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ABSTRACT Objective: To determine one-month mortality in patients with ischemic stroke using Score for Early Ischemic Stroke Mortality. Study Design: Prospective longitudinal study. Place and Duration of Study: Combined Military Hospital, Jhelum Pakistan, from Jan 2020 to May 2021. Methodology: All patients with acute ischemic stroke, aged more than 18 years, of either gender, were consecutively enrolled. Mortality at 1 month in patients with ischemic stroke was noted along with the demographic and clinical characteristics (comorbidities, smoking status, clinical stroke at admission, and cause of the stroke). Mortality at 1 month was predicted by using Predicting Early Mortality of Ischemic Stroke score. Additionally, National Institutes of Health Stroke Scale, Glasgow Coma Scale, and previous Modified Ranking Scale at admission was also recorded. Results: Among 160 patients, the Mean age was 66.07±9.92 years. 121(75.6%) patients were males and 39(24.4%) were females. Mortality at 1 month was observed in 26(16.3%) patients. A significant association of mortality at 1 month was observed with age (p<0.001), dyslipidemia (p<0.001), hypertension (p=0.006), carotid stenosis (p<0.001), and atrial fibrillation (p<0.001). A significantly higher mean Predicting Early Mortality of Ischemic Stroke score (p<0.001), National Institutes of Health Stroke Scale score (p<0.001), previous Modified Ranking Scale (p<0.001) was noted among patients in whom mortality was observed at 1 month whereas Glasgow Coma Scale level (p<0.001) was found significantly lower in deceased patients. The Area Under the Curve of the Predicting Early Mortality of Ischemic Stroke score was 91.6% (95% CI 87.0%-96.1%). Conclusion: The Predicting Early Mortality of Ischemic Stroke scoring system accurately predicted one-month mortality in patients with ischemic stroke.

Background The current neonatal mortality rate in Uganda is high at 22 deaths per 1000 live births, while it had been stagnant at 27 deaths per 1000 live births in the past decade. This is still more than double the World Health Organization target of < 12 deaths per 1,000 live births. Three-quarters of new born deaths occur within the first week of life, which is a very vulnerable period and the causes reflect the quality of obstetric and neonatal care. At Mbarara Regional Referral Hospital (MRRH), the modifiable contributors and predictors of mortality remain undocumented, yet neonates make the bulk of admissions and contribute significantly to the overall infant mortality rate. We therefore examined the clinical profiles, incidence and predictors of early neonatal mortality of neonates admitted at MRRH in south-western Uganda. Methods We conducted a prospective cohort study at the Neonatal Unit of MRRH between August – November, 2022 among neonates. We consecutively included all live neonates aged < 7 days admitted to neonatal unit and excluded those whose outcomes could not be ascertained at day 7 of life. We obtained baseline data including; maternal social-demographic and obstetric information, and performed neonatal physical examinations for clinical profiles. We followed up neonates at 24 and 72 h of life, and at 7 days of life for mortality. We summarized the clinical profiles and incidence of mortality as frequencies and percentages and performed modified Poisson regression analysis to identify the predictors of early neonatal mortality. Results We enrolled 384 neonates. The majority of neonates were in-born (68.5%, n  = 263) and were admitted within 24 h after birth (54.7%, n  = 210). The most common clinical profiles at admission were prematurity (46%, n  = 178), low birth weight (LBW) (44%, n  = 170), sepsis (36%, n  = 139), hypothermia (35%, n  = 133), and birth asphyxia (32%, n  = 124). The incidence of early neonatal mortality was at 12.0%, 46 out of the 384 neonates died. The predictors of early neonatal mortality were hypothermia, [adjusted Risk Ratio: 4.10; 95% C.I (1.15–14.56)], birth asphyxia, [adjusted Risk Ratio: 3.6; 95% C.I (1.23–10.73)] and delayed initiation of breastfeeding, [adjusted Risk Ratio: 7.20; 95% C.I (1.01–51.30)]. Conclusion Prematurity, LBW, sepsis, birth asphyxia and hypothermia are the commonest admission diagnoses. The incidence of early neonatal mortality was high, 12.0%. We recommend targeted interventions by the clinical care team at MRRH to enable timely identification of neonates with or at risk of hypothermia to reduce incidence of adverse outcomes. Intrapartum care should be improved in order to mitigate the risk of birth asphyxia. Breastfeeding within the first hour of birth should be strengthened were possible, as this is associated with vast benefits for the baby and may reduce the incidence of complications like hypothermia.

