Prognostic Factors and Survival Outcomes of Preterm Infants: A Cohort Study at the University Clinics of Graben, Butembo

Prognostic Factors and Survival Outcomes of Preterm Infants: A Cohort Study at the University Clinics of Graben, Butembo | 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 Prognostic Factors and Survival Outcomes of Preterm Infants: A Cohort Study at the University Clinics of Graben, Butembo Junior Kasomo, Apollinaire Saasita, Roland Muyisa, Mamy Uliwabo, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7242035/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The management of preterm births is still a major concern in different health facilities in Butembo, a town in the eastern part of the Democratic Republic of Congo. This study aimed to describe the clinical progress and the survival rate of preterm births managed at the University Clinics of Graben (UCG) to improve the quality of care. Methods This was a cohort study involving preterm births managed at the UCG. The study was performed from January 2021 to May 2023. The information was gathered from preterm birth files and analyzed using Excel to determine the survival rate. Results The most common clinical complications (prognostic factors) observed in preterm birth were infections (87.8%), hypothermia (81.6%), respiratory distress (79.6%), and anemia (57.1%), most of which occurred in the early neonatal period. The total survival rate was 55.1%, with the survival curve exhibiting a decline in the first three days and a subsequent increase from the seventh to the eleventh day of follow-up. The Mantel test at a confidence level of 95% (M = 24.51279) revealed that death was early in preterm births whose gestational age was less than 32 weeks. Conclusion Abdominal bloating, enterocolitis, and hemorrhage were the complications that worsened the prognosis of preterm births. Therefore, there is a dire need to improve both the prevention measures and the treatment of preterm births in this part of the Democratic Republic of Congo. preterm births morbidity and mortality prognostic survival analysis Figures Figure 1 Figure 2 Figure 3 Background According to the World Health Organization (WHO), preterm birth is defined as a birth that occurs before 37 Weeks of Amenorrhea (WA) or 259 days after the first day of the last menstrual period. Generally, a distinction is made between late preterm (birth between 34 and 36 completed WA), moderate preterm (32 to 34 WA), very preterm (28 to 32 WA), and extremely preterm (inferior to 28 WA) ( 1 , 2 ). Preterm birth is a major concern in neonatology because of its very high morbidity and mortality. In the region, specifically in North Kivu in the Democratic Republic of the Congo (DRC), care of preterm babies remains difficult because of limited resources. The number of preterm births is estimated at 15 million each year worldwide, which represents 11% of living births ( 3 ). About 85% of babies born before 37 weeks of pregnancy were late preterm or moderate preterm, 10% were very preterm, and 5% were extremely preterm ( 4 – 7 ). Sixty percent of these births occur in South Asia and sub-Saharan Africa, the largest birth basins in the world ( 6 , 8 ) but also in poverty. While the number of preterm infants surviving the neonatal period continues to rise, neonatal morbidity is still high, and there are concerns about medium- and long-term prognosis ( 7 , 9 ). Preterm births, complications during childbirth, infections, and birth defects are the causes of most neonatal deaths. Indeed, the early neonatal mortality rate is an indicator of the quality of care and the level of economic and social development of a population ( 10 ). Preterm birth is the leading cause of neonatal mortality worldwide, with approximately 3.1 million deaths per year directly related to it ( 11 ). A WHO-supported global study estimated that death from preterm birth accounted for 15.4% of total under-5 mortality, making it the leading cause in this age category ( 12 ). Deaths related to preterm birth concern both developing and developed countries ( 11 , 13 , 14 ). In developing countries, less than 10% of children are born in the 28th week of gestation, and this figure barely reaches 50% in the 34th week of pregnancy ( 5 , 15 ), with survival rates increasing with gestational age ( 16 , 17 ). The neonatology department of the University Clinics of Graben (UCG) admits preterm babies referred from the surrounding health facilities without medical equipment for monitoring, respiratory assistance, and thermal protection. In addition, the department is not equipped for parenteral nutrition of proteins and lipids. Thus, in the context of improving the quality of care in UCG and reducing neonatal mortality, we conducted this study to describe the clinical course and the probability of survival of children born prematurely in the UCG, in the east of the Democratic Republic of Congo (DRC), and finally to improve care and minimize complications. Methodology The present study was carried out at UCG located in the East of the DRC, North Kivu province, city of Butembo in the urban-rural health zone of Butembo. The study population consisted of all preterm children followed at UCG for management. The sheets of preterm children and the collection grid designed in Excel were used to collect the data. The study was descriptive of the cohort of preterm children treated in a period from January 2021 to May 2023. The literature search was conducted using the Medline and PubMed computer databases between 2010 and 2023. We consulted several review journals on the subject and supplemented the computerized search with a manual search of certain basic documents. To study the problem, we used the following variables: Sex (male or female), family address (urban or rural), siblings of the child, gestational age (in weeks of amenorrhea), birth weight (in grams), temperature at admission (in degrees Celsius), the clinical course (prognostic factors) of prematurity from day to day, time zero being the day or time of birth, and the mode of discharge from hospital (survivor or deceased). Due to the small size of the study population, survival analysis was performed using the KAPLAN-MEIR method to estimate the probability of survival of preterm infants, day after day ( 18 – 20 ). Since the probability of survival at time 0 (at birth) is equal to 1, during the first day it was calculated by dividing the number of survivors by the total number of preterm babies at the beginning of the day; At the end of the first day, this probability was obtained by multiplying the probability of time 0 by the probability of survival during the first day. The probability of survival on the second day was calculated by dividing the number of survivors on the same day by the number of preterm infants at the beginning of the day (day 2); The probability of survival at the end of day 2 was obtained by multiplying the probability of survival at the end of the previous day (day 1) by the probability of survival during the day (day 2). The rest of the calculations were done by analogy and in an automatic way using the Excel 2013 software; with the values of the probability of survival at the end of the day, we generated the different survival curves using the same software. Considering gestational age, we subdivided our sample into two groups to confirm or refute the hypothesis of equal survival in these groups by using the Mantel statistical test; the first group (A) consisted of preterm infants with GA between 32 weeks and 37 weeks of gestation and the second group consisted of GA less than 32 weeks of