Edema melting length and therapeutic failure during hospitalization as factors associated with long-term mortality after basic treatment of severe acute malnutrition: Lwiro cohort follow-up in the Eastern Democratic Republic of the Congo

Edema melting length and therapeutic failure during hospitalization as factors associated with long-term mortality after basic treatment of severe acute malnutrition: Lwiro cohort follow-up in the Eastern Democratic Republic of the Congo | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Edema melting length and therapeutic failure during hospitalization as factors associated with long-term mortality after basic treatment of severe acute malnutrition: Lwiro cohort follow-up in the Eastern Democratic Republic of the Congo Jean Corneille Lembebu, Amani Ngaboyeka Gaylord, Ghislain Bisimwa, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3791050/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Oct, 2025 Read the published version in BMC Nutrition → Version 1 posted 14 You are reading this latest preprint version Abstract Purpose The aim of this study was to identify the factors associated with long-term mortality in subjects treated for SAM in childhood 11 to 30 years after nutritional rehabilitation. Methodology Referring to the data collected from December 2017 to November 2018 from the Lwiro cohort; we updated this database with additional data. Records of subjects admitted for SAM between 1988 and 2007 were extracted from the archives of the pediatric hospital in Lwiro, South Kivu, Democratic Republic of Congo (DRC). A multivariate Cox proportional hazards regression was used to identify factors associated with long-term mortality. Results A total of 816 subjects were found to be alive and 119 died. The mean age at admission to nutritional rehabilitation was 46 months. Around two third of the subjects had edema, and in 6,8% of these subjects, edema had subsided after thirty days in hospital. Almost one in ten (9.5%) cases of SAM resulted in treatment failure. The risk of death was significantly higher in subjects with a history of therapeutic failure (hospital stay ≥ 45 days) and in those whose edema had melted late (≥ 30 days) during their hospitalization, with respective risks of HR = 1.98 (1.07; 3.67) and 2.81 (1.12; 7.03) respectively. Conclusion Good follow-up after hospital discharge is imperative to ensure the success of SAM management in the medium and long term. However, this follow-up must be more intensive in patients who have failed treatment and whose edema has melted late during hospitalization. Severe acute malnutrition Childhood long-term mortality and Lwiro cohort Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Malnutrition, in all its forms, is a genuine global public health problem. In 2023, the World Health Organization (WHO) reported that 148.1 million children were stunted, 45 million were wasted and 37 million were overweight ( 1 ) due to malnutrition. It is a central concern for both children and adults' health. Despite an increase in the prevalence of overweight, undernutrition is still endemic, especially in Sub-Saharan Africa (SSA) ( 2 – 4 ). Although there has been a slight decrease in its rate over the past two decades worldwide, undernutrition reduction rates have not been the same everywhere, SSA being the region with the lowest decline in the prevalence of malnutrition. As of today, SSA accounts for over a third of the burden of malnourished children ( 5 , 6 ). This high prevalence is a threat to future economic development, the health system and human well-being ( 7 ). Furthermore, progress in the management of acute malnutrition (AM) has reduced the mortality rate attributed to it during hospitalization, which in turn has led to good survival results for patients ( 8 , 9 ). Therefore, the long-term future of survivors has become an area that also needs to be addressed ( 10 , 11 ). Studies have shown that people who have suffered from Severe Acute Malnutrition (SAM) are still at high risk of relapse and short-term mortality after nutritional rehabilitation, since in most cases they return to the same precarious conditions ( 12 – 14 ). In addition, these subjects present a major risk of developing non-transmissible disease (NTD) in adulthood, as suggested by Barker's hypothesis ( 15 , 16 ). However, this thematic has been much more extensively documented in high- and middle-income countries (HMMICs). To date, little data exists on the long-termin low-income countries (LICs). Recently, in studies conducted by Mwene-batu et al. on a cohort of adults with a history of SAM during childhood in the east of the Democratic Republic of Congo (DRC), it was observed that among deaths following nutritional rehabilitation, a third occurred within two years of discharge from hospital and more than half within 5 years. The main causes of death were malaria, relapse of kwashiorkor, respiratory infections, and diarrheal diseases. Furthermore, most of the deceased subjects had passed away before celebrating their tenth birthday ( 17 ). Finally, for those who survived, more adverse effects in adulthood were reported in terms of an increased risk of non-communicable diseases (NCDs) and diminished human capital 11 to 30 years after nutritional rehabilitation ( 18 – 20 ). As for factors associated with long-term mortality, the existing studies have focused more on the influence of anthropometric indices at admission, the age of onset of SAM, gender, and vaccination status at the time of admission ( 17 ). Unfortunately, to this day, there have been almost no studies in the endemic context of SAM that have examined the impact of the duration of edema and the length of hospitalization on survival rates after nutritional rehabilitation. Using secondary data from the Lwiro cohort ( 17 ), this study aimed to assess the impact of edema duration and therapeutic failure (assessed via length of hospitalization) on the long-term risk of death. METHODOLOGY Study design and population The study population consisted of individuals admitted for SAM from 1988 to 2007 at the Provincial Hospital of Lwiro (HPL) in the South Kivu province of the DRC. The study subjects were identified from the HPL database and subsequently located in their respective villages of origin. They were then categorized into four groups: living in the village (or surrounding area), deceased, displaced or lost to follow-up. At the time, the diagnosis of SAM at HPL was based on: the weight-height ratio (WHR) relative to the local growth curve established by DeMaeyer in 1959 and not published (21) ; the presence of nutritional oedema. serum hypoalbuminemia (by protein electrophoresis). Based on these criteria, the following three forms of SAM were distinguished ( 22 ) : 1) Kwashiorkor : weight for height > percentile 5 and presence of nutritional oedema and/or serum albumin < 30 g/l, 2) Kwashiorkor-marasmic : weight for height < percentile 5 and presence of nutritional oedema and/or serum albumin < 30 g/l, 3) Marasmus : weight for height 30 g/l. Nutritional treatment at the time had evolved over the years and there were 3 periods to consider ( 23 ) : During the first period (1987–1994), treatment was based on MASOSO porridge, which is a mixture of maize, soy, and sorghum. The second period (1994–1996) was characterized by the administration of locally made High-Energy Milk (HEM), a mixture of milk, oil, and sugar with an energy density of approximately 90 kcal/liter. In the third period (August 1996-December 2007), HEM was replaced by therapeutic milk F-75 (in the first phase of treatment) and F-100 (in the second phase). Study framework The study took place at the Lwiro Natural Science Research Center (CRSN-Lwiro) in the health zones (HZ) of Miti-Murhesa and Katana, in South Kivu, DRC. The Miti-Murhesa and Katana health zones are located approximately 33 and 40 kilometers, respectively, from the city of Bukavu (the capital of South Kivu province). These health zones have an estimated population of over 400,000 residents. The CRSN was created in 1947 and organises its activities through four research departments: biology, geophysics, nutrition and documentation. The nutrition department has a HPL and several integrated health centres that monitor children in the community. The HPL, with a capacity of 70 beds, is located 50 kilometers from the city of Bukavu. In the 1970s, it operated as a nutrition center, admitting only children suffering from Severe Acute Malnutrition (SAM). Since the 1980s, HPL has evolved into a referral hospital treating various pediatric conditions, with approximately 80% of admissions being for SAM. It had a staff of 5 to 7 physicians, and consultations were conducted by a general practitioner under the supervision of specialists (pediatricians and infectious disease specialists) ( 23 ). The main economic activities of the population in these two areas are farming, livestock rearing, fishing and petty trading. The various conflicts that have led to insecurity in the region have disrupted the various economic activities of this population, especially farming and livestock rearing, which account for almost 70% of their income. This has led to the perpetuation of food insecurity in the region ( 24 ). Interest variables This study’s primary area of interest was long-term survival (with its corollary death). Survival was defined as a subject found and seen or reliably reported to be alive by relatives. For mortality, the parameters considered were age at death and the time elapsed between discharge from hospital and death. Data collection Referring to the data collected from December 2017 to November 2018 from the Lwiro cohort as part of a research project on the long-term effects of childhood malnutrition ( 17 ), we updated this database with additional data using the identities of patients who were admitted to the said cohort, including mainly the duration of oedema melting, the duration of hospitalization and the type of nutritional treatment by reviewing the medical records kept in the archives of the CRSN nutrition department from 1988 to 2007. Over a three-month period (April 2021 to June 2021), five investigators, a secretary and a supervisor worked full-time to update this cohort. Data were collected using a survey form that had been drawn up and tested beforehand. The pre-test was carried out on the medical records for a single year, 1988, and the questionnaire was adjusted on the basis of the results of this pre-test. Each file contained information on the subject's identity (name of child and parents, date of birth, sex, original health area and ethnicity), anthropometric parameters (weight, height and BMI) on admission, vaccination status, serum albumin level, clinical examination, nutritional diagnosis, duration of oedema melting, weight after oedema melting, infectious