Growth patterns in children with spinal muscular atrophy.

BACKGROUND: Spinal muscular atrophy (SMA) is a neuromuscular disorder characterized by muscle atrophy and weakness. SMA type 1 (SMA1) is the most severe form: affected infants are unable to sit unaided; SMA type 2 (SMA2) children can sit, but are not able to walk independently. The Standards of Care has improved quality of life and the increasing availability of disease-modifying treatments is progressively changing the natural history; so, the clinical assessment of nutritional status has become even more crucial. Aims of this multicenter study were to present the growth pattern of treatment-naïve SMA1 and SMA2, and to compare it with the general growth standards. RESULTS: Body Weight (BW, kg) and Supine Length (SL, cm) were collected using a published standardized procedure. SMA-specific growth percentiles curves were developed and compared to the WHO reference data. We recruited 133 SMA1 and 82 SMA2 (48.8% females). Mean ages were 0.6 (0.4-1.6) and 4.1 (2.1-6.7) years, respectively. We present here a set of disease-specific percentiles curves of BW, SL, and BMI-for-age for girls and boys with SMA1 and SMA2. These curves show that BW is significantly lower in SMA than healthy peers, while SL is more variable. BMI is also typically lower in both sexes and at all ages. CONCLUSIONS: These data on treatment-naïve patients point toward a better understanding of growth in SMA and could be useful to improve the clinical management and to assess the efficacy of the available and forthcoming therapies not only on motor function, but also on growth.

The prognostic impact of BIA-derived fat-free mass index in patients with cancer.

BACKGROUND & AIMS: Reduced muscle mass represents one of the top ranked phenotypic criteria for malnutrition proposed by the Global Leadership Initiative on Malnutrition. Although height-indexed fat-free mass (FFMI) thresholds have been proposed as useful surrogate measures of reduced muscle mass, the independent prognostic value of BIA-derived FFMI by bioelectric impedance analysis (BIA) in patients with cancer still needs to be fully explored. METHODS: Data on body mass index (BMI), 6-month percentage of weight loss (%WL), FFMI by BIA and quality of life (QoL by EORTC Quality of Life Questionnaire [EORTC QLQ-C30]) of Italian and German patients observed prospectively until death or censoring were used (N = 1217). Patients were stratified in 5 risk categories according to a robustly validated scoring system based on BMI and %WL. Low FFMI was defined as follows: men, <17 kg/m2; women, <15 kg/m2. RESULTS: Reduced FFMI was found in 234 patients (19.2%). After a median follow-up of 57 months [25th-75th, 31-60], 620 patients (50.9%) had died. The study detected differences in survival between patients presenting with and without reduced FFMI (14.0 months vs. 45.1 months; P < 0.001). The fully-adjusted hazard ratio of mortality for low FFMI was 1.46 [95%CI, 1.18-1.81] (P < 0.001). Low FFMI was also independently associated with reduced QoL: fully-adjusted odds ratio, 1.50 [95%CI, 1.00-2.25] (P = 0.050). CONCLUSIONS: Reduced FFMI by BIA independently predicted survival and was associated with impaired QoL. Altered body composition should always be considered in all patients with cancer as additional phenotypic criterion of poor prognosis and BIA offers the possibility of multiple, noninvasive bedside assessments.

Predictive fat mass equations for spinal muscular atrophy type I children: Development and internal validation.

BACKGROUND: Body composition assessment is paramount for spinal muscular atrophy type I (SMA I) patients, as weight and BMI have proven to be misleading for these patients. Despite its importance, no disease-specific field method is currently available, and the assessment of body composition of SMA I patients requires reference methods available only in specialized settings. OBJECTIVE: To develop predictive fat mass equations for SMA I children based on simple measurements, and compare existing equations to the new disease-specific equations. DESIGN: Demographic, clinical and anthropometric data were examined as potential predictors of the best candidate response variable and non-linear relations were taken into account by transforming continuous predictors with restricted cubic splines. Alternative models were fitted including all the dimensions revealed by cluster analysis of the predictors. The best models were then internally validated, quantifying optimism of the obtained performance measures. The contribution of nusinersen treatment to the unexplained variability of the final models was also tested. RESULTS: A total of 153 SMA I patients were included in the study, as part of a longitudinal observational study in SMA children conducted at the International Center for the Assessment of Nutritional Status (ICANS), University of Milan. The sample equally represented both sexes (56% females) and a wide age range (from 3 months to 12 years, median 1.2 years). Four alternative models performed equally in predicting fat mass fraction (fat mass/body weight). The most convenient was selected and further presented. The selected model uses as predictors sex, age, calf circumference and the sum of triceps, suprailiac and calf skinfold thicknesses. The model showed high predictive ability (optimism corrected coefficient of determination, R2 = 0.72) and internal validation indicated little optimism both in performance measures and model calibration. The addition of nusinersen as a predictor variable did not improve the prediction. The disease-specific equation was more accurate than the available fat mass equations. CONCLUSIONS: The developed prediction model allows the assessment of body composition in SMA I children with simple and widely available measures and with reasonable accuracy.