age. Results During our study period, UCG recorded 49 cases of preterm infants, 18 boys (36.7%) and 31 girls (63.3%). Thirty-three cases (67.3%) were from urban areas and 16 cases (32.7%) were from rural areas. The description of the quantitative variables in Table 1 shows a mean of 31.9 (SD = 3.3). Table 1 Description of quantitative variables Variables Number Minimum Maximum Mean Standard deviation (SD) Gestational age in WA 49 25.0 36.0 31.9 3.3 Birth weight 49 800.0 3300.0 1549.3 496.8 Temperature at admission 49 32.0 37.7 34.8 1.5 Siblings 49 1.0 6.0 2.3 1.6 Legend: WA = weeks of amenorrhea In Table 2, we describe the evolution day by day of preterm birth followed at the University Clinics of Graben. From Table 3, the survival probability is 55.1% whereas the death risk is 44.9%. Table 3 Probability of survival and risk of death in preterm infants Hospital exit modality Frequence % Survivals 27 55.1 Deaths 22 44.9 Total 49 100.0 Legend: %= percentage Table 4 and Fig. 1 analyze the daily survival of preterm infants managed at the University Clinics of Graben. Table 4 Analysis of daily survival of preterm infants managed at the University Clinics of Graben. Day Frequence Deaths Survivals Probability of survival per day Probability of survival at the end of the day Day1 49 2 47 0.96 0.96 Day2 47 3 44 0.94 0.90 Day3 44 5 39 0.89 0.80 Day4 39 1 38 0.97 0.78 Day5 38 0 38 1.00 0.78 Day6 38 0 38 1.00 0.78 Day7 38 0 38 1.00 0.78 Day8 38 2 36 0.95 0.73 Day9 36 2 34 0.94 0.69 Day10 34 1 33 0.97 0.67 Day11 33 1 32 0.97 0.65 Day12 32 1 31 0.97 0.63 Day13 31 0 31 1.00 0.63 Day14 31 0 31 1.00 0.63 Day15 31 0 31 1.00 0.63 Day16 31 1 30 0.97 0.61 Day17 30 0 30 1.00 0.61 Day18 30 0 30 1.00 0.61 Day19 30 0 30 1.00 0.61 Day20 30 0 30 1.00 0.61 Day21 30 1 29 0.97 0.59 Day22 29 1 28 0.97 0.57 Day23 28 0 28 1.00 0.57 Day24 28 0 28 1.00 0.57 Day25 28 0 28 1.00 0.57 Day26 28 0 28 1.00 0.57 Day27 28 0 28 1.00 0.57 Day28 28 0 28 1.00 0.57 Day29 28 0 28 1.00 0.57 Day30 28 0 28 1.00 0.57 Day31 28 0 28 1.00 0.57 Day32 28 0 28 1.00 0.57 Day33 28 0 28 1.00 0.57 Day34 28 1 27 0.96 0.55 Day35 27 0 27 1.00 0.55 Table 5 presents the probability of survival according to the gestational age in weeks of amenorrhea, and Fig. 2 presents curves of survival accordingly, and the application of the statistical Mantel (M) test. Table 5 Gestational age and survival of preterm infants at the UCG Gestational age Frequence Survivors % Inferior to 28 WA (extremely preterm) 7 0 0.0 28 WA − 31 WA + 6 days (very preterm) 14 5 35.7 32 WA − 33 WA + 6 days (moderate preterm) 8 4 50.0 34 WA − 36 WA + 6 days (late preterm) 20 2 90.0 Legend: WA = weeks of amenorrhea; %= percentage The calculated value of M (for the Mantel test) is 24.51279, superior to 3.84 at the confidence of 95%. In Table 6, there is presented the survival probability according to the birth weight of preterm infants, and Fig. 3 presents the curves of survival accordingly. Table 6 Survival and weight at birth Birth weight in grams Frequence Survival % Inferior to 1000 8 0 0.0 1000 to 1499 15 5 33.3 1500 and more 26 22 84.6 Legend: % = percentage Table 7 presents the influencing factors of survival of preterm births followed at the University Clinics of Graben. Table 7 Prognostic factors of preterm birth survival Prognostic factors Frequence Survivors % Enterocolitis 5 0 0.0 Abdominal distension 10 0 0.0 Hemorrhage 9 1 11.1 Respiratory distress 39 17 43.6 Temperature trouble 37 17 45.9 Glycemic trouble 12 6 50.0 Anemia 28 16 57.1 Infections 43 25 58.1 Jaundice 20 12 60.0 Vomiting 5 4 80.0 Legend: % = percentage Discussion This preliminary work is important because little data is available on the prognostic factors and survival of preterm infants in sub-Saharan African countries and in the Democratic Republic of the Congo. From the study results, the description of quantitative variables shows the mean gestational age of 31.9 ( 25 – 37 ) weeks, the mean birth weight of 1549.3 (800–3300) grams, the mean intake temperature of 34.8 (32.0 -37.8) degrees Celsius, and the mean sibling age of 2.3 ( 1 – 6 ). The average weight in our study is higher than that found in a study in Tunisia, where it was 1032 grams ( 21 ). This trend is due to the presence in our sample of obese preterm infants weighing 3300 grams from a diabetic woman. In another study in Côte d'Ivoire, the average weight of 1750 grams ( 22 ) was noted, a weight higher than that found in the present study. Most of our respondents were hypothermic, i.e., below the normal value (Standard Deviation 1.5C °C). Hypothermia in preterm infants is due to a decrease in thermogenesis (metabolic activity is reduced and takes longer to establish and the brown fat present from 26 weeks is in lower quantities) and an increase in heat loss (the thin thickness of the subcutaneous fatty tissue reduces the efficiency of vasoconstriction; the surface/volume ratio is increased, which facilitates discharge and the skin is immature and does not play its role as a barrier) ( 23 ). The problem of prematurity affects not only the delivery itself and how it affects the mother and child at this time, but also the permanent challenges they face during the neonatal period (early and late) in terms of survival, with particular attention to the resulting morbidities. the results of this study suggest that 87.8% of preterm infants developed the infection, with 71.4% occurring in the early neonatal period. In a study in Senegal, infectious and respiratory complications were the most common, occurring in most cases in the early neonatal period ( 24 ). In neonatology, infections are more pronounced in preterm infants due to several factors: an immature immune system, absence or low concentration of antibodies, an initially axenic organism subjected in a few days to massive contamination from the environment and personnel, and artificial ventilation ( 25 , 26 ). From this study's results, it appears that 81.6% of preterm infants had hypothermia during their stays, including 65.3% in the early neonatal period. In a study conducted in Cameroon, 71.2% of cases of hypothermia were observed ( 27 ), results similar to this study’s. Furthermore, the results of this study show that respiratory distress was observed in 79.6% of cases, with 65.3% of these cases occurring in the early neonatal period. A study conducted in Cameroon found 68.7% respiratory distress in premature babies weighing less than 1000g ( 27 ) while another one conducted in Tunisia found that 27% of preterm infants ( 21 ). Neonatal respiratory distress in preterm infants is related to several factors, including neonatal infection, surfactant insufficiency, immaturity of the respiratory center, imperforation of the choana, esophageal atresia, hiatal hernia, etc. Our results suggest that 57.1% of preterm infants developed anemia during their stays in the neonatal unit, including 30.6% in the early neonatal period. In a study in Côte d'Ivoire, the frequency of anemia was 25% ( 22 ). Another study in Cameroon reported a frequency of preterm anemia of 24.2% ( 27 ). Neonatal anemia is a common problem in preterm infants ( 27 , 28 , 38 ). They are more likely to suffer, as about 80% of iron reserves are accumulated during the last quarter of the year. This study reflects that the main complications of prematurity are infections, hypothermia, respiratory distress, and anemia. Another local study reported prematurity as a factor associated with early-onset neonatal infection ( 41 ). Torchin and his collaborators in their study suggest neurological complications, respiratory distress, digestive complications (enterocolitis and abdominal bloating), infectious