Influencing factors of Pediatric Intensive Care Unit Mortality at Bernard Mevs Hospital from January 2017 to December 2017

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Chery, Anne-Rose Miguel, Naïka Paulemie Désir, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4385973/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 Introduction: The morbi-mortality in a pediatric intensive care unit is an important determinant of child mortality worldwide. In Haiti, there are only two hospitals in the metropolitan area with a pediatric intensive care unit. The objective of this study is to identify the main factors influencing the mortality of patients aged 1 month to 16 years hospitalized in the pediatric intensive care unit at the Bernard Mevs Hospital (HBM). Methodology: We carried out a retrospecptive cross-sectional and analytical study over one year, within the Bernard Mevs Hospital Medishare Project (HBMPM). Our population consisted of all the patients aged 1 month to 16 years hospitalized in the pediatric intensive care unit of HBM from January 2017 to December 2017. Results From January 1, 2017, to December 31, 2017, 122 files of patients admitted to the pediatric intensive care units (PICU) at HBM were selected. Among those patients, a male predominance was demonstrated with 76 patients, or 63.30%, with a sex ratio of 1.65. The average age of the patients was 5.73 ± 4.73 years. In 43 patients (35.26%), trauma was the main cause of hospitalization, followed by respiratory illnesses, found in 22 patients, or 18.04% of admissions. The mortality rate was 33.60%, dominated by septic shock in 24% of cases. The average days of hospitalization in the deceased population was 12 days. This study demonstrated that the probability of dying in the PICU is higher in male patients (p-value of 0.0049) and in patients who have been intubated (p-value of 0.0021). Conclusion Our study has demonstrated a high mortality rate among male patients and those who have been intubated. Most of the causes of admission were preventable. Other studies should be carried out to generalize data and identify key measures to reduce the infant and child mortality in Haiti. Pediatrics Pediatric intensive care unit mortality rate morbidity low-resource country Haiti Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Millions of children around the world experience serious medical conditions that require adequate and rigorous care in PICU ( 1 ). Pediatric intensive care units include all pathological conditions that require not only rigorous and constant medical supervision but also the competence and expertise of a well-organized and trained multidisciplinary team. In fact, an intensive care unit, or ICU, is a hospital service that brings together health professionals who provide care to patients treated for severe health conditions with a poor prognosis ( 2 ). Pediatric care units were only created six decades ago, in the 1950s. Their existence and increasing number in the world over the past decades have been strongly associated with a significant drop in the infant and child mortality rate ( 3 ). Unfortunately, to our knowledge, in Haiti, only two hospitals in the metropolitan area, created less than 20 years ago, have with a pediatric intensive care unit for the entire pediatric population of this area. Our study is one of the rare elaborates on this topic in Haïti. Our main goal was to describe and analyze the morbidity, the epidemiological profile of children admitted to an intensive care unit, and mainly the factors influencing their mortality in a hospital in the metropolitan area among patients aged from 1 month to 16 years hospitalized in the PICU of HBM from January 2017 to December 2017. 2. Materials and Methods a. Type of study Our study is a retrospective cross-sectional and analytical study of patients aged 1 month to 16 years admitted to the pediatric intensive care unit of Bernard Mews Hospital in Haïti from January 2017 to December 2017. b. Study framework We conducted this study at HBMPM, a private haitian institution in the west department, founded in 1994, located at Boulevard Toussaint Louverture Village Solidarité, serving the population of this town and its surroundings. Its geographic coordinates are -72.318993 longitude and 18.561775 latitude. The pediatric intensive care unit is subdivided into a neonatal intensive care unit (NICU) with a capacity of 4 beds accommodating newborns from 0 to 28 days old and a PICU with a capacity of 4 beds intended for patients aged over 1 month to 18 years. For the ongoing year, 129 patients have been admitted to this intensive care unit. c. Study population All the patients aged 1 month to 16 years admitted to the pediatric intensive care unit from January 2017 to December 2017. d. Inclusion and exclusion Inclusion criteria: patients aged 1 month to 16 years who were admitted to the pediatric intensive care unit from January 2017 to December 2017. Exclusion criteria: we excluded all records that had missing information, damaged files, or illegible information. e. Data collection and analyzes The data was collected by manual counting using a pre-elaborated questionnaire. A few variables—age, sex, address, lengths of stay, diagnostics, mortality rate—have been studied. The Epi Info 7 software (version 7.1.2.0.) was used to collect, enter, and analyze the data. We used the Mendeley software (Version 1.15.3) to create the bibliography. The odds ratio (OR) was used as an association measure, and the hypotheses of the study were verified with Pearson's or Fisher's exact Chi square tests. The significance level of statistical tests is reached with a “p” value of less than 0.05. For the descriptive analysis, we also used the Wilcoxon or Mann-Whitney test and the t-student. 3. Results From January 1, 2017, to December 31, 2017, 129 patients were admitted to the pediatric intensive care unit of Hospital Bernard Mevs (HBM PICU). However, 7 records have been excluded because of missing or illegible information (Figure 1). Out of 122 patients hospitalized in the PICU from January 1, 2017, to December 31, 2017, a male predominance was demonstrated with 76 patients (63.30%), with a sex ratio M/F of 1.65. The average age of the patients was 5.73 ± 4.73 years. The average age of male patients was 5.42 ± 4.61 and for the female patients was 6.24 ± 4.81. 98 patients of our cohort were mostly living in urban areas (80.33%) whereas 24 (19.67%) lived in rural areas. (Table 1) a. Comorbidities. Of the 122 patients admitted to the PICU, 34 (27.87%) had comorbidities or a significant disability at the time of admission. 43 patients (35.25%) had a previous hospitalization. 66 patients (54.10%) had been placed on assisted ventilation at the time of admission, 13 patients (10.66%), had an objective and up-to-date vaccination record. (Figure 2) The main comorbidities found in PICU patients during the period were hydrocephalus in 8 patients out of 34 with comorbidity (23.53%); prematurity in 6 patients (17.65%), heart disease in 3 patients (8.82%), sickle cell anemia in 3 patients (8.82%), acute severe malnutrition in 2 patients (4.88%) and asthma in 2 patients, i.e., 4.88% of cases. (Figure 2) b. Origin of patients. Among the patients in PICU, 55 (45.08%) came directly from their home and 67 of them i.e., 54.92% of admissions were referrals from other health structures. Among those who came from other heath structures, 47 patients (38.52%) were from another hospital; 16 (13.11%) were from a health care center; 4 (3.28%) came from a medical office. (Table 1) c. Time frame for seeking care. The time between the onset of symptoms and referral to a first hospital facility varies from 1 day to 150 days with an average time of 5.96 ± 16.46 days. With 64.72% of the population seeking care in less than 24 hours, 25.38% between 1 to 7 days, 18.03% between 7 to 14 days, 9% between 12 to 21 days and 4.1% more than 21 days after the onset of symptoms. (Table 1) d. Length of stay. The length of hospitalization for patients varies from less than 24 hours to more than 30 days with an average of 12.59 ± 16.15 days and a maximum of 121 days. (Table 1) e. Outcome. Regarding the outcome of the patients admitted to PICU during this period: 78 patients (69.93%) were discharged. Of those, 15 (19.23%) with neurological or physical sequelae; 3 patients (2.46%) left before completing their treatment; 41 (33.60%) died. (Table 1) Table 1- Socio-demographic characteristics of patients admitted to the HBM PICU Variables Categories N (%) Age (years) 12 15 (12,30%) Sex F 46 (37,70%) M 76 (62,30%) Residence Rural area 24 (19,67%) Urban area 98 (80,33%) Medical History Comorbidities Yes 43 (35,25% No 79 (64,75%) Previous hospitalization Yes 34 (27,87%) No 88 (72,13%) Vaccination status Yes 13 (10,66%) No 109 (89,34%) Intubation Yes 66 (54,10%) No 56 (45,90% Time to seek care (days) ≤ 1 68 (55,73%) 1-7 31 (25,39%) 7-14 7 (5,74%) ≥14 16 (13,28%) Origin Reference 67 (54,92%) Non reference 55 (45.08%) Diagnostic Trauma 43 (35,26%) Respiratory illness 22 (18,04% Meningial illnesses 15 (12,30%) Post-Surgical 21 (17,22%) Septic shock 12 (9,84%) Other 9 (7,38%) Length of hospital stay (days) 30 8 (6,56%) Final Outcome Survivors 81 (66,40%) Deceased 41 (33,60%) f. Mortality. Of the 122 PICU admissions, 41 patients died and 81 survived, i.e., a mortality and survival rate of 33.60% and 66.40% respectively. (Figure 3) · Socio-demographic characteristics of deceased patients. 63.41% of the patients who died had a M/F sex ratio of 1.73. 14 (34.15%) of them, were under 1 year old; 13 i.e., 31.70% aged 1 to 5 years; 9 (21.95%) aged 6 to 12 years old; 5 or 12.20% over 12 years old. The average age was 6.33 ± 4.67 years. 9 patients among the deceased patients (21.95%), lived in rural areas and 32 (78.05%) in urban areas. (Table 1) · Comorbidities found in deceased population. 14 (34.14%) of the patients who died had a comorbidity at the time of admission. 