies were conducted on non-Japanese pediatric populations, who are generally taller and heavier than Japanese children [12]. Moreover, knowledge regarding the relationship between short stature and clinical outcomes in the overall pediatric ICU population remains limited. These observations prompted us to investigate the association between short stature and pediatric ICU outcomes, including mortality and the length of ICU stay, using the Japanese nationwide database.

Methods

Study design and cohort

We performed a retrospective cohort study using the same data as our previously published study [9] derived from the Japanese Intensive Care Patient Database (JIPAD). JIPAD is the largest national ICU registry in Japan [13]. We obtained the 5-year data of pediatric patients aged less than 16 years who were admitted to ICU from April 2015 to March 2020. The data obtained from JIPAD included patient demographics (sex and age), anthropometric measurements (bodyweight and height), clinical variables (admission category, elective/emergency admission status, reason for ICU admission, readmission during the same hospitalization, and Pediatric Index of Mortality 2 [PIM2] scores) [14], and outcomes (ICU mortality and length of stay [LOS] in ICU). For the entire dataset, we obtained age- and sex-adjusted SD scores for height (HT-SDS) and body mass index (BMI-SDS), which were calculated using the Excel-based Clinical Tool for Growth Evaluation of Children provided by the Japanese Society for Pediatric Endocrinology (JSPE: A general version can be downloaded at http://jspe.umin.jp/medical/chart_dl.html, Accessed on April 2021. A special form for big data analysis was provided courtesy of Dr. Yoshiya Ito on behalf of JSPE). Each SD score demanded age-in-month to be calculated. However, the JIPAD provides age-in-year for subjects aged more than 3 years. Thus, for subjects aged 3 years or older, we computed SD scores employing a surrogate age-in-month of “12 × (age) + 6” as previously described [9]. Subjects were excluded if they had missing or improbable anthropometric data, or anthropometric outliers defined as BMI-SDS <  − 5 or > 5 [15], or if their admission category was recorded as “operative procedures in the ICU”, or if they were readmission cases within the same hospitalization.

Definition of anthropometric categories

Subjects were firstly classified into two height categories according to height status (short stature and normal height). Short stature was defined as height SD score (HT-SDS) <  − 2 [16, 17]. Subjects were also classified according to BMI categories. There are 4 BMI categories based on BMI-SDS: BMI-SDS <  − 2 to define underweight, − 2 ≦ BMI-SDS < 1 to define normal weight, 1 ≦ BMI-SDS < 2 to define overweight, and BMI-SDS ≧ 2 to define obesity [18, 19].

Outcomes

The primary outcome of this study was all-cause ICU mortality. The secondary outcome was the LOS in ICU.

Statistical analysis

All statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria) [20]. The description of the study population such as demographic, anthropometric, clinical, and outcome variables is presented as a frequency or the median with the interquartile range (IQR), as appropriate, with bivariate associations with height status category tested by using chi-square analysis or Wilcoxon rank test, respectively. Continuous variables that were normally distributed such as HT-SDS and BMI-SDS are documented as means (± standard deviations). Expected numbers of mortality were also calculated using PIM2 [21].

We performed multivariable logistic regression analysis to determine the association of height categories with all-cause ICU mortality controlling potential confounders. The potential confounders considered for inclusion in the model were age, sex, admission categories (status post-elective surgery, status post-emergency surgery, non-surgical), emergency admission, reasons for ICU admission (cardiovascular disease, respiratory disease, gastrointestinal disease, neurological disease, sepsis, cardiopulmonary arrest, and others), BMI status, and PIM2 scores. We next performed Gray’s test to describe LOS in ICU between the normal-height group and the short-stature group. Additionally, we performed the Fine–Gray subdistribution hazards model for multi-factor analysis using the same covariates shown above to determine the association of short stature with LOS in ICU while accounting for the competing events of death. These analyses were restricted to the cases with complete datasets.

Ethics

This study was reviewed and approved by the Tokyo Medical and Dental University Review Board (M2020-245) and the JIPAD steering committee. The need for informed consent was waived considering the retrospective design and complete anonymization. The anonymized data were provided for analysis by the JIPAD. The study was performed following the relevant guidelines and regulations.