complications, and ophthalmological complications (retinopathy of prematurity); In the case of extreme prematurity, respiratory distress is the most common complication ( 7 ). The other complications of prematurity observed during this study are respectively jaundice 40.8%, of which 8.1% in the early neonatal period; blood sugar disorder 24.5%, including 20.4% in the early neonatal period; abdominal bloating 20.4%, including 6.1% in the early neonatal period; hemorrhage 18.4%, of which 6.1% in the early neonatal period; enterocolitis 10.2%, of which 4.1% in the early neonatal period and vomiting 10.2% in late neonatal period. It is estimated that jaundice is present in just over half of term newborns and that it affects 80% of premature newborns; In the latter, hyperbilirubinemia is more frequent and its course more prolonged compared to the term newborn ( 29 , 30 ). The elevation of bilirubin is due to the increased destruction of red blood cells in the neonatal period as well as to the immaturity of the purification systems, particularly in the liver. In preterm infants, low birth weight is a factor that promotes hypoglycemia. This is correlated with insufficient glycogen and lipid stores (little adipose tissue), which deprives tissues of alternative substrates and increases tissue glucose demand ( 31 ). The risk of hypoglycemia is high with the occurrence of perinatal asphyxia and hypothermia, which increase the body's need for glucose ( 32 ). In a study in Cameroon, the frequency of necrotizing enterocolitis was reported to be 1.6% with a case fatality rate of 79.4% ( 33 ). In preterm infants, enterocolitis is a major cause of mortality and morbidity ( 34 ). Preterm birth remains a determining factor in the severity of intestinal atresia, the probable cause of abdominal bloating, and can also explain the occurrence of certain congenital anomalies; According to some authors, 1/3 of newborns with a digestive malformation are preterm babies ( 35 ). The diagnosis of necrotizing enterocolitis in preterm birth is a serious intestinal complication that must be monitored in neonatology. It is a condition in which there is significant inflammation of the intestinal lining that can lead to damage or perforation. Initially, this condition can cause vomiting, diarrhea, and considerable bleeding ( 33 , 34 ). The main results of this study suggest that the mortality rate of preterm infants is significantly high, and this is outrageously high in extremely preterm infants (GA 28 weeks or birth weight 1000g). The overall probability of survival of preterm infants was 55.1% (Table 3 ). A significant proportion of mortality occurred in the early neonatal period, the first three days of life, followed by the period from days 8 to 12 of life. The trend in deaths was only stabilized from the 13th day of life despite the few deaths recorded on the 16th, 21st, 22nd, and 34th days of life (Table 4 and Fig. 1 ). Compared to GA, survival was 90.0% in preterm infants (34 weeks–36 weeks + 6 days), 50.0% of average preterm infants (32 weeks–33 weeks + 6 days), 35.7% of very preterm infants (28 weeks), and 0.0% of preterm infants (28 weeks) (Table 5 ). Most of the preterm infants of GA inferior to 28 WA (6 of the 7) died during the early neonatal period, with the last survivor surviving to day 11 (Fig. 2 ). According to the result of the Mantel statistical test at the 95% confidence level (M = 24.51279, a value greater than 3.84), deaths occurred earlier in the group of preterm infants with GA less than 32 weeks of age (second group). Alluding to birth weight, the probability of survival was 84.6% in very preterm infants (1500g), 33.3% in very preterm infants (1000g − 1500g), and 0.0% in preterm infants (1000g) (Table 4 ). The last survivor weighing less than 1000g survived to the 11th day, with most deaths occurring during the early neonatal period (Fig. 3 ). The survival rate for premature babies improves as gestational age increases, although there are considerable differences between countries. At GA at 28 weeks, child survival is up to 90% in industrialized countries, while below 28 weeks of age, it is between 7% and 90%. For some countries, such as Japan, this probability increases to 34% between 22 and 24 weeks (3.36–38). Neonatal mortality is higher if the birth weight is less than 1000g( 4 , 7 ) and survival is close to 0% in developing countries ( 39 ). Data from a weight-based survival study of preterm infants suggested that survival improved for newborns weighing 1500g, with excellent survival for newborns weighing more than 2500g ( 40 ). Survival data for clinical complications in preterm infants revealed that the prognosis was poor for children who developed enterocolitis, abdominal bloating, and hemorrhage; the probability of survival was 0.0% (for the first two complications) and 11.1%, respectively. Enterocolitis is most commonly seen in preterm infants, with a survival rate of less than 10% in developing countries ( 34 ); It is one of the main causes of mortality in preterm babies, and its fatality varies between 30% and 40% in developed countries. For preterm infants who presented with respiratory distress, heat disorder, blood glucose disorder, anemia, infection, jaundice, and vomiting, the probabilities of survival were 43.6%, 45.9%, 50.0%, 57.1%, 58.1%, 60.0%, and 80.0%, respectively. Prematurity is characterized by insufficient reserves and immaturity of large ones, two phenomena that are at the root of all possible complications of premature infants. Delayed care and/or inadequate care negatively influence its probability of survival. Conclusion Prematurity is a major concern in neonatology because of its still very high morbidity and mortality. In the region, the care of premature babies remains difficult because of the very limited resources. Improved care will minimize complications and therefore increase the likelihood of survival. Abbreviations DRC = Democratic Republic of the Congo. UCG = University Clinics of Graben. WHO = World Health Organization, WA = Weeks of Amenorrhea, SD= standard deviation SD, GA = Gestational Age Declarations Acknowledgments Our acknowledgment to the LD English Club for helping in the translation of this article. Authors’ contributions JK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing – original draft, and writing– review & editing; AS: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing – original draft, and writing– review & editing; RM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing – original draft, and writing– review & editing; MU: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; LS: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; JK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; JM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; AK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; JM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; JW: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; FA: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; PV: supervision, validation, visualization, writing – original draft, and writing– review & editing; FM: supervision, validation, visualization, writing – original draft, and writing– review & editing; LS: supervision, validation, visualization, writing – original draft, and writing– review & editing. Ethical approval After approval of the research protocol by the Ethics Committee of the Catholic University of Graben in collaboration with the health authorities of the University Clinics of the Graben, we obtained permission to collect the data following the principles of scientific research. Anonymity and respect for human dignity have been respected. All methods were performed in accordance with relevant guideline. Consent for participation Obtained from all participants’ parents or guardians. Data availability All important data are described in the article. Funding No funding was obtained. Consent for publication The consent for publication was obtained from all authors. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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Intestinal atresia in Niger: clinical presentation, management and prognosis. HEALTH SCIENCES AND DISEASE [Internet]. 2023;24(4):19‑22. Disponible sur: www.hsd-fmsb.org Guo X, Li X, Qi T, Pan Z, Zhu X, Wang H, et al. A birth population-based survey of preterm morbidity and mortality by gestational age. BMC Pregnancy Childbirth. 1 déc 2021;21(1). Ancel PY, Goffinet F, Kuhn P, Langer B, Matis J, Hernandorena X, et al. Survival and morbidity of preterm children born at 22 through 34 weeks’ gestation in France in 2011 results of the EPIPAGE-2 cohort study. JAMA Pediatr. 1 mars 2015;169(3):230‑8. Harrison MS, Goldenberg RL. Global burden of prematurity. Vol. 21, Seminars in Fetal and Neonatal Medicine. W.B. Saunders Ltd; 2016. p. 74‑9. Nlend AEN, Zeudja C, Motaze AN, Suzie M, Lydie N. Immediate neonatal outcome of extreme prematurity: retrospective data of a neonatal unit in Yaounde, Cameroon from 2009 to 2013. Pan Afr Med J. 2015;20:321. Morisaki N, Togoobaatar G, Vogel JP, Souza JP, Rowland Hogue CJ, Jayaratne K, et al. Risk factors for spontaneous and provider-initiated preterm delivery in high and low Human Development Index countries: a secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health. BJOG. 2014;121 Suppl 1:101‑9. Saasita A, Kaghoma B, Muyisa R, Tayivweka JM, Mughania T, Kaliremwira R, et al. Incidence and risk factors of early-onset neonatal infections in Butembo: case of Katwa Health Zone from January 2020 to December 2022. BMC Pediatr [Internet]. 2025;25. Available from: https://doi.org/10.1186/s12887-025-05774-7 Table 2 Table 2 is available in the Supplementary Files section. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7242035","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495332510,"identity":"43f62214-d0f8-4129-816d-e3fe232d3dd8","order_by":0,"name":"Junior Kasomo","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Junior","middleName":"","lastName":"Kasomo","suffix":""},{"id":495332511,"identity":"b74997b9-fc61-42af-9f51-98267e9a0985","order_by":1,"name":"Apollinaire Saasita","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Apollinaire","middleName":"","lastName":"Saasita","suffix":""},{"id":495332512,"identity":"bcd9bf82-6a40-449d-87e8-458f251fe9d7","order_by":2,"name":"Roland Muyisa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYFAC5gYGBjYQDeJUgBggEbyAEVnLGRCDkVgtYHYbTAQPMG9vbPxcULYtccNx9oefbs6rjeZvB2r5UbENpxaZMwebpWecu5244TCPsXTutuO5Mw4zNjD2nLmNU4uERGKDNG8bWAsDUMux3AagFmbGNrxamn9DtLA//p0751jufCK0tEFtYTCTzm2oyd1AUAvPwTZrnnO3jWce5jGzzjl2IHcjUMtBvH5hbz58m6fstmzf+eOPb+fU1OXOO3/44IMfFbi1wIHCATB1GEweIKweCOQbwFQdUYpHwSgYBaNgZAEA16JgGlh9yjEAAAAASUVORK5CYII=","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":true,"prefix":"","firstName":"Roland","middleName":"","lastName":"Muyisa","suffix":""},{"id":495332513,"identity":"68d5ae88-0ab3-4110-87cb-995fde84dedf","order_by":3,"name":"Mamy Uliwabo","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Mamy","middleName":"","lastName":"Uliwabo","suffix":""},{"id":495332514,"identity":"2a53d78d-f553-4e13-8d14-2ead061d3377","order_by":4,"name":"Lydie Sikumbili","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Lydie","middleName":"","lastName":"Sikumbili","suffix":""},{"id":495332515,"identity":"e74f4557-c403-4a18-aece-de9cd2c73977","order_by":5,"name":"Jackson Kyoghero","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Jackson","middleName":"","lastName":"Kyoghero","suffix":""},{"id":495332516,"identity":"153ab0f6-c81e-4225-ae0b-e42527b5ef2d","order_by":6,"name":"Jackson Musumba","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Jackson","middleName":"","lastName":"Musumba","suffix":""},{"id":495332517,"identity":"1c679866-65a8-4714-94f8-5ed0d416ba4f","order_by":7,"name":"Alpha Kavuyiro","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Alpha","middleName":"","lastName":"Kavuyiro","suffix":""},{"id":495332518,"identity":"9d0701ba-d56d-444f-a596-7e006e3a6026","order_by":8,"name":"Jean-Paul Mwalitsa","email":"","orcid":"","institution":"Catholic University of Graben","correspondingAuthor":false,"prefix":"","firstName":"Jean-Paul","middleName":"","lastName":"Mwalitsa","suffix":""},{"id":495332519,"identity":"c042231d-ebcf-43f5-8b54-281589b7c4d1","order_by":9,"name":"Jacques Wahangire","email":"","orcid":"","institution":"Catholic University of 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Graben","correspondingAuthor":false,"prefix":"","firstName":"François","middleName":"","lastName":"Mbahweka","suffix":""},{"id":495332523,"identity":"453a4487-a1b8-444f-8a6d-3f47ecd78d94","order_by":13,"name":"Louis Sabuni","email":"","orcid":"","institution":"Official University of Ruwenzori","correspondingAuthor":false,"prefix":"","firstName":"Louis","middleName":"","lastName":"Sabuni","suffix":""}],"badges":[],"createdAt":"2025-07-29 10:09:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7242035/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7242035/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91562038,"identity":"fef57b8b-e7ce-46a7-b1c2-8bb5e26b7f0d","added_by":"auto","created_at":"2025-09-17 18:51:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22766,"visible":true,"origin":"","legend":"\u003cp\u003eCurve of total survival of preterm births followed at the UCG\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7242035/v1/4201d28e1230a284fd636fb0.png"},{"id":91562042,"identity":"bfb13281-49b0-485d-a9e8-594fde1fdabf","added_by":"auto","created_at":"2025-09-17 18:51:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93171,"visible":true,"origin":"","legend":"\u003cp\u003eCurve of survival according to the gestational age (GA)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7242035/v1/4553037ac9f61176fe13f0e7.png"},{"id":91562805,"identity":"6a338ac2-e54a-4498-b965-83acae694325","added_by":"auto","created_at":"2025-09-17 18:59:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":70637,"visible":true,"origin":"","legend":"\u003cp\u003eCurve of survival according to birth weight of preterm babies\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7242035/v1/48a2a8c92e006d90a32485ca.png"},{"id":93875796,"identity":"a6c312d7-9113-4557-b1e9-fce3453dc8fa","added_by":"auto","created_at":"2025-10-19 14:01:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1087015,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7242035/v1/a0b7885f-8cae-48de-b393-0952888c8b18.pdf"},{"id":91562039,"identity":"33d19e21-b711-4253-bb87-8b2c633a2d8d","added_by":"auto","created_at":"2025-09-17 18:51:38","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18234,"visible":true,"origin":"","legend":"","description":"","filename":"Table2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7242035/v1/b34cfd5f90cdff0f96d28663.