Background: Substantial mortality occurs after hospital discharge in children younger than 5 years with suspected sepsis, especially in low-income countries. A better understanding of its epidemiology is needed for effective interventions to reduce child mortality in these countries. We evaluated risk factors for death after discharge in children admitted to hospital for suspected sepsis in Uganda, and assessed how these differed by age, time of death, and location of death. Methods: In this prospective observational cohort study, we recruited 0-60-month-old children admitted with suspected sepsis from the community to the paediatric wards of six Ugandan hospitals. The primary outcome was six-month post-discharge mortality among those discharged alive. We evaluated the interactive impact of age, time of death, and location of death on risk factors for mortality. Findings: 6,545 children were enrolled, with 6,191 discharged alive. The median (interquartile range) time from discharge to death was 28 (9-74) days, with a six-month post-discharge mortality rate of 5·5%, constituting 51% of total mortality. Deaths occurred at home (45%), in-transit to care (18%), or in hospital (37%) during a subsequent readmission. Post-discharge death was strongly associated with weight-for-age z-scores < -3 (adjusted risk ratio [aRR] 4·7, 95% CI 3·7–5·8 vs a Z score of >–2), referral for further care (7·3, 5·6–9·5), and unplanned discharge (3·2, 2·5–4·0). The hazard ratio of those with severe anaemia increased with time since discharge, while the hazard ratios of discharge vulnerabilities (unplanned, poor feeding) decreased with time. Age influenced the effect of several variables, including anthropometric indices (less impact with increasing age), anaemia (greater impact), and admission temperature (greater impact). Data Collection Methods: All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada). At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge. Data Processing Methods: For this analysis, data from both cohorts (0-6 months and 6-60 months) were combined and analysed as a single dataset. We used periods of overlapping enrolment (72% of total enrolment months) between the two cohorts to determine site-specific proportions of children who were 0-6 and 6-60 months of age. These proportions were used to weight the cohorts for the calculation of overall mortality rate. Z-scores were calculated using height and weight. Hematocrit was converted to hemoglobin. Distance to hospital was calculated using latitude and longitude. Extra symptom and diagnosis categories were created based on text field in these two variables. BCS score was created by summing all individual components. Abbreviations: MUAC -mid upper arm circumference wfa – weight for age wfl – weight for length bmi – body mass index lfa – length for age abx - antibiotics hr – heart rate rr – respiratory rate antimal - antimalarial sysbp – systolic blood pressure diasbp – diastolic blood pressure resp – respiratory cap - capillary BCS - Blantyre Coma Scale dist- distance hos - hospital ed - education disch - discharge dis -discharge fu – follow-up pd – post-discharge loc - location materl - maternal Ethics Declaration: This study was approved by the Mbarara University of Science and Technology Research Ethics Committee (No. 15/10-16), the Uganda National Institute of Science and Technology (HS 2207), and the University of British Columbia / Children & Women’s Health Centre of British Columbia Research Ethics Board (H16-02679). This manuscript adheres to the guidelines for STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Study Protocol & Supplementary Materials: Smart Discharges to improve post-discharge health outcomes in children: A prospective before-after study with staggered implementation, NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

Mortality rate of sepsis cases during hospitalization (%) by age group.

The age-specific mortality rate of sepsis at all ages in Canada increased by 0.3 deaths (+5.36 percent) compared to the previous year. In total, the age-specific mortality rate amounted to 5.9 deaths in 2023.

In 2019, around 306 men aged 65 and over per 100,000 population in the United States died due to sepsis or septicemia, compared to around 255 deaths per 100,000 among females in the same age group. This statistic illustrates sepsis-related death rates for adults in the United States aged 65 and over as of 2019, by age and gender.

