Predictors Of Early Mortality Research Articles

Predictors of Early Mortality After Traumatic Spinal Cord Injury in South Africa

Study Design Retrospective cohort study. Objectives To identify predictors for early mortality following traumatic spinal cord injury (TSCI), as recognition of factors associated with early mortality is essential for public resource allocation and optimized acute care. Methods Retrospective Analysis of SCI patients admitted to the acute SCI ward from 2003 to 2022 was performed. Days elapsing from the date of injury to date of death established the survival time. Early mortality was defined as survival time ≤ 365 days. Multivariable logistic regression was used in modeling of early death following TSCI with age, gender, neurologic deficit, type of neurologic injury, ventilation status, and count of complications as covariates. Results Simple logistic regression indicated a significant association of early mortality with the number of complications ( P < .0001), neurological deficit ( P < .0001), complete neurological injury ( P < .0001), ventilation status ( P < .0001), and age group ( P < .0003). After adjusting for other covariates, complete neurological injury (OR: 1.75, P < .0001), ventilation (OR: 2.80, P < .0001), and Age group (over 60 OR: 17.71, P < .0001) were significantly associated with early mortality. The multivariable model showed a good overall fit (Hosmer-Lemeshow P = .315; AUC 0.85). Conclusions Predictors of early mortality after TSCI are high complete spinal cord injury, age, number of complications, and the need for ventilation. Identification of high-risk patients is crucial to rationalize and improve acute care to potentially reduce mortality rates.

Prediction of Early Mortality in Esophageal Cancer Patients with Liver Metastasis Using Machine Learning Approaches

Patients with esophageal cancer liver metastasis face a high risk of early mortality, making accurate prediction crucial for guiding clinical decisions. However, effective predictive tools are currently limited. In this study, we used clinicopathological data from 1897 patients diagnosed with esophageal cancer liver metastasis between 2010 and 2020, which were sourced from the SEER database. Prognostic factors were identified using univariate and multivariate logistic regression, and seven machine learning models, including extreme gradient boosting (XGBoost) and support vector machine (SVM), were developed to predict early mortality. The models were evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and F1 scores. Results showed that 40% of patients experienced all-cause early mortality and 38% had cancer-specific early mortality. Key predictors of early mortality included age, location, chemotherapy, and lung metastasis. Among the models, XGBoost performed best in predicting all-cause early mortality, while SVM excelled in predicting cancer-specific early mortality. These findings demonstrate that machine learning models, particularly XGBoost and SVM, can serve as valuable tools for predicting early mortality in patients with esophageal cancer liver metastasis, aiding clinical decision making.

A predictive score for early in-patient tuberculosis mortality: A case-control study

IntroductionIn-hospital mortality rates for tuberculosis (TB) patients are high within the first seven days of admission. This study sought to identify predictors of early inpatient mortality and assess the performance of a predictive score for early mortality in a Ugandan tertiary hospital. Materials and methodsA case-control study was conducted at Kiruddu National Referral Hospital in Kampala, Uganda. Cases included patients admitted with TB who died within seven days of admission, while controls survived beyond this period. Logistic regression was utilized to identify early mortality predictors. The performance of an adapted predictive score (PROS score) was evaluated, assigning scores based on the following criteria: Pulse rate >100 beats/min (1 point), Respiratory rate >20 breaths/min (2 points), Oxygen saturation <92 % (4 points), and Systolic blood pressure <90 mmHg (2 points). ResultsOf 602 hospitalized TB patients, 187 (31.0 %) died during admission. Among these, 78 (41.7 %) died within seven days. Wasting (adjusted odds ratio [aOR] = 5.76, 95 % confidence interval [CI] 2.12–15.63, p = 0.001) and respiratory rate >20 breaths/min (aOR = 2.89, 95 % CI 1.19–7.00, p = 0.019) predicted early mortality. PROS score of ≥1 demonstrated a sensitivity of 87.8 % and negative predictive value of 90.0 %. The ultimate TB treatment success rate of all hospitalized patients (n = 599) was 47.4 % with 275 (45.9 %) dying during TB treatment. ConclusionEarly and long term mortality rates among hospitalized TB patients are high. Wasting and tachypnea predict early inpatient mortality. The PROS score could be useful in ruling out low-risk patients in low-resource settings.