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic Factors and Survival Outcomes of Preterm Infants: A Cohort Study at the University Clinics of Graben, Butembo","fulltext":[{"header":"Background","content":"\u003cp\u003eAccording to the World Health Organization (WHO), preterm birth is defined as a birth that occurs before 37 Weeks of Amenorrhea (WA) or 259 days after the first day of the last menstrual period. Generally, a distinction is made between late preterm (birth between 34 and 36 completed WA), moderate preterm (32 to 34 WA), very preterm (28 to 32 WA), and extremely preterm (inferior to 28 WA) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePreterm birth is a major concern in neonatology because of its very high morbidity and mortality. In the region, specifically in North Kivu in the Democratic Republic of the Congo (DRC), care of preterm babies remains difficult because of limited resources. The number of preterm births is estimated at 15\u0026nbsp;million each year worldwide, which represents 11% of living births (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). About 85% of babies born before 37 weeks of pregnancy were late preterm or moderate preterm, 10% were very preterm, and 5% were extremely preterm (\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSixty percent of these births occur in South Asia and sub-Saharan Africa, the largest birth basins in the world (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) but also in poverty. While the number of preterm infants surviving the neonatal period continues to rise, neonatal morbidity is still high, and there are concerns about medium- and long-term prognosis (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Preterm births, complications during childbirth, infections, and birth defects are the causes of most neonatal deaths. Indeed, the early neonatal mortality rate is an indicator of the quality of care and the level of economic and social development of a population (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePreterm birth is the leading cause of neonatal mortality worldwide, with approximately 3.1\u0026nbsp;million deaths per year directly related to it (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). A WHO-supported global study estimated that death from preterm birth accounted for 15.4% of total under-5 mortality, making it the leading cause in this age category (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Deaths related to preterm birth concern both developing and developed countries (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In developing countries, less than 10% of children are born in the 28th week of gestation, and this figure barely reaches 50% in the 34th week of pregnancy (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), with survival rates increasing with gestational age (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe neonatology department of the University Clinics of Graben (UCG) admits preterm babies referred from the surrounding health facilities without medical equipment for monitoring, respiratory assistance, and thermal protection. In addition, the department is not equipped for parenteral nutrition of proteins and lipids. Thus, in the context of improving the quality of care in UCG and reducing neonatal mortality, we conducted this study to describe the clinical course and the probability of survival of children born prematurely in the UCG, in the east of the Democratic Republic of Congo (DRC), and finally to improve care and minimize complications.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThe present study was carried out at UCG located in the East of the DRC, North Kivu province, city of Butembo in the urban-rural health zone of Butembo. The study population consisted of all preterm children followed at UCG for management. The sheets of preterm children and the collection grid designed in Excel were used to collect the data. The study was descriptive of the cohort of preterm children treated in a period from January 2021 to May 2023. The literature search was conducted using the Medline and PubMed computer databases between 2010 and 2023. We consulted several review journals on the subject and supplemented the computerized search with a manual search of certain basic documents.\u003c/p\u003e\u003cp\u003eTo study the problem, we used the following variables: Sex (male or female), family address (urban or rural), siblings of the child, gestational age (in weeks of amenorrhea), birth weight (in grams), temperature at admission (in degrees Celsius), the clinical course (prognostic factors) of prematurity from day to day, time zero being the day or time of birth, and the mode of discharge from hospital (survivor or deceased). Due to the small size of the study population, survival analysis was performed using the KAPLAN-MEIR method to estimate the probability of survival of preterm infants, day after day (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e–\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Since the probability of survival at time 0 (at birth) is equal to 1, during the first day it was calculated by dividing the number of survivors by the total number of preterm babies at the beginning of the day; At the end of the first day, this probability was obtained by multiplying the probability of time 0 by the probability of survival during the first day.\u003c/p\u003e\u003cp\u003eThe probability of survival on the second day was calculated by dividing the number of survivors on the same day by the number of preterm infants at the beginning of the day (day 2); The probability of survival at the end of day 2 was obtained by multiplying the probability of survival at the end of the previous day (day 1) by the probability of survival during the day (day 2). The rest of the calculations were done by analogy and in an automatic way using the Excel 2013 software; with the values of the probability of survival at the end of the day, we generated the different survival curves using the same software. Considering gestational age, we subdivided our sample into two groups to confirm or refute the hypothesis of equal survival in these groups by using the Mantel statistical test; the first group (A) consisted of preterm infants with GA between 32 weeks and 37 weeks of gestation and the second group consisted of GA less than 32 weeks of age.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring our study period, UCG recorded 49 cases of preterm infants, 18 boys (36.7%) and 31 girls (63.3%). Thirty-three cases (67.3%) were from urban areas and 16 cases (32.7%) were from rural areas.\u003c/p\u003e\n\u003cp\u003eThe description of the quantitative variables in Table\u0026nbsp;1 shows a mean of 31.9 (SD\u0026thinsp;=\u0026thinsp;3.3).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDescription of quantitative variables\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard deviation (SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGestational age in WA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e31.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBirth weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e800.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3300.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1549.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e496.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTemperature at admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSiblings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eLegend: WA\u0026thinsp;=\u0026thinsp;weeks of amenorrhea\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn Table\u0026nbsp;2, we describe the evolution day by day of preterm birth followed at the University Clinics of Graben.\u003c/p\u003e\n\u003cdiv\u003eFrom Table 3, the survival probability is 55.1% whereas the death risk is 44.9%.