diagnosis, treatment initiated, duration of hospitalization and discharge outcome. A case of therapeutic failure was defined as a failure to respond to treatment after 45 days in hospital for a patient who had been properly monitored. Patients whose records were incomplete (records without simultaneous data on the duration of oedema melting, the length of hospitalization and the nutritional treatment received), those who had left or died during hospitalization, and those who had been transferred to another health facility were excluded. Based on the above criteria, out of 1981 files obtained, 1378 (69.6%) met the inclusion criteria for this study. Of the 1378 files retained in our study, only 935 (67.9%) had been traced and 443 (32.1%) had been lost to follow-up. Of those traced, 816 patients (87.3%) were still alive and 119 (12.7%) had died. Of the living patients, 514 (63%) had been seen by Community Health Workers (CHWs) and 302 (37%) had moved to other regions but were reported reliably to be alive (Fig. 1) Figure 1 : Recruiting the sample. Data analysis Additional information were coded and entered using Kobotoolbox software, and the data were analyzed using Stata 16 software. Categorical variables were summarized in terms of absolute numbers and proportions. Continuous quantitative variables were summarized as the mean with standard deviation (SD) or as the median with the 25th and 75th percentiles, depending on whether the distribution was symmetrical or asymmetrical. First, we carried out an initial binary analysis with long-term survival as the 'survival/death' dependent variable. For this analysis, we have included all living subjects (seen and moved) and deceased subjects. Proportions were compared using Pearson's chi-squared test or Fisher's chi-squared test, depending on the conditions of application. Means and medians were compared using Student's parametric test or the non-parametric Wilcoxon-Mann-Whitney test, respectively. Second, we performed a survival analysis taking into account the timing. For the survival analysis, time 0 was the date of discharge from the HPL. Patient follow-up time was calculated in years by subtracting the date of discharge from the date of final outcome (alive or dead). For the alive subjects that moved, we have derived the date of survival on the basis of information provided by the victims' relatives. We excluded patients who had been lost from sight due to lack of information regarding their survival after discharge from hospital. We compared their childhood parameters with those of children for whom we had survival information, in order to assess their impact on outcomes. A Kaplan Meier curve was used to estimate the survival function based on survival time data and the log-rank test was used to compare the curves from different groups. Cox regression was used to determine the proportional risks associated with long-term death. To handle the collinearity between the variables of therapeutic failure and the duration of oedema melting ( 30 days), two distinct models were constructed. In the first model, we adjusted for therapeutic failure, age, sex, vaccination status and anthropometric parameters (height, weight, and brachial circumference). In the second model, In model 2, "therapeutic failure" has been replaced by "duration of oedema", and we have kept all the remaining confounding factors. The hypothesis of proportionality of the risks of instantaneous death (Proportional Hazards = PH model) was verified by the ln(-ln(S(t)) curves. The adjusted HR (Hazard Ratio) is followed by the p-value of the Wald. For all these analyses, we set a type I error threshold (alpha) of 5%. RESULTS SOCIO-DEMOGRAPHIC AND CLINICAL CHARACTERISTICS OF PATIENTS The socio-demographic and clinical characteristics of our patients are described in Table 1 . The average age of the population at admission was approximately 46 months, with a slight male predominance (55.9%). These children came from households with a median size of six and a median number of deceased children of one. Over two-thirds of the study sample had edema, with nearly three-quarters of them limited to the feet. A median duration of seven days was observed for oedema to melt, with 6.8% of subjects taking over 30 days. Most subjects (67.5%) had a history of kwashiorkor. Almost half had received WHO standard therapeutic milk, and the median length of hospitalization was 23 days, with 9.5% of cases of therapeutic failure. Table 1 Socio-demographic characteristics of our patients admitted to the study Variables Numbers (proportions) Mean ± SD or Median (P25; P75) Sex (n = 1371 and missing = 7) Women 605 (44.13%) Men 766 (55.87%) Age at admission (months) (n = 1349 and missing = 29) 46.58 ± 30.80 Anthropometry at admission Weight (grams) (n = 1251 and missing = 127 ) 9565.43 ± 3495.37 Size (cm) (n = 1340 and missing = 38 ) 82.15 ± 12.89 Brachial circumference (mm) (n = 1269 and missing = 109 ) 128.09 ± 18.94 Presence of oedema (n = 1362 and missing = 16) No 443 (32.53%) Yes 919 (67.47%) Level of oedema (n = 906 and missing = 13) On the foot 657 (72.52%) Face 43 (4.75%) Generalized 206 (22.74%) Melting time (days) (n = 837 and missing = 82) 7 (5; 13) Duration of melting (n = 1280 and missing = 98) No oedema 443 (34.61%) Under 30 days 780 (60.94%) Over 30 days 57 (4.45%) Albumin J0 (n = 941 and missing = 437) 1.91 (1.47; 2.52) Type of SAM (n = 1042 and missing = 336) Kwashiorkor 703 (67.47%) Slump 116 (11.13%) Mixed 223 (21.40%) Vaccination schedule (n = 1236 and missing = 142) Complete 912 (73.79%) Incomplete 84 (6.80%) Not vaccinated 240 (19.42%) Nutrition treatment (n = 881 and missing = 497) No milk 221 (25.09%) F75/F100 milk 417 (47.33%) Cow's milk 243 (27.58%) Length of hospital stay (days) (n = 1335 and missing = 43) 23 (15; 33) Therapeutic failure (n = 1335 and missing = 43) No 1208 (90.49%) Yes 127 (9.51%) SD: Standard deviation; P25: Percentile 25; P75: Percentile 75; cm: centimeter; mm: millimeter. Comparison of sociodemographic and clinical characteristics of patients in relation to long-term mortality Table 2 compares the characteristics during hospitalization between the two groups (deceased vs alive as adults) in univariate analyses. In comparison with the patients who were still alive deceased patients had more often a therapeutic failure during hospitalization and had a longer duration of hospitalization. In subjects with oedema, deceased subjects had more often an oedema that has taken a longer time to melt. These differences were significant. The other characteristics did not differ significantly in the two groups (deceased vs alive as adults). Table 2 Comparison of sociodemographic and clinical characteristics of our patients in relation to long-term survival Variables Current status P Value Alive Deceased Sex (n = 930 and missing = 5) 0.357* Men 452 (55.67) 71 (60.17) Age at admission (months) (n = 912 and missing = 23) 46.51 ± 31.16 44.89 ± 32.26 0.602** Anthropometry at admission Weight (grams) (n = 850 and missing = 85) 9581.72 ± 3490.04 9283.19 ± 3838.69 0.411** Size (cm) (n = 910 and missing = 25) 82.33 ± 12.92 80.25 ± 13.13 0.109** Brachial circumference (mm) (n = 864 and missing = 71) 128.67 ± 18.89 126.48 ± 21.55 0.268** Presence of oedema (n = 921 and missing = 14) Yes 534 (66.58) 84 (70.59) 0.386* Level of oedema (n = 607 and missing = 11) 0.958* On the foot 377 (71.95) 61 (73.49) Face 20 (3.82) 3 (3.61) Generalized 127 (24.24) 19 (22.89) Melting time (days) (n = 568 and missing = 50) 7 (5; 12) 8 (5; 16) 0.256*** Duration of melting (n = 871 and missing = 64) 0.007 No oedema 268 (35.36) 35 (30.97) Under 30 days 468 (61.74) 68 (60.18) Over 30 days 22 (2.90) 10 (8.85) Type of SAM (n = 687 and missing = 248) 0.112* Kwashiorkor 413 (69.18) 56 (62.22) Marasmus 68 (11.39) 8 (8.89) Mixed 116 (19.43) 26 (28.89) Nutrition treatment (n = 612 and missing = 323) 0.295* No milk 124 (23.05) 20 (27.03) F75/F100 milk 267 (49.63) 40 (54.05) Cow's milk 147 (27.32) 14 (18.92) Vaccination schedule (n = 692 and missing = 243) 0.469* Not vaccinated/Not up to date 177 (23.92) 24 (22.64) Length of hospital stay (days) (n = 894 and missing = 41) 23 (15; 32) 27 (18; 41) 0.005*** Therapeutic failure (n = 905 and missing = 30) 0.001* Yes 65 (8.21) 20 (17.70) SAM: Severe acute malnutrition; MAM: Moderate acute malnutrition; cm: centimeter; mm: millimeter; dL: deciliter; g: gramme; F75: Therapeutic milk 75mg/100ml; F100: Therapeutic milk 100mg/100ml. * Pearson chi-square test; ** Student test; *** Non-parametric Wilcoxon Man-Whitney test Apart from the vaccination status, no significant differences were observed between subjects traced and subjects lost from sight (supplementary Table 1 in appendix) Relationship between treatment failure and oedema melting with long-term survival Figure 2 displays the Kaplan-Meier curve by therapeutic failure Patients with therapeutic failure have significantly lower survival than those without therapeutic failure ( P = 0.011). Figure 2: Kaplan-Meier survival estimates Figure 3 shows the Kaplan-Meier curve by the duration of oedema melting. Patients with a longer duration of oedema melting (more than 30 days) have a poorer survival compared with those whose oedema melted before 30 days and those who did not have oedema. However, this difference was not statistically significant (P = 0.213). Figure 3: Kaplan-Meier survival estimates INSTANTANEOUS DEATH PREDICTORS For both models, the PH condition was satisfied (supplementary Table 2 in appendix). The instantaneous risk of death was significantly higher in patients whose oedema had melted for more than 30 days and in those whose treatment had failed. However, sex, anthropometry at admission, immune status and age at onset of malnutrition showed no statistically significant influence on the instantaneous risk of death. (Table 3 ) Table 3 Predictors of instantaneous death Variables HR aj (IC 95%) HR aj (IC 95%) Model 1 result (n = 640) Model 2 result (n = 615) Sex Women 1 1 Men 1.27 (0.80; 2.04) 1.17 (0.73; 1.86) Age at admission (months) 1.01 (0.99; 1.02) 1.01 (0.99; 1.02) Anthropometry at admission Weight (grams) 1.00 (0.99; 1.01) 1.00 (0.99; 1.01) Size (cm) 0.97 (0.94; 1.01) 0.96 (0.93; 1.01) Brachial circumference in mm 0.99 (0.98; 1.01) 0.99 (0.98; 1.01) Duration of melting Not included in model 1 No oedema 1 Under 30 days 0.99 (0.59; 1.66) Over 30 days 2.81 (1.12; 7.03) Therapeutic failure Not included in model 2 No 1 Yes 1.98 (1.07; 3.67) Vaccination schedule Vaccinated 1.36 (0.75; 2.46) 1.68 (0.89; 3.19) Not vaccinated/Not up to date 1 1 HRnaj: Hazard Ratio unadjusted; HRaj: Hazard Ratio adjusted; F75: Therapeutic milk 75mg/100ml; F100: Therapeutic milk 100mg/100ml. Model 1 result: we adjusted for therapeutic failure, age, sex, vaccination status and anthropometric parameters (height, weight, and brachial circumference); Model 