Validation of mitochondrial FMN as a predictor for early allograft dysfunction and patient survival measured during hypothermic oxygenated perfusion

Hypothermic oxygenated machine perfusion (HOPE) preconditions liver grafts before transplantation. While beneficial effects on patient outcomes were demonstrated, biomarkers for viability assessment during HOPE are scarce and lack validation. This study aims to validate the predictive potential of perfusate flavin mononucleotide (FMN) during HOPE to enable the implementation of FMN-based assessment into clinical routine and to identify safe organ acceptance thresholds. FMN was measured in perfusate samples of 50 liver grafts at multiple time points. After transplantation, patients were followed up for development of early allograft dysfunction (EAD), transplantation, and 1-year survival. FMN concentrations were significantly higher for grafts that developed EAD at 5 and 60 minutes into HOPE (p = 0.008, p = 0.026). The strongest predictive potential of FMN for EAD was observed at 5 minutes of HOPE with an AUC of 0.744. Similarly, 5-minute FMN was predictive for 1-year mortality (p &lt; 0.001), reaching a remarkable AUC of 0.890. Cutoffs for prediction of EAD (10.6 ng/mL) and early mortality (23.5 ng/mL) were determined and allowed risk stratification of grafts. Particularly, patients receiving low-risk grafts developed EAD in 9% of cases, while all patients survived the first postoperative year. In contrast, high-risk organs developed an incidence of EAD at 62%, accompanied by the necessity of retransplantation in 38% of cases. One-year mortality in the high-risk cohort was 62%. Evaluation of FMN as early as 5 minutes during HOPE allows for risk stratification of liver grafts. Low-risk grafts, according to FMN, display a negligible risk for patients. Yet, high-risk grafts are associated with increased risk for EAD, transplantation, and early mortality and should not be used for transplantation without further assessment.

Three-Month Mortality in Nonhaematological Patients with Chronic Pulmonary Aspergillosis: Differences between Subtypes.

Objectives: Chronic pulmonary aspergillosis (CPA) is a fungal lung infection characterised by the slowly progressing destruction of the lung parenchyma and has four main subtypes. The objective of this work was to evaluate the epidemiology of CPA in our area and evaluate the involvement of the different subtypes in mortality. Methods: This was a descriptive longitudinal retrospective study developed in three tertiary hospitals in Spain. Among all patients admitted with a pulmonary aspergillosis diagnosis, we selected those who fulfilled the criteria for chronic aspergillosis according to the criteria of Denning, excluding those with a haematological disorder. Results: Among 409 inpatients recorded as having a pulmonary aspergillosis infection, only 76 (18.5%) fulfilled the criteria for CPA, with an estimated incidence of 0.67 cases/100,000 inhabitants/year. The subtypes detected were subacute invasive aspergillosis (SAIA) in 33 (43.4%) patients, simple aspergilloma (SA) in 25 (32.9%) patients, cavitary chronic aspergillosis (CCPA) in 13 (17.1%) patients, and chronic fibrosis (CFPA) in five (6.5%) patients. The overall three-month mortality rate was 23%, which was higher in SAIA patients. The predictors of early mortality were age > 65 years (OR 3.0 CI 95 1.0-9.5 p = 0.043) and the SAIA subtype vs. other subtypes (OR 3.1 CI 95 1.0-9.5 p = 0.042). Conclusions: The incidence rate estimated was inferior to that previously reported. The three-month mortality in patients with CPA was high, with older age and the SAIA subtype being the variable independent predictors of a worse prognosis.

Low leucocyte, neutrophil and lymphocyte count (tri-low phenotype) in melioidosis: A predictor of early mortality

IntroductionMelioidosis is a bacterial disease caused by Burkholderia pseudomallei, a gram-negative bacillus endemic to parts of Asia and Northern Australia. This study aimed to identify the role of total and differential leucocyte count in predicting 48-h mortality in patients with melioidosis. MethodologyThis retrospective cohort study included patients diagnosed with culture-proven melioidosis at Kasturba Medical College between 2017 and 2023. Total leucocyte count (TLC), absolute neutrophil count (ANC), and absolute lymphocytic count (ALC) were classified into low (first quartile), medium (second and third quartile) and high (last quartile). The chi-square test was used to compare each group's early (48-h) mortality. ResultsOf the 170 patients with culture-confirmed melioidosis, 24 patients died within 48 h. The mortality was significantly higher in those with low TLC, ANC and ALC. When all three parameters were found to be low (tri-low phenotype), the specificity in predicting mortality was 93.2 %. ConclusionLow TLC, ANC and ALC are significant predictors of mortality among melioidosis patients. There is a need to explore new strategies to improve clinical outcomes among melioidosis patients with tri-low phenotype.

Preoperative prediction of early mortality after surgery for spinal metastases.