\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eProbability of survival and risk of death in preterm infants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHospital exit modality\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSurvivals\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDeaths\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eLegend: %= percentage\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;4 and Fig.\u0026nbsp;1 analyze the daily survival of preterm infants managed at the University Clinics of Graben.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eAnalysis of daily survival of preterm infants managed at the University Clinics of Graben.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDay\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDeaths\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvivals\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProbability of survival per day\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProbability of survival at the end of the day\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDay35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;5 presents the probability of survival according to the gestational age in weeks of amenorrhea, and Fig.\u0026nbsp;2 presents curves of survival accordingly, and the application of the statistical Mantel (M) test.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eGestational age and survival of preterm infants at the UCG\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGestational age\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvivors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior to 28 WA (extremely preterm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 WA \u0026minus;\u0026thinsp;31 WA\u0026thinsp;+\u0026thinsp;6 days (very preterm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 WA \u0026minus;\u0026thinsp;33 WA\u0026thinsp;+\u0026thinsp;6 days (moderate preterm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 WA \u0026minus;\u0026thinsp;36 WA\u0026thinsp;+\u0026thinsp;6 days (late preterm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eLegend: WA\u0026thinsp;=\u0026thinsp;weeks of amenorrhea; %= percentage\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe calculated value of M (for the Mantel test) is 24.51279, superior to 3.84 at the confidence of 95%.\u003c/p\u003e\n\u003cp\u003eIn Table\u0026nbsp;6, there is presented the survival probability according to the birth weight of preterm infants, and Fig.\u0026nbsp;3 presents the curves of survival accordingly.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSurvival and weight at birth\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBirth weight in grams\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvival\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInferior to 1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1000 to 1499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1500 and more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eLegend: % = percentage\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;7 presents the influencing factors of survival of preterm births followed at the University Clinics of Graben.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003ePrognostic factors of preterm birth survival\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePrognostic factors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSurvivors\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnterocolitis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAbdominal distension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory distress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTemperature trouble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlycemic trouble\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInfections\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJaundice\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVomiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eLegend: % = percentage\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis preliminary work is important because little data is available on the prognostic factors and survival of preterm infants in sub-Saharan African countries and in the Democratic Republic of the Congo.\u003c/p\u003e\u003cp\u003eFrom the study results, the description of quantitative variables shows the mean gestational age of 31.9 (\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e) weeks, the mean birth weight of 1549.3 (800\u0026ndash;3300) grams, the mean intake temperature of 34.8 (32.0 -37.8) degrees Celsius, and the mean sibling age of 2.3 (\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The average weight in our study is higher than that found in a study in Tunisia, where it was 1032 grams (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). This trend is due to the presence in our sample of obese preterm infants weighing 3300 grams from a diabetic woman. In another study in C\u0026ocirc;te d'Ivoire, the average weight of 1750 grams (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) was noted, a weight higher than that found in the present study.\u003c/p\u003e\u003cp\u003eMost of our respondents were hypothermic, i.e., below the normal value (Standard Deviation 1.5C \u0026deg;C). Hypothermia in preterm infants is due to a decrease in thermogenesis (metabolic activity is reduced and takes longer to establish and the brown fat present from 26 weeks is in lower quantities) and an increase in heat loss (the thin thickness of the subcutaneous fatty tissue reduces the efficiency of vasoconstriction; the surface/volume ratio is increased, which facilitates discharge and the skin is immature and does not play its role as a barrier) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe problem of prematurity affects not only the delivery itself and how it affects the mother and child at this time, but also the permanent challenges they face during the neonatal period (early and late) in terms of survival, with particular attention to the resulting morbidities. the results of this study suggest that 87.8% of preterm infants developed the infection, with 71.4% occurring in the early neonatal period. In a study in Senegal, infectious and respiratory complications were the most common, occurring in most cases in the early neonatal period (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn neonatology, infections are more pronounced in preterm infants due to several factors: an immature immune system, absence or low concentration of antibodies, an initially axenic organism subjected in a few days to massive contamination from the environment and personnel, and artificial ventilation (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). From this study's results, it appears that 81.6% of preterm infants had hypothermia during their stays, including 65.3% in the early neonatal period. In a study conducted in Cameroon, 71.2% of cases of hypothermia were observed (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), results similar to this study\u0026rsquo;s.