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Research paper
Early weight loss in amyotrophic lateral sclerosis: outcome relevance and clinical correlates in a population-based cohort
  1. Cristina Moglia1,2,
  2. Andrea Calvo1,2,
  3. Maurizio Grassano1,
  4. Antonio Canosa1,
  5. Umberto Manera1,
  6. Fabrizio D'Ovidio1,
  7. Alessandro Bombaci1,
  8. Enrica Bersano3,
  9. Letizia Mazzini3,
  10. Gabriele Mora4,
  11. Adriano Chiò1,2,5
  12. Piemonte and Valle d’Aosta Register for ALS (PARALS)
    1. 1 ALS Center, ‘Rita Levi Montalcini’ Department of Neuroscience, University of Torino, Turin, Italy
    2. 2 Azienda Ospedaliera Universitaria Città della Salute e della Scienza, Torino, Italy
    3. 3 ALS Center, Department of Neurology, Azienda Ospedaliera Universitaria Maggiore della Carità, Novara, Italy
    4. 4 ALS Center, Istituti Clinici Scientifici Maugeri IRCCS, Milan, Italy
    5. 5 National Research Council (CNR), Institute of Cognitive Sciences and Technologies, Rome, Italy
    1. Correspondence to Adriano Chiò, ALS Center, ‘Rita Levi Montalcini’ Department of Neuroscience, University of Torino, Turin 10126, Italy; achio{at}usa.net

    Abstract

    Objectives To assess the role of body mass index (BMI) and of the rate of weight loss as prognostic factors in amyotrophic lateral sclerosis (ALS) and to explore the clinical correlates of weight loss in the early phases of the disease.

    Methods The study cohort included all ALS patients in Piemonte/Valle d’Aosta in the 2007–2011 period. Overall survival and the probability of death/tracheostomy at 18 months (logistic regression model) were calculated.

    Results Of the 712 patients, 620 (87.1%) were included in the study. Patients ’ survival was related to the mean monthly percentage of weight loss at diagnosis (p<0.0001), but not to pre-morbid BMI or BMI at diagnosis. Spinal onset patients with dysphagia at diagnosis had a median survival similar to bulbar onset patients. About 20% of spinal onset patients without dysphagia at diagnosis had severe weight loss and initial respiratory impairment, and had a median survival time similar to bulbar onset patients.

    Conclusions The rate of weight loss from onset to diagnosis was found to be a strong and independent prognostic factor in ALS. Weight loss was mainly due to the reduction of nutritional intake related to dysphagia, but a subgroup of spinal onset patients without dysphagia at diagnosis had a severe weight loss and an outcome similar to bulbar patients. According to our findings, we recommend that in clinical trials patients should be stratified according to the presence of dysphagia at the time of enrolment and not by site of onset of symptoms.

    • amyotrophic lateral sclerosis
    • body mass index
    • weight loss
    • dysphagia
    • respiratory function
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    Introduction

    Amyotrophic lateral sclerosis (ALS) is the most common motor neuron disorder of adult life, characterised by the loss of motor neurons at the spinal, bulbar and cortical level. Its cause is still unknown, with the exception of genetically determined cases which account for about 10% of published series.1 One recent observation is the phenotypic heterogeneity of the disease, encompassing cases with a predominance of either upper motor or lower motor neuron degeneration, different degrees of bulbar function involvement and levels of cognitive impairment, ranging from normal cognition to frontotemporal dementia.2 Although it is clear that motor and cognitive phenotypes influence ALS prognosis,3 4 their determinants remain largely unknown.5

    In recent years, interest in weight loss, nutritional status and bulbar involvement as prognostic factors in ALS has grown. In a pivotal paper, body mass index (BMI) was reported to be a strong predictor of prognosis.6 Subsequently, several papers have assessed the prognostic relevance of BMI at diagnosis with inconclusive findings.7–17 Conversely, some papers supported the prognostic relevance of the rate of weight loss.7 8 11 15 18–20

    The aim of this study is to assess the relative role of BMI and rate of weight loss as prognostic factors to explore the clinical correlates of early weight loss in ALS.