Results

Patient characteristics

There were 7,433 consecutive patient records identified in the JIPAD between the inclusive study dates, and 6,377 had complete data for anthropometric data and met the study inclusion criteria (Fig. 1). Short-stature subjects account for as much as 27.2% of the cohort.

Fig. 1
figure 1

Cohort creation flowchart

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The demographic characteristics are described in Table 1. Although most between-height category differences were statistically significant due to the large sample size, some of these differences may not be clinically relevant. However, the median PIM2 score was higher in the overall short-stature group than the normal-height group (median: 1.2 [0.4–2.6] vs. 0.8 [0.2–1.9], p < 0.01). The estimated mortality calculated by PIM2 was 69.9 (4.0%) in the short-stature group and 144.4 (3.1%) in the normal height group (p = 0.08).

Table 1 Demographic and clinical characteristics in children admitted to intensive care unit
Full size table

Primary outcome: all-cause ICU mortality

A total of 129 (2.0%) subjects in the overall cohort died in the ICU. All-cause ICU mortality was higher in the short-stature group compared with the normal-height group (3.6% vs. 1.4%, respectively, p < 0.01; Table 1).

To determine whether height status independently contributes to ICU mortality and to exclude potential confounders, we conducted a multivariable logistic regression analysis. In cases where anthropometric data were fully available, all adjustment variables were complete; however, mortality data were missing for three cases. Consequently, the subsequent analyses were performed using complete datasets comprising 6,374 subjects. The multivariable analysis revealed a statistically significant increase in ICU mortality for the short-stature group compared to the normal height reference group (OR = 2.73, 95%CI 1.81–4.11; Table 2). As a side note, we considered the possibility of a statistical interaction between BMI categories and height categories, but it was computed to be not significant.

Table 2 Variables associated with mortality in children admitted to intensive care unit
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Secondary outcome: LOS in ICU

The median ICU LOS was 3 days (IQR; 2–6 days). The distribution of ICU LOS between the short-stature group and the normal-height group was statistically different (3.0 [IQR: 2.0–7.0] days vs. 3.0 [2.0–6.0] days, respectively, p < 0.01). The cumulative incidence for ICU LOS (up to 28 days) in each height category is depicted in Fig. 2 (p < 0.01). The Fine–Gray subdistribution hazard model demonstrated the significant association of height status with ICU LOS in this cohort (Table 3). For each additional day in the ICU, short-stature subjects had a 15% (hazard ratio [HR], 0.85; 95% CI 0.81–0.90; p < 0.01) lower chance of being discharged than normal-height subjects, after controlling for age, sex, admission categories, emergency admission, reasons for ICU admission, BMI categories, and PIM2 scores.

Fig. 2
figure 2

The cumulative incidence for length of stay in ICU (up to 28 days) in each height category

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Table 3 The Fine-Gray subdistribution hazard model of variables associated with length of stay in intensive care unit among pediatric patients, n = 6,374
Full size table

For thoroughness, we repeated the two analyses including the three cases with missing mortality data by treating them as deceased as a sensitivity analysis (n = 6,377). There were no changes in the variables with statistical significance and in the direction of the estimates for each variable.

Discussion

In this study, we examined the association between short stature and ICU outcomes including mortality and ICU LOS. We confirmed a high prevalence of short stature, as high as over one-quarter of children requiring intensive care. Our study found that being short, significantly increases the risk for ICU mortality of children requiring intensive care, even after adjustment for possible confounders within the scope of the available database. In addition, we showed that short-stature subjects had a lower chance of being discharged than normal-height subjects for each additional day in the ICU. Our study highlighted the importance of assessing height as an additional critical factor in evaluating the risk associated with pediatric patients in the ICU.