\u003c/p\u003e\u003cp\u003eFurthermore, the results of this study show that respiratory distress was observed in 79.6% of cases, with 65.3% of these cases occurring in the early neonatal period. A study conducted in Cameroon found 68.7% respiratory distress in premature babies weighing less than 1000g (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) while another one conducted in Tunisia found that 27% of preterm infants (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Neonatal respiratory distress in preterm infants is related to several factors, including neonatal infection, surfactant insufficiency, immaturity of the respiratory center, imperforation of the choana, esophageal atresia, hiatal hernia, etc. Our results suggest that 57.1% of preterm infants developed anemia during their stays in the neonatal unit, including 30.6% in the early neonatal period. In a study in C\u0026ocirc;te d'Ivoire, the frequency of anemia was 25% (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Another study in Cameroon reported a frequency of preterm anemia of 24.2% (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Neonatal anemia is a common problem in preterm infants (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). They are more likely to suffer, as about 80% of iron reserves are accumulated during the last quarter of the year.\u003c/p\u003e\u003cp\u003eThis study reflects that the main complications of prematurity are infections, hypothermia, respiratory distress, and anemia. Another local study reported prematurity as a factor associated with early-onset neonatal infection (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Torchin and his collaborators in their study suggest neurological complications, respiratory distress, digestive complications (enterocolitis and abdominal bloating), infectious complications, and ophthalmological complications (retinopathy of prematurity); In the case of extreme prematurity, respiratory distress is the most common complication (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The other complications of prematurity observed during this study are respectively jaundice 40.8%, of which 8.1% in the early neonatal period; blood sugar disorder 24.5%, including 20.4% in the early neonatal period; abdominal bloating 20.4%, including 6.1% in the early neonatal period; hemorrhage 18.4%, of which 6.1% in the early neonatal period; enterocolitis 10.2%, of which 4.1% in the early neonatal period and vomiting 10.2% in late neonatal period.\u003c/p\u003e\u003cp\u003eIt is estimated that jaundice is present in just over half of term newborns and that it affects 80% of premature newborns; In the latter, hyperbilirubinemia is more frequent and its course more prolonged compared to the term newborn (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The elevation of bilirubin is due to the increased destruction of red blood cells in the neonatal period as well as to the immaturity of the purification systems, particularly in the liver. In preterm infants, low birth weight is a factor that promotes hypoglycemia. This is correlated with insufficient glycogen and lipid stores (little adipose tissue), which deprives tissues of alternative substrates and increases tissue glucose demand (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). The risk of hypoglycemia is high with the occurrence of perinatal asphyxia and hypothermia, which increase the body's need for glucose (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn a study in Cameroon, the frequency of necrotizing enterocolitis was reported to be 1.6% with a case fatality rate of 79.4% (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). In preterm infants, enterocolitis is a major cause of mortality and morbidity (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Preterm birth remains a determining factor in the severity of intestinal atresia, the probable cause of abdominal bloating, and can also explain the occurrence of certain congenital anomalies; According to some authors, 1/3 of newborns with a digestive malformation are preterm babies (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The diagnosis of necrotizing enterocolitis in preterm birth is a serious intestinal complication that must be monitored in neonatology. It is a condition in which there is significant inflammation of the intestinal lining that can lead to damage or perforation. Initially, this condition can cause vomiting, diarrhea, and considerable bleeding (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe main results of this study suggest that the mortality rate of preterm infants is significantly high, and this is outrageously high in extremely preterm infants (GA 28 weeks or birth weight 1000g). The overall probability of survival of preterm infants was 55.1% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A significant proportion of mortality occurred in the early neonatal period, the first three days of life, followed by the period from days 8 to 12 of life. The trend in deaths was only stabilized from the 13th day of life despite the few deaths recorded on the 16th, 21st, 22nd, and 34th days of life (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Compared to GA, survival was 90.0% in preterm infants (34 weeks\u0026ndash;36 weeks\u0026thinsp;+\u0026thinsp;6 days), 50.0% of average preterm infants (32 weeks\u0026ndash;33 weeks\u0026thinsp;+\u0026thinsp;6 days), 35.7% of very preterm infants (28 weeks), and 0.0% of preterm infants (28 weeks) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMost of the preterm infants of GA inferior to 28 WA (6 of the 7) died during the early neonatal period, with the last survivor surviving to day 11 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). According to the result of the Mantel statistical test at the 95% confidence level (M\u0026thinsp;=\u0026thinsp;24.51279, a value greater than 3.84), deaths occurred earlier in the group of preterm infants with GA less than 32 weeks of age (second group). Alluding to birth weight, the probability of survival was 84.6% in very preterm infants (1500g), 33.3% in very preterm infants (1000g \u0026minus;\u0026thinsp;1500g), and 0.0% in preterm infants (1000g) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The last survivor weighing less than 1000g survived to the 11th day, with most deaths occurring during the early neonatal period (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The survival rate for premature babies improves as gestational age increases, although there are considerable differences between countries.\u003c/p\u003e\u003cp\u003eAt GA at 28 weeks, child survival is up to 90% in industrialized countries, while below 28 weeks of age, it is between 7% and 90%. For some countries, such as Japan, this probability increases to 34% between 22 and 24 weeks (3.36\u0026ndash;38). Neonatal mortality is higher if the birth weight is less than 1000g(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) and survival is close to 0% in developing countries (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Data from a weight-based survival study of preterm infants suggested that survival improved for newborns weighing 1500g, with excellent survival for newborns weighing more than 2500g (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSurvival data for clinical complications in preterm infants revealed that the prognosis was poor for children who developed enterocolitis, abdominal bloating, and hemorrhage; the probability of survival was 0.0% (for the first two complications) and 11.1%, respectively. Enterocolitis is most commonly seen in preterm infants, with a survival rate of less than 10% in developing countries (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e); It is one of the main causes of mortality in preterm babies, and its fatality varies between 30% and 40% in developed countries.\u003c/p\u003e\u003cp\u003eFor preterm infants who presented with respiratory distress, heat disorder, blood glucose disorder, anemia, infection, jaundice, and vomiting, the probabilities of survival were 43.6%, 45.9%, 50.0%, 57.1%, 58.1%, 60.0%, and 80.0%, respectively. Prematurity is characterized by insufficient reserves and immaturity of large ones, two phenomena that are at the root of all possible complications of premature infants. Delayed care and/or inadequate care negatively influence its probability of survival.