2 result: we adjusted for duration of oedema melting,age, sex, vaccination status and anthropometric parameters (height,weight and brachial circumference). DISCUSSION The aim of this study was to identify in-hospital clinical and therapeutic predictors of long-term risk of death based on secondary data from a cohort of former SAMs in eastern DRC (Lwiro Follow up Study). The results show that delayed oedema melting beyond thirty days and therapeutic failure are significantly associated with an increased risk of long-term death after an episode of SAM. In relation to the existing literature, this study is one of the few, if not the first, in a low-income country to have reconstituted a very large cohort of subjects with a history of SAM and to have followed them for a long time after discharge from hospital in a context of endemic malnutrition. The novelty in this study lies in the fact that it included many subjects with a history of kwashiorkor (67.5%), it examined subjects who had continued to live in an unfavorable environment throughout their lives and it assessed several clinical parameters (including the duration of oedema) and various anthropometric measurements on the occurrence of long-term death. In terms of long-term survival, it was observed that the risk of death was significantly higher in children whose oedema melted in more than thirty days than in those whose oedema melted in less than thirty days (HR: 2.79 IC95%: 1,13; 6.91). These results are in line with the literature, because although kwashiorkor remains an enigma ( 25 ), oxidative stress and disruption of the intestinal microbiome are among the possible causes of oedema and are present in kwashiorkor ( 26 , 27 ). Oxidative stress, which can cause significant cellular damage and contribute to various health problems and the ageing process, could have several harmful effects over time ( 28 , 29 ). Diarrheal diseases, which are among the causes of death in individuals who developed malnutrition during childhood ( 17 ), may be due to a disturbance in the intestinal microbiota present during an episode of Kwashiorkor ( 30 ). Some studies, including those by M. Kerac et al. and Bwakura et al., found that patients who developed marasmus during hospitalization were at a much higher risk of death in the year following discharge from the hospital. However, the duration of edema resolution was not taken into account in their studies ( 31 , 32 ). Nevertheless, it is important to note that Bitwe et al. had suggested classifying individuals at risk of death during hospitalization when they present with nutritional edema ( 33 ). The cases of therapeutic failure had a proportional risk of long-term death four times higher (HR: 4.07 and IC95%: 1.29; 12.80) than those without a therapeutic failure. Cases of therapeutic failure suggest a long hospital stay with a high probability of having developed untreated complications which, in the medium term, increase the risk of serious infections, potentially fatal for patients. According to Mwene-Batu et al, the main causes of death after discharge from therapeutic feeding centers among patients treated for SAM were infectious diseases, including malaria and respiratory infections ( 17 ). Treatment failures can also result from acquired immunosuppression due to other diseases such as tuberculosis and HIV, particularly in this study’s context ( 34 – 36 ). Similar studies within the region have reported a low prevalence of HIV (2%) among malnourished children ( 34 ), these factors could also contribute significantly to the high proportion of deaths among children who have experienced treatment failure, as the medium-term survival of immunocompromised children with malnutrition generally remains limited after discharge ( 37 – 40 ). Unfortunately, serological data for these malnourished children were not collected. However, in Zambia, Bwankura et al. were unable to identify long hospital stays as a risk factor for short-term death after an episode of SAM ( 32 ). This disparity could be explained by the fact that 43.6% of patients discharged from health facilities in Zambia had a current SAM. This would explain the fact that many of the patients discharged to these facilities would not have been able to obtain authorization for discharge to the HPL. The present study has some methodological limitations that should be considered in interpreting the results. Essentially, the subjects for this study were chosen based on the Lwiro cohort of malnourished individuals. However, nearly a third (32.15%) of the subjects were not located during the identification process for this study, 11 to 30 years after their discharge from the hospital, making it impossible to assess their long-term outcomes. Additionally, some patients were excluded because their medical records were incomplete. We could not include subjects lost from sight in our survival analyses because we have no data on their outcome after hospital discharge. By comparing their characteristics with those of the traced subjects, we found that only vaccination status was statistically different between the two groups (p = 0,004). Our results showed that a large proportion of "lost to follow-up" subjects had incomplete vaccination status compared with traced subjects. We have to accept this limitation as we are unable to demonstrate how this would influence the survival analysis results. Furthermore, the Lwiro database, which this study is based upon, did not include data on possible confounding factors such as demographic data concerning the beginning of life, the crucial 1000 days and data on the evolution of these children from discharge from hospital to the time of our identification, which could play a role in the different associations of long-term survival with the other variables. Finally, another major limitation of this study is the lack of serological data on malnourished children, which prevents us from making an exhaustive assessment of the prevalence of HIV and tuberculosis in this population. This lack of data makes it difficult to precisely determine the impact of these diseases on the therapeutic failures observed. CONCLUSION SAM during childhood has harmful long-term effects on the patients wellbeing and on their survival. Donors and policymakers wishing to reduce the burden of SAM and improve management should pay particular attention to the risk factors identified in this study in order to improve management and long-term survival. Effective post-hospitalization follow-up is crucial to ensure the long-term success of SAM management. Nonetheless, a more intensive level of follow-up is required for patients who have not responded well to treatment and whose edema has resolved late during their hospital stay. Finally, the study’s results show that the fight against SAM and its consequences must remain a public health priority. Abbreviations AM : Acute malnutrition BP : Brachial perimeter CHO : Community Health Officer CNRS : Natural Sciences Research Centre DRC : Democratic Republic of Congo HEM : High-Energy Milk HIV : Human Immunodeficiency Virus HMMIC : High- and middle-income countries. HPL : Lwiro Paediatric Hospital HR : Hazard Ratio MAM : Moderate Acute Malnutrition NASH : Non-alcoholic steatohepatitis NTM : Non-transmissible disease OR : Odds Ratio P25 : Percentile 25 P75 : Percentile 75 PH : Proportional Hazards SAM : Severe acute malnutrition SD : Standard deviation SSA : Sub-Saharan Africa UNICEF : United Nations Children's Fund WHO : World Health Organization WHR : Weight-height ratio Declarations Ethics approval and consent to participate This study was approved by the ethics committee of the Catholic University of Bukavu. All procedures were carried out in accordance with the ethical standards of the institutional ethics committee and the 1964 Declaration of Helsinki and its subsequent amendments. Sign informed consent was obtained from respondent himself if he was an adult, or by the subject's parent in the case of minors. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding The authors have no relevant financial or non-financial interests to disclose and no competing interests to declare that are relevant to the content of this article. Author contributions JCL, GB, PM and PD contributed to the conception and design of the study. Material preparation, data collection and analysis were carried out by JCL, SLM, ANG, AN, CC, CZC and BBB. The first draft of the manuscript was written by JCL, while PM, SLM, ANG, AN and RB commented on earlier versions of the manuscript. All authors read and approved the final manuscript. 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Follow-up of a historic cohort of children treated for severe acute malnutrition between 1988 and 2007 in Eastern Democratic Republic of Congo. PLoS ONE. 2020;15(3):e0229675. Mwene-Batu P, Lemogoum D, de le Hoye L, Bisimwa G, Hermans MP, Minani J, et al. Association between severe acute malnutrition during childhood and blood pressure during adulthood in the eastern Democratic Republic of the Congo: the Lwiro cohort study. BMC Public Health 2 mai. 2021;21(1):847. Mwene-Batu P, Bisimwa G, Baguma M, Chabwine J, Bapolisi A, Chimanuka C, et al. Long-term effects of severe acute malnutrition during childhood on adult cognitive, academic and behavioural development in African fragile countries: The Lwiro cohort study in Democratic Republic of the Congo. PLoS ONE. 2020;15(12):e0244486. Mwene-Batu P, Bisimwa G, Ngaboyeka G, Dramaix M, Macq J, Hermans MP, et al. Severe acute malnutrition in childhood, chronic diseases, and human capital in adulthood in the Democratic Republic of Congo: the Lwiro Cohort Study. Am J Clin Nutr 1 juill. 2021;114(1):70–9. Daniel, Lemmonier. Yves Ingenbleek. Les Carences nutritionnelles dans les pays en voie de développement. 1989. Dramaix M, Hennart P, Brasseur D, Bahwere P, Mudjene O, Tonglet R, et al. Serum albumin concentration, arm circumference, and oedema and subsequent risk of dying in children in central Africa. BMJ 18 sept. 1993;307(6906):710–3. Bahwere P, Hennart P. Contribution à l’amélioration et à l’évaluation de la prise en charge globale de l’enfant hospitalisé en Afrique Centrale (Sud Kivu). undefined [Internet]. 2002 [cité 17 juill 2021]; Disponible sur: https://www.semanticscholar.org/paper/Contribution-%C3%A0-l%27am%C3%A9lioration-et-%C3%A0-l%27%C3%A9valuation-de-Bahwere-Hennart/30e 525777f1a9f83e93713c888ad5ec237d733af. Action contre la faim. Enquete nutritionnelle anthropométrique dans la Zone de Santé de Miti-Murhesa. 