BackgroundEmergency departments (ED) are becoming increasingly overwhelmed, increasing poor outcomes. Triage scores aim to optimize the waiting time and prioritize the resource usage. Artificial intelligence (AI) algorithms offer advantages for creating predictive clinical applications.ObjectiveEvaluate a state-of-the-art machine learning model for predicting mortality at the triage level and, by validating this automatic tool, improve the categorization of patients in the ED.DesignAn institutional review board (IRB) approval was granted for this retrospective study. Information of consecutive adult patients (ages 18–100) admitted at the emergency department (ED) of one hospital were retrieved (January 1, 2012–December 31, 2018). Features included the following: demographics, admission date, arrival mode, referral code, chief complaint, previous ED visits, previous hospitalizations, comorbidities, home medications, vital signs, and Emergency Severity Index (ESI). The following outcomes were evaluated: early mortality (up to 2 days post ED registration) and short-term mortality (2–30 days post ED registration). A gradient boosting model was trained on data from years 2012–2017 and examined on data from the final year (2018). The area under the curve (AUC) for mortality prediction was used as an outcome metric. Single-variable analysis was conducted to develop a nine-point triage score for early mortality.Key ResultsOverall, 799,522 ED visits were available for analysis. The early and short-term mortality rates were 0.6% and 2.5%, respectively. Models trained on the full set of features yielded an AUC of 0.962 for early mortality and 0.923 for short-term mortality. A model that utilized the nine features with the highest single-variable AUC scores (age, arrival mode, chief complaint, five primary vital signs, and ESI) yielded an AUC of 0.962 for early mortality.ConclusionThe gradient boosting model shows high predictive ability for screening patients at risk of early mortality utilizing data available at the time of triage in the ED.

Among the elements that impact Infant Mortality, Perinatal Mortality stands out, which involves deaths that occur during the period that begins at 22 completed weeks (or 154 days) of gestation (fetal period) and ends at 7 completed days after birth, that is, from 0 to 6 days of life (early neonatal period). The objective of this research is to describe the profile of perinatal deaths reported in municipalities of Piauí’s Coastal Plain from 2013 to 2017. This is a retrospective, descriptive study with a quantitative analysis approach, resulting from the Course Completion Work entitled ‘Perinatal mortality profile in municipalities of Piaui’s Coastal Plain’. The sample consisted of death certificates and infant death and fetal death investigation forms of children whose mothers lived in the Coastal Plain, PI, and who had their deaths confirmed in the perinatal period, between January 2013 and December 2017. During the study period, the Perinatal Mortality Rate (PMR) of the Coastal Plain, PI, was 22.97 deaths per 1,000 births, with little variation between 2013 and 2017. Fetal deaths were predominant, comprising 61.9% of the sample. Hospital deaths that occurred in Parnaíba were the most frequent, revealing this to be the reference municipality in the region. This shows the need for greater attention on the part of health professionals and managers to such conditions, in order to improve the quality of care for pregnant women, parturient women, and newborns.

Background In patients with acute promyelocytic leukemia (APL), early mortality, defined as death within 30 days following diagnosis, is the main driver of overall survival. Intensivists play a pivotal role in the management of patients with APL. Method The PubMed and Embase databases were searched on December 1, 2023. All studies focusing on early mortality in patients with newly diagnosed APL were included. Two reviewers independently selected the studies and assessed bias using the risk-of-bias 2 scale for randomized controlled trials (RCT) and the Newcastle-Ottawa scale for other types of studies. A meta-analysis using a random effects model was performed. The primary outcome was early mortality. A subgroup analysis was performed to assess the differences between interventional and observational studies. Secondary outcomes included reasons for early mortality and the occurrence of severe hemorrhage or differentiation syndrome (DS). Results Of the 950 studies screened, 140 met the inclusion criteria. A total of 54,923 patients newly diagnosed with APL were included in the meta-analysis. A meta-analytical early mortality rate of 12% was calculated across 122 studies. Early mortality was lower in interventional studies (8%) than in observational studies (15%). Hemorrhage was the main cause of early mortality (57%), followed by sepsis (18%), DS (12%), and thrombotic events (2%). In a meta-regression, early mortality was influenced by patients’ age, white blood cell count at diagnosis, time, study type, and country of origin according to income classification. Conclusion There is an encouraging decrease over time of early mortality in patients with APL. Early mortality is lower in interventional studies. This result reflects the difficulty of translating the successes of RCT and interventional research into real-world clinical practice. This study puts forward the need to improve and standardize early management, notably in the intensive care unit. Trial registration This study’s protocol was preregistered on PROSPERO (CRD42023488480).