BackgroundDue to its potent antibacterial activity, vancomycin is widely used in the treatment of sepsis. Therapeutic drug monitoring (TDM) can optimize personalized vancomycin dosing regimens, enhancing therapeutic efficacy and minimizing nephrotoxic risk, thereby potentially improving patient outcomes. However, it remains uncertain whether TDM affects the mortality rate among sepsis patients or whether age plays a role in this outcome.MethodsWe analyzed data from the Medical Information Mart of Intensive Care–IV database, focusing on sepsis patients who were admitted to the intensive care unit (ICU) and treated with vancomycin. The primary variable of interest was the use of vancomycin TDM during the ICU stay. The primary outcome was 30-day mortality. To control for potential confounding factors and evaluate associations, we used Cox proportional hazards regression and propensity score matching (PSM). Subgroup and sensitivity analyses were performed to assess the robustness of our findings. Furthermore, restricted cubic spline models were utilized to investigate the relationship between age and mortality among different groups of sepsis patients, to identify potential non-linear associations.ResultsA total of 14,053 sepsis patients met the study criteria, of whom 6,826 received at least one TDM during their ICU stay. After PSM, analysis of 4,329 matched pairs revealed a significantly lower 30-day mortality in the TDM group compared with the non-TDM group (23.3% vs.27.7%, p < 0.001). Multivariable Cox proportional hazards regression showed a significantly reduced 30-day mortality risk in the TDM group [adjusted hazard ratio (HR): 0.66; 95% confidence interval (CI): 0.61–0.71; p < 0.001]. This finding was supported by PSM-adjusted analysis (adjusted HR: 0.71; 95% CI: 0.66–0.77; p < 0.001) and inverse probability of treatment weighting analysis (adjusted HR: 0.72; 95% CI: 0.67–0.77; p < 0.001). Kaplan–Meier survival curves also indicated significantly higher 30-day survival in the TDM group (log-rank test, p < 0.0001). Subgroup analyses by gender, age, and race yielded consistent results. Patients with higher severity of illness—indicated by sequential organ failure assessment scores ≥6, acute physiology score III ≥40, or requiring renal replacement therapy, vasopressors, or mechanical ventilation—experienced more pronounced mortality improvement from vancomycin TDM compared with those with lower severity scores or not requiring these interventions. The results remained robust after excluding patients with ICU stays

In 2019, around 377 non-Hispanic Black adults per 100,000 population in the United States aged 65 and over died due to sepsis or septicemia, compared to around 276 deaths per 100,000 among non-Hispanic white adults in the same age group. This statistic illustrates sepsis-related death rates for adults in the United States aged 65 and over as of 2019, by age and ethnicity.

Sepsis is defined as a clinical syndrome in which patients have an infection that is accompanied by an extreme systemic response. Sepsis of sufficient severity that the function of major organ systems in the body (such as heart, kidney, brain, and others) is impaired is referred to as “severe sepsis.” Patients with severe sepsis that have continued organ system impairment and/or low blood pressure that does not respond to treatment with adequate fluid replacement are considered to be in “septic shock.” The combination of early detection of sepsis coupled with timely, appropriate interventions can significantly improve the chances of survival for patients with all types of sepsis.

The datasets contain hospital-level treatment measures for pediatric (age < 18) patients with a diagnosis of severe sepsis or septic shock seen at New York State Article 28 (acute care) facilities and reported to the New York State Department of Health in 2015 and 2016.

The treatment measures are presented by hospital. Only hospital level measure data for which there were at least ten cases in the denominator is reported. Statewide measures are calculated using all hospitals, regardless of the number of sepsis cases treated.

Background: In many low-income countries, over five percent of hospitalized children die following hospital discharge. The lack of available tools to identify those at risk of post-discharge mortality has limited the ability to make progress towards improving outcomes. We aimed to develop algorithms designed to predict post-discharge mortality among children admitted with suspected sepsis.

Methods: Four prospective cohort studies of children in two age groups (0–6 and 6–60 months) were conducted between 2012–2021 in six Ugandan hospitals. Prediction models were derived for six-months post-discharge mortality, based on candidate predictors collected at admission, each with a maximum of eight variables, and internally validated using 10-fold cross-validation.

Findings: 8,810 children were enrolled: 470 (5.3%) died in hospital; 257 (7.7%) and 233 (4.8%) post-discharge deaths occurred in the 0-6-month and 6-60-month age groups, respectively. The primary models had an area under the receiver operating characteristic curve (AUROC) of 0.77 (95%CI 0.74–0.80) for 0-6-month-olds and 0.75 (95%CI 0.72–0.79) for 6-60-month-olds; mean AUROCs among the 10 cross-validation folds were 0.75 and 0.73, respectively. Calibration across risk strata was good: Brier scores were 0.07 and 0.04, respectively. The most important variables included anthropometry and oxygen saturation. Additional variables included: illness duration, jaundice-age interaction, and a bulging fontanelle among 0-6-month-olds; and prior admissions, coma score, temperature, age-respiratory rate interaction, and HIV status among 6-60-month-olds.