2011. André Briend MD. Kwashiorkor: still an enigma – the search must go on. 31 déc 2014 [cité 5 déc 2021]; Disponible sur: https://www.ennonline.net/www.ennonline.net/kwashiorkorstillanenigma . Smith MI, Yatsunenko T, Manary MJ, Trehan I, Mkakosya R, Cheng J, et al. Gut microbiomes of Malawian twin pairs discordant for kwashiorkor. Sci 1 févr. 2013;339(6119):548–54. Golden MH, Ramdath D. Free radicals in the pathogenesis of kwashiorkor. Proc Nutr Soc févr. 1987;46(1):53–68. Wadley AJ, van Veldhuijzen JJCS, Aldred S. The interactions of oxidative stress and inflammation with vascular dysfunction in ageing: the vascular health triad. Age Dordr Neth juin. 2013;35(3):705–18. Dinh QN, Drummond GR, Sobey CG, Chrissobolis S. Roles of inflammation, oxidative stress, and vascular dysfunction in hypertension. BioMed Res Int. 2014;2014:406960. R I, O I AN. S B, Y N, A A. Gut microbiota in the pathogenesis of inflammatory bowel disease. Clin J Gastroenterol [Internet]. févr 2018 [cité 5 déc 2021];11(1). Disponible sur: https://pubmed.ncbi.nlm.nih.gov/29285689/ . Kerac M, Bunn J, Chagaluka G, Bahwere P, Tomkins A, Collins S, et al. Follow-up of post-discharge growth and mortality after treatment for severe acute malnutrition (FuSAM study): a prospective cohort study. PLoS ONE. 2014;9(6):e96030. Bwakura-Dangarembizi M, Dumbura C, Amadi B, Ngosa D, Majo FD, Nathoo KJ et al. Risk factors for postdischarge mortality following hospitalization for severe acute malnutrition in Zimbabwe and Zambia. Am J Clin Nutr. 11 mars. 2021;113(3):665–74. Bitwe R, Dramaix M, Hennart P. [Simplified prognostic model of overall intrahospital mortality of children in central Africa]. Trop Med Int Health TM IH janv. 2006;11(1):73–80. Kambale RM, Ngaboyeka GA, Ntagazibwa JN, Bisimwa MHI, Kasole LY, Habiyambere V, et al. Severe acute malnutrition in children admitted in an Intensive Therapeutic and Feeding Centre of South Kivu, Eastern Democratic Republic of Congo: Why do our patients die? PLoS ONE. 2020;15(7):e0236022. Jesson J, Leroy V. Challenges of malnutrition care among HIV-infected children on antiretroviral treatment in Africa. Med Mal Infect mai. 2015;45(5):149–56. Jaganath D, Mupere E. Childhood tuberculosis and malnutrition. J Infect Dis 15 déc. 2012;206(12):1809–15. Fergusson P, Tomkins A. HIV prevalence and mortality among children undergoing treatment for severe acute malnutrition in sub-Saharan Africa: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg juin. 2009;103(6):541–8. Chinkhumba J, Tomkins A, Banda T, Mkangama C, Fergusson P. The impact of HIV on mortality during in-patient rehabilitation of severely malnourished children in Malawi. Trans R Soc Trop Med Hyg juill. 2008;102(7):639–44. Mody A, Bartz S, Hornik CP, Kiyimba T, Bain J, Muehlbauer M, et al. Effects of HIV infection on the metabolic and hormonal status of children with severe acute malnutrition. PLoS ONE. 2014;9(7):e102233. Bwakura-Dangarembizi M, Dumbura C, Amadi B, Ngosa D, Majo FD, Nathoo KJ et al. Risk factors for postdischarge mortality following hospitalization for severe acute malnutrition in Zimbabwe and Zambia. Am J Clin Nutr. 11 mars. 2021;113(3):665–74. Additional Declarations No competing interests reported. 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Bukavu","correspondingAuthor":false,"prefix":"","firstName":"Pacifique","middleName":"","lastName":"Mwene-Batu","suffix":""}],"badges":[],"createdAt":"2023-12-22 09:14:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3791050/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3791050/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40795-025-01173-4","type":"published","date":"2025-10-14T15:57:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49127296,"identity":"35f3e5b5-9017-44cc-ab4e-ebd1c47f3f40","added_by":"auto","created_at":"2024-01-03 14:59:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRecruiting the sample.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3791050/v1/19e56e0288e7b40f45a9a263.png"},{"id":49127295,"identity":"8ebc7d54-3d51-486c-bd63-aaed64f96354","added_by":"auto","created_at":"2024-01-03 14:59:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54408,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier survival estimates\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3791050/v1/a75f5213145a4a3f1a69dcca.png"},{"id":49127294,"identity":"08d58b83-4251-4cff-9c24-548235ffd6ce","added_by":"auto","created_at":"2024-01-03 14:59:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56282,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier survival estimates\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3791050/v1/ef3d6c2c311f64a6f48230b8.png"},{"id":93956189,"identity":"e3386525-27cf-45f2-a6d1-4b8c0ef28a0d","added_by":"auto","created_at":"2025-10-20 16:11:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1871224,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3791050/v1/b83f2c5f-d8ee-49aa-96a5-41c0a307067f.pdf"},{"id":49128449,"identity":"3e3ee415-4b01-493d-a2e7-64178c6ec065","added_by":"auto","created_at":"2024-01-03 15:07:34","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18106,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDICES.docx","url":"https://assets-eu.researchsquare.com/files/rs-3791050/v1/bb4545455f524e65bdea6ec9.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Edema melting length and therapeutic failure during hospitalization as factors associated with long-term mortality after basic treatment of severe acute malnutrition: Lwiro cohort follow-up in the Eastern Democratic Republic of the Congo","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eMalnutrition, in all its forms, is a genuine global public health problem. In 2023, the World Health Organization (WHO) reported that 148.1\u0026nbsp;million children were stunted, 45\u0026nbsp;million were wasted and 37\u0026nbsp;million were overweight (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) due to malnutrition. It is a central concern for both children and adults' health. Despite an increase in the prevalence of overweight, undernutrition is still endemic, especially in Sub-Saharan Africa (SSA) (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough there has been a slight decrease in its rate over the past two decades worldwide, undernutrition reduction rates have not been the same everywhere, SSA being the region with the lowest decline in the prevalence of malnutrition. As of today, SSA accounts for over a third of the burden of malnourished children (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). This high prevalence is a threat to future economic development, the health system and human well-being (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, progress in the management of acute malnutrition (AM) has reduced the mortality rate attributed to it during hospitalization, which in turn has led to good survival results for patients (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Therefore, the long-term future of survivors has become an area that also needs to be addressed (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eStudies have shown that people who have suffered from Severe Acute Malnutrition (SAM) are still at high risk of relapse and short-term mortality after nutritional rehabilitation, since in most cases they return to the same precarious conditions (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In addition, these subjects present a major risk of developing non-transmissible disease (NTD) in adulthood, as suggested by Barker's hypothesis (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). However, this thematic has been much more extensively documented in high- and middle-income countries (HMMICs). To date, little data exists on the long-termin low-income countries (LICs).\u003c/p\u003e \u003cp\u003eRecently, in studies conducted by Mwene-batu et al. on a cohort of adults with a history of SAM during childhood in the east of the Democratic Republic of Congo (DRC), it was observed that among deaths following nutritional rehabilitation, a third occurred within two years of discharge from hospital and more than half within 5 years. The main causes of death were malaria, relapse of kwashiorkor, respiratory infections, and diarrheal diseases. Furthermore, most of the deceased subjects had passed away before celebrating their tenth birthday (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Finally, for those who survived, more adverse effects in adulthood were reported in terms of an increased risk of non-communicable diseases (NCDs) and diminished human capital 11 to 30 years after nutritional rehabilitation (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs for factors associated with long-term mortality, the existing studies have focused more on the influence of anthropometric indices at admission, the age of onset of SAM, gender, and vaccination status at the time of admission (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Unfortunately, to this day, there have been almost no studies in the endemic context of SAM that have examined the impact of the duration of edema and the length of hospitalization on survival rates after nutritional rehabilitation.\u003c/p\u003e \u003cp\u003eUsing secondary data from the Lwiro cohort (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), this study aimed to assess the impact of edema duration and therapeutic failure (assessed via length of hospitalization) on the long-term risk of death.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design and population\u003c/h2\u003e\n \u003cp\u003eThe study population consisted of individuals admitted for SAM from 1988 to 2007 at the Provincial Hospital of Lwiro (HPL) in the South Kivu province of the DRC. The study subjects were identified from the HPL database and subsequently located in their respective villages of origin. They were then categorized into four groups: living in the village (or surrounding area), deceased, displaced or lost to follow-up.\u003c/p\u003e\n \u003cp\u003eAt the time, the diagnosis of SAM at HPL was based on:\u003c/p\u003e\n \u003col style=\"list-style-type: lower-roman;\"\u003e\n \u003cli\u003ethe weight-height ratio (WHR) relative to the local growth curve established by DeMaeyer in 1959 and not published (21) ;\u0026nbsp;\u003c/li\u003e\n \u003cli\u003ethe presence of nutritional oedema.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eserum hypoalbuminemia (by protein electrophoresis).\u003c/li\u003e\n \u003c/ol\u003e\n \u003cp\u003eBased on these criteria, the following three forms of SAM were distinguished (\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e) :\u003c/p\u003e\n \u003cp\u003e1) \u003cstrong\u003eKwashiorkor\u003c/strong\u003e: weight for height\u0026thinsp;\u0026gt;\u0026thinsp;percentile 5 and presence of nutritional oedema and/or serum albumin\u0026thinsp;\u0026lt;\u0026thinsp;30 g/l,\u003c/p\u003e\n \u003cp\u003e2) \u003cstrong\u003eKwashiorkor-marasmic\u003c/strong\u003e: weight for height\u0026thinsp;\u0026lt;\u0026thinsp;percentile 5 and presence of nutritional oedema and/or serum albumin\u0026thinsp;\u0026lt;\u0026thinsp;30 g/l,\u003c/p\u003e\n \u003cp\u003e3) \u003cstrong\u003eMarasmus\u003c/strong\u003e: weight for height\u0026thinsp;\u0026lt;\u0026thinsp;percentile 5 and absence of nutritional oedema and serum albumin\u0026thinsp;\u0026gt;\u0026thinsp;30 g/l.