16 of them (39.03%), had at least one previous hospitalization and 38 (92.68%) had been intubated at the time of admission. The main comorbidities found in the deceased patients were hydrocephalus in 9.75% of cases, heart disease found in 3 patients (7.31%); 2 cases (4.87%) of sickle cell anemia; 1 case (2.44%) of acute severe malnutrition, and 1 patient (2.44%) with Down Syndrome. (Figure 4) · Diagnostics retained in deceased population. The main diagnostics retained in the 41 deceased patients were dominated by: septic shock, in 24.39% of cases, meningeal conditions in 19.51% of cases, trauma in 17.07% of cases, respiratory conditions in 14.63% of cases and post-surgical admissions in 14.63% of cases. (Figure 5) g. Bivariate descriptive analysis. This analysis made it possible to explore the distribution of the data obtained according to the outcome. Table 2 allowed us to establish whether there was a significant statistical difference between patients who survived their hospitalization and patients who died, referring to our hypothesis. According to the outcome of the patients in our series, 34.15% of the patients under 1 year of age died, while 16.05% of them survived. No statistically significant difference was observed (p value of 0.09). (Table 2) Table 2 - Socio-demographic characteristics of patients by outcome Variables Outcome p-value Survivors n= 81 Deceased n=41 N (%) Age (years) 0.09 12 10 (12,35%) 5 (12,20%) Gender 0.0049 F 31 (38,27%) 15 (36,59%) M 50 (61,73%) 26 (63,41%) Residence Rural area 15 (18,52%) 9 (21,95%) 0.64 Urban area 66 (81,48%) 32 (78,05%) Medical History Comorbidities Oui 20 (24,69%) 14 (34,25%) 0.7142 Previous hospitalization Oui 27 (33,33%) 16 (39,02%) 0.196 Intubation Oui 28 (34,57%) 38 (92,68%) 0.0021 Origin Reference 46 (56,79) 21 (51,22%) 0.56 Non reference 35 (43, 21%) 20 (48,78%) Diagnostic Trauma 36 (44,44%) 7 (17,07%) Respiratory illnesses 16 (19,73%) 6 (14,63%) Meningeal illnesses 7 (8,64%) 8 (19,51%) 0,65 Post-surgery 15 (18,52%) 6 (14,63%) Septic shock 2 (2,47% 10 (24,39%) Other 5 (6,17%) 4 (9,75%) Length of hospitalization (days) 30 8 (9.88%) 0 (0.00%) h. Statistical inference · Multivariate dynamic analysis. This analysis is used below to measure the association between mortality and the different factors likely to influence it, which allowed us to test our hypotheses. The model is generally well specified with a p-value likelihood ratio = 0.0020). Therefore, the results obtained are valid. This analysis of the results made it possible to identify the factors associated with a greater probability of dying. Thus, intubation and male gender are statistically significant factors in mortality in the HBM’s PICU. Intubation increased the risk of dying by 2.87 times in our series (p-value = 0.0021, OR = 2.8723). Patients of male gender have a 34% higher probability of dying than patients of female gender (p-value = 0.0049, OR = 0.3399). Indeed, comorbidities as well as previous hospitalization are statistically insignificant factors. (Table 3) Table 3 - Results of hypothesis verification obtained by multivariate analysis Factors Odds Ratio 95% C.I. P-Value Comorbidities (Yes/No) 0.82 [0.2910; 2.3297] 0.7142 G ender (M/F) 0.34 [0.1602; 0.7210] 0.0049 Intubation (Yes/No ) 2.87 [1.4651; 5.6310] 0.0021 Previous Hospitalization (Yes/No) 0.54 [0.2122; 1.3742] 0.196 4. Discussion To our knowledge, our research regarding the factors influencing the mortality among patients hospitalized in a pediatric intensive care unit in Haïti is one of the first to be published. The average age of patients hospitalized in the intensive care unit of the HBM in our study was 5.73 ± 4.73 years (0.08 to 16 years) and the median age was 5 years. Male patients had an average age of 5.42 ± 4.61 years and female patients 6.24 ± 4.81 years. Which is like the results of the study carried out in Brazil in 2009, in which: the median age of patients was 4.9 ± 2.7 years – 4.6 years in male patients and 5.3 years in female patients ( 2 ). Our results were also similar to the study carried out in Europe where the average age was 5 years. Our results were different to the study carried out in Africa by Coetzee, S. where the median age was 7 months. This study used a methodology different from ours (observational study) and analyzed the epidemiological profile of the population admitted to the PICU for a specific factor, namely measles ( 4 ). Our results also differ from the retrospective study carried out in Europe by Lanetzki, C. S. et al; where the median age of patients was 2.7 years ( 5 ). Our results could be explained by the high mortality rate among children less than 5 years old who are more at risk of dying from preventable and treatable causes mostly due to socioeconomic disparities ( 3 ). Our study revealed a strong predominance of male patients hospitalized in the PICU: 76 patients (63.30%,), with a M/F sex ratio of 1.65. Result similar to the various studies mentioned in our literature review, namely the work of: Araujo et al. in Brazil; Lanetzki, C. et al, in Europe; Kwizera, A. et al, in Africa. ( 2 , 5 , 6 ). Indeed, studies have shown that the mortality rate among boys is higher than girls in most parts of the world. For this age group, this has been explained by sex differences in genetic and biological makeup, with boys being biologically weaker and more susceptible to diseases and premature death ( 7 ) . Regarding the residence area, our study population mainly resided in urban areas with 98 patients (80.33%) and 24 (19.67%) in rural areas. However, in the observational study conducted by O'Callaghan D.J. et al; the infant mortality is slightly higher in rural areas than in urban areas (59% versus 56%) ( 8 ). 1/3 of the patients in the study carried out by El Halal M.G. et al., were referred from other hospitals (34.7%). Only 0.7% of admissions came directly from their home ( 9 ). The study carried out by Javad Ghaffari et al in 2011 revealed that 49% of patients came directly from their homes and 51% from other hospital structures. This latest study matches ourhas similar results to ours. Indeed, among our study populations 55 patients (45.08%) came directly from their home and 67 patients (54.92%) of admissions were referrals from other health structures (9). This high referral rate could be explained by the fact that HBM is one of the rare hospitals in the metropolitan area, accessible to the population, and equipped with an emergency and intensive care unit. In our series, the average time to seek care was 1 day. These results are similar to those of the study carried out in Africa by Karin Källander et al., according to which the average time to seek care outside the home was 2 days ( 4 ). Results that could be explained by the tendency of our population to resort to traditional medicine before any contact with any medical structure. Regarding the duration of stay in the hospital, in our study it varied from less than 24 hours to more than 30 days with a maximum duration of 121 days, and an average duration of 12.59 ± 16.15 days. These findings differ from studies carried out in Africa by Karin Källander et al, with an average duration of hospitalization of 3 days ( 10 ) and which could be explained by the fact that it is a series of cases carried out on a population of children aged less than 5 years and relates exclusively to admissions due to pneumonia. Our research also demonstrated that 54.10% of patients admitted to the PICU during this period were intubated and received mechanical ventilation at the time of their admission. These results are almost similar to the study of Navin P. Boeddha et al, who demonstrated that 69% of their patients benefited from invasive ventilation ( 11 ). The retrospective study carried out in Iran revealed that 24.60% of deceased patients were intubated during their hospitalization in PICU. ( 12 ). Results which differ from our study, where 92.68% of deceased patients were intubated. The differences could be explained by the fact that the study carried out in Iran, although having a similar methodology, had excluded cases of trauma and post-surgical admissions. The main diagnostic of the patients in our study were classified into different categories: first trauma, found in 43 patients or 35.26% of admission, followed by respiratory diseases, found in 22 patients or 18.04% of admission and third post-surgical admissions, in 17.22% of cases. Our results are similar to the study carried out in 2009 in Brazil by Taisa E. Araujo et al., ( 2 ) which demonstrated that respiratory illnesses represented the most common causes of admission to intensive care units (32.7%), followed by post-operative care (30.9%) and trauma cases (12.8%). However, the results of other studies, although all having in common respiratory illnesses as the most common cause of hospitalization; differ from our results. In Uganda, the study carried out by Kwizera, A. et al, demonstrated that the most frequent cause of admission was post-surgical treatments. The percentage was not mentioned in this study ( 6 ). The latest studies carried out around the world have demonstrated that the mortality rate in PICU is now < 3%. Studies carried out in Europe, North America, and Africa, by Agra Tuñas et al., Namachivayam et al., Markita L. and Suttle et al; demonstrated similar results with a respective mortality rate of 2.20%, and 2.38% ( 11 , 13 – 15 ). Results completely different from the mortality rate found in our study work i.e., 33.60%. This high mortality rate in the pediatric intensive care unit of HBM could be explained by the generally late delay in seeking care of the haïtian population and by the high rate of trauma due to motor vehicle accidents and falls, admitted during this period; and knowing that HBM is known for the management of emergencies from all causes. 56.10% of deaths occurred in a context of brain death, 41.46% after failure of cardiovascular resuscitation and 2.44%, after a decision of limitation of therapeutic intervention. This differs from the data published by Agra Tuñas M.C. et al, in Spain where 50.7% of deaths occurred after a decision to limit therapeutic intervention; 114 (33.8%) after cardiovascular resuscitation and 52 (15.4%) were due to cases of brain death. And also those published by Markita L. Suttle et al., in the United States of America where 133 patients (70%) died after interruption of life-sustaining treatment, 30 (16%); after a diagnosis of brain death and 26 (14%) following an attempt at cardiopulmonary resuscitation ( 13 , 14 ). In our research, the deceased patients were mainly male i.e., 26 patients (63.41%), with a M/F sex ratio of 1.73. Result similar to the study of Rashma R.P. et al, where 52% of the deceased patients were male; and similar to the result of Valavi E. et al, where death was observed in 51.80% of M ​​patients ( 12 , 16 ). 14 patients (or 34.15%) died in our study, they were less than 1 year old. The results are similar to those of the study carried out by El Halal M.G. et al, where 37.5% of the deceased patients were aged less than 1 year ( 9 ). The average age of patients who died in our study was 6.33 ± 4.67 years. This differs from the results of Rashma R.P. et al, where the average age of the deceased children was 3.40 + 4.16 years; note that this study, although having a similar methodology to ours, was carried out on a younger population (1 month to 14 years old). It also differs from the retrospective study carried out in Iran by Valavi E. et al, where the average age of deceased patients was 2.2 years ( 12 , 16 ). Our research also demonstrated that the mortality rate decreased with age; 14 deaths i.e., 34.15% aged less than 1 year; 13 i.e., 31.70% aged 1 to 5 years; 9 i.e., 21.95% aged 6 to 12 years old and 5 i.e., 12.20% over 12 years old. (Table 2 ). This result differs from El. Halal M.G. et al, who found that mortality increased significantly with age. The mortality rate was 0.9%, 8.9%, 12.3%, 10.4% and 17%, respectively, for children ≤ 1 month, < 1 year, 1–5 years old, 5–12 years old and ≥ 12 years old ( 9 ). Among the 41 deaths recorded in our study, 34.14% of patients had a comorbidity at the time of admission. 