Predictive energy equations for spinal muscular atrophy type I children.

BACKGROUND: Knowledge on resting energy expenditure (REE) in spinal muscular atrophy type I (SMAI) is still limited. The lack of a population-specific REE equation has led to poor nutritional support and impairment of nutritional status. OBJECTIVE: To identify the best predictors of measured REE (mREE) among simple bedside parameters, to include these predictors in population-specific equations, and to compare such models with the common predictive equations. METHODS: Demographic, clinical, anthropometric, and treatment variables were examined as potential predictors of mREE by indirect calorimetry (IC) in 122 SMAI children consecutively enrolled in an ongoing longitudinal observational study. Parameters predicting REE were identified, and prespecified linear regression models adjusted for nusinersen treatment (discrete: 0 = no; 1 = yes) were used to develop predictive equations, separately in spontaneously breathing and mechanically ventilated patients. RESULTS: In naïve patients, the median (25th, 75th percentile) mREE was 480 (412, 575) compared with 394 (281, 554) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.009).In nusinersen-treated patients, the median (25th, 75th percentile) mREE was 609 (592, 702) compared with 639 (479, 723) kcal/d in spontaneously breathing and mechanically ventilated patients, respectively (P = 0.949).Both in spontaneously breathing and mechanically ventilated patients, the best prediction of REE was obtained from 3 models, all using as predictors: 1 body size related measurement and nusinersen treatment status. Nusinersen treatment was correlated with higher REE both in spontaneously breathing and mechanically ventilated patients. The population-specific equations showed a lower interindividual variability of the bias than the other equation tested, however, they showed a high root mean squared error. CONCLUSIONS: We demonstrated that ventilatory status, nusinersen treatment, demographic, and anthropometric characteristics determine energy requirements in SMAI. Our SMAI-specific equations include variables available in clinical practice and were generally more accurate than previously published equations. At the individual level, however, IC is strongly recommended for assessing energy requirements. Further research is needed to externally validate these predictive equations.

Anthropometric measurement standardization for a multicenter nutrition survey in children with spinal muscular atrophy.

Spinal muscular atrophy (SMA) is a neuromuscular disease associated with nutritional status derangement and altered body composition. New drugs are changing the natural history of the disease, so now more than ever is important to focus on the correct assessment of nutritional status in SMA. We implemented a standardization process for the anthropometric measurement as part of our ongoing longitudinal study of growth patterns in SMA patients. It features a procedural manual, included in this communication, observers training and reliability assessment, of which we publish the values obtained in our pilot study. The standardization process was able to produce inter-observer reliability values in agreement with the literature and a procedure manual is now available for multicentre studies of nutritional status and body composition in SMA and possibly other pediatric neuromuscular disorders.

Paediatric Home Artificial Nutrition in Italy: Report from 2016 Survey on Behalf of Artificial Nutrition Network of Italian Society for Gastroenterology, Hepatology and Nutrition (SIGENP).

Home Artificial Nutrition (HAN) is a safe and efficacious technique that insures children's reintegration into the family, society and school. Epidemiological data on paediatric HAN in Italy are not available. AIM: to detect the prevalence and incidence of Home Parenteral Nutrition (HPN) and Home Enteral Nutrition (HEN), either via tube or mouth, in Italy in 2016. MATERIALS AND METHODS: a specific form was sent to all registered SIGENP members and investigators of local HAN centres, inviting them to provide the requested centre's data and demographics, underlying diseases and HAN characteristics of the patients. RESULTS: we recorded 3403 Italian patients on HAN aged 0 to 19 years from 22 centres: 2277 HEN, 950 Oral Nutritional Supplements (ONS) and 179 HPN programs. The prevalence of HEN (205 pts/million inhabitants) and HPN (16 pts/million inhabitants) has dramatically increased in Italy in the last 9 years. Neurodisabling conditions were the first indication for HEN by tube or mouth while HPN is mainly requested in digestive disorders. CONCLUSIONS: HAN is a widespread and rapidly growing treatment in Italy, as well as in other European countries. Awareness of its extent and characteristics helps improving HAN service and patients' quality of life.