Shaohuai Xia,1,* Junhong Hu,2,* Jing Wu,1 Yingye Liao,2 Guifeng Liang,3 Jinping Li,4 Xiaoguang Fan,2 Xuewei Xia,2 Xinrong Zhong,2 Li Chen5 1Department of Neuro-Oncology, Beijing Xiaotangshan Hospital, Beijing, 100000, People’s Republic of China; 2Department of Neurosurgery, The First Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, 541001, People’s Republic of China; 3Diecai District Maternal and Child Health Hospital of Guilin City, Guilin, Guangxi, 541001, People’s Republic of China; 4Reproductive Center of The 924th Hospital of The Joint Logistic Support Force of The Chinese People’s Liberation Army, Guilin, Guangxi, 541001, People’s Republic of China; 5Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China*These authors contributed equally to this workCorrespondence: Li Chen, Department of Neurosurgery, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Affiliated Provincial Hospital of Fuzhou University, Fuzhou, 350001, People’s Republic of China, Email fjmuchenli@163.comPurpose: This study aimed to evaluate the predictive value of inflammatory markers, particularly the neutrophil-to-platelet ratio (NPR), combined with clinical parameters for early mortality following mechanical thrombectomy (MT) in patients with large artery occlusive acute ischemic stroke (LAO-AIS), to guide timely clinical interventions.Patients and methods: This retrospective study analyzed 320 LAO-AIS patients who underwent MT between January 2023 and January 2025. Missing data (< 15%) were imputed. Boruta feature selection identified variables for multiple logistic regression. The dataset was randomly divided into training and test sets (7:3). A nomogram was constructed, and four machine learning algorithms—Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Naive Bayes (NB)—were developed and validated.Results: Early mortality occurred in 67 cases. Multivariate analysis identified six independent predictors: standardized NPR (NPR_std; OR = 4.51, P < 0.001), age (OR = 1.10, P < 0.001), decompressive craniectomy (DC; OR = 0.19, P < 0.001), responsible artery location (OR = 0.34, P = 0.006), lymphocyte count (LYM; OR = 2.14, P = 0.008), and prothrombin time (PT; OR = 1.31, P = 0.011). The nomogram showed high reliability. XGBoost achieved superior predictive performance, with SHapley Additive exPlanations (SHAP) analysis confirming NPR_std as the most important predictor.Conclusion: The neutrophil-to-platelet ratio (NPR) is an independent predictor of early mortality after MT in LAO-AIS patients. The predictive model provides valuable guidance for clinicians to adjust treatment strategies early.Keywords: stroke, mechanical thrombectomy, prognosis, early mortality, neutrophil-to-platelet ratio

Our knowledge about acute promyelocytic leukemia (APL) patients is mainly based on data from clinical trials, whereas population-based information is scarce. We studied APL patients diagnosed between 1997 and 2006 in the population-based Swedish Adult Acute Leukemia Registry. Of a total of 3897 acute leukemia cases, 3205 (82%) had non-APL acute myeloid leukemia (AML) and 105 (2.7%) had APL. The incidence of APL was 0.145 per 100 000 inhabitants per year. The median age at the time of diagnosis was 54 years; 62% were female and 38% male. Among younger APL patients, female sex predominated (89% of patients <40 years). Of the 105 APL patients, 30 (29%) died within 30 days (that is, early death (ED)) (median 4 days) and 28 (26%) within 14 days from diagnosis. In all, 41% of the EDs were due to hemorrhage; 35% of ED patients never received all- trans -retinoic acid treatment. ED rates increased with age but more clearly with poor performance status. ED was also associated with high white blood cells, lactate dehydrogenase, creatinine, C-reactive protein and low platelet count. Of non-ED patients, 97% achieved complete remission of which 16% subsequently relapsed. In total, 62% are still alive at 6.4 years median follow-up. We conclude that ED rates remain very high in an unselected APL population.