16 of them i.e., 39.03%, had at least one previous hospitalization. These results differ from those of Agra Tuñas M.C. et al, in Spain where a total of 86 patients (25.5%) had a previous hospitalization, 273 (75%) of them suffered from a chronic pathology and 78 (23%) had a serious disability at the time of admission ( 13 ). This difference could be explained by the fact this study was carried out over several years in several hospital centers. The comorbidities found in the 14 deceased patients were mainly of a neurological aspect with 4 patients, i.e., 28.56% with hydrocephalus, 21.43% i.e., 3 patients with heart diseases, 2 i.e., 14.28%, had hematological disease (sickle cell disease), 1 patient i.e., 7.42% had chromosomal anomaly (Down syndrome). These were also the most frequent comorbidities in the study by Halal M.G. et al: neurological (11.5%), hematological/oncological (11.4%) and genetic (7.3%) ( 9 ). Which could probably be explained by the fact that HBM is one of the rare hospitals with a neurosurgery department that serve the adult and pediatric population ( 9 ). The main diagnostics retained in the 41 deceased patients in our work, were dominated by: septic shock in 24.39% of cases knowing that preventable infections still play a major role in the pediatric mortality in Haiti. Meningeal conditions were found in 19.51% of cases, trauma in 17.07% of cases, respiratory illnesses in 14.63% of cases and post-surgical admissions in 14.63% of cases. These diagnostics are different from those published by Agra Tuñas M.C. et al, a retrospective study carried out in Spain for which the most frequent causes of hospitalization were in 32.6% of cases, cardiac and in 22.6% of cases, respiratory illnesses ( 13 ). They also differ from the results of El Halal M.G. et al, where the mortality was mainly due to cardiopulmonary arrest in 29% of cases, sepsis 19%, pneumonia 16%, multi-system dysfunction 14%, hepatic diseases in 7% of cases, an inborn error of metabolism 6%, and acute respiratory distress syndrome in 6% of cases ( 16 ). Predictive factors of mortality. Our research allowed us to identify among the different hypotheses mentioned, two factors associated with greater mortality rate within the PICU of HBM. Indeed, following our various analyses, male gender and intubation were retained as predictive factors of mortality (p = 0.0021, and p = 0.0049) respectively. Intubation was also incriminated in the studies of Navin P. Boeddha et al, and Valavi E. et al. This factor could be explained by the fact that patients generally placed under mechanical ventilation within an ICU are patients in more critical shape than patients who are not ( 11 , 12 ). Our results are also similar to the studies of Rashma R.P. et al, and Valavi E. et al, ( 12 , 16 ) where in fact also male sex was identified as a predictive factor of mortality. This could be explained by the fact that our study population is mainly boys with a significant statistical difference as shown in Table 5 (poled 0.042). Results which should arouse scientific curiosity and constitute an avenue for future scientific research. Strengths and limitations. The predictors of mortality in a PICU is a subject of great importance in Haiti, but unfortunately informations, studies and even researches are very limited. Indeed, very few studies on this subject have been carried out in Haiti ( 17 ). Although there are only two hospitals in the metropolotain area with a pediatric intensive care unit, this study was carried out in only one center, namely HBM, which is known for the management of medical emergencies, intensive care, and surgical intervention. Recommendations. We made some recommendations to the Ministry of Public Health and Population, on the importance of the implementation of strategies to promote equitable access to health services, promote the continuous training of medical staff, create new PICUs, and create more rehabilitation centers for patients with physical or neurological sequelae. 5. Conclusion A pediatric intensive care unit is a critical care entity essential to the care and survival of children who face life-threatening illnesses every day. The literature and this research have allowed us to see that, in fact, without a qualified staff and rigorous care, many seriously ill children would die. Many predictable or avoidable admissions often lead to deaths in a PICU. However, in Haiti, although aware of this sad reality, there are very few hospitals with a pediatric intensive care unit, very few pediatricians with training in this area and even fewer data on this theme. Morbidity in PICU in Haiti and the factors influencing mortality are not known to everyone. Morbidity within the HBM’s PICU during the year 2017 was mainly dominated by trauma in 35.26% of cases, followed by respiratory conditions (18.04%), and post-surgical cases (17 .22%). The high mortality rate (33.60%) was dominated by septic shock (24.39%), followed by meningeal diseases (19.51%) and trauma (17.07%). Two factors in our study were identified as influencing of mortality in patients admitted to the HBM’s PICU during 2017: male gender and mechanical ventilation. Other studies preferentially multicenter studies should be carried out to reinforce these findings and identify new factors influencing mortality in a PICU. This would allow us to generalize data in Haiti, implement and identify key measures to reduce the mortality in PICU and therefore reduce the infant and child mortality in Haiti. Declarations Conflict of interest. The authors declare no conflicts of interest. Consideration of ethics. We obtained authorization from our faculty, Faculty of Medicine and Health Sciences of the University of Notre Dame D'Haïti (FMSS-UNDH) and from the research department of HBM. Authorship Contributions. · Taïna Brice participated in conception and design of the study, data acquisition, data analysis, manuscript preparation and editing. · Maurice J. Chery participated in manuscript preparation, data analysis, critical review and editing of the finalizing manuscript. · Anne-Rose Miguel participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Naïka Paulemie Désir participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Maraïka Jean-Noël participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Nelenda Laflèche participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Richcard Alexandre participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Steeven Joseph participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Kohlz Erley Saint Jusca participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Raymonde Pinchinat participated in manuscript preparation, critical review and editing of the finalizing manuscript. · Adonaï Aly Isaac Julien participated in manuscript preparation, critical review and editing of the finalizing manuscript. 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The epidemiological profile of Pediatric Intensive Care Center at Hospital Israelita Albert Einstein. Einstein São Paulo 10:16–21 Kwizera A, Dünser M, Nakibuuka J (2012) National intensive care unit bed capacity and ICU patient characteristics in a low-income country. BMC Res Notes 5(1):475 Pongou R (2013) Why Is Infant Mortality Higher in Boys Than in Girls? A New Hypothesis Based on Preconception Environment and Evidence From a Large Sample of Twins. Demography 50(2):421–444 O’Callaghan DJ, Jayia P, Vaughan-Huxley E, Gribbon M, Templeton M, Skipworth JR et al (2012) An observational study to determine the effect of delayed admission to the intensive care unit on patient outcome. Crit Care 16(5):R173 El Halal MGDS, Barbieri E, Filho RM, Trotta EDA (2012) Carvalho P.R.A. Admission source and mortality in a pediatric intensive care unit. Indian J Crit Care Med 16(2):81–86 Källander K, Hildenwall H, Waiswa P, Galiwango E, Peterson S, Pariyo G (2008) Delayed care seeking for fatal pneumonia in children aged under five years in Uganda: a case-series study. Bull World Health Organ 86(5):332–338 on behalf of the EUCLIDS consortium, Boeddha NP, Schlapbach LJ, Driessen GJ, Herberg JA, Rivero-Calle I et al (2018) Mortality and morbidity in community-acquired sepsis in European pediatric intensive care units: a prospective cohort study from the European Childhood Life-threatening Infectious Disease Study (EUCLIDS). Crit Care 22(1):143 Valavi E, Aminzadeh M, Shirvani E, Jaafari L, Madhooshi S The Main Causes of Mortality in Pediatric Intensive Care Unit in South West of Iran. Zahedan J Res Med Sci [Internet]. 2018 [cited 2024 May 6];20(4). https://brieflands.com/articles/zjrms-63006#abstract Agra Tuñas MC, Pilar Orive FJ, Merino ER, López-Herce Cid J, Martín GM, Casas PG et al (2019) Modos de fallecimiento de los niños en Cuidados Intensivos en España. Estudio MOMUCIP (modos de muerte en UCIP). Pediatría 91(4):228–236 Suttle ML, Jenkins TL, Tamburro RF (2017) End-of-Life and Bereavement Care in Pediatric Intensive Care Units. Pediatr Clin North Am 64(5):1167–1183 Ghaffari J, Abbaskhanian A, Nazari Z (2014) Mortality Rate in Pediatric Intensive Care Unit (PICU): A Local Center Experience. Int J Pediatr Rp R (2018) Mortality Profile of Children Admitted to Intensive Care Unit of a Tertiary Care Hospital in Kerala, South India Valcin J, Jean-Charles S, Malfa A, Tucker R, Dorcélus L, Gautier J et al (2020) Mortality, morbidity and clinical care in a referral neonatal intensive care unit in Haïti. PLoS ONE 15(10):e0240465 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4385973","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":307473795,"identity":"a0b89b0c-9e8a-4197-966c-37814e1a6e96","order_by":0,"name":"Taïna Brice","email":"","orcid":"","institution":"Bon Sauveur Hospital in Cange","correspondingAuthor":false,"prefix":"","firstName":"Taïna","middleName":"","lastName":"Brice","suffix":""},{"id":307473796,"identity":"ef67d233-f997-4af4-927a-0afbcbbcf3e2","order_by":1,"name":"Maurice J. Chery","email":"","orcid":"","institution":"University of Miami Miller School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Maurice","middleName":"J.","lastName":"Chery","suffix":""},{"id":307473797,"identity":"4a1d3be3-a9da-42ea-8dd5-9a02e93aa956","order_by":2,"name":"Anne-Rose Miguel","email":"","orcid":"","institution":"Saint-Damien Hospital, Nos Petis Freres et Soeurs","correspondingAuthor":false,"prefix":"","firstName":"Anne-Rose","middleName":"","lastName":"Miguel","suffix":""},{"id":307473798,"identity":"26938c12-6d02-41f8-a62f-e5ce601dc632","order_by":3,"name":"Naïka Paulemie Désir","email":"","orcid":"https://orcid.org/0009-0002-4705-9619","institution":"University of Notre Dame D’Haïti","correspondingAuthor":false,"prefix":"","firstName":"Naïka","middleName":"Paulemie","lastName":"Désir","suffix":""},{"id":307473799,"identity":"67c2a723-25ea-4a60-9eee-ab74834b057e","order_by":4,"name":"Maraïka Jean-Noël","email":"","orcid":"https://orcid.org/0009-0007-0592-1094","institution":"Faculty of