Data Processing Methods: The post-processed data files were created using R version 4.2.2. (R Foundation for Statistical Computing, Vienna, Austria) and briefly involved renaming columns from the different datasets so that they are consistent, converting categories coded as “unknown”, “don’t know”, or “missing” to NA, creating new columns, calculating z-scored variables, and converting relevant columns to factors or dates.

Ethics Declaration: These studies were approved by the Mbarara University of Science and Technology (No. 15/10-16), the Uganda National Council for Science and Technology (HS 2207), and the University of British Columbia (H16-02679).

the Original data of this research,Our data showed that the survivors had higher lactate clearance rate, rather than 10% lactate clearance rate. This result was consistent with the results reported by recent similar studies, showing that >30% lactate clearance rate could improve the clinical prognosis of systemic infection related to hyperlactacidemia patients,Our data also find the actual lactate clearance rate showed no significant difference between the survivors of both the groups, suggesting that elderly patients were not required to obtain higher lactate clearance rate than that of adults to obtain equal survival rate.

As per the Centers for Disease Control and Prevention (CDC), sepsis-related deaths decreased from 2000 to 2019, but the mortality rate for people aged 65 and over increased from 277 per 100,000 in 2019 to 331 per 100,000 in 2021. Studies also show a strong correlation between septic shock to advanced age, with the incidence of septic shock reported to rise significantly in people over 50 years.

Background: Under-five mortality remains concentrated in resource-poor countries. Post-discharge mortality is becoming increasingly recognized as a significant contributor to overall child mortality. With a substantial recent expansion of research and novel data synthesis methods, this study aims to update the current evidence base by providing a more nuanced understanding of the burden and associated risk factors of pediatric post-discharge mortality after acute illness. Methods: Eligible studies published between January 1, 2017 and January 31, 2023, were retrieved using MEDLINE, Embase, and CINAHL databases. Studies published before 2017 were identified in a previous review and added to the total pool of studies. Only studies from countries with low or low-middle Socio-Demographic Index with a post-discharge observation period greater than seven days were included. Risk of bias was assessed using a modified version of the Joanna Briggs Institute critical appraisal tool for prevalence studies. Studies were grouped by patient population, and 6-month post-discharge mortality rates were quantified by random-effects meta-analysis. Secondary outcomes included post-discharge mortality relative to in-hospital mortality, pooled risk factor estimates, and pooled post-discharge Kaplan–Meier survival curves. PROSPERO study registration: #CRD42022350975. Findings: Of 1963 articles screened, 42 eligible articles were identified and combined with 22 articles identified in the previous review, resulting in 64 total articles. These articles represented 46 unique patient cohorts and included a total of 105,560 children. For children admitted with a general acute illness, the pooled risk of mortality six months post-discharge was 4.4% (95% CI: 3.5%–5.4%, I2 = 94.2%, n = 11 studies, 34,457 children), and the pooled in-hospital mortality rate was 5.9% (95% CI: 4.2%–7.7%, I2 = 98.7%, n = 12 studies, 63,307 children). Among disease subgroups, severe malnutrition (12.2%, 95% CI: 6.2%–19.7%, I2 = 98.2%, n = 10 studies, 7760 children) and severe anemia (6.4%, 95% CI: 4.2%–9.1%, I2 = 93.3%, n = 9 studies, 7806 children) demonstrated the highest 6-month post-discharge mortality estimates. Diarrhea demonstrated the shortest median time to death (3.3 weeks) and anemia the longest (8.9 weeks). Most significant risk factors for post-discharge mortality included unplanned discharges, severe malnutrition, and HIV seropositivity. Interpretation: Pediatric post-discharge mortality rates remain high in resource-poor settings, especially among children admitted with malnutrition or anemia. Global health strategies must prioritize this health issue by dedicating resources to research and policy innovation. Data Processing Methods: Data were extracted using a standard data extraction form developed by the review authors. Kaplan–Meier survival curves, where provided, were extracted using a plot digitizer. The data extraction file, “PDMSR2024_DataExtraction_Dataset_SD” was generated as described above and analyzed as is. Co-ordinates were extracted from the survival curves in their original, published form, using a plot digitizer (https://automeris.io/WebPlotDigitizer/). The co-ordinates for each survival curve were then cleaned up to: 1. Re-scale the time points to weeks 2. Curves which reported % mortality were converted to % survival (1 – mortality) 3. First co-ordinate was set to (0, 1), i.e., survival is 100% at time-point 0 4. Include the numbers at risk (if reported), primary reference, and subgroup information Using these cleaned co-ordinates, individual-level patient data were extracted (see Guyot et al, 2012, doi.org/10.1186/1471-2288-12-9) and the survival curves re-constructed to obtain the survival and number at risk at specified time-points (0-52 weeks). Where possible, disease and age subgroups were combined to create all admissions curves by combining the individual-level patient data from multiple curves in the same study. Additional data from the survival curves were extracted to produce the “PDMSR2024_AdditionalDataSurvivalCurves6M_Dataset_SD” and “PDMSR2024_AdditionalDataSurvivalCurves12M_Dataset_SD” files by extracting the survival rate at 6 and 12 months. Previously unpublished hazards ratios were extracted from the dataset used in the Wiens et al (2015) study on post-discharge mortality (doi:10.1136/bmjopen-2015-009449) to produce the “PDMSR2024_Wiens2015HazardsRatios_Dataset_SD.xlsx” file. These original data are published on Dataverse at: doi.org/10.5683/SP2/VBPLRM Analyses were in R version 4.3.0 (R Foundation for Statistical Computing, Vienna, Austria), and RStudio version 2023.6.1 (RStudio, Boston, MA). Additional Files: Survival curves in their original, published form, as well as survival curve coordinates files can be made available by request. NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business...