There are limited studies specifically addressing the prevalence and impact of short stature in ICU settings. A secondary analysis of pediatric oncology patients admitted to an ICU in China (n = 160) showed that 16.3% had short stature, correlating with a longer duration of mechanical ventilation [5]. A retrospective cohort study in a Brazilian pediatric ICU (n = 1,753) found that 23.6% had short stature [3]. A retrospective, single-center cohort study of children undergoing cardiac surgery in Singapore (n = 302) reported 26.8% had short stature, which was associated with longer hospital stays, mechanical ventilation, and increased inotrope use post-surgery [7]. A prospective, single-center cohort study of children undergoing cardiac surgery in the United Kingdom (n = 117) found that 28.5% of infants (≤ 12 months) and 20.6% of older children (1–16 years) had short stature, which was linked to a longer ICU LOS [6]. Another prospective cohort study in a Brazilian pediatric ICU (n = 72) found that 41.2% had short stature, also linked to a longer duration of mechanical ventilation [4]. In a tertiary ICU in Brazil, primarily attending to pediatric patients with chronic diseases (n = 90), 50% were reported to have short stature [8]. These findings collectively suggest that short stature prevalence varies with patient backgrounds, but remains significant and associated with unfavorable clinical outcomes in pediatric ICU admissions. Our study, utilizing a national ICU database with over 6,300 subjects, strongly reinforces the associations between short stature and poor clinical outcomes—especially mortality and ICU LOS—observed in previous smaller-scale single-center studies, which reaffirms the importance of height status assessment in pediatric intensive care.

Multiple studies have predominantly focused so far on the association between pediatric ICU outcomes and weight status as an indicator of nutritional status [19, 22,23,24,25,26,27,28,29,30,31,32,33,34,35,36]. Especially, BMI, calculated as weight (kg) divided by height squared (m2), has been shown as a valuable prognostic indicator for children in ICUs, aiding in the prediction of clinical outcomes such as mortality [27,28,29,30,31,32,33], the duration of mechanical ventilation [22, 27], and the length of ICU stay [27, 28, 34, 36]. However, the relationship between BMI status and clinical outcomes is inconsistent in other studies [3, 19, 36]. For instance, a systematic review by Toh et al. [19] found no significant association between BMI status and outcomes in critically ill children, including mortality, ICU LOS, hospital LOS, or duration of mechanical ventilation. Recently, we published a study that illustrated the distribution of height, weight and BMI among children admitted to ICUs in Japan using the same dataset as in this study [9]. The study demonstrated that the BMI-for-age distribution maintained a normal bell-shaped pattern while the distributions of height-for-age and weight-for age skewed towards the lower end. This indicates that the pediatric ICU population generally maintains a balanced physique but tends to be small for age. Lara-Pompa et al. [37] described similar anthropometric characteristics in children requiring hospital care, with poor agreement between BMI and height in nutritional status assessment. These discrepancies arise from the fact that BMI cannot distinguish between children with short stature and those of normal height. This means that among children with the same BMI, some could be short, while others might be of normal height [26]. Accordingly, in the population of children requiring intensive care with a high prevalence of short stature, height status may more accurately reflect the under-nutritional status. Indeed, in our analysis, height status in children was associated with ICU mortality, whereas BMI status was not. This supports the superiority of height status, compared to BMI, in identifying patients at risk of suboptimal clinical outcomes.

On the other hand, the etiology of short stature is not limited to undernutrition. It is highly multifaceted, ranging from physiological normal variants such as familial short stature to pathological causes like genetic/chromosomal, neonatal, skeletal, or hormonal diseases [16, 17, 38]. The effect of medications, such as steroids, may also be an important factor [38]. These various factors are intricately intertwined, and it cannot be denied that they may deeply influence the relationship between short stature and ICU outcomes. In particular, in the pediatric population requiring intensive care, the impact of malnutrition caused by metabolic stress response in conjunction with preexisting chronic diseases must be considered [2]. Children with complex chronic conditions (CCC) are those who suffer from one or more significant health issues that are expected to last at least 12 months, potentially resulting in functional limitations, dependency on medical technology, and frequent healthcare needs [39]. CCCs encompass a wide range of diagnoses, including chromosomal anomalies, complex congenital heart diseases, neurologic diseases, genetic disorders, and chronic respiratory diseases. The number of children with CCC is increasing, representing a growing proportion of patients in the ICU [40, 41]. Indeed, Edwards et al. [42] demonstrated that as many as 53% of PICU admissions involved CCC, and these children were at greater risk for ICU mortality and prolonged ICU LOS in a multicenter study in the United States involving 52,791 critically ill children. Furthermore, children with CCC have a higher prevalence of short stature. Rupp Hanzen Andrades et al. [3] reported that 32.2% of ICU children with CCC had short stature, which is higher than the 15.0% observed in those without CCC. Accordingly, the poor ICU outcomes associated with short stature may be closely related to CCC. At the same time, these facts underscore the importance of acknowledging the numerous unmeasured and potentially significant confounding factors that may explain the observed relationship between short stature and poor ICU outcomes, which were not accounted for in our study.