The objective of this study was to provide a convenient preoperative prediction of the risk of early postoperative mortality. This retrospective study included patients who underwent surgery for spinal metastasis at our hospital between 2009 and 2021. Preoperative blood test data of all patients were collected, and the survival time was calculated by dividing the blood data. A multivariate analysis was conducted using a Cox proportional hazards model to identify prognostic factors. The study population included 83 patients (average: 64.5years), 22 of whom died within 3 months. The most common lesion was the thoracic spine, and incomplete paralysis was observed in 57 patients. The surgical methods included posterior implant fixation (n=17), posterior decompression (n=31), and posterior decompression with fixation (n=35). In the univariate analysis, the presence of abnormal values was significantly associated with postoperative survival in six preoperative blood collection items (hemoglobin, C-reactive protein, albumin, white blood cell, gamma-glutamyl transpeptidase, and lactate dehydrogenase). In a multivariate analysis, four test items (hemoglobin, C-reactive protein, white blood cell, and lactate dehydrogenase) were identified as independent prognostic factors.Comparing cases with ≥3 abnormal values among the above four items (high-risk group; n=23) and those with ≤2 (low-risk group; n=60), there was a significant difference in survival time. In addition, it was possible to predict cases of early death within 3months after surgery with 73% sensitivity and 89% specificity. The study showed that four preoperative blood test abnormalities (hemoglobin, C-reactive protein white blood cell, and lactate dehydrogenase) indicated the possibility of early death within 3months after surgery.

1496P Predictors of early mortality after hemodialysis in patients with cancer and acute kidney injury

1496P Predictors of early mortality after hemodialysis in patients with cancer and acute kidney injury

The FLARE Score and Circulating Neutrophils in Patients with Cancer and COVID-19 Disease.

Inflammation and neutrophils play a central role in both COVID-19 disease and cancer. We aimed to assess the impact of pre-existing tumor-related inflammation on COVID-19 outcomes in patients with cancer and to elucidate the role of circulating neutrophil subpopulations. We conducted a multicenter retrospective analysis of 524 patients with cancer and SARS-CoV-2 infection, assessing the relationship between clinical outcomes and circulating inflammatory biomarkers collected before and during COVID-19 infection. Additionally, a single-center prospective cohort study provided data for an exploratory analysis, assessing the immunophenotype of circulating neutrophils and inflammatory cytokines. The primary endpoints were 30-day mortality and the severity of COVID-19 disease. Prior to COVID-19, 25% of patients with cancer exhibited elevated dNLR, which increased to 55% at the time of COVID-19 diagnosis. We developed the FLARE score, incorporating both tumor- and infection-induced inflammation, which categorized patients into four prognostic groups. The poor prognostic group had a 30-day mortality rate of 68%, significantly higher than the 23% in the favorable group (p < 0.0001). This score proved to be an independent predictor of early mortality. This prospective analysis revealed a shift towards immature forms of neutrophils and higher IL-6 levels in patients with cancer and severe COVID-19 infection. A pre-existing tumor-induced pro-inflammatory state significantly impacts COVID-19 outcomes in patients with cancer. The FLARE score, derived from circulating inflammatory markers, emerges as an easy-to-use, globally accessible, effective tool for clinicians to identify patients with cancer at heightened risk of severe COVID-19 complications and early mortality who might benefit most from immediate and intensive treatment strategies. Furthermore, our findings underscore the significance of immature neutrophils in the progression of COVID-19 in patients with cancer, advocating for further investigation into how these cells contribute to both cancer and COVID-19 disease.

Revisiting the COVID-19 Pandemic: Mortality and Predictors of Death in Adult Patients in the Intensive Care Unit.

COVID-19 has generated a global impact due to its contagiousness and high lethality rates, with a large number of deaths occurring in intensive care units (ICUs). This study aimed to verify the occurrence of and understand the factors related to mortality in adult patients with COVID-19 admitted to the ICU in a tertiary hospital. This is a retrospective cohort study, which included COVID-19 patients admitted between March 2020 and December 2021. A total of 588 patients were included, of whom the majority (55.27%) did not survive. Invasive mechanical ventilation was the strongest predictor of the risk of death in the ICU with OR = 97.85 (95% CI = 39.10-244.86; p < 0.001), along with age and Simplified Acute Physiology Score 3 (SAPS3). The length of the ICU stay was protective. Evaluating patients on invasive mechanical ventilation in isolation, using an adjusted model, we found the following risk factors: use of vasopressin, renal replacement therapy, red cell distribution width > 15, use of hydrocortisone, and age in years. Protective factors included the days of mechanical ventilation use, being admitted from another service, and being of female sex. Identifying early predictors of mortality in patients with COVID-19 who require hospitalization is essential in the search for actions to prevent and manage complications, which can increase the survival of these patients and reduce the impact on health services.