    Methods

    The study design and the characteristics of the cohort have been reported previously.21 In brief, all patients diagnosed with ALS during the period 1 January 2007 to 31 December 2011 (n=712) were eligible to be enrolled in the study. The patients were identified through the Piemonte and Valle d’Aosta Register for ALS (PARALS). ALS diagnosis was based on the revised El Escorial diagnostic criteria.22 Patients classified as possible ALS at the time of diagnosis were reclassified to a higher El Escorial level during the follow-up. Disease severity was assessed with the ALS Functional Rating Scale Revised (ALSFRS-R). ALSFRS-R decline was calculated as the mean monthly number of points lost from onset to diagnosis:

    [(48-ALSFRS-Rdiagnosis)*100/48]/time from onset to diagnosis (in months)

    Body weight at diagnosis (DBW) was measured on subjects wearing only underwear and without shoes by means of the steelyard scale (precision ±100 g). Body weight before ALS onset (health body weight, HBW) was obtained by asking patients, and their caregivers, about their weight 3 years before the onset of motor symptoms. In all but 16 patients, there was no reported difference between their weight at the time of disease onset and 3 years before the onset of ALS. BMI was calculated at diagnosis as weight/height2 (kg/m2). BMI levels were categorised according to the WHO classification23 (underweight <18.49; normal range 18.50–24.99; pre-obese 25.0–29.99; obese class I 30.0–34.99; obese class II 35.0–39.99; obese class III ≥40) (WHO, 2013). Since only five patients had a pre-morbid weight classified as obese class III (three of them at diagnosis), these were included in the obese class II group.

    To determine the role of the rate of weight loss on survival, we calculated the monthly percentage of weight loss as:

    [(HBW-DBW)*100/HBW]/time from onset to diagnosis (in months)

    For this variable, we classified patients into four groups: those with an increase of weight, those with a steady weight, those with a monthly percentage of weight loss <1% (moderate weight loss), and those with a monthly percentage of weight loss ≥1% (severe weight loss). We chose 1% as the cut-off because it is the median value of weight loss in patients who had a decrease in weight.

    The outcome analyses were performed according to the steps shown in figure 1.

    Figure 1

    Flow chart reporting the steps of the analysis.

    1. First, we assessed the effect of variation of BMI, comparing bulbar onset to spinal onset patients;

    2. Second, we assessed the effect of variation of BMI, splitting spinal onset patients according to the presence or not of dysphagia at the time of diagnosis;

    3. Third, we further subdivided the group of spinal onset patients with non-alleged dysphagia at the time of diagnosis according to their monthly percentage of weight loss (<1% vs ≥1%).

    Statistical methods

    Comparisons between means were made with Student’s t-test or analysis of variance (ANOVA); comparisons between categorical variables were made with χ2 test. All tests were two-tailed. Survival was calculated from onset to death/tracheostomy or censoring date (31 December 2017), using the Kaplan-Meier method, and compared with the log-rank test. No patients were lost to follow-up. Multivariable analysis for survival was performed with the Cox proportional hazards model (stepwise backward) with a retention criterion of p<0.1. A level of p<0.05 was considered significant. Statistical analyses were carried out using the SPSS 24.0 statistical package (SPSS, Chicago, IL, USA). We also calculated the probability of survival/tracheostomy at 18 months after diagnosis according to pre-morbid BMI, BMI at diagnosis, and mean monthly percentage of weight loss (pre-morbid to diagnosis). The logistic curve for the conditional probability of the response was calculated with the function

    Embedded Image

    where P is the probability of the event, e is the base of the natural logarithm, and α and β are the estimated regression coefficients of the logistic model. The model was corrected by age, gender, smoking (current, former, never smoker), site of onset (bulbar, spinal), respiratory function at diagnosis. The predicted probabilities were computed in R v. 3.5.1.

    Standard protocol approvals, registrations, and patient consents

    The study design was approved by the ethical committee of the Azienda Ospedale-Università Città della Salute e della Scienza. Patients signed a written informed consent.

    Anonymised data will be shared by request from any qualified investigator.

    Results

    Of the 712 incident patients, 620 (87.1%) were included in the study. The remaining 92 patients, not included because of incomplete data on pre-morbid BMI, did not differ as regards to any demographic or clinical variable from included patients (data not shown). The patients comprised 342 men and 278 women, with a mean age at onset of 66.2 (SD 10.7) years.