The PIM2 has been shown to have excellent discriminatory power and good calibration in Japanese children requiring intensive care, although it tended to overestimate the number of deaths [43, 44]. From this perspective, it seems reasonable that the estimated mortality calculated by PIM2 was higher than the observed mortality in the normal-height group. Conversely, in the short-stature group, the number of deaths was similar to the estimated mortality, which was expected to be an overestimate, leading to worse outcomes compared to the normal-height group. This relationship between PIM2 and observed mortality suggests a higher mortality risk in the short-stature group, underscoring the need for further investigation into the underlying causes.

The key strength of our study is the large size of cohort from the national ICU database. The dataset allowed us to conduct in-depth analyses, examining connections between short stature and short-term outcomes. This large dataset enabled us to eliminate potential confounding factors as much as possible and to minimize statistical bias. In addition, we calculated SDS of height and BMI based on Japanese local growth charts [45], which contributed to providing a more accurate anthropometric assessment of the studied populations. However, limitations still remain. First, there is a concern about unmeasured confounders regarding the etiology of short stature, such as familial socioeconomic status, chromosomal abnormality, birth history including birth weight/height and gestational age, and exposures from earlier stages of life. Additionally, in our analysis, we included the reason for ICU admission as one of the confounding factors, but underlying conditions, including CCCs, were not measured and could not be evaluated. Moreover, we were unable to evaluate how individual interventional factors affected the study outcomes. Furthermore, there may be variations among hospitals in the care provided to short-stature children. The second limitation is the accuracy of height measurement, as seen in previous studies [9, 33, 36]. In our study, height measurement methods were not standardized, although obtaining precise and standardized height measurements may pose challenges in critically ill children [46]. Third, our findings might not be generalizable to ICU patients outside Japan. It is recognized that there are noteworthy variations among countries in the definition of intensive care, patient demographics, admission and discharge practices, severity of illness, mortality rates, and LOS [47]. Specifically, it is worth noting that the proportion of obesity, which has been pointed out to influence ICU outcomes, is significantly lower in our study population compared to data from other countries [28,29,30, 33, 34].

Conclusions

In conclusion, short stature is associated with pediatric ICU mortality and prolonged LOS in the ICU. Including height status in the risk assessment using anthropometry for ICU children is crucial for a more comprehensive evaluation.

Availability of data and materials

The data that support the findings of this study are available from JIPAD, but restrictions apply to the availability of these data, which were used under permission for the current study, and are thus not publicly available. However, data are available from the authors upon reasonable request and with permission of the steering committee of JIPAD.

Abbreviations

BMI:

Body mass index

BMI-SDS:

BMI standard deviation score

CCC:

Complex chronic condition

CI:

Confidence interval

HT-SDS:

Height standard deviation score

HR:

Hazard ratio

ICU:

Intensive care unit

IQR:

Interquartile range

JIPAD:

The Japanese Intensive Care Patient Database

LOS:

Length of stay

OR:

Odds ratio

PIM2:

Pediatric Index of Mortality 2

PRISM:

The pediatric risk of mortality

SD(S):

Standard deviation (scores)

References

  1. Alderman H, Shekar M. Nutrition, food security, and health. In: Kliegman R, Stanton B, St Geme J, Schor N, Behrman R, editors. Nelson textbook of pediatrics. 19th ed. Philadelphia: Saunders; 2011. p. 170–8.

    Chapter  Google Scholar 

  2. Mehta NM, Corkins MR, Lyman B, Malone A, Goday PS, Carney LN, et al. Defining pediatric malnutrition: a paradigm shift toward etiology-related definitions. JPEN J Parenter Enteral Nutr. 2013;37(4):460–81.

    Article  PubMed  Google Scholar 

  3. Rupp Hanzen Andrades G, Abud Drumond Costa C, Crestani F, Tedesco Tonial C, Fiori H, Santos IS, et al. Association of nutritional status with clinical outcomes of critically ill pediatric patients with complex chronic conditions. Clin Nutr. 2022;41(12):2786–91.