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePrematurity is a major concern in neonatology because of its still very high morbidity and mortality. In the region, the care of premature babies remains difficult because of the very limited resources. Improved care will minimize complications and therefore increase the likelihood of survival.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDRC = Democratic Republic of the Congo.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUCG = University Clinics of Graben.\u003c/p\u003e\n\u003cp\u003eWHO = World Health Organization,\u003c/p\u003e\n\u003cp\u003eWA = Weeks of Amenorrhea,\u003c/p\u003e\n\u003cp\u003eSD= standard deviation SD,\u003c/p\u003e\n\u003cp\u003eGA = Gestational Age\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eOur acknowledgment to the LD English Club for helping in the translation of this article.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eJK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing; \u003c/p\u003e\n\u003cp\u003eAS: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing; \u003c/p\u003e\n\u003cp\u003eRM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources, software, supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing; \u003c/p\u003e\n\u003cp\u003eMU: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; \u003c/p\u003e\n\u003cp\u003eLS: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; \u003c/p\u003e\n\u003cp\u003eJK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; \u003c/p\u003e\n\u003cp\u003eJM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; \u003c/p\u003e\n\u003cp\u003eAK: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources;\u003c/p\u003e\n\u003cp\u003eJM: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources; \u003c/p\u003e\n\u003cp\u003eJW: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources;\u003c/p\u003e\n\u003cp\u003eFA: conceptualization, data curation, formal analysis, investigation, methodology, project administration, resources;\u003c/p\u003e\n\u003cp\u003ePV: supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing; \u003c/p\u003e\n\u003cp\u003eFM: supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing; \u003c/p\u003e\n\u003cp\u003eLS: supervision, validation, visualization, writing \u0026ndash; original draft, and writing\u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e \u003c/sup\u003e\u003c/p\u003e\n\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003eAfter approval of the research protocol by the Ethics Committee of the Catholic University of Graben in collaboration with the health authorities of the University Clinics of the Graben, we obtained permission to collect the data following the principles of scientific research. Anonymity and respect for human dignity have been respected. All methods were performed in accordance with relevant guideline.\u003c/p\u003e\n\u003ch2\u003eConsent for participation\u003c/h2\u003e\n\u003cp\u003eObtained from all participants\u0026rsquo; parents or guardians.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eAll important data are described in the article.\u003c/p\u003e\n\u003ch2\u003eFunding \u003c/h2\u003e\n\u003cp\u003eNo funding was obtained.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eThe consent for publication was obtained from all authors.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003eThe authors declare the following financial interest/personal relationship which may be considered as potential competing interests:\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDelnord M, Zeitlin J. 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JAMA Pediatr. 1 mars 2015;169(3):230‑8. \u003c/li\u003e\n\u003cli\u003eHarrison MS, Goldenberg RL. Global burden of prematurity. Vol. 21, Seminars in Fetal and Neonatal Medicine. W.B. Saunders Ltd; 2016. p. 74‑9. \u003c/li\u003e\n\u003cli\u003eNlend AEN, Zeudja C, Motaze AN, Suzie M, Lydie N. Immediate neonatal outcome of extreme prematurity: retrospective data of a neonatal unit in Yaounde, Cameroon from 2009 to 2013. Pan Afr Med J. 2015;20:321. \u003c/li\u003e\n\u003cli\u003eMorisaki N, Togoobaatar G, Vogel JP, Souza JP, Rowland Hogue CJ, Jayaratne K, et al. Risk factors for spontaneous and provider-initiated preterm delivery in high and low Human Development Index countries: a secondary analysis of the World Health Organization Multicountry Survey on Maternal and Newborn Health. BJOG. 2014;121 Suppl 1:101‑9. \u003c/li\u003e\n\u003cli\u003eSaasita A, Kaghoma B, Muyisa R, Tayivweka JM, Mughania T, Kaliremwira R, et al. Incidence and risk factors of early-onset neonatal infections in Butembo: case of Katwa Health Zone from January 2020 to December 2022. BMC Pediatr [Internet]. 2025;25. Available from: https://doi.org/10.1186/s12887-025-05774-7\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 2","content":"\u003cp\u003eTable 2 is available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"preterm births, morbidity and mortality, prognostic, survival analysis","lastPublishedDoi":"10.21203/rs.3.rs-7242035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7242035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe management of preterm births is still a major concern in different health facilities in Butembo, a town in the eastern part of the Democratic Republic of Congo. This study aimed to describe the clinical progress and the survival rate of preterm births managed at the University Clinics of Graben (UCG) to improve the quality of care.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis was a cohort study involving preterm births managed at the UCG. The study was performed from January 2021 to May 2023. The information was gathered from preterm birth files and analyzed using Excel to determine the survival rate.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe most common clinical complications (prognostic factors) observed in preterm birth were infections (87.8%), hypothermia (81.6%), respiratory distress (79.6%), and anemia (57.1%), most of which occurred in the early neonatal period. The total survival rate was 55.1%, with the survival curve exhibiting a decline in the first three days and a subsequent increase from the seventh to the eleventh day of follow-up. The Mantel test at a confidence level of 95% (M\u0026thinsp;=\u0026thinsp;24.51279) revealed that death was early in preterm births whose gestational age was less than 32 weeks.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAbdominal bloating, enterocolitis, and hemorrhage were the complications that worsened the prognosis of preterm births. Therefore, there is a dire need to improve both the prevention measures and the treatment of preterm births in this part of the Democratic Republic of Congo.\u003c/p\u003e","manuscriptTitle":"Prognostic Factors and Survival Outcomes of Preterm Infants: A Cohort Study at the University Clinics of Graben, Butembo","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-17 18:51:34","doi":"10.21203/rs.3.rs-7242035/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"90384cac-060e-43b4-9c83-3b66e46c4354","owner":[],"postedDate":"September 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-19T13:53:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-17 18:51:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7242035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7242035","identity":"rs-7242035","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}