OBJECTIVE: To evaluate the long-term survival rate of critically ill sepsis survivors following cardiopulmonary resuscitation on a national scale. DESIGN: Retrospective and observational cohort study. SETTING: Data were extracted from Taiwan's National Health Insurance Research Database. PATIENTS: A total of 272,897 ICU patients with sepsis were identified during 2000-2010. Patients who survived to hospital discharge were enrolled. Post-discharge survival outcomes of ICU sepsis survivors who received cardiopulmonary resuscitation were compared with those of patients who did not experience cardiopulmonary arrest using propensity score matching with a 1:1 ratio. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: Only 7% (n = 3,207) of sepsis patients who received cardiopulmonary resuscitation survived to discharge. The overall 1-, 2-, and 5-year postdischarge survival rates following cardiopulmonary resuscitation were 28%, 23%, and 14%, respectively. Compared with sepsis survivors without cardiopulmonary arrest, sepsis survivors who received cardiopulmonary resuscitation had a greater risk of all-cause mortality after discharge (hazard ratio, 1.38； 95% CI, 1.34-1.46). This difference in mortality risk diminished after 2 years (hazard ratio, 1.11； 95% CI, 0.96-1.28). Multivariable analysis showed that independent risk factors for long-term mortality following cardiopulmonary resuscitation were male sex, older age, receipt of care in a nonmedical center, higher Charlson Comorbidity Index score, chronic kidney disease, cancer, respiratory infection, vasoactive agent use, and receipt of renal replacement therapy during ICU stay. CONCLUSION: The long-term outcome was worse in ICU survivors of sepsis who received in-hospital cardiopulmonary resuscitation than in those who did not, but this increased risk of mortality diminished at 2 years after discharge.

"BACKGROUND: Antiplatelet agents are widely used for cardiovascular disea ses, but their pleiotropic effects in sepsis are controversial.

OBJECTIVE: To investigate the association between antiplatelet agents and the survival benefit for sepsis patients.

DESIGN: A nationwide population-based cohort and nested case-control study.

SETTING: Taiwan National Health Insurance database.

PARTICIPANTS: All patients (age ?18 years) who were hospitalized for sepsis between January 2000 and December 2010.

MEASUREMENTS: Conditional logistic regression was used to adjust for confounding. Adjusted odd ratios (ORs) were used to compare the mortality rate due to sepsis in antiplatelet drug users and nonusers.