    Article  PubMed  CAS  Google Scholar 

  4. Grippa RB, Silva PS, Barbosa E, Bresolin NL, Mehta NM, Moreno YM. Nutritional status as a predictor of duration of mechanical ventilation in critically ill children. Nutrition. 2017;33:91–5.

    Article  PubMed  Google Scholar 

  5. Feng S, Cheng L, Lu H, Shen N. Nutritional status and clinical outcomes in children with cancer on admission to intensive care units. Nutr Cancer. 2021;73(1):83–8.

    Article  PubMed  Google Scholar 

  6. Marino LV, Meyer R, Johnson M, Newell C, Johnstone C, Magee A, et al. Bioimpedance spectroscopy measurements of phase angle and height for age are predictive of outcome in children following surgery for congenital heart disease. Clin Nutr. 2018;37(4):1430–6.

    Article  PubMed  CAS  Google Scholar 

  7. Lim CYS, Lim JKB, Moorakonda RB, Ong C, Mok YH, Allen JC, et al. The impact of pre-operative nutritional status on outcomes following congenital heart surgery. Front Pediatr. 2019;7:429.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Zamberlan P, Delgado AF, Leone C, Feferbaum R, Okay TS. Nutrition therapy in a pediatric intensive care unit: indications, monitoring, and complications. JPEN J Parenter Enteral Nutr. 2011;35(4):523–9.

    Article  PubMed  Google Scholar 

  9. Nosaka N, Anzai T, Uchimido R, Mishima Y, Takahashi K, Wakabayashi K. An anthropometric evidence against the use of age-based estimation of bodyweight in pediatric patients admitted to intensive care units. Sci Rep. 2023;13(1):3574.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. de Onis M, Branca F. Childhood stunting: a global perspective. Matern Child Nutr. 2016;12:12–26.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Moschovis PP, Addo-Yobo EO, Banajeh S, Chisaka N, Christiani DC, Hayden D, et al. Stunting is associated with poor outcomes in childhood pneumonia. Trop Med Int Health. 2015;20(10):1320–8.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kato N, Takimoto H, Yokoyama T, Yokoya S, Tanaka T, Tada H. Updated Japanese growth references for infants and preschool children, based on historical, ethnic and environmental characteristics. Acta Paediatr. 2014;103(6):e251–61.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Irie H, Okamoto H, Uchino S, Endo H, Uchida M, Kawasaki T, et al. The Japanese Intensive care PAtient Database (JIPAD): a national intensive care unit registry in Japan. J Crit Care. 2020;55:86–94.

    Article  PubMed  Google Scholar 

  14. Slater A, Shann F, Pearson G. Paediatric index of mortality study G. PIM2: a revised version of the paediatric index of mortality. Intensive Care Med. 2003;29(2):278–85.

    Article  PubMed  Google Scholar 

  15. Lowe C, Kelly M, Sarma H, Richardson A, Kurscheid JM, Laksono B, et al. The double burden of malnutrition and dietary patterns in rural Central Java, Indonesia. Lancet Reg Health West Pac. 2021;14:100205.

    PubMed  PubMed Central  Google Scholar 

  16. Cheetham T, Davies JH. Investigation and management of short stature. Arch Dis Child. 2014;99(8):767–71.

    Article  PubMed  Google Scholar 

  17. Patel R, Bajpai A. Evaluation of short stature in children and adolescents. Indian J Pediatr. 2021;88(12):1196–202.

    Article  PubMed  Google Scholar 

  18. de Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Development of a WHO growth reference for school-aged children and adolescents. Bull World Health Organ. 2007;85(9):660–7.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Toh S, Ong C, Sultana R, Kirk AHP, Koh JC, Lee JH. Association between admission body mass index and outcomes in critically ill children: a systematic review and meta-analysis. Clin Nutr. 2021;40(5):2772–83.

    Article  PubMed  Google Scholar 

  20. Kanda Y. Investigation of the freely available easy-to-use software “EZR” for medical statistics. Bone Marrow Transplant. 2013;48(3):452–8.

    Article  PubMed  CAS  Google Scholar 

  21. Fonseca JG, Ferreira AR. Application of the pediatric index of mortality 2 in pediatric patients with complex chronic conditions. J Pediatr (Rio J). 2014;90(5):506–11.