    Compared with the HBW, DBW decreased in 383 patients, was unchanged in 179, and increased in 58. Figure 2 shows the trend of BMI change (HBW vs DBW): the highest probability of transition was from a given BMI to the next lower stage, particularly in bulbar onset patients, but there was a substantial probability (ranging from 0.58 to 0.86) that the patients did not change level. A small percentage of patients (17% of spinal onset patients and 6% of bulbar onset patients) moved from their BMI to their next higher level. Skipping levels was relatively infrequent.

    Figure 2

    Probability of transition between body mass index (BMI) levels, from pre-morbid weight to weight at diagnosis; the frequency of patients who had a stable BMI level is reported in each oval.

    BMI, weight loss and survival

    BMI at diagnosis was not related to prognosis, although overweight patients had a slightly longer survival than all other groups (p=0.62) (table 1). No difference was found for gender. Conversely, pre-morbid BMI groups had a significant differential survival (p=0.02), with a U-shaped (non-linear) curve, the worse prognosis being for those patients with pre-obese BMI (table 1). However, when assessing pre-morbid BMI and BMI at diagnosis with a non-linear equation, both were found to be not significantly correlated with survival after controlling for age, gender, smoking habits, pulmonary function (forced vital capacity, FVC) at diagnosis, and type of onset (data not shown).

    Table 1

    Frequency and median survival of BMI classes according to WHO in the pre-morbid period and at diagnosis

    Patient outcome was significantly related to the mean monthly percentage of weight loss at diagnosis (p<0.0001): those patients with a mean monthly weight loss ≥1% had less than half median survival compared with those with an increase of weight at diagnosis (figure 3). Remarkably, the prognostic effect of the percentage decrease of weight from onset to diagnosis remained significant also after stratification for site of onset (bulbar vs spinal) (data not shown). In figure 4 the conditional probability of survival at 18 months after diagnosis according to pre-morbid BMI (figure 4A), BMI at diagnosis (figure 4B), and mean weight loss (figure 4C) are reported; only the mean monthly percentage of weight loss at diagnosis was strongly predictive of survival at 18 months (p<0.0001).

    Figure 3

    Survival curves according to mean monthly weight loss (blue, weight increase; red, unchanged weight; green, mean monthly weight loss 0.01% to 0.99%; purple, mean monthly weight loss ≥1% (p<0.0001). Ticks indicate censored patients.

    Figure 4

    Predicted probabilities of 18 months survival (logistic regression model); all probabilities are adjusted for age, gender, smoking habits, site of onset and respiratory function at diagnosis. (A) The predicted probability of survival at 18 months is not affected by pre-morbid body mass index (BMI) (p=0.781). (B) The predicted probability of survival at 18 months is not affected by BMI at diagnosis, although there is a non-significant trend toward a higher survival probability with increasing BMI (p=0.054). (C) The rate of weight loss remained a strong predictor of amyotrophic lateral sclerosis outcome even after adjustment (p<0.0001).

    We then stratified spinal onset patients according to the presence or absence of dysphagia at diagnosis. We found that spinal onset patients who had developed swallowing disturbances at time of diagnosis had a mean monthly percentage weight loss (1.26, SD 2.31) intermediate between bulbar onset patients (1.53, SD 3.25) and spinal onset patients without dysphagia at diagnosis (0.60, SD 1.42), but their survival was quite similar to that of bulbar onset patients (figure 5A). We finally assessed the conditional probability of survival at 18 months of the four groups of patients (bulbar onset; spinal onset who had swallowing disturbances at diagnosis; spinal onset without dysphagia at diagnosis with mean monthly weight loss ≥1%; and spinal onset without dysphagia at diagnosis with mean monthly weight loss <1%) corrected by respiratory function at diagnosis. The predicted probability of survival at 18 months was similar in all groups, except the spinal onset without dysphagia at diagnosis with mean monthly weight loss <1%, along all the range of respiratory function at diagnosis (figure 5B).