Medicine and Pharmacy, State University of Haïti","correspondingAuthor":false,"prefix":"","firstName":"Maraïka","middleName":"","lastName":"Jean-Noël","suffix":""},{"id":307473800,"identity":"cdf341d6-6b1e-414c-9cd1-6df53afa149d","order_by":5,"name":"Nelenda Laflèche","email":"","orcid":"https://orcid.org/0009-0007-2169-7053","institution":"University Hospital of Mirebalais","correspondingAuthor":false,"prefix":"","firstName":"Nelenda","middleName":"","lastName":"Laflèche","suffix":""},{"id":307473801,"identity":"e91f9430-7110-4ae4-b345-a326637ffc1e","order_by":6,"name":"Richcard Alexandre","email":"","orcid":"https://orcid.org/0009-0003-3593-4399","institution":"Bon Sauveur Hospital in 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Mirebalais","correspondingAuthor":false,"prefix":"","firstName":"Raymonde","middleName":"","lastName":"Pinchinat","suffix":""},{"id":307473805,"identity":"b74dc765-9bc4-4bf0-b60f-4aa83bebe67d","order_by":10,"name":"Adonaï Aly Isaac Julien","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABD0lEQVRIiWNgGAWjYFCCBCA2YJBhYDjAeADIlgOJHXhAhBYeoDoGkBZjsJYEgloYQFpAmhgYEhsQgtgBf3vysQc/Cux4DA6eMTjwoOJO+vywww+BttjJ6TZg1yJx5lm6YY9BMo/BAaCWhDPPcjfeTgMyGJKNzQ7gsOZGjpkEjwEzREti2+HcjbMTQFoOJG7DoUUeqEXyj0E9VMu/w+mGs9M/4NViANQizWNwGKql4XCCvHQOflsMzzxLk5YxOM4jeeBYwYGEY4cNN0jnABkGuP0idzz5mOSbP9VyfDcOb3z4o+awvPzs9M0fPlTYyeH0Pgwo3ICqMADTBgSUg4B8fwOU0UCE6lEwCkbBKBhRAABMBm5sM0PjjQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-9024-2585","institution":"Faculty of Medicine and Pharmacy, State University of Haiti","correspondingAuthor":true,"prefix":"","firstName":"Adonaï","middleName":"Aly Isaac","lastName":"Julien","suffix":""}],"badges":[],"createdAt":"2024-05-08 02:31:12","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4385973/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4385973/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57426999,"identity":"3c9d2a6c-7748-4898-be73-bd29e0898296","added_by":"auto","created_at":"2024-05-30 14:29:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85556,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlgorithm of selection of patients aged 1 month to 16 years hospitalized in the PICU of the HBM\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/cf452697461829e41f80b600.png"},{"id":57428184,"identity":"e5a42b72-e8ee-4903-9e7f-445ac83f4656","added_by":"auto","created_at":"2024-05-30 14:37:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTypes of comorbidities found in PICU patient\u003c/strong\u003es\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/43db7dd4719b2514d0d12ae2.png"},{"id":57426996,"identity":"92b9c0bf-e89b-45c1-9720-c7fb57735854","added_by":"auto","created_at":"2024-05-30 14:29:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":41298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMortality of PICU patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/8c3604a17e119783c67515e6.png"},{"id":57426994,"identity":"599e21f3-6df8-4eac-a8c8-bd10a16fd76f","added_by":"auto","created_at":"2024-05-30 14:29:52","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":54800,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTypes of comorbidities found in deceased patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/bf26e686787b96a06c1ff75a.png"},{"id":57426998,"identity":"277bd12f-1d00-405c-b683-7a6c77fc0167","added_by":"auto","created_at":"2024-05-30 14:29:52","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":48317,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of the main diagnoses found in deceased patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/b1aaeb7da0a9034a3aee114b.png"},{"id":57429127,"identity":"ae76f55b-b25b-4734-9c39-63a661614de3","added_by":"auto","created_at":"2024-05-30 14:45:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1185867,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4385973/v1/a9e21061-794a-4e13-ab51-02a95f6be311.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eInfluencing factors of Pediatric Intensive Care Unit Mortality at Bernard Mevs Hospital from January 2017 to December 2017\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMillions of children around the world experience serious medical conditions that require adequate and rigorous care in PICU (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Pediatric intensive care units include all pathological conditions that require not only rigorous and constant medical supervision but also the competence and expertise of a well-organized and trained multidisciplinary team. In fact, an intensive care unit, or ICU, is a hospital service that brings together health professionals who provide care to patients treated for severe health conditions with a poor prognosis (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePediatric care units were only created six decades ago, in the 1950s. Their existence and increasing number in the world over the past decades have been strongly associated with a significant drop in the infant and child mortality rate (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Unfortunately, to our knowledge, in Haiti, only two hospitals in the metropolitan area, created less than 20 years ago, have with a pediatric intensive care unit for the entire pediatric population of this area.\u003c/p\u003e \u003cp\u003eOur study is one of the rare elaborates on this topic in Ha\u0026iuml;ti. Our main goal was to describe and analyze the morbidity, the epidemiological profile of children admitted to an intensive care unit, and mainly the factors influencing their mortality in a hospital in the metropolitan area among patients aged from 1 month to 16 years hospitalized in the PICU of HBM from January 2017 to December 2017.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003ea. \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eType of study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study is a retrospective cross-sectional and analytical study of patients\u0026nbsp;aged 1 month to 16 years\u0026nbsp;admitted to the pediatric intensive care unit of Bernard Mews Hospital in Ha\u0026iuml;ti from January 2017 to December 2017.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStudy framework\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted this study at HBMPM, a private haitian institution in the west department, founded in 1994, located at Boulevard Toussaint Louverture Village Solidarit\u0026eacute;, serving the population of this town and its surroundings. Its geographic coordinates are -72.318993 longitude and 18.561775 latitude. The pediatric intensive care unit is subdivided into a neonatal intensive care unit (NICU) with a capacity of 4 beds accommodating newborns from 0 to 28 days old and a PICU with a capacity of 4 beds intended for patients aged over 1 month to 18 years. For the ongoing year, 129 patients have been admitted to this intensive care unit.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the patients\u0026nbsp;aged 1 month to 16 years\u0026nbsp;admitted to the pediatric intensive care unit from January 2017 to December 2017.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eInclusion and exclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInclusion criteria: patients aged 1 month to 16 years who were admitted to the pediatric intensive care unit from January 2017 to December 2017.\u003c/p\u003e\n\u003cp\u003eExclusion criteria: we excluded all records that had missing information, damaged files, or illegible information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eData collection and analyzes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data was collected by manual counting using a pre-elaborated questionnaire. A few variables\u0026mdash;age, sex, address, lengths of stay, diagnostics, mortality rate\u0026mdash;have been studied. The Epi Info 7 software (version 7.1.2.0.) was used to collect, enter, and analyze the data. We used the Mendeley software (Version 1.15.3) to create the bibliography. The odds ratio (OR) was used as an association measure, and the hypotheses of the study were verified with Pearson\u0026apos;s or Fisher\u0026apos;s exact Chi square tests. The significance level of statistical tests is reached with a \u0026ldquo;p\u0026rdquo; value of less than 0.05. For the descriptive analysis, we also used the Wilcoxon or Mann-Whitney test and the t-student.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eFrom January 1, 2017, to December 31, 2017, 129 patients were admitted to the pediatric intensive care unit of Hospital Bernard Mevs (HBM PICU). However, 7 records have been excluded because of missing or illegible information (Figure 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOut of 122 patients hospitalized in the PICU from January 1, 2017, to December 31, 2017, a male predominance was demonstrated with 76 patients (63.30%), with a sex ratio M/F of 1.65. The average age of the patients was 5.73 \u0026plusmn; 4.73 years. The average age of male patients was 5.42 \u0026plusmn; 4.61 and for the female patients was 6.24 \u0026plusmn; 4.81. 98 patients of our cohort were mostly living in urban areas (80.33%) whereas 24 (19.67%) lived in rural areas. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eComorbidities.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 122 patients admitted to the PICU, 34 (27.87%) had comorbidities or a significant disability at the time of admission. 43 patients (35.25%) had a previous hospitalization. 66 patients (54.10%) had been placed on assisted ventilation at the time of admission, 13 patients (10.66%), had an objective and up-to-date vaccination record. (Figure 2) The main comorbidities found in PICU patients during the period were hydrocephalus in 8 patients out of 34 with comorbidity (23.53%); prematurity in 6 patients (17.65%), heart disease in 3 patients (8.82%), sickle cell anemia in 3 patients (8.82%), acute severe malnutrition in 2 patients (4.88%) and asthma in 2 patients, i.e., 4.88% of cases. (Figure 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eOrigin of patients.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the patients in PICU, 55 (45.08%) came directly from their home and 67 of them i.e., 54.92% of admissions were referrals from other health structures. Among those who came from other heath structures, 47 patients (38.52%) were from another hospital; 16 (13.11%) were from a health care center; 4 (3.28%) came from a medical office. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ec.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTime frame for seeking care.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe time between the onset of symptoms and referral to a first hospital facility varies from 1 day to 150 days with an average time of 5.96 \u0026plusmn; 16.46 days. With 64.72% of the population seeking care in less than 24 hours, 25.38% between 1 to 7 days, 18.03% between 7 to 14 days, 9% between 12 to 21 days and 4.1% more than 21 days after the onset of symptoms. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eLength of stay.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe length of hospitalization for patients varies from less than 24 hours to more than 30 days with an average of 12.59 \u0026plusmn; 16.15 days and a maximum of 121 days. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ee.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eOutcome.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegarding the outcome of the patients admitted to PICU during this period: 78 patients (69.93%) were discharged. Of those, 15 (19.23%) with neurological or physical sequelae; 3 patients (2.46%) left before completing their treatment; 41 (33.60%) died. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1-\u003c/strong\u003e \u003cstrong\u003eSocio-demographic characteristics of patients admitted to the HBM PICU\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCategories\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eN (%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAge (years)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (22,13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.01075268817205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1-5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.989247311827956%\" valign=\"top\"\u003e\n \u003cp\u003e40 (32,79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.01075268817205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e6-12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.989247311827956%\" valign=\"top\"\u003e\n \u003cp\u003e40 (32,79%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.01075268817205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.989247311827956%\" valign=\"top\"\u003e\n \u003cp\u003e15 (12,30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSex\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e46 (37,70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.01075268817205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.989247311827956%\" valign=\"top\"\u003e\n \u003cp\u003e76 (62,30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eResidence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRural area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e24 (19,67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.01075268817205%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban area\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.989247311827956%\" valign=\"top\"\u003e\n \u003cp\u003e98 (80,33%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMedical History\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e43 (35,25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e79 (64,75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePrevious hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e34 (27,87%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.21802935010482%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.834381551362682%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.947589098532493%\" valign=\"top\"\u003e\n \u003cp\u003e88 (72,13%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVaccination status \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e13 (10,66%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"48.21802935010482%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.834381551362682%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.947589098532493%\" valign=\"top\"\u003e\n \u003cp\u003e109 (89,34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" valign=\"top\"\u003e\n \u003cp\u003eIntubation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e66 (54,10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.764119601328904%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.262458471760798%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e56 (45,90%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eTime to seek care (days)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026le; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e68 (55,73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;1-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e31 (25,39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;7-14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e7 (5,74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u0026ge;14\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e16 (13,28%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOrigin\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e67 (54,92%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eNon reference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e55 (45.08%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDiagnostic\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTrauma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43 (35,26%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e22 (18,04%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMeningial illnesses\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e15 (12,30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePost-Surgical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e21 (17,22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSeptic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e12 (9,84%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e9 (7,38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLength of hospital stay (days)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9 (7,38%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1-7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e51 (41,80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e8-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e54 (44,26%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e8 (6,56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFinal Outcome\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSurvivors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e81 (66,40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.205980066445186%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"42.0265780730897%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eDeceased\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.767441860465116%\" valign=\"top\"\u003e\n \u003cp\u003e41 (33,60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ef. \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMortality.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf the 122 PICU admissions, 41 patients died and 81 survived, i.e., a mortality and survival rate of 33.60% and 66.40% respectively. (Figure 3)\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eSocio-demographic characteristics of deceased patients.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e63.41% of the patients who died had a M/F sex ratio of 1.73. 14 (34.15%) of them, were under 1 year old; 13 i.e., 31.70% aged 1 to 5 years; 9 (21.95%) aged 6 to 12 years old; 5 or 12.20% over 12 years old. The average age was 6.33 \u0026plusmn; 4.67 years. 9 patients among the deceased patients (21.95%), lived in rural areas and 32 (78.05%) in urban areas. (Table 1)\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eComorbidities found in deceased population.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e14 (34.14%) of the patients who died had a comorbidity at the time of admission. 16 of them (39.03%), had at least one previous hospitalization and 38 (92.68%) had been intubated at the time of admission. The main comorbidities found in the deceased patients were hydrocephalus in 9.75% of cases, heart disease found in 3 patients (7.31%); 2 cases (4.87%) of sickle cell anemia; 1 case (2.44%) of acute severe malnutrition, and 1 patient (2.44%) with Down Syndrome. (Figure 4)\u003c/p\u003e\n\u003cp\u003e\u0026middot;\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003cstrong\u003eDiagnostics retained in deceased population.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main diagnostics retained in the 41 deceased patients were dominated by: septic shock, in 24.39% of cases, meningeal conditions in 19.51% of cases, trauma in 17.07% of cases, respiratory conditions in 14.63% of cases and post-surgical admissions in 14.63% of cases. (Figure 5)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eg.\u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eBivariate descriptive analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis analysis made it possible to explore the distribution of the data obtained according to the outcome. Table 2 allowed us to establish whether there was a significant statistical difference between patients who survived their hospitalization and patients who died, referring to our hypothesis.\u003c/p\u003e\n\u003cp\u003eAccording to the outcome of the patients in our series, 34.15% of the patients under 1 year of age died, while 16.05% of them survived. No statistically significant difference was observed (p value of 0.09). (Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 - Socio-demographic characteristics of patients by outcome\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"602\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.5%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.833333333333333%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.166666666666667%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.666666666666667%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.833333333333334%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.44758735440932%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.948419301164726%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSurvivors n= 81\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDeceased n=41\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.44758735440932%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.948419301164726%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;N (%)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eAge (years)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e13 (16,05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e14 (34,15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e1-5 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e27 (33,33% \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e13 (31,71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e6-12\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e31 (38,27%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e9 (21,95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e10 (12,35%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;5 (12,20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eGender\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e0.0049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e31 (38,27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e15 (36,59%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e50 (61,73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e26 (63,41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eResidence\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRural area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e15 (18,52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e9 (21,95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUrban area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e66 (81,48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e32 (78,05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMedical History\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eComorbidities \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eOui \u0026nbsp; \u0026nbsp;20 (24,69%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e14 (34,25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e0.7142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePrevious hospitalization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eOui \u0026nbsp; \u0026nbsp;27 (33,33%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e16 (39,02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eIntubation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eOui \u0026nbsp; \u0026nbsp;28 (34,57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e38 (92,68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOrigin\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eReference \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e46 (56,79) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e21 (51,22%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"68.43065693430657%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNon reference \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.62773722627737%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e35 (43, 21%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.941605839416058%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e20 (48,78%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eDiagnostic\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTrauma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e36 (44,44%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e7 (17,07%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory illnesses \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e16 (19,73%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e6 (14,63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMeningeal illnesses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e7 (8,64%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e8 (19,51%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0,65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePost-surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e15 (18,52%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e6 (14,63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSeptic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e2 (2,47% \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e10 (24,39%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e5 (6,17%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e4 (9,75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLength of hospitalization (days)\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.785357737104825%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;1 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e6 (7,41%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e3 (7,31%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e32 (39,50%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e19 (46,34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0,75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8-30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e35 (43,21%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e19 (46,34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.39600665557404%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.632279534109816%\" colspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003e8 (9.88%) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.153078202995008%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.81863560732113%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eh. \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eStatistical inference\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eMultivariate dynamic analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis analysis is used below to measure the association between mortality and the different factors likely to influence it, which allowed us to test our hypotheses. The model is generally well specified with a p-value likelihood ratio = 0.0020). Therefore, the results obtained are valid. This analysis of the results made it possible to identify the factors associated with a greater probability of dying. Thus, intubation and male gender are statistically significant factors in mortality in the HBM\u0026rsquo;s PICU. Intubation increased the risk of dying by 2.87 times in our series (p-value = 0.0021, OR = 2.8723). Patients of male gender have a 34% higher probability of dying than patients of female gender (p-value = 0.0049, OR = 0.3399). Indeed, comorbidities as well as previous hospitalization are statistically insignificant factors. (Table 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 - Results of hypothesis verification obtained by multivariate analysis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"554\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eFactors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOdds Ratio\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e95% \u0026nbsp; C.I.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP-Value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eComorbidities (Yes/No)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.2910; 2.3297]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.7142\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eG\u003c/em\u003eender\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003e(M/F)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.1602; 0.7210]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003eIntubation (Yes/No\u003c/em\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[1.4651; 5.6310]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.0021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cem\u003ePrevious Hospitalization (Yes/No)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.2122; 1.3742]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo our knowledge, our research regarding the factors influencing the mortality among patients hospitalized in a pediatric intensive care unit in Ha\u0026iuml;ti is one of the first to be published. The average age of patients hospitalized in the intensive care unit of the HBM in our study was 5.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73 years (0.08 to 16 years) and the median age was 5 years. Male patients had an average age of 5.42\u0026thinsp;\u0026plusmn;\u0026thinsp;4.61 years and female patients 6.24\u0026thinsp;\u0026plusmn;\u0026thinsp;4.81 years. Which is like the results of the study carried out in Brazil in 2009, in which: the median age of patients was 4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 years \u0026ndash; 4.6 years in male patients and 5.3 years in female patients (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Our results were also similar to the study carried out in Europe where the average age was 5 years. Our results were different to the study carried out in Africa by Coetzee, S. where the median age was 7 months. This study used a methodology different from ours (observational study) and analyzed the epidemiological profile of the population admitted to the PICU for a specific factor, namely measles (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Our results also differ from the retrospective study carried out in Europe by Lanetzki, C. S. et al; where the median age of patients was 2.7 years (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Our results could be explained by the high mortality rate among children less than 5 years old who are more at risk of dying from preventable and treatable causes mostly due to socioeconomic disparities (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study revealed a strong predominance of male patients hospitalized in the PICU: 76 patients (63.30%,), with a M/F sex ratio of 1.65. Result similar to the various studies mentioned in our literature review, namely the work of: Araujo et al. in Brazil; Lanetzki, C. et al, in Europe; Kwizera, A. et al, in Africa. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Indeed, studies have shown that the mortality rate among boys is higher than girls in most parts of the world. For this age group, this has been explained by sex differences in genetic and biological makeup, with boys being biologically weaker and more susceptible to diseases and premature death (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003eRegarding the residence area, our study population mainly resided in urban areas with 98 patients (80.33%) and 24 (19.67%) in rural areas. However, in the observational study conducted by O'Callaghan D.J. et al; the infant mortality is slightly higher in rural areas than in urban areas (59% versus 56%) (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e1/3 of the patients in the study carried out by El Halal M.G. et al., were referred from other hospitals (34.7%). Only 0.7% of admissions came directly from their home (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The study carried out by Javad Ghaffari et al in 2011 revealed that 49% of patients came directly from their homes and 51% from other hospital structures. This latest study matches ourhas similar results to ours. Indeed, among our study populations 55 patients (45.08%) came directly from their home and 67 patients (54.92%) of admissions were referrals from other health structures (9). This high referral rate could be explained by the fact that HBM is one of the rare hospitals in the metropolitan area, accessible to the population, and equipped with an emergency and intensive care unit.\u003c/p\u003e \u003cp\u003eIn our series, the average time to seek care was 1 day. These results are similar to those of the study carried out in Africa by Karin K\u0026auml;llander et al., according to which the average time to seek care outside the home was 2 days (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Results that could be explained by the tendency of our population to resort to traditional medicine before any contact with any medical structure.\u003c/p\u003e \u003cp\u003eRegarding the duration of stay in the hospital, in our study it varied from less than 24 hours to more than 30 days with a maximum duration of 121 days, and an average duration of 12.59\u0026thinsp;\u0026plusmn;\u0026thinsp;16.15 days. These findings differ from studies carried out in Africa by Karin K\u0026auml;llander et al, with an average duration of hospitalization of 3 days (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and which could be explained by the fact that it is a series of cases carried out on a population of children aged less than 5 years and relates exclusively to admissions due to pneumonia.