RESULTS: Of 683,421 included patients, 229,792 (33.6 %) patients died during hospitalization for sepsis, and the rest (64.4 %) survived to discharge. Use of antiplatelet agents before admission was associated with a lower risk of mortality in sepsis patients (aOR 0.82, 95 % confidence interval [CI] 0.81-0.83, P ＜ 0.001). By using another case-control study design, the beneficial effect was more significant in current users (aOR 0.78, 95 % CI 0.76-0.79) than in recent users (aOR 0.88, 95 % CI 0.85-0.91), but was not significant in past users (aOR 1.00, 95 % CI 0.98-1.02).

LIMITATIONS: Observational study.

CONCLUSIONS: Prior use of antiplatelet agents was associated with a survival benefit in sepsis patients."

Objective: Most sepsis studies have looked at the general population. The aim of this study is to report on the characteristics, treatment and hospital mortality of patients with cancer diagnosed with sepsis or septic shock. Setting: A single-centre retrospective study at a tertiary care centre looking at patients with cancer who presented to our tertiary hospital with sepsis, septic shock or bacteraemia between 2010 and 2015. Participants: 176 patients with cancer were compared with 176 cancer-free controls. Primary and secondary outcomes: The primary outcome of this study was the in hospital mortality in both cohorts. Secondary outcomes included patient demographics, emergency department (ED) vital signs and parameters of resuscitation along with laboratory work. Results: A total of 352 patients were analysed. The mean age at presentation for the cancer group was 65.39±15.04 years, whereas the mean age for the control group was 74.68±14.04 years (p<0.001). In the cancer cohort the ...

Elevated plasma levels of plasminogen activator inhibitor type 1 (PAI-1) are documented in patients with sepsis and levels positively correlate with disease severity and mortality. Our prior work demonstrated that PAI-1 in plasma is positively associated with acute kidney injury (AKI) in septic patients and mice. The objective of this study was to determine if PAI-1 is causally related to AKI and worse sepsis outcomes using a clinically-relevant and age-appropriate murine model of sepsis. Sepsis was induced by cecal slurry (CS)-injection to wild-type (WT, C57BL/6) and PAI-1 knockout (KO) mice at young (5–9 months) and old (18–22 months) age. Survival was monitored for at least 10 days or mice were euthanized for tissue collection at 24 or 48 h post-insult. Contrary to our expectation, PAI-1 KO mice at old age were significantly more sensitive to CS-induced sepsis compared to WT mice (24% vs. 65% survival, p = 0.0037). In comparison, loss of PAI-1 at young age had negligible effects on sepsis survival (86% vs. 88% survival, p = 0.8106) highlighting the importance of age as a biological variable. Injury to the kidney was the most apparent pathological consequence and occurred earlier in aged PAI-1 KO mice. Coagulation markers were unaffected by loss of PAI-1, suggesting thrombosis-independent mechanisms for PAI-1-mediated protection. In summary, although high PAI-1 levels are clinically associated with worse sepsis outcomes, loss of PAI-1 rendered mice more susceptible to kidney injury and death in a CS-induced model of sepsis using aged mice. These results implicate PAI-1 as a critical factor in the resolution of sepsis in old age.

The age-specific mortality rate of certain other intestinal infections at all ages in Canada increased by 0.4 deaths (+20 percent) compared to the previous year. While the age-specific mortality rate increased significantly in the first phase of the observed period, the increase slowed down in the last years.

The Synthetic Sepsis Prediction Dataset is a large-scale, anonymised synthetic dataset designed for research and education in critical care and infectious disease analytics. It includes patient demographic, clinical, pharmacological, and outcome-related features, simulating real-world scenarios to support the prediction, diagnosis, and treatment analysis of sepsis.

Dataset Features

• cod: Unique patient identifier (integer).
• Fecha_ing: Date of hospital admission.
• Sexo: Biological sex (Male/Female/Other).
• Edad: Patient age at admission (years).
• Hospital: Name of the hospital.
• Proced & Reg_salud: Healthcare procedural and regional codes.
• Peso / Talla / IMC: Weight (kg), height (cm), and BMI.
• Initial & 12h/24h Vitals: Systolic, diastolic, mean arterial pressures; heart and respiratory rates; saturation; capillary glucose.
• HTA, DM_2, Hipotiroidismo, Obesidad, Tabaco, ERC, Enf_coronaria, Dislipidemia, ACV, Fib_aur, Autoinmune: Binary variables indicating presence of chronic conditions.
• Antihypertensives: IECA, ARA_2, beta-blockers, calcium antagonists, diuretics, and others.
• Antidiabetics: Metformin, iSGLT2, GLP1a, DPPIV inhibitors, insulin (basal & preprandial), and others.
• Norepinephrine/Vasopressin: Use and dosage at 0h and 24h.
• Lactate, WBC, Neutrophils, Lymphocytes, NL Ratio, PCR, Procalcitonin, HCO3, pH, SOFA Score. All at baseline and after 24 hours.
• Glucose Monitoring: Glucose at 3 time points and coefficient of variation.
• Sepsis: Binary variable indicating presence of sepsis.
• Cultivos / ATB_1/2/3: Culture tests and antibiotic administration.
• IOT, Dialysis, IRA: Mechanical ventilation, renal failure, and related interventions.
• Dias_iot: Duration of intubation.
• Muerte: Mortality outcome.