\u003c/p\u003e\n \u003cp\u003eNutritional treatment at the time had evolved over the years and there were 3 periods to consider (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e) :\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eDuring the first period (1987\u0026ndash;1994), treatment was based on MASOSO porridge, which is a mixture of maize, soy, and sorghum.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eThe second period (1994\u0026ndash;1996) was characterized by the administration of locally made High-Energy Milk (HEM), a mixture of milk, oil, and sugar with an energy density of approximately 90 kcal/liter.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eIn the third period (August 1996-December 2007), HEM was replaced by therapeutic milk F-75 (in the first phase of treatment) and F-100 (in the second phase).\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy framework\u003c/h2\u003e\n \u003cp\u003eThe study took place at the Lwiro Natural Science Research Center (CRSN-Lwiro) in the health zones (HZ) of Miti-Murhesa and Katana, in South Kivu, DRC. The Miti-Murhesa and Katana health zones are located approximately 33 and 40 kilometers, respectively, from the city of Bukavu (the capital of South Kivu province). These health zones have an estimated population of over 400,000 residents.\u003c/p\u003e\n \u003cp\u003eThe CRSN was created in 1947 and organises its activities through four research departments: biology, geophysics, nutrition and documentation. The nutrition department has a HPL and several integrated health centres that monitor children in the community.\u003c/p\u003e\n \u003cp\u003eThe HPL, with a capacity of 70 beds, is located 50 kilometers from the city of Bukavu. In the 1970s, it operated as a nutrition center, admitting only children suffering from Severe Acute Malnutrition (SAM). Since the 1980s, HPL has evolved into a referral hospital treating various pediatric conditions, with approximately 80% of admissions being for SAM. It had a staff of 5 to 7 physicians, and consultations were conducted by a general practitioner under the supervision of specialists (pediatricians and infectious disease specialists) (\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eThe main economic activities of the population in these two areas are farming, livestock rearing, fishing and petty trading. The various conflicts that have led to insecurity in the region have disrupted the various economic activities of this population, especially farming and livestock rearing, which account for almost 70% of their income. This has led to the perpetuation of food insecurity in the region (\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eInterest variables\u003c/h2\u003e\n \u003cp\u003eThis study\u0026rsquo;s primary area of interest was long-term survival (with its corollary death). Survival was defined as a subject found and seen or reliably reported to be alive by relatives. For mortality, the parameters considered were age at death and the time elapsed between discharge from hospital and death.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eData collection\u003c/h2\u003e\n \u003cp\u003eReferring to the data collected from December 2017 to November 2018 from the Lwiro cohort as part of a research project on the long-term effects of childhood malnutrition (\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e), we updated this database with additional data using the identities of patients who were admitted to the said cohort, including mainly the duration of oedema melting, the duration of hospitalization and the type of nutritional treatment by reviewing the medical records kept in the archives of the CRSN nutrition department from 1988 to 2007. Over a three-month period (April 2021 to June 2021), five investigators, a secretary and a supervisor worked full-time to update this cohort.\u003c/p\u003e\n \u003cp\u003eData were collected using a survey form that had been drawn up and tested beforehand. The pre-test was carried out on the medical records for a single year, 1988, and the questionnaire was adjusted on the basis of the results of this pre-test.\u003c/p\u003e\n \u003cp\u003eEach file contained information on the subject\u0026apos;s identity (name of child and parents, date of birth, sex, original health area and ethnicity), anthropometric parameters (weight, height and BMI) on admission, vaccination status, serum albumin level, clinical examination, nutritional diagnosis, duration of oedema melting, weight after oedema melting, infectious diagnosis, treatment initiated, duration of hospitalization and discharge outcome. A case of therapeutic failure was defined as a failure to respond to treatment after 45 days in hospital for a patient who had been properly monitored.\u003c/p\u003e\n \u003cp\u003ePatients whose records were incomplete (records without simultaneous data on the duration of oedema melting, the length of hospitalization and the nutritional treatment received), those who had left or died during hospitalization, and those who had been transferred to another health facility were excluded.\u003c/p\u003e\n \u003cp\u003eBased on the above criteria, out of 1981 files obtained, 1378 (69.6%) met the inclusion criteria for this study. Of the 1378 files retained in our study, only 935 (67.9%) had been traced and 443 (32.1%) had been lost to follow-up. Of those traced, 816 patients (87.3%) were still alive and 119 (12.7%) had died. Of the living patients, 514 (63%) had been seen by Community Health Workers (CHWs) and 302 (37%) had moved to other regions but were reported reliably to be alive (Fig.\u0026nbsp;1)\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFigure 1 : Recruiting the sample.\u003c/strong\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cp\u003eAdditional information were coded and entered using Kobotoolbox software, and the data were analyzed using Stata 16 software.\u003c/p\u003e\n \u003cp\u003eCategorical variables were summarized in terms of absolute numbers and proportions. Continuous quantitative variables were summarized as the mean with standard deviation (SD) or as the median with the 25th and 75th percentiles, depending on whether the distribution was symmetrical or asymmetrical.\u003c/p\u003e\n \u003cp\u003eFirst, we carried out an initial binary analysis with long-term survival as the \u0026apos;survival/death\u0026apos; dependent variable. For this analysis, we have included all living subjects (seen and moved) and deceased subjects. Proportions were compared using Pearson\u0026apos;s chi-squared test or Fisher\u0026apos;s chi-squared test, depending on the conditions of application. Means and medians were compared using Student\u0026apos;s parametric test or the non-parametric Wilcoxon-Mann-Whitney test, respectively.\u003c/p\u003e\n \u003cp\u003eSecond, we performed a survival analysis taking into account the timing. For the survival analysis, time 0 was the date of discharge from the HPL. Patient follow-up time was calculated in years by subtracting the date of discharge from the date of final outcome (alive or dead). For the alive subjects that moved, we have derived the date of survival on the basis of information provided by the victims\u0026apos; relatives. We excluded patients who had been lost from sight due to lack of information regarding their survival after discharge from hospital. We compared their childhood parameters with those of children for whom we had survival information, in order to assess their impact on outcomes. A Kaplan Meier curve was used to estimate the survival function based on survival time data and the log-rank test was used to compare the curves from different groups. Cox regression was used to determine the proportional risks associated with long-term death. To handle the collinearity between the variables of therapeutic failure and the duration of oedema melting (\u0026lt;\u0026thinsp;30 days and \u0026gt;\u0026thinsp;30 days), two distinct models were constructed. In the first model, we adjusted for therapeutic failure, age, sex, vaccination status and anthropometric parameters (height, weight, and brachial circumference). In the second model, In model 2, \u0026quot;therapeutic failure\u0026quot; has been replaced by \u0026quot;duration of oedema\u0026quot;, and we have kept all the remaining confounding factors. The hypothesis of proportionality of the risks of instantaneous death (Proportional Hazards\u0026thinsp;=\u0026thinsp;PH model) was verified by the ln(-ln(S(t)) curves. The adjusted HR (Hazard Ratio) is followed by the p-value of the Wald.\u003c/p\u003e\n \u003cp\u003eFor all these analyses, we set a type I error threshold (alpha) of 5%.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSOCIO-DEMOGRAPHIC AND CLINICAL CHARACTERISTICS OF PATIENTS\u003c/h2\u003e \u003cp\u003eThe socio-demographic and clinical characteristics of our patients are described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The average age of the population at admission was approximately 46 months, with a slight male predominance (55.9%). These children came from households with a median size of six and a median number of deceased children of one. Over two-thirds of the study sample had edema, with nearly three-quarters of them limited to the feet. A median duration of seven days was observed for oedema to melt, with 6.8% of subjects taking over 30 days. Most subjects (67.5%) had a history of kwashiorkor. Almost half had received WHO standard therapeutic milk, and the median length of hospitalization was 23 days, with 9.5% of cases of therapeutic failure.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of our patients admitted to the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumbers (proportions)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Median (P25; P75)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex (n\u0026thinsp;=\u0026thinsp;1371 and missing\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e605 (44.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e766 (55.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at admission (months) (n\u0026thinsp;=\u0026thinsp;1349 and missing\u0026thinsp;=\u0026thinsp;29)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e46.58\u0026thinsp;\u0026plusmn;\u0026thinsp;30.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometry at admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (grams) (n\u0026thinsp;=\u0026thinsp;1251 \u003cb\u003eand missing\u0026thinsp;=\u0026thinsp;127\u003c/b\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e9565.43\u0026thinsp;\u0026plusmn;\u0026thinsp;3495.