\u003c/p\u003e \u003cp\u003eOur research also demonstrated that 54.10% of patients admitted to the PICU during this period were intubated and received mechanical ventilation at the time of their admission. These results are almost similar to the study of Navin P. Boeddha et al, who demonstrated that 69% of their patients benefited from invasive ventilation (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The retrospective study carried out in Iran revealed that 24.60% of deceased patients were intubated during their hospitalization in PICU. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Results which differ from our study, where 92.68% of deceased patients were intubated. The differences could be explained by the fact that the study carried out in Iran, although having a similar methodology, had excluded cases of trauma and post-surgical admissions.\u003c/p\u003e \u003cp\u003eThe main diagnostic of the patients in our study were classified into different categories: first trauma, found in 43 patients or 35.26% of admission, followed by respiratory diseases, found in 22 patients or 18.04% of admission and third post-surgical admissions, in 17.22% of cases. Our results are similar to the study carried out in 2009 in Brazil by Taisa E. Araujo et al., (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) which demonstrated that respiratory illnesses represented the most common causes of admission to intensive care units (32.7%), followed by post-operative care (30.9%) and trauma cases (12.8%). However, the results of other studies, although all having in common respiratory illnesses as the most common cause of hospitalization; differ from our results. In Uganda, the study carried out by Kwizera, A. et al, demonstrated that the most frequent cause of admission was post-surgical treatments. The percentage was not mentioned in this study (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe latest studies carried out around the world have demonstrated that the mortality rate in PICU is now \u0026lt;\u0026thinsp;3%. Studies carried out in Europe, North America, and Africa, by Agra Tu\u0026ntilde;as et al., Namachivayam et al., Markita L. and Suttle et al; demonstrated similar results with a respective mortality rate of 2.20%, and 2.38% (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Results completely different from the mortality rate found in our study work i.e., 33.60%. This high mortality rate in the pediatric intensive care unit of HBM could be explained by the generally late delay in seeking care of the ha\u0026iuml;tian population and by the high rate of trauma due to motor vehicle accidents and falls, admitted during this period; and knowing that HBM is known for the management of emergencies from all causes.\u003c/p\u003e \u003cp\u003e56.10% of deaths occurred in a context of brain death, 41.46% after failure of cardiovascular resuscitation and 2.44%, after a decision of limitation of therapeutic intervention. This differs from the data published by Agra Tu\u0026ntilde;as M.C. et al, in Spain where 50.7% of deaths occurred after a decision to limit therapeutic intervention; 114 (33.8%) after cardiovascular resuscitation and 52 (15.4%) were due to cases of brain death. And also those published by Markita L. Suttle et al., in the United States of America where 133 patients (70%) died after interruption of life-sustaining treatment, 30 (16%); after a diagnosis of brain death and 26 (14%) following an attempt at cardiopulmonary resuscitation (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn our research, the deceased patients were mainly male i.e., 26 patients (63.41%), with a M/F sex ratio of 1.73. Result similar to the study of Rashma R.P. et al, where 52% of the deceased patients were male; and similar to the result of Valavi E. et al, where death was observed in 51.80% of M ​​patients (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). 14 patients (or 34.15%) died in our study, they were less than 1 year old. The results are similar to those of the study carried out by El Halal M.G. et al, where 37.5% of the deceased patients were aged less than 1 year (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The average age of patients who died in our study was 6.33\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67 years. This differs from the results of Rashma R.P. et al, where the average age of the deceased children was 3.40\u0026thinsp;+\u0026thinsp;4.16 years; note that this study, although having a similar methodology to ours, was carried out on a younger population (1 month to 14 years old). It also differs from the retrospective study carried out in Iran by Valavi E. et al, where the average age of deceased patients was 2.2 years (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur research also demonstrated that the mortality rate decreased with age; 14 deaths i.e., 34.15% aged less than 1 year; 13 i.e., 31.70% aged 1 to 5 years; 9 i.e., 21.95% aged 6 to 12 years old and 5 i.e., 12.20% over 12 years old. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This result differs from El. Halal M.G. et al, who found that mortality increased significantly with age. The mortality rate was 0.9%, 8.9%, 12.3%, 10.4% and 17%, respectively, for children\u0026thinsp;\u0026le;\u0026thinsp;1 month, \u0026lt; 1 year, 1\u0026ndash;5 years old, 5\u0026ndash;12 years old and \u0026ge;\u0026thinsp;12 years old (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the 41 deaths recorded in our study, 34.14% of patients had a comorbidity at the time of admission. 16 of them i.e., 39.03%, had at least one previous hospitalization. These results differ from those of Agra Tu\u0026ntilde;as M.C. et al, in Spain where a total of 86 patients (25.5%) had a previous hospitalization, 273 (75%) of them suffered from a chronic pathology and 78 (23%) had a serious disability at the time of admission (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This difference could be explained by the fact this study was carried out over several years in several hospital centers.\u003c/p\u003e \u003cp\u003eThe comorbidities found in the 14 deceased patients were mainly of a neurological aspect with 4 patients, i.e., 28.56% with hydrocephalus, 21.43% i.e., 3 patients with heart diseases, 2 i.e., 14.28%, had hematological disease (sickle cell disease), 1 patient i.e., 7.42% had chromosomal anomaly (Down syndrome). These were also the most frequent comorbidities in the study by Halal M.G. et al: neurological (11.5%), hematological/oncological (11.4%) and genetic (7.3%) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Which could probably be explained by the fact that HBM is one of the rare hospitals with a neurosurgery department that serve the adult and pediatric population (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main diagnostics retained in the 41 deceased patients in our work, were dominated by: septic shock in 24.39% of cases knowing that preventable infections still play a major role in the pediatric mortality in Haiti. Meningeal conditions were found in 19.51% of cases, trauma in 17.07% of cases, respiratory illnesses in 14.63% of cases and post-surgical admissions in 14.63% of cases. These diagnostics are different from those published by Agra Tu\u0026ntilde;as M.C. et al, a retrospective study carried out in Spain for which the most frequent causes of hospitalization were in 32.6% of cases, cardiac and in 22.6% of cases, respiratory illnesses (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). They also differ from the results of El Halal M.G. et al, where the mortality was mainly due to cardiopulmonary arrest in 29% of cases, sepsis 19%, pneumonia 16%, multi-system dysfunction 14%, hepatic diseases in 7% of cases, an inborn error of metabolism 6%, and acute respiratory distress syndrome in 6% of cases (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePredictive factors of mortality.\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eOur research allowed us to identify among the different hypotheses mentioned, two factors associated with greater mortality rate within the PICU of HBM. Indeed, following our various analyses, male gender and intubation were retained as predictive factors of mortality (p\u0026thinsp;=\u0026thinsp;0.0021, and p\u0026thinsp;=\u0026thinsp;0.0049) respectively. Intubation was also incriminated in the studies of Navin P. Boeddha et al, and Valavi E. et al. This factor could be explained by the fact that patients generally placed under mechanical ventilation within an ICU are patients in more critical shape than patients who are not (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Our results are also similar to the studies of Rashma R.P. et al, and Valavi E. et al, (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) where in fact also male sex was identified as a predictive factor of mortality. This could be explained by the fact that our study population is mainly boys with a significant statistical difference as shown in Table\u0026nbsp;5 (poled 0.042). Results which should arouse scientific curiosity and constitute an avenue for future scientific research.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eStrengths and limitations.\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe predictors of mortality in a PICU is a subject of great importance in Haiti, but unfortunately informations, studies and even researches are very limited. Indeed, very few studies on this subject have been carried out in Haiti (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough there are only two hospitals in the metropolotain area with a pediatric intensive care unit, this study was carried out in only one center, namely HBM, which is known for the management of medical emergencies, intensive care, and surgical intervention.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRecommendations.\u003c/b\u003e \u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eWe made some recommendations to the Ministry of Public Health and Population, on the importance of the implementation of strategies to promote equitable access to health services, promote the continuous training of medical staff, create new PICUs, and create more rehabilitation centers for patients with physical or neurological sequelae.