Distribution

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Usage

This dataset can be used for:

• Predictive Modeling: Forecast onset of sepsis, mortality risk, or treatment responsiveness.
• Clinical Decision Support: Test triage and alert systems for sepsis detection.
• Healthcare Analytics: Examine treatment trends and comorbidity impact in critical care.
• Education: Train students in clinical data science, epidemiology, and bioinformatics.

Coverage

All data is synthetically generated and anonymized to resemble real ICU patients while ensuring full privacy compliance. It includes realistic variability in patient responses and care outcomes.

License

CC0 (Public Domain)

Who Can Use It

• Healthcare AI Researchers and Clinicians: For prototyping early detection and treatment recommendation systems.
• Data Scientists: To build time-aware or multi-modal models in critical care settings.
• Medical Educators and Students: As a complex dataset for hands-on training in clinical data analysis and prediction.

This record contains raw data related to article “A cytokine/PTX3 prognostic index as a predictor of mortality in sepsis"

Abstract

Background: Early prognostic stratification of patients with sepsis is a difficult clinical challenge. Aim of this study was to evaluate novel molecules in association with clinical parameters as predictors of 90-days mortality in patients admitted with sepsis at Humanitas Research Hospital.

Methods: Plasma samples were collected from 178 patients, diagnosed based on Sepsis-3 criteria, at admission to the Emergency Department and after 5 days of hospitalization. Levels of pentraxin 3 (PTX3), soluble IL-1 type 2 receptor (sIL-1R2), and of a panel of pro- and anti-inflammatory cytokines were measured by ELISA. Cox proportional-hazard models were used to evaluate predictors of 90-days mortality.

Results: Circulating levels of PTX3, sIL-1R2, IL-1β, IL-6, IL-8, IL-10, IL-18, IL-1ra, TNF-α increased significantly in sepsis patients on admission, with the highest levels measured in shock patients, and correlated with SOFA score (PTX3: r=0.44, p<0.0001; sIL-1R2: r=0.35, p<0.0001), as well as with 90-days mortality. After 5 days of hospitalization, PTX3 and cytokines, but not sIL-1R2 levels, decreased significantly, in parallel with a general improvement of clinical parameters. The combination of age, blood urea nitrogen, PTX3, IL-6 and IL-18, defined a prognostic index predicting 90-days mortality in Sepsis-3 patients and showing better apparent discrimination capacity than the SOFA score (AUC=0.863, 95% CI: 0.780-0.945 vs. AUC=0.727, 95% CI: 0.613-0.840; p=0.021 respectively).

Conclusion: These data suggest that a prognostic index based on selected cytokines, PTX3 and clinical parameters, and hence easily adoptable in clinical practice, performs in predicting 90-days mortality better than SOFA. An independent validation is required.