    Article  PubMed  Google Scholar 

  22. Alipoor E, Hosseinzadeh-Attar MJ, Yaseri M, Maghsoudi-Nasab S, Jazayeri S. Association of obesity with morbidity and mortality in critically ill children: a systematic review and meta-analysis of observational studies. Int J Obes (Lond). 2019;43(4):641–51.

    Article  PubMed  Google Scholar 

  23. Numa A, McAweeney J, Williams G, Awad J, Ravindranathan H. Extremes of weight centile are associated with increased risk of mortality in pediatric intensive care. Crit Care. 2011;15(2):R106.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Prince NJ, Brown KL, Mebrahtu TF, Parslow RC, Peters MJ. Weight-for-age distribution and case-mix adjusted outcomes of 14,307 paediatric intensive care admissions. Intensive Care Med. 2014;40(8):1132–9.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ayalon I, Woo JG, Basu RK, Kaddourah A, Goldstein SL, Kaplan JM, et al. Weight as a risk factor for mortality in critically ill patients. Pediatrics. 2020;146(2):e20192829.

    Article  PubMed  Google Scholar 

  26. Leite HP, de Lima LF, de Oliveira Iglesias SB, Pacheco JC, de Carvalho WB. Malnutrition may worsen the prognosis of critically ill children with hyperglycemia and hypoglycemia. JPEN J Parenter Enteral Nutr. 2013;37(3):335–41.

    Article  PubMed  Google Scholar 

  27. Bagri NK, Jose B, Shah SK, Bhutia TD, Kabra SK, Lodha R. Impact of malnutrition on the outcome of critically ill children. Indian J Pediatr. 2015;82(7):601–5.

    Article  PubMed  Google Scholar 

  28. Irving SY, Daly B, Verger J, Typpo KV, Brown AM, Hanlon A, et al. The association of nutrition status expressed as body mass index z score with outcomes in children with severe sepsis: a secondary analysis from the sepsis prevalence, outcomes, and therapies (SPROUT) study. Crit Care Med. 2018;46(11):e1029–39.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bechard LJ, Duggan C, Touger-Decker R, Parrott JS, Rothpletz-Puglia P, Byham-Gray L, et al. Nutritional status based on body mass index is associated with morbidity and mortality in mechanically ventilated critically ill children in the PICU. Crit Care Med. 2016;44(8):1530–7.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ross E, Burris A, Murphy JT. Obesity and outcomes following burns in the pediatric population. J Pediatr Surg. 2014;49(3):469–73.

    Article  PubMed  Google Scholar 

  31. Anton-Martin P, Papacostas M, Lee E, Nakonezny PA, Green ML. Underweight status is an independent predictor of in-hospital mortality in pediatric patients on extracorporeal membrane oxygenation. JPEN J Parenter Enteral Nutr. 2018;42(1):104–11.

    Article  PubMed  CAS  Google Scholar 

  32. Ventura JC, Hauschild DB, Barbosa E, Bresolin NL, Kawai K, Mehta NM, et al. Undernutrition at PICU admission is predictor of 60-day mortality and PICU length of stay in critically ill children. J Acad Nutr Diet. 2020;120(2):219–29.

    Article  PubMed  Google Scholar 

  33. Ross PA, Newth CJ, Leung D, Wetzel RC, Khemani RG. Obesity and mortality risk in critically ill children. Pediatrics. 2016;137(3):e20152035.

    Article  PubMed  Google Scholar 

  34. Ross PA, Klein MJ, Nguyen T, Leung D, Khemani RG, Newth CJL, et al. Body habitus and risk of mortality in pediatric sepsis and septic shock: a retrospective cohort study. J Pediatr. 2019;210(178–83):e2.

    Google Scholar 

  35. Valla FV, Berthiller J, Gaillard-Le-Roux B, Ford-Chessel C, Ginhoux T, Rooze S, et al. Faltering growth in the critically ill child: prevalence, risk factors, and impaired outcome. Eur J Pediatr. 2018;177(3):345–53.