    Figure 5

    (A) Survival curves according to the different subgroups identified in the text (orange: spinal onset patients without dysphagia at diagnosis and with mean monthly weight loss<1%; green: spinal onset patients without dysphagia at diagnosis and with mean monthly weight loss ≥1%; red: spinal onset patients with dysphagia at diagnosis; blue: bulbar onset patients) (p<0.0001). The median survival (IQR) of each subgroup is reported in the box. (B) Predicted probabilities of survival at 18 months based on respiratory function in the different subgroups of patients identified in the text. The spinal onset patients without dysphagia at diagnosis and mean monthly weight loss ≥1% (green) have a worse outcome than spinal patients without dysphagia at diagnosis and mean monthly weight loss <1% (orange). The prognosis of this group is similar to patients with bulbar onset (blue) and to patients with spinal onset with dysphagia at diagnosis (red). The difference in the predicted probabilities remains along all the range of respiratory function at diagnosis. FVC, forced vital capacity; WL, weight loss.

    Among spinal onset patients without swallowing symptoms at diagnosis, 62 out of 325 (19.1%) had a mean monthly percentage weight loss ≥1%; this subgroup had a median survival time of 1.8 years (IQR 1.0–3.0), substantially identical to that of bulbar onset patients (figure 3). Comparing these two groups of purely spinal patients we found that those with severe weight loss at diagnosis had a higher age at onset (p=0.04), a shorter diagnostic delay (p<0.0001), a lower FVC% (p=0.04), a higher mean monthly loss of ALSFRS-R score (p<0.0001), and were more frequently former or current cigarette smokers (p=0.01). Moreover, they had a shorter time from diagnosis to respiratory support (non-invasive ventilation or invasive ventilation) (5.0 (IQR 1.0–16.3) vs 20.2 (IQR 10.2–37.5) months, p<0.0001), and a lower mean ALSFRS-R respiratory score at diagnosis (11.2 (SD 2.0) vs 11.8 (SD 0.9), p<0.0001) (table 2).

    Table 2

    Spinal patients without swallowing disturbances at diagnosis: comparison of subjects with monthly weight loss ≥1% with patients with weight loss <1%

    Cox multivariable analysis

    The mean monthly weight loss remained significant in Cox multivariable analysis (p=0.004). Other significant variables in the analysis were age at onset, diagnostic delay, El Escorial classification at diagnosis, chronic obstructive pulmonary disease, and the mean monthly loss of ALSFRS-R.

    Discussion

    In this population-based study, which has included about 90% of ALS patients in the Piemonte and Valle d’Aosta Italian regions during the period from 2007–2011, we provided some novel observations about the prognostic relevance of early weight loss and the mechanism underlying it. First, we found that the rate of weight loss from onset to diagnosis is strongly and independently related to ALS outcome, while BMI at diagnosis, classified according to the WHO categories, is not a prognostic factor. Second, we observed that the presence of dysphagia at diagnosis in spinal onset patients carries the same prognostic effect of bulbar onset, challenging the classical dichotomy based on type of onset (bulbar vs spinal) used for patient stratification in ALS clinical trials. Third, we identified a subgroup of spinal onset patients who, although not displaying dysphagia at the time of diagnosis, had severe weight loss from onset to diagnosis and exhibited an outcome similar to bulbar onset patients. Remarkably, in this group of purely spinal patients, weight loss is caused by mechanisms unrelated to a reduction of nutritional intake due to dysphagia.

    Many different and overlapping causes have been identified for early weight loss in ALS. The more obvious cause is the reduction of food intake related to bulbar disturbances, either as presenting symptoms or appearing during the course of the disease. In these cases weight loss may be a very early phenomenon and precede the diagnosis of ALS.24 However, dietary imbalance is clearly not the only mechanism causing weight loss in ALS. There are indeed indications of the presence of metabolic problems in ALS, since it has been found that some patients even with appropriate caloric intake lose weight.25 An explanation is the observation that about 50% of ALS patients have an increased energy expenditure compared with controls persisting over the course of the disease,26 which could be present already in the pre-symptomatic phases of the disease.20 Finally, recent studies have also found a possible central mechanism of weight loss in at least a proportion of ALS patients: in about one fifth of ALS patients in a small clinical series, hypothalamic atrophy was identified by MRI, which was slightly correlated with BMI27; and in another study, in one third of ALS patients TDP-43 inclusions were found in the hypothalamus, indicating the involvement of this area in ALS pathology.28

    Weight at diagnosis and weight loss have been extensively studied as prognostic factors in ALS, with contrasting findings.7–17 In our series, both pre-morbid BMI and BMI at diagnosis did not affect ALS outcome after controlling for more relevant prognostic factors. More consistent results were reported in the literature as regards the prognostic effect of weight loss comparing DBW to HBW.7 8 11 15 18–20 In our study, the mean monthly percentage weight loss was found to be a strong prognostic factor, and remained independently significant in Cox multivariable analysis.