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSize (cm) (n\u0026thinsp;=\u0026thinsp;1340 \u003cb\u003eand missing\u0026thinsp;=\u0026thinsp;38\u003c/b\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e82.15\u0026thinsp;\u0026plusmn;\u0026thinsp;12.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrachial circumference (mm) (n\u0026thinsp;=\u0026thinsp;1269 \u003cb\u003eand missing\u0026thinsp;=\u0026thinsp;109\u003c/b\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e128.09\u0026thinsp;\u0026plusmn;\u0026thinsp;18.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of oedema (n\u0026thinsp;=\u0026thinsp;1362 and missing\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e443 (32.53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e919 (67.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of oedema (n\u0026thinsp;=\u0026thinsp;906 and missing\u0026thinsp;=\u0026thinsp;13)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn the foot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e657 (72.52%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (4.75%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneralized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e206 (22.74%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMelting time (days) (n\u0026thinsp;=\u0026thinsp;837 and missing\u0026thinsp;=\u0026thinsp;82)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e7 (5; 13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of melting (n\u0026thinsp;=\u0026thinsp;1280 and missing\u0026thinsp;=\u0026thinsp;98)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo oedema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e443 (34.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e780 (60.94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57 (4.45%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin J0 (n\u0026thinsp;=\u0026thinsp;941 and missing\u0026thinsp;=\u0026thinsp;437)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.91 (1.47; 2.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of SAM (n\u0026thinsp;=\u0026thinsp;1042 and missing\u0026thinsp;=\u0026thinsp;336)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKwashiorkor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e703 (67.47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlump\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (11.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223 (21.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination schedule (n\u0026thinsp;=\u0026thinsp;1236 and missing\u0026thinsp;=\u0026thinsp;142)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e912 (73.79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncomplete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84 (6.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (19.42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutrition treatment (n\u0026thinsp;=\u0026thinsp;881 and missing\u0026thinsp;=\u0026thinsp;497)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221 (25.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF75/F100 milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417 (47.33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCow's milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e243 (27.58%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of hospital stay (days) (n\u0026thinsp;=\u0026thinsp;1335 and missing\u0026thinsp;=\u0026thinsp;43)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e23 (15; 33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTherapeutic failure (n\u0026thinsp;=\u0026thinsp;1335 and missing\u0026thinsp;=\u0026thinsp;43)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1208 (90.49%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (9.51%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSD: Standard deviation; P25: Percentile 25; P75: Percentile 75; cm: centimeter; mm: millimeter.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eComparison of sociodemographic and clinical characteristics of patients in relation to long-term mortality\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e compares the characteristics during hospitalization between the two groups (deceased vs alive as adults) in univariate analyses. In comparison with the patients who were still alive deceased patients had more often a therapeutic failure during hospitalization and had a longer duration of hospitalization. In subjects with oedema, deceased subjects had more often an oedema that has taken a longer time to melt. These differences were significant. The other characteristics did not differ significantly in the two groups (deceased vs alive as adults).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of sociodemographic and clinical characteristics of our patients in relation to long-term survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCurrent status\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c5\" namest=\"c4\" rowspan=\"2\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDeceased\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex (n\u0026thinsp;=\u0026thinsp;930 and missing\u0026thinsp;=\u0026thinsp;5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.357*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e452 (55.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (60.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at admission (months) (n\u0026thinsp;=\u0026thinsp;912 and missing\u0026thinsp;=\u0026thinsp;23)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.51\u0026thinsp;\u0026plusmn;\u0026thinsp;31.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.89\u0026thinsp;\u0026plusmn;\u0026thinsp;32.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.602**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometry at admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (grams) (n\u0026thinsp;=\u0026thinsp;850 and missing\u0026thinsp;=\u0026thinsp;85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9581.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3490.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9283.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3838.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.411**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSize (cm) (n\u0026thinsp;=\u0026thinsp;910 and missing\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.33\u0026thinsp;\u0026plusmn;\u0026thinsp;12.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.25\u0026thinsp;\u0026plusmn;\u0026thinsp;13.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.109**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrachial circumference (mm) (n\u0026thinsp;=\u0026thinsp;864 and missing\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128.67\u0026thinsp;\u0026plusmn;\u0026thinsp;18.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126.48\u0026thinsp;\u0026plusmn;\u0026thinsp;21.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.268**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePresence of oedema (n\u0026thinsp;=\u0026thinsp;921 and missing\u0026thinsp;=\u0026thinsp;14)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e534 (66.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (70.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.386*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of oedema (n\u0026thinsp;=\u0026thinsp;607 and missing\u0026thinsp;=\u0026thinsp;11)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.958*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn the foot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e377 (71.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (73.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (3.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneralized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e127 (24.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (22.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMelting time (days) (n\u0026thinsp;=\u0026thinsp;568 and missing\u0026thinsp;=\u0026thinsp;50)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (5; 12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (5; 16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.256***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of melting (n\u0026thinsp;=\u0026thinsp;871 and missing\u0026thinsp;=\u0026thinsp;64)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo oedema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268 (35.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (30.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e468 (61.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (60.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (2.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (8.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of SAM (n\u0026thinsp;=\u0026thinsp;687 and missing\u0026thinsp;=\u0026thinsp;248)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.112*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKwashiorkor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413 (69.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (62.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarasmus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (11.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (8.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (19.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (28.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNutrition treatment (n\u0026thinsp;=\u0026thinsp;612 and missing\u0026thinsp;=\u0026thinsp;323)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.295*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124 (23.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (27.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eF75/F100 milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e267 (49.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (54.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCow's milk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147 (27.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (18.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination schedule (n\u0026thinsp;=\u0026thinsp;692 and missing\u0026thinsp;=\u0026thinsp;243)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.469*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated/Not up to date\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e177 (23.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (22.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of hospital stay (days) (n\u0026thinsp;=\u0026thinsp;894 and missing\u0026thinsp;=\u0026thinsp;41)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (15; 32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (18; 41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTherapeutic failure (n\u0026thinsp;=\u0026thinsp;905 and missing\u0026thinsp;=\u0026thinsp;30)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (8.