    Article  PubMed  Google Scholar 

  36. Sharma K, Raszynski A, Totapally BR. The impact of body mass index on resource utilization and outcomes of children admitted to a pediatric intensive care unit. SAGE Open Med. 2019;7:2050312119825509.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Lara-Pompa NE, Hill S, Williams J, Macdonald S, Fawbert K, Valente J, et al. Use of standardized body composition measurements and malnutrition screening tools to detect malnutrition risk and predict clinical outcomes in children with chronic conditions. Am J Clin Nutr. 2020;112(6):1456–67.

    Article  PubMed  Google Scholar 

  38. Rogol AD, Hayden GF. Etiologies and early diagnosis of short stature and growth failure in children and adolescents. J Pediatr. 2014;164:S1-14.

    Article  PubMed  Google Scholar 

  39. Lindley LC, Cozad MJ, Fortney CA. Pediatric complex chronic conditions: evaluating two versions of the classification system. West J Nurs Res. 2020;42(6):454–61.

    Article  PubMed  Google Scholar 

  40. Burns KH, Casey PH, Lyle RE, Bird TM, Fussell JJ, Robbins JM. Increasing prevalence of medically complex children in US hospitals. Pediatrics. 2010;126(4):638–46.

    Article  PubMed  Google Scholar 

  41. Bjur KA, Wi CI, Ryu E, Crow SS, King KS, Juhn YJ. Epidemiology of children with multiple complex chronic conditions in a mixed urban-rural US community. Hosp Pediatr. 2019;9(4):281–90.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Edwards JD, Houtrow AJ, Vasilevskis EE, Rehm RS, Markovitz BP, Graham RJ, et al. Chronic conditions among children admitted to US pediatric intensive care units: their prevalence and impact on risk for mortality and prolonged length of stay*. Crit Care Med. 2012;40(7):2196–203.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Imamura T, Nakagawa S, Goldman RD, Fujiwara T. Validation of pediatric index of mortality 2 (PIM2) in a single pediatric intensive care unit in Japan. Intensive Care Med. 2012;38(4):649–54.

    Article  PubMed  Google Scholar 

  44. JIPAD Annual Report 2022. Tokyo: JIPAD Working Group, The Japanese Society of Intensive Care Medicine; 2024.

  45. Isojima T, Kato N, Ito Y, Kanzaki S, Murata M. Growth standard charts for Japanese children with mean and standard deviation (SD) values based on the year 2000 national survey. Clin Pediatr Endocrinol. 2016;25(2):71–6.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Srinivasan V, Seiple S, Nagle M, Falk S, Kubis S, Lee HM, et al. improving the performance of anthropometry measurements in the pediatric intensive care unit. Pediatr Qual Saf. 2017;2(3):e022.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Wunsch H, Angus DC, Harrison DA, Collange O, Fowler R, Hoste EA, et al. Variation in critical care services across North America and Western Europe. Crit Care Med. 2008;36(10):2787–93.

    Article  PubMed  Google Scholar 

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Acknowledgements

None.

Funding

This study had no funding support.

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Authors and Affiliations

  1. Department of Intensive Care Medicine, Graduate School of Medical and Dental Sciences, Institute of Science Tokyo, 1-5-45 Yushima, Bunkyo-Ku, Tokyo, 113-8510, Japan

    Nobuyuki Nosaka & Kenji Wakabayashi

  2. Department of Biostatistics, M&D Data Science Center, Institute of Integrated Research, Institute of Science Tokyo, Tokyo, Japan

    Tatsuhiko Anzai

Authors
  1. Nobuyuki Nosaka
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  2. Tatsuhiko Anzai
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  3. Kenji Wakabayashi
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Contributions

Study design (NN, TA, KW), data analysis (NN, TA), manuscript preparation (NN, TA, KW). All authors gave final approval for the submitted manuscript and agree to be accountable for all aspects of the work.

Corresponding author

Correspondence to Nobuyuki Nosaka.

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Ethics approval and consent to participate

This study was reviewed and approved by the Tokyo Medical and Dental University Review Board (M2020-245) and the JIPAD steering committee.

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The authors declare that they have no competing interests.

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Nosaka, N., Anzai, T. & Wakabayashi, K. Height status matters for risk of mortality in critically ill children. j intensive care 12, 42 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40560-024-00757-9

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s40560-024-00757-9

Keywords

Journal of Intensive Care

ISSN: 2052-0492