Prognostic Value of Prolonged QT Interval in Patients with Acute Ischemic Stroke

Abstract Background Early predictors of mortality and poor functional outcome are crucial for planning the level of care and optimizing resource utilization. Nonetheless, rapid and noninvasive methods for assessing the prognosis of patients with acute hemorrhagic stroke in the emergency department (ED) are currently lacking. Aim of the Work The aim of this work is to assess and evaluate the QT- prolongation in patients with acute stroke without known cardiac disease and to correlate between prolonged QT interval and different neurological outcomes. Patients and Methods This was a case control study. Data from patients with acute ischemic stroke (stroke patients) who were admitted to the neurological intensive care unit were collected for the period from June 2021 to December 2021 at the First Affiliated Ahmad Maher teaching hospital, and patients in other departments were enrolled as controls. Results This study had several limitations. First, the study was performed in a single center, which may reduce its generalizability. In addition, we were unable to determine non-fatal long-term outcomes, such as major adverse cerebro-cardiovascular events (MACCE). Second, the mechanism underlying QTc interval prolongation remains tentative because ECG was performed at single time points, not overtime. Furthermore, major cardiac and non-cardiac comorbidities were defined as the previous history and/or ECG results at admission, thus possibly underestimating subclinical conditions. In addition, the contribution of each cardiac and non-cardiac condition to QTc interval prolongation is not equally the same. We also could not absolutely exclude patients with coronary artery disease who shared similar risk factors because we did not conduct echocardiography or coronary angiography, and this may have affected the QTc interval changes in ECG. Conclusion Prolonged QTc interval was associated with the increased risk of long-term mortality, in parallel with the increasing trend of the prevalence of cardiovascular risk profiles and stroke severity, across sex differences, such as different distributions of age, comorbidities, morality, and QTc intervals in AIS patients. Acute ischemic stroke patients may have a longer QT interval and a higher incidence of electrocardiogram abnormalities. In clinical practice, careful attention should be paid to acute ischemic stroke patients to prevent malignant arrhythmia.

Predictors of early mortality following surgical or nonsurgical treatment of subaxial cervical spine fractures: a retrospective nationwide registry study

BACKGROUNDTraumatic subaxial cervical spine fractures are a significant public health concern due to their association with spinal cord injuries (SCI). Despite being mostly caused by low-energy trauma, these fractures significantly contribute to morbidity and mortality. Currently, research regarding early mortality based on the choice of treatment following these fractures is limited. Identifying predictors of early mortality may aid in postoperative patient monitoring and improve outcomes. PURPOSEThis study aimed to identify predictors of 30-days, 90-days, and 1-year mortality in adults treated for subaxial fractures. STUDY DESIGNA retrospective review of the nationwide Swedish Fracture Register (SFR). PATIENT SAMPLEAll adult patients in the SFR who underwent treatment for a subaxial cervical fracture (n = 1,963). OUTCOME MEASURESAnalyzed variables included age, sex, injury mechanism, neurological function, fracture characteristics, and treatment type. The primary endpoints were 30-days, 90-days, and 1-year mortality. METHODSAbout 1,963 patients in the SFR, treated for subaxial cervical fractures between 2013 and 2021, were analyzed. Surgical procedures included anterior, posterior, or anteroposterior approaches. Nonsurgical treatment included collar treatment or medical examinations without intervention. Stepwise regression and Cox regression analysis were used to determine predictors. Model performance was tested using the area under the receiver operating characteristic curve (AUC). RESULTSA total of 620 patients underwent surgery and 1,343 received nonsurgical treatment. Surgical cases had primarily translation fractures, with 323 (52%) displaying no neurological deficits. Mortality rates at 30 days, 90 days, and 1 year were 22/620 (3.5%), 35/620 (5.6%), and 53/620 (8.5%), respectively. Age and SCI were predictors of mortality. Nonsurgically treated patients mostly had compression fracture, with 1,214 (90%) experiencing no neurological deficits. Mortality rates at 30 days, 90 days, and 1 year were 41/1,343 (3.1%), 71/1,343 (5.3%), and 118/1,343 (8.7%). Age, male sex, SCI and fractures occurring at the C3 or C6 levels were predictors of mortality. An intact neurological function was a positive predictor of survival among nonsurgically treated patients (AUC >0.78). CONCLUSIONSAge and SCI emerged as significant predictors of early mortality in both surgically and nonsurgically treated patients. An intact neurological function served as a protective factor against early mortality in nonsurgically treated patients. Fractures at C3 or C6 vertebrae may impact mortality.