    Another novel finding of our study is the identification of a group of patients with spinal onset (corresponding to 10% of the whole series and 19% of spinal onset patients) who, despite not reporting any impairment of swallowing at the time of diagnosis, had a mean monthly weight loss ≥1%, and displayed a survival comparable to bulbar onset patients. Compared with the other spinal onset patients, these patients were older, had a shorter diagnostic delay, a lower FVC% at the time of diagnosis, a lower ALSFRS-R respiratory score, and a higher rate of loss of ALSFRS-R score. Interestingly, these patients underwent respiratory support (non-invasive ventilation (NIV) or invasive ventilation (IV)) much earlier than pure spinal patients with moderate or no weight loss at diagnosis. In these patients severe weight loss can be attributed to several causes: first, a reduction of nutritional intake due to loss of appetite, a phenomenon that has been reported to be associated with reduced respiratory function in about 50% of ALS patients29; second, a reduction of food intake due to difficulty in handling food; and third, the hypermetabolic state that has been reported in ALS patients, which increases their nutritional requirement and has a negative impact on their outcome.30 31

    Our findings have important implications for the design of clinical trials and for clinical practice. First, we observed that the presence of swallowing disturbances at diagnosis in spinal onset patients is as relevant as bulbar onset as a prognostic factor; accordingly we suggest that the stratification of patients for clinical trials should not be based on the type of onset (bulbar vs spinal) but to the actual presence of dysphagia at the time of trial enrolment. Second, we identified a subgroup of patients with spinal onset and no swallowing impairment at diagnosis who had a rapid and severe weight loss before diagnosis and experienced an outcome similar to bulbar patients; this finding indicates the importance of evaluating early weight changes in purely spinal patients, in order to identify and promptly treat the potential underlying respiratory impairment. Prospective studies aimed at better characterising this subgroup of patients will help to elucidate the mechanisms causing weight loss that differ from dysphagia in the ALS population.

    Acknowledgments

    We thank Professor Cesare Gregoretti, University of Palermo, for his precious advice. This work was in part supported by the Italian Ministry of Health (Ministero della Salute, Ricerca Sanitaria Finalizzata, 2010, grant RF-2010-2309849), the European Community’s Health Seventh Framework Programme (FP7/2007-2013 under grant agreement 259867), and the Joint Programme - Neurodegenerative Disease Research (Strength and Brain-Mend projects), granted by the Italian Ministry of Education, University and Research. This study was supported by Ministero dell'Istruzione, dell'Università e della Ricerca – MIUR project "Dipartimenti di Eccellenza 2018 – 2022" to Department of Neuroscience "Rita Levi Montalcini", University of Turin, Italy. AC has full access to the data. The corresponding author confirms that all authors have read and approved the final draft of the manuscript and given written permission to include their names in the manuscript.

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    View Abstract

    Footnotes

    • Collaborators Stefania Cammarosano, Rosario Vasta, Maria Claudia Torrieri, Luca Solero, (ALS Center, Azienda Ospedaliera Universitaria Città della Salute e della Scienza, Torino Italy). Marinella Clerico, Stefania De Mercanti, (Azienda Ospedaliera Universitaria San Luigi, University of Torino, Orbassano, Italy). Alessandro Mauro, Luca Pradotto (Istituto Auxologico Italiano, IRCCS, Piancavallo, Italy). Fabiola De Marchi (University of Eastern Piedmont, Novara, Italy). Luisa Sosso (Ospedale Mauriziano, Torino, Italy). Daniela Leotta (Ospedale Martini, Torino, Italy). Lucia Appendino, Daniele Imperiale (Ospedale Maria Vittoria, Torino, Italy). Roberto Cavallo (Ospedale San Giovanni Bosco, Torino, Italy). Claudio Geda (Ospedale di Ivrea, Ivrea, Italy). Fabio Poglio (Ospedale di Pinerolo, Pinerolo, Italy). Paola Santimaria (Ospedale di Vercelli, Vercelli, Italy). Umberto Massazza (Azienda Sanitaria, Biella, Italy). Antonio Villani, Roberto Conti (Ospedale di Domodossola, Domodossola, Italy). Luigi C Ruiz, Mario Palermo (Azienda Ospedaliera Nazionale Santi Ambrogio e Biagio e Cesare Arrigo, Alesssandria, Italy). Franco Vergnano (spedale di Casale Monferrato, Casale Monferrato, Italy). Eugenia Rota (Ospedale di Novi Ligure, Novi Ligure, Italy). Maria Teresa Penza (Ospedale di Valenza, Valenza, Italy). Marco Aguggia (Ospedale di Asti, Asti, Italy). Piero Meineri (Azienda Ospedaliera Santa Croce e Carle, Cuneo, Italy). Paolo Ghiglione (Ospedale di Savigliano, Savigliano, Italy). Nicola Launaro (Ospedale di Saluzzo, Saluzzo, Italy). Giuseppe Astegiano (Ospedale di Alba, Alba, Italy). Giovanni Corso (Azienda Unitaria Sanitaria Locale di Aosta, Aosta, Italy). Role: Site investigator (Stefania Cammarosano, Rosario Vasta, Maria Claudia, Luca Solero, Stefania De Mercanti, Luca Pradotto, Fabiola De Marchi, Luisa Sosso, Daniela Leotta, Lucia Appendino, Daniele Imperiale, Roberto Cavallo, Fabio Poglio, Paola Santimaria, Umberto Massazza, Roberto Conti, Mario Palermo, Franco Vergnano, Eugenia Rota, Maria Teresa Penza, Marco Aguggia, Piero Meineri, Paolo Ghiglione, Nicola Launaro, Giovanni Corso), Advisory committee (Marinella Clerico, Claudio Geda, Antonio Villani, Luigi C Ruiz, Giuseppe Astegiano). Contribution: Case ascertainment and follow-up (Stefania Cammarosano, Rosario Vasta, Maria Claudia, Luca Solero, Stefania De Mercanti, Luca Pradotto, Fabiola De Marchi, Luisa Sosso, Daniela Leotta, Lucia Appendino, Daniele Imperiale, Roberto Cavallo, Fabio Poglio, Paola Santimaria, Umberto Massazza, Roberto Conti, Mario Palermo, Franco Vergnano, Eugenia Rota, Maria Teresa Penza, Marco Aguggia, Piero Meineri, Paolo Ghiglione, Nicola Launaro, Giovanni Corso). Local data revision; Case ascertainment and follow-up: (Claudio Geda, Antonio Villani, Luigi C Ruiz, Giuseppe Astegiano).

    • Contributors Study concept and design: CM, AC, UM, FD’O, LM, GM, AC. Acquisition of data: MG, UM, AB, De Marchi. Analysis and interpretation of data: CM, AC, MG, UM, FD’O, LM, GM, AC. Drafting of the manuscript: AC, GM. Critical revision of the manuscript for important intellectual content: CM, MG, AC, AC, UM, FD’O, AB, De Marchi, LM, GM, AC. Obtained funding: AC. Administrative, technical, and material support: CM, MG, AC, AC, UM, FD’O, ABi, De Marchi, LM, GM, AC. Study supervision: GM, AC. AC has full access to data. The corresponding author confirms that all authors have read and approved the final draft of the manuscript and given written permission to include their names in the manuscript.

    • Funding This study was funded by FP (7259867) and also Joint Programme - Neurodegenerative Disease Research (Brain-Mend), Ministero della Salute, Ricerca Sanitaria Finalizzata, 2010 (RF-2010-2309849), Ministero dell'Istruzione, dell'Università e della Ricerca (Dipartimenti di Eccellenza 2018 – 2022) and Joint Programme - Neurodegenerative Disease Research (Strength).

    • Competing interests AC serves on a scientific advisory board for Mitsubishi Tanabe, Roche, and Cytokinetics.

    • Patient consent for publication Obtained.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement Anonymised data will be shared upon request from any qualified investigator.

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