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eA pediatric intensive care unit is a critical care entity essential to the care and survival of children who face life-threatening illnesses every day. The literature and this research have allowed us to see that, in fact, without a qualified staff and rigorous care, many seriously ill children would die. Many predictable or avoidable admissions often lead to deaths in a PICU. However, in Haiti, although aware of this sad reality, there are very few hospitals with a pediatric intensive care unit, very few pediatricians with training in this area and even fewer data on this theme. Morbidity in PICU in Haiti and the factors influencing mortality are not known to everyone. Morbidity within the HBM\u0026rsquo;s PICU during the year 2017 was mainly dominated by trauma in 35.26% of cases, followed by respiratory conditions (18.04%), and post-surgical cases (17 .22%). The high mortality rate (33.60%) was dominated by septic shock (24.39%), followed by meningeal diseases (19.51%) and trauma (17.07%).\u003c/p\u003e \u003cp\u003eTwo factors in our study were identified as influencing of mortality in patients admitted to the HBM\u0026rsquo;s PICU during 2017: male gender and mechanical ventilation. Other studies preferentially multicenter studies should be carried out to reinforce these findings and identify new factors influencing mortality in a PICU. This would allow us to generalize data in Haiti, implement and identify key measures to reduce the mortality in PICU and therefore reduce the infant and child mortality in Haiti.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsideration of ethics.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained authorization from our faculty, Faculty of Medicine and Health Sciences of the University of Notre Dame D\u0026apos;Ha\u0026iuml;ti (FMSS-UNDH) and from the research department of HBM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthorship Contributions.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eTa\u0026iuml;na Brice\u003c/strong\u003e participated in conception and design of the study, data acquisition, data analysis, manuscript preparation and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eMaurice J. Chery\u003c/strong\u003e participated in manuscript preparation, data analysis, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eAnne-Rose Miguel\u0026nbsp;\u003c/strong\u003eparticipated\u0026nbsp;in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eNa\u0026iuml;ka Paulemie D\u0026eacute;sir\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eMara\u0026iuml;ka Jean-No\u0026euml;l\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eNelenda Lafl\u0026egrave;che\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eRichcard Alexandre\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eSteeven Joseph\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eKohlz Erley Saint Jusca\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eRaymonde Pinchinat\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026middot; \u0026nbsp; \u0026nbsp;\u003cstrong\u003eAdona\u0026iuml; Aly Isaac Julien\u003c/strong\u003e participated in manuscript preparation, critical review and editing of the finalizing manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors received no financial support for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpecial thank you to the staff working in the Archives of Hospital Bernard Mevs who made this study possible.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNABHANI M. UNICEF. (2023) [cited 2024 May 7]. Mortalit\u0026eacute; infantile: 1,9 million de b\u0026eacute;b\u0026eacute;s sont morts tragiquement en 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unicef.fr/article/rapport-de-lonu-toutes-les-44-secondes-un-enfant-ou-un-jeune-est-decede-en-2021/\u003c/span\u003e\u003cspan address=\"https://www.unicef.fr/article/rapport-de-lonu-toutes-les-44-secondes-un-enfant-ou-un-jeune-est-decede-en-2021/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAraujo TE, Vieira SMG, Carvalho PRA (2010) Stress ulcer prophylaxis in pediatric intensive care units. J Pediatr (Rio J) 86(6):525\u0026ndash;530\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003edatadot [Internet] [cited 2024 May 6]. COVID-19 cases | WHO COVID-19 dashboard. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.who.int/dashboards/covid19/cases\u003c/span\u003e\u003cspan address=\"https://data.who.int/dashboards/covid19/cases\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoetzee S, Morrow BM, Argent AC (2014) Measles in a S outh A frican paediatric intensive care unit: Again! J Paediatr Child Health 50(5):379\u0026ndash;385\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLanetzki CS, de Oliveira CAC, Bass LM, Abramovici S, Troster E (2012) J. The epidemiological profile of Pediatric Intensive Care Center at Hospital Israelita Albert Einstein. Einstein S\u0026atilde;o Paulo 10:16\u0026ndash;21\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKwizera A, D\u0026uuml;nser M, Nakibuuka J (2012) National intensive care unit bed capacity and ICU patient characteristics in a low-income country. BMC Res Notes 5(1):475\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePongou R (2013) Why Is Infant Mortality Higher in Boys Than in Girls? A New Hypothesis Based on Preconception Environment and Evidence From a Large Sample of Twins. Demography 50(2):421\u0026ndash;444\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO\u0026rsquo;Callaghan DJ, Jayia P, Vaughan-Huxley E, Gribbon M, Templeton M, Skipworth JR et al (2012) An observational study to determine the effect of delayed admission to the intensive care unit on patient outcome. Crit Care 16(5):R173\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Halal MGDS, Barbieri E, Filho RM, Trotta EDA (2012) Carvalho P.R.A. Admission source and mortality in a pediatric intensive care unit. Indian J Crit Care Med 16(2):81\u0026ndash;86\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK\u0026auml;llander K, Hildenwall H, Waiswa P, Galiwango E, Peterson S, Pariyo G (2008) Delayed care seeking for fatal pneumonia in children aged under five years in Uganda: a case-series study. Bull World Health Organ 86(5):332\u0026ndash;338\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eon behalf of the EUCLIDS consortium, Boeddha NP, Schlapbach LJ, Driessen GJ, Herberg JA, Rivero-Calle I et al (2018) Mortality and morbidity in community-acquired sepsis in European pediatric intensive care units: a prospective cohort study from the European Childhood Life-threatening Infectious Disease Study (EUCLIDS). Crit Care 22(1):143\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValavi E, Aminzadeh M, Shirvani E, Jaafari L, Madhooshi S The Main Causes of Mortality in Pediatric Intensive Care Unit in South West of Iran. Zahedan J Res Med Sci [Internet]. 2018 [cited 2024 May 6];20(4). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://brieflands.com/articles/zjrms-63006#abstract\u003c/span\u003e\u003cspan address=\"https://brieflands.com/articles/zjrms-63006#abstract\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgra Tu\u0026ntilde;as MC, Pilar Orive FJ, Merino ER, L\u0026oacute;pez-Herce Cid J, Mart\u0026iacute;n GM, Casas PG et al (2019) Modos de fallecimiento de los ni\u0026ntilde;os en Cuidados Intensivos en Espa\u0026ntilde;a. Estudio MOMUCIP (modos de muerte en UCIP). Pediatr\u0026iacute;a 91(4):228\u0026ndash;236\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuttle ML, Jenkins TL, Tamburro RF (2017) End-of-Life and Bereavement Care in Pediatric Intensive Care Units. Pediatr Clin North Am 64(5):1167\u0026ndash;1183\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhaffari J, Abbaskhanian A, Nazari Z (2014) Mortality Rate in Pediatric Intensive Care Unit (PICU): A Local Center Experience. Int J Pediatr\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRp R (2018) Mortality Profile of Children Admitted to Intensive Care Unit of a Tertiary Care Hospital in Kerala, South India\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValcin J, Jean-Charles S, Malfa A, Tucker R, Dorc\u0026eacute;lus L, Gautier J et al (2020) Mortality, morbidity and clinical care in a referral neonatal intensive care unit in Ha\u0026iuml;ti. PLoS ONE 15(10):e0240465\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Université Notre Dame d'Haïti","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":"Pediatric intensive care unit, mortality rate, morbidity, low-resource country, Haiti","lastPublishedDoi":"10.21203/rs.3.rs-4385973/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4385973/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eThe morbi-mortality in a pediatric intensive care unit is an important determinant of child mortality worldwide. In Haiti, there are only two hospitals in the metropolitan area with a pediatric intensive care unit. The objective of this study is to identify the main factors influencing the mortality of patients aged 1 month to 16 years hospitalized in the pediatric intensive care unit at the Bernard Mevs Hospital (HBM).\u003c/p\u003e\u003ch2\u003eMethodology:\u003c/h2\u003e \u003cp\u003eWe carried out a retrospecptive cross-sectional and analytical study over one year, within the Bernard Mevs Hospital Medishare Project (HBMPM). Our population consisted of all the patients aged 1 month to 16 years hospitalized in the pediatric intensive care unit of HBM from January 2017 to December 2017.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFrom January 1, 2017, to December 31, 2017, 122 files of patients admitted to the pediatric intensive care units (PICU) at HBM were selected. Among those patients, a male predominance was demonstrated with 76 patients, or 63.30%, with a sex ratio of 1.65. The average age of the patients was 5.73\u0026thinsp;\u0026plusmn;\u0026thinsp;4.73 years. In 43 patients (35.26%), trauma was the main cause of hospitalization, followed by respiratory illnesses, found in 22 patients, or 18.04% of admissions. The mortality rate was 33.60%, dominated by septic shock in 24% of cases. The average days of hospitalization in the deceased population was 12 days. This study demonstrated that the probability of dying in the PICU is higher in male patients (p-value of 0.0049) and in patients who have been intubated (p-value of 0.0021).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study has demonstrated a high mortality rate among male patients and those who have been intubated. Most of the causes of admission were preventable. Other studies should be carried out to generalize data and identify key measures to reduce the infant and child mortality in Haiti.\u003c/p\u003e","manuscriptTitle":"Influencing factors of Pediatric Intensive Care Unit Mortality at Bernard Mevs Hospital from January 2017 to December 2017","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-30 14:29:48","doi":"10.21203/rs.3.rs-4385973/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":"1e2afc51-1138-4e19-b740-0a988e415095","owner":[],"postedDate":"May 30th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":32474146,"name":"Pediatrics"}],"tags":[],"updatedAt":"2024-05-30T14:29:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-30 14:29:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4385973","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4385973","identity":"rs-4385973","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}