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (17.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSAM: Severe acute malnutrition; MAM: Moderate acute malnutrition; cm: centimeter; mm: millimeter; dL: deciliter; g: gramme; F75: Therapeutic milk 75mg/100ml; F100: Therapeutic milk 100mg/100ml. * Pearson chi-square test; ** Student test; *** Non-parametric Wilcoxon Man-Whitney test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eApart from the vaccination status, no significant differences were observed between subjects traced and subjects lost from sight (supplementary Table\u0026nbsp;1 in appendix)\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRelationship between treatment failure and oedema melting with long-term survival\u003c/h2\u003e \u003cp\u003eFigure 2 displays the Kaplan-Meier curve by therapeutic failure Patients with therapeutic failure have significantly lower survival than those without therapeutic failure (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2: Kaplan-Meier survival estimates\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFigure 3 shows the Kaplan-Meier curve by the duration of oedema melting. Patients with a longer duration of oedema melting (more than 30 days) have a poorer survival compared with those whose oedema melted before 30 days and those who did not have oedema. However, this difference was not statistically significant (P\u0026thinsp;=\u0026thinsp;0.213).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3: Kaplan-Meier survival estimates\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eINSTANTANEOUS DEATH PREDICTORS\u003c/h2\u003e \u003cp\u003eFor both models, the PH condition was satisfied (supplementary Table\u0026nbsp;2 in appendix). The instantaneous risk of death was significantly higher in patients whose oedema had melted for more than 30 days and in those whose treatment had failed. However, sex, anthropometry at admission, immune status and age at onset of malnutrition showed no statistically significant influence on the instantaneous risk of death. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of instantaneous death\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR aj (IC 95%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eHR aj (IC 95%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1 result (n\u0026thinsp;=\u0026thinsp;640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eModel 2 result (n\u0026thinsp;=\u0026thinsp;615)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27 (0.80; 2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.17 (0.73; 1.86)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at admission (months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.99; 1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.01 (0.99; 1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthropometry at admission\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (grams)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.99; 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.00 (0.99; 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSize (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.94; 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.96 (0.93; 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrachial circumference in mm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99 (0.98; 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.99 (0.98; 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of melting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot included in model 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo oedema\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.99 (0.59; 1.66)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 30 days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.81 (1.12; 7.03)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTherapeutic failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNot included in model 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.98 (1.07; 3.67)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVaccination schedule\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaccinated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.36 (0.75; 2.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.68 (0.89; 3.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot vaccinated/Not up to date\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHRnaj: Hazard Ratio unadjusted; HRaj: Hazard Ratio adjusted; F75: Therapeutic milk 75mg/100ml; F100: Therapeutic milk 100mg/100ml. Model 1 result: we adjusted for therapeutic failure, age, sex, vaccination status and anthropometric parameters (height, weight, and brachial circumference); Model 2 result: we adjusted for duration of oedema melting,age, sex, vaccination status and anthropometric parameters (height,weight and brachial circumference).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe aim of this study was to identify in-hospital clinical and therapeutic predictors of long-term risk of death based on secondary data from a cohort of former SAMs in eastern DRC (Lwiro Follow up Study).\u003c/p\u003e \u003cp\u003eThe results show that delayed oedema melting beyond thirty days and therapeutic failure are significantly associated with an increased risk of long-term death after an episode of SAM.\u003c/p\u003e \u003cp\u003eIn relation to the existing literature, this study is one of the few, if not the first, in a low-income country to have reconstituted a very large cohort of subjects with a history of SAM and to have followed them for a long time after discharge from hospital in a context of endemic malnutrition. The novelty in this study lies in the fact that it included many subjects with a history of kwashiorkor (67.5%), it examined subjects who had continued to live in an unfavorable environment throughout their lives and it assessed several clinical parameters (including the duration of oedema) and various anthropometric measurements on the occurrence of long-term death.\u003c/p\u003e \u003cp\u003eIn terms of long-term survival, it was observed that the risk of death was significantly higher in children whose oedema melted in more than thirty days than in those whose oedema melted in less than thirty days (HR: 2.79 IC95%: 1,13; 6.91). These results are in line with the literature, because although kwashiorkor remains an enigma (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), oxidative stress and disruption of the intestinal microbiome are among the possible causes of oedema and are present in kwashiorkor (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Oxidative stress, which can cause significant cellular damage and contribute to various health problems and the ageing process, could have several harmful effects over time (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Diarrheal diseases, which are among the causes of death in individuals who developed malnutrition during childhood (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), may be due to a disturbance in the intestinal microbiota present during an episode of Kwashiorkor (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSome studies, including those by M. Kerac et al. and Bwakura et al., found that patients who developed marasmus during hospitalization were at a much higher risk of death in the year following discharge from the hospital. However, the duration of edema resolution was not taken into account in their studies (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Nevertheless, it is important to note that Bitwe et al. had suggested classifying individuals at risk of death during hospitalization when they present with nutritional edema (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe cases of therapeutic failure had a proportional risk of long-term death four times higher (HR: 4.07 and IC95%: 1.29; 12.80) than those without a therapeutic failure. Cases of therapeutic failure suggest a long hospital stay with a high probability of having developed untreated complications which, in the medium term, increase the risk of serious infections, potentially fatal for patients. According to Mwene-Batu et al, the main causes of death after discharge from therapeutic feeding centers among patients treated for SAM were infectious diseases, including malaria and respiratory infections (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTreatment failures can also result from acquired immunosuppression due to other diseases such as tuberculosis and HIV, particularly in this study\u0026rsquo;s context (\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Similar studies within the region have reported a low prevalence of HIV (2%) among malnourished children (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), these factors could also contribute significantly to the high proportion of deaths among children who have experienced treatment failure, as the medium-term survival of immunocompromised children with malnutrition generally remains limited after discharge (\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Unfortunately, serological data for these malnourished children were not collected.\u003c/p\u003e \u003cp\u003eHowever, in Zambia, Bwankura et al. were unable to identify long hospital stays as a risk factor for short-term death after an episode of SAM (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This disparity could be explained by the fact that 43.6% of patients discharged from health facilities in Zambia had a current SAM. This would explain the fact that many of the patients discharged to these facilities would not have been able to obtain authorization for discharge to the HPL.\u003c/p\u003e \u003cp\u003eThe present study has some methodological limitations that should be considered in interpreting the results. Essentially, the subjects for this study were chosen based on the Lwiro cohort of malnourished individuals. However, nearly a third (32.15%) of the subjects were not located during the identification process for this study, 11 to 30 years after their discharge from the hospital, making it impossible to assess their long-term outcomes. Additionally, some patients were excluded because their medical records were incomplete.\u003c/p\u003e \u003cp\u003eWe could not include subjects lost from sight in our survival analyses because we have no data on their outcome after hospital discharge. By comparing their characteristics with those of the traced subjects, we found that only vaccination status was statistically different between the two groups (p\u0026thinsp;=\u0026thinsp;0,004). Our results showed that a large proportion of \"lost to follow-up\" subjects had incomplete vaccination status compared with traced subjects. We have to accept this limitation as we are unable to demonstrate how this would influence the survival analysis results.