Background: Particulate matter from household air pollution (HAP) is linked to half of all lower respiratory infection deaths among children under 5 years of age. In rural Uganda, similar number of children die 6-months post discharge as during hospitalization for severe infections. However, it is unclear whether exposure to HAP contributes to poor health and death after discharge. We investigated the association between cooking and household lighting practices and mortality 6-months post-discharge among children under 5 years of age treated for severe infection in rural Uganda. Methods: We conducted a secondary analysis of data from observational cohort studies, conducted between July 2017 to July 2021, among 6,955 children 0 to 5 years admitted to one of six Ugandan hospitals for a severe infectious illness. Clinical signs and symptoms, sociodemographic variables, and mortality up to 6-months post-discharge was collected for all participants, and follow-up rates were >95%. Exposure variables included type of cooking fuel used, location of cooking (e.g. indoors, outdoors), and primary source of household lighting. We assessed post-discharge mortality using simple and multivariate Poisson regression. Results: The unadjusted risk ratio of 6-month post-discharge mortality by dual or single exposure to pollutant fuel sources for cooking indoors and household lighting, when compared to minimal exposure, was 1.57 (95%CI 1.17, 2.11) and 1.20 (95%CI 0.94, 1.54), respectively. Adjusting for age, sex, distance to hospital, maternal education, and maternal HIV status, the adjusted risk ratios for dual and single exposure became 1.30 (95%CI 0.96, 1.76] and 1.08 (95%CI 0.84, 1.38). There was no significant interaction between exposure and age, sex, maternal education, or anemia status. Results: This analysis did not find a statistically significant association between HAP and 6-month post-discharge mortality. However, HAP cannot be ruled out as a contributor in this population where malnutrition, comorbidities and sociodemographic vulnerabilities are common. Data Collection Methods: All data were collected at the point of care using encrypted study tablets and these data were then uploaded to a Research Electronic Data Capture (REDCap) database hosted at the BC Children’s Hospital Research Institute (Vancouver, Canada).   At admission, trained study nurses systematically collected data on clinical, social and demographic variables. Following discharge, field officers contacted caregivers at 2 and 4 months by phone, and in-person at 6 months, to determine vital status, post-discharge health-seeking, and readmission details. Verbal autopsies were conducted for children who had died following discharge.  Data Processing Methods: A proxy exposure variable was created to classify whether each participant was exposed to a pollutant fuel source. This was stratified into three exposure levels. Ethics Declaration: These studies were approved by the Mbarara University of Science and Technology Research Ethics Committee (15/10–16, 27-Jan-2017), and the University of British Columbia–Children and Women’s Health Centre of British Columbia Research Ethics Board (H16–02679, 09-May-2017). Study Protocol & Supplementary Materials: Smart Discharges to improve post-discharge health outcomes in children: A prospective before-after study with staggered implementation NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

Background:In Sub-Saharan Africa, pediatric post-discharge death is increasingly recognized as an important contributor to mortality. To address morbidity and mortality during this period, it is critical to generate a representative evidence base throughout sub-Saharan Africa to inform resource prioritization, as well as policy and guideline development. To date, no studies have been conducted in Rwanda, limiting the understanding of the epidemiology of post-discharge mortality in this region. This study aims to describe the epidemiology of post-discharge mortality in a group of children admitted for suspected sepsis in Rwanda. Methods: We prospectively recruited children aged 0-60 months admitted for suspected sepsis at two sites in Rwanda: Ruhengeri Referral Hospital in Musanze, Rwanda (rural) and University Hospital of Kigali in Kigali, Rwanda (urban) from May 2022 - February 2023. Clinical, laboratory and social variables were collected at admission. Following discharge, participants were followed up to 6 months to determine vital status and health-seeking. We analyzed data in two age-specific cohorts, defined a priori: 0-6m and 6-60m. Multivariate logistic regression was used to identify risk factors. Age-stratified Kaplan-Meier curves were used to estimate the cumulative hazard of 6-month post-discharge mortality. Findings:Of 1218 children enrolled, 115 died (11%): 50% in-hospital (n=57) and 50% after discharge (n=58). Post-discharge mortality was higher in 0-6m cohort (n=28/274, 10%) than in those 6-60m (30/850, 4%), and in Kigali (n=37/413, 9%) vs Ruhengeri (n=21/805, 3%). Median time to post-discharge death was ~1 month (38d in 0-6m; 33d in 6-60m). In both cohorts, increased odds of post-discharge death were associated with weight-for-age z-score <-3 (OR=3.16 (1.26-7.93), 0-6m; OR=7.44 (2.93-18.89), 6-60m) while higher maternal education was protective (OR=0.15 (0.03-0.85), 0-6m; OR=0.09 (0.02-0.75), 6-60m). Abnormal coma scale (OR=3.29 (1.47-7.38)), travel time of >2h (OR=4.63 (1.40-15.22)) and being referred for higher level of care (OR=4.09 (1.04-16.12)) were significant in 6-60 months. Younger children were at highest risk of cumulative mortality. Ethics Declaration: Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).