Spinal Muscular Atrophy, types I and II: What are the differences in body composition and resting energy expenditure?

BACKGROUND & AIMS: Different neuromuscular functional domains in types I and II Spinal Muscular Atrophy (SMAI and SMAII) could lead to differences in body composition (BC) and resting energy expenditure (REE). Their identification could provide the key to defining appropriate strategies in clinical dietary management, but data comparing SMAI and SMAII in terms of BC and REE are not yet available. We measured total and regional fat (FM), lean (LBM), mineral (BMC) masses, body water (total, intra- and extra-cellular, TBW, ICW, ECW) and REE in a sample of SMAI and II children, matched for age and sex, and also adjusting for body size to compare these features of the two SMA phenotypes. METHODS: 15 SMAI and 15 SMAII children, (M/F = 9/6 vs 9/6, age 3.6 ± 1.9 vs 3.5 ± 1.8 years, p = 0.99), confirmed genetically, were measured as follows: Anthropometric measurements [Body Weight (BW), Supine Length (SL), Arm Length (AL), Femur Length (FL), Tibia Length (TL)], Dual x-ray Energy Absorptiometry (DEXA) [total and segmental FM, LBM, FFM, and BMC], Bioelectrical impedance (BIA) [TBW, ICW, ECW] and Indirect Calorimetry (REE, respiratory quotients) were collected by the same trained dietician. BW, SL and Body Mass Index (BMI) Z-scores were calculated according to CDC Growth Charts (2000). RESULTS: SMA children had high percentages of FM and a lower percentage of TBW and ECW compared to the respective reference values for sex and age, whereas the BMC percentages did not differ, even splitting the two phenotypes. SMA I children had a lower BW and BMI-Z score compared to children with SMA II, but similar total and segmental FM. On the contrary, total FFM and LBM were significantly lower in SMAI (7290.0 ± 1729.1 g vs 8410.1 ± 1508.4 g; 6971.8 ± 1637.1 g vs 8041.7 ± 1427.7 g, p = 0.039, p = 0.037, respectively), particularly at the trunk level. Arm BMC also resulted significantly lower in SMAI. The measured REE values were similar (684 ± 143 kcal/day vs 703 ± 122 Kcal/day p = 0.707) whereas REE per FFM unit was higher in SMA I children than in SMA II (95 ± 12 kcal/FFMkg vs 84 ± 11 kcal/FFMkg p = 0.017). CONCLUSIONS: This study has shown that BW and BMI Z-score measurements alone can be misleading in assessing nutritional status, particularly in SMAI. The differences between SMAI and II in total and regional BC are related only to FFM, LBM and BMC, and seem to be more linked to the magnitude of neurofunctional impairment rather than to the nutritional status derangement. SMA I and SMA II children can have different energy requirements in relation to their specific BC and hypermetabolism of FFM. Based on these results, our recommendation is to use direct BC and REE measurements in the nutritional care process until SMA-specific predictive equations become available.

[Diet prescription in obese patients]. / La scelta della terapia dietetica nel soggetto obeso.

Diet is a cornerstone in the treatment of obese patients with or without metabolic complications. To optimize outcome, diet treatment should always take into account factors such as the Body Mass Index, the timeframe for reaching the recommended weight loss, comorbidities (e.g. arterial hypertension, diabetes mellitus, renal disease, lipid abnormalities, hyperuricemia) and, finally, individual patient characteristics (e.g. habits, preferences, adherence capacity). Hypocaloric diets need to be adequately balanced in terms of glucides, lipids and proteins, vitamins and minerals. For these reasons the diet prescription for obese patients, particularly those with comorbidities or cardiovascular disease, should be under the guidance of expert nutrition professionals who are aware of the risks of an unbalanced diet.