BackgroundImmune checkpoint inhibitors (ICIs) are standard treatments for advanced solid cancers. Resistance to ICIs, both primary and secondary, poses challenges, with early mortality (EM) within 30–90 days indicating a lack of benefit. Prognostic factors for EM, including the lung immune prognostic index (LIPI), remain underexplored.MethodsWe performed a retrospective, observational study including patients affected by advanced solid tumors, treated with ICI as single agent or combined with other agents. Logistic regression models identified factors associated with EM and 90-day progression risks. A nomogram for predicting 90-day mortality was built and validated within an external cohort.ResultsIn total, 637 patients received ICIs (single agent or in combination with other drugs) for advanced solid tumors. Most patients were male (61.9%), with NSCLC as the prevalent tumor (61.8%). Within the cohort, 21.3% died within 90 days, 8.4% died within 30 days, and 34.5% experienced early progression. Factors independently associated with 90-day mortality included ECOG PS 2 and a high/intermediate LIPI score. For 30-day mortality, lung metastasis and a high/intermediate LIPI score were independent risk factors. Regarding early progression, high/intermediate LIPI score was independently associated. A predictive nomogram for 90-day mortality combining LIPI and ECOG PS achieved an AUC of 0.76 (95% CI 0.71–0.81). The discrimination ability of the nomogram was confirmed in the external validation cohort (n = 255) (AUC 0.72, 95% CI 0.64–0.80).ConclusionLIPI and ECOG PS independently were able to estimate 90-day mortality, with LIPI also demonstrating prognostic validity for 30-day mortality and early progression.

Acinetobacter baumannii (AB) has emerged as a major pathogen in vulnerable and severely ill patients. It remains unclear whether early mortality (EM) due to AB bacteremia is because of worse clinical characteristics of the infected patients or the virulence of the pathogen. In this study, we aimed to investigate the effect of AB virulence on EM due to bacteremia. This retrospective study included 138 patients with AB bacteremia (age: ≥ 18 years) who were admitted to a tertiary care teaching hospital in South Korea between 2015 and 2019. EM was defined as death occurring within 7 days of bacteremia onset. The AB clinical isolates obtained from the patients’ blood cultures were injected into 15 Galleria mellonella larvae each, which were incubated for 5 days. Clinical isolates were classified into high- and low-virulence groups based on the number of dead larvae. Patients’ clinical data were combined and subjected to multivariate Cox regression analyses to identify the risk factors for EM. In total, 48/138 (34.8%) patients died within 7 days of bacteremia onset. The Pitt bacteremia score was the only risk factor associated with EM. In conclusion, AB virulence had no independent effect on EM in patients with AB bacteremia.

Respiratory distress syndrome (RDS) is the leading cause of respiratory failure and neonatal mortality, particularly in preterm infants. Despite global advances in neonatal care, RDS remains a significant problem in low-resource settings such as Uganda, where limited evidence exists on clinical profiles, mortality, and associated risk factors. Although these advances have greatly reduced mortality in high-income settings, their limited availability in Uganda contributes to the continued high burden of RDS-related deaths. To determine the clinical–radiological profile, early mortality, and risk factors for mortality among preterm neonates admitted with RDS at Hoima Regional Referral Hospital. A prospective cohort study was conducted among 150 preterm neonates with clinically and radiologically confirmed RDS. Data on sociodemographic, clinical, and obstetric characteristics were collected using structured questionnaires and chest X-rays. Participants were followed for seven days to determine outcomes. Descriptive statistics summarized baseline characteristics, while Poisson regression identified independent predictors of mortality. Of the 150 neonates, 62.7% were male and 70.7% were born before 32 weeks of gestation. Tachypnea (84.7%) and intercostal/subcostal retractions (71.3%) were the most frequent clinical features, while ground-glass patterns were the predominant radiological finding. Twenty-nine neonates died within the first seven days, giving an early mortality rate of 19.3%. Independent predictors of mortality were delayed presentation beyond six hours of life (aRR = 1.72, 95% CI: 1.43–2.07, p  < 0.001) and birth weight < 1.5 kg (aRR = 1.12, 95% CI: 1.02–1.22, p  = 0.015). RDS contributes substantially to early neonatal mortality in Uganda. Prompt recognition, early referral, and improved neonatal care—particularly for very low birth weight infants—are critical to improving outcomes. Although not directly measured in this study, improving access to antenatal corticosteroids and respiratory support—well-established interventions—remains essential for broader improvement of RDS outcomes.