Prognostic Value of Fibrosis 4 (FIB-4) Index in Sepsis Patients.

Sepsis remains a major health challenge worldwide, characterized by a dysregulated host response to infection, leading to high mortality and morbidity in intensive care units (ICUs). The Fibrosis 4 (FIB-4) index, originally developed to assess liver fibrosis in hepatitis C patients, has recently been explored for its potential prognostic value in sepsis patients. this study retrospectively analyzed 309 sepsis patients admitted to the Internal Medicine and An-aesthesia ICUs between 12 December 2021 and 15 December 2023 to investigate the relationship between FIB-4 levels, the Acute Physiology and Chronic Health Evaluation (APACHE), the Sequential Organ Failure Assessment (SOFA), and clinical outcomes. This study found that higher FIB-4 measurements were statistically significantly associated with increased 28-day mortality, with a cut-off value of 4.9, providing a sensitivity of 54.92% and specificity of 74.25%. Logistic regression analysis indicated that elevated FIB-4 levels were a significant predictor of early mortality, suggesting that the FIB-4 index could serve as a valuable prognostic tool in assessing the severity and prognosis of sepsis patients. by elucidating the potential role of the FIB-4 index in sepsis prognosis, this study contributes to the ongoing efforts to improve risk stratification and enhance patient care in sepsis management.

Predicting early mortality and severe intraventricular hemorrhage in very-low birth weight preterm infants: a nationwide, multicenter study using machine learning

Our aim was to develop a machine learning-based predictor for early mortality and severe intraventricular hemorrhage (IVH) in very-low birth weight (VLBW) preterm infants in Taiwan. We collected retrospective data from VLBW infants, dividing them into two cohorts: one for model development and internal validation (Cohort 1, 2016–2021), and another for external validation (Cohort 2, 2022). Primary outcomes included early mortality, severe IVH, and early poor outcomes (a combination of both). Data preprocessing involved 23 variables, with the top four predictors identified as gestational age, birth body weight, 5-min Apgar score, and endotracheal tube ventilation. Six machine learning algorithms were employed. Among 7471 infants analyzed, the selected predictors consistently performed well across all outcomes. Logistic regression and neural network models showed the highest predictive performance (AUC 0.81–0.90 in both internal and external validation) and were well-calibrated, confirmed by calibration plots and the lowest two mean Brier scores (0.0685 and 0.0691). We developed a robust machine learning-based outcome predictor using only four accessible variables, offering valuable prognostic information for parents and aiding healthcare providers in decision-making.

Ischemic stroke subtypes: risk factors, treatments, and 1-month prognosis – The Lille, France Stroke Registry

ObjectivesFirst, this registry-based study aimed to comprehensively analyze patients' medical histories and treatments based on ischemic strokes’ etiology. We focused on the management of atrial fibrillation among patients diagnosed with cardioembolic stroke. Then, our objective was to identify prognostic factors associated with 28-day mortality. Materials and methodsAll ischemic strokes occurring in adults between 2014 and 2021 in Lille, France, were categorized using the TOAST classification. Comparative analyses of patients' medical characteristics were conducted across subtypes. Survival rates within 28 days post-stroke were assessed, and factors influencing mortality were identified using a multivariate Cox model. Results1912 ischemic strokes were recorded, due to cardioembolism (36%), large-artery atherosclerosis (9%), small-artery occlusion (9%), other determined causes (6%), or undetermined causes (39%). The median NIHSS score after cardioembolic stroke (6, IQR: 3-13) was twice that after small-artery occlusion (3, IQR: 2-5). Among patients with cardioembolic stroke, 26% were diagnosed post-admission with atrial fibrillation. For the 42% diagnosed pre-admission, only 54% had prior prescriptions for oral anticoagulants. Reperfusion therapies were administered in 21% of cases, with significant variations across subtypes. Mortality rates were higher after cardioembolic strokes (17%) than after small-artery occlusions (3%). Prognostic factors included etiology, high NIHSS score, atrial fibrillation, and previous heparin prescription. ConclusionsWhile atrial fibrillation was underdiagnosed and undertreated, patients with cardioembolic stroke exhibited high severity and elevated mortality rates. Etiology emerged as an independent predictor of early mortality, regardless of NIHSS score