\u003c/p\u003e \u003cp\u003eFurthermore, the Lwiro database, which this study is based upon, did not include data on possible confounding factors such as demographic data concerning the beginning of life, the crucial 1000 days and data on the evolution of these children from discharge from hospital to the time of our identification, which could play a role in the different associations of long-term survival with the other variables.\u003c/p\u003e \u003cp\u003eFinally, another major limitation of this study is the lack of serological data on malnourished children, which prevents us from making an exhaustive assessment of the prevalence of HIV and tuberculosis in this population. This lack of data makes it difficult to precisely determine the impact of these diseases on the therapeutic failures observed.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eSAM during childhood has harmful long-term effects on the patients wellbeing and on their survival. Donors and policymakers wishing to reduce the burden of SAM and improve management should pay particular attention to the risk factors identified in this study in order to improve management and long-term survival. Effective post-hospitalization follow-up is crucial to ensure the long-term success of SAM management. Nonetheless, a more intensive level of follow-up is required for patients who have not responded well to treatment and whose edema has resolved late during their hospital stay. Finally, the study\u0026rsquo;s results show that the fight against SAM and its consequences must remain a public health priority.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAM \u0026nbsp; \u0026nbsp; : Acute malnutrition\u003c/p\u003e\n\u003cp\u003eBP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;: Brachial perimeter\u003c/p\u003e\n\u003cp\u003eCHO \u0026nbsp; \u0026nbsp;: Community Health Officer\u003c/p\u003e\n\u003cp\u003eCNRS \u0026nbsp;: Natural Sciences Research Centre\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDRC \u0026nbsp; \u0026nbsp;: Democratic Republic of Congo\u003c/p\u003e\n\u003cp\u003eHEM \u0026nbsp; : High-Energy Milk\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHIV \u0026nbsp; \u0026nbsp; : Human Immunodeficiency Virus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHMMIC\u0026nbsp;:\u0026nbsp;High- and middle-income countries.\u003c/p\u003e\n\u003cp\u003eHPL \u0026nbsp; \u0026nbsp; : Lwiro Paediatric Hospital\u003c/p\u003e\n\u003cp\u003eHR \u0026nbsp; \u0026nbsp; \u0026nbsp; : Hazard Ratio\u003c/p\u003e\n\u003cp\u003eMAM \u0026nbsp;: Moderate Acute Malnutrition\u003c/p\u003e\n\u003cp\u003eNASH\u0026nbsp;:\u0026nbsp;Non-alcoholic steatohepatitis\u003c/p\u003e\n\u003cp\u003eNTM \u0026nbsp; : Non-transmissible disease\u003c/p\u003e\n\u003cp\u003eOR \u0026nbsp; \u0026nbsp; \u0026nbsp; : Odds Ratio\u003c/p\u003e\n\u003cp\u003eP25 \u0026nbsp; \u0026nbsp; \u0026nbsp;: Percentile 25\u003c/p\u003e\n\u003cp\u003eP75 \u0026nbsp; \u0026nbsp; \u0026nbsp;: Percentile 75\u003c/p\u003e\n\u003cp\u003ePH \u0026nbsp; \u0026nbsp; \u0026nbsp;: Proportional Hazards\u003c/p\u003e\n\u003cp\u003eSAM \u0026nbsp; \u0026nbsp;: Severe acute malnutrition\u003c/p\u003e\n\u003cp\u003eSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;: Standard deviation\u003c/p\u003e\n\u003cp\u003eSSA \u0026nbsp; \u0026nbsp; : Sub-Saharan Africa\u003c/p\u003e\n\u003cp\u003eUNICEF \u0026nbsp; \u0026nbsp;: United Nations Children\u0026apos;s Fund\u003c/p\u003e\n\u003cp\u003eWHO \u0026nbsp; : World Health Organization\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWHR \u0026nbsp;: Weight-height ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the ethics committee of the Catholic University of Bukavu. All procedures were carried out in accordance with the ethical standards of the institutional ethics committee and the 1964 Declaration of Helsinki and its subsequent amendments. Sign informed consent was obtained from respondent himself if he was an adult, or by the subject\u0026apos;s parent in the case of minors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose\u0026nbsp;and\u0026nbsp;no competing interests to declare that are relevant to the content of this article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJCL, GB, PM and PD contributed to the conception and design of the study. Material preparation, data collection and analysis were carried out by JCL, SLM, ANG, AN, CC, CZC and BBB. The first draft of the manuscript was written by JCL, while PM, SLM, ANG, AN and RB commented on earlier versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization, United Nations Children\u0026rsquo;s Fund (\u0026lrm;UNICEF)., International Bank for Reconstruction and Development/The World Bank. Levels and trends in child malnutrition: UNICEF/WHO/The World Bank Group joint child malnutrition estimates: key findings of the 2023. mai 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNg M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, et al. 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Childhood tuberculosis and malnutrition. J Infect Dis 15 d\u0026eacute;c. 2012;206(12):1809\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFergusson P, Tomkins A. HIV prevalence and mortality among children undergoing treatment for severe acute malnutrition in sub-Saharan Africa: a systematic review and meta-analysis. Trans R Soc Trop Med Hyg juin. 2009;103(6):541\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChinkhumba J, Tomkins A, Banda T, Mkangama C, Fergusson P. The impact of HIV on mortality during in-patient rehabilitation of severely malnourished children in Malawi. Trans R Soc Trop Med Hyg juill. 2008;102(7):639\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMody A, Bartz S, Hornik CP, Kiyimba T, Bain J, Muehlbauer M, et al. Effects of HIV infection on the metabolic and hormonal status of children with severe acute malnutrition. PLoS ONE. 2014;9(7):e102233.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBwakura-Dangarembizi M, Dumbura C, Amadi B, Ngosa D, Majo FD, Nathoo KJ et al. Risk factors for postdischarge mortality following hospitalization for severe acute malnutrition in Zimbabwe and Zambia. Am J Clin Nutr. 11 mars. 2021;113(3):665\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Severe acute malnutrition, Childhood, long-term mortality and Lwiro cohort","lastPublishedDoi":"10.21203/rs.3.rs-3791050/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3791050/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aim of this study was to identify the factors associated with long-term mortality in subjects treated for SAM in childhood 11 to 30 years after nutritional rehabilitation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReferring to the data collected from December 2017 to November 2018 from the Lwiro cohort; we updated this database with additional data. Records of subjects admitted for SAM between 1988 and 2007 were extracted from the archives of the pediatric hospital in Lwiro, South Kivu, Democratic Republic of Congo (DRC). A multivariate Cox proportional hazards regression was used to identify factors associated with long-term mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 816 subjects were found to be alive and 119 died. The mean age at admission to nutritional rehabilitation was 46 months. Around two third of the subjects had edema, and in 6,8% of these subjects, edema had subsided after thirty days in hospital. Almost one in ten (9.5%) cases of SAM resulted in treatment failure. The risk of death was significantly higher in subjects with a history of therapeutic failure (hospital stay ≥ 45 days) and in those whose edema had melted late (≥ 30 days) during their hospitalization, with respective risks of HR = 1.98 (1.07; 3.67) and 2.81 (1.12; 7.03) respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGood follow-up after hospital discharge is imperative to ensure the success of SAM management in the medium and long term. However, this follow-up must be more intensive in patients who have failed treatment and whose edema has melted late during hospitalization.\u003c/p\u003e","manuscriptTitle":"Edema melting length and therapeutic failure during hospitalization as factors associated with long-term mortality after basic treatment of severe acute malnutrition: Lwiro cohort follow-up in the Eastern Democratic Republic of the Congo","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 14:59:30","doi":"10.21203/rs.3.rs-3791050/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-06T18:25:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-27T21:45:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-06T15:12:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2024-10-01T08:57:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-19T10:34:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"135582011264673441420525768676041483572","date":"2024-09-19T08:36:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"33871924720741258820293215411989505530","date":"2024-09-18T17:41:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"253888899447701450679381631349201734884","date":"2024-05-05T06:06:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154407320758976386408096091540495643599","date":"2024-05-02T19:12:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-22T09:11:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-01-03T13:46:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-12-29T14:28:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-29T14:28:42+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nutrition","date":"2023-12-22T09:07:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nutrition","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nutn","sideBox":"Learn more about [BMC Nutrition](http://bmcnutr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nutn/default.aspx","title":"BMC Nutrition","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82a8daaa-36cc-4cdc-8eab-65a569ac39fc","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T16:07:10+00:00","versionOfRecord":{"articleIdentity":"rs-3791050","link":"https://doi.org/10.1186/s40795-025-01173-4","journal":{"identity":"bmc-nutrition","isVorOnly":false,"title":"BMC Nutrition"},"publishedOn":"2025-10-14 15:57:12","publishedOnDateReadable":"October 14th, 2025"},"versionCreatedAt":"2024-01-03 14:59:30","video":"","vorDoi":"10.1186/s40795-025-01173-4","vorDoiUrl":"https://doi.org/10.1186/s40795-025-01173-4","workflowStages":[]},"version":"v1","identity":"rs-3791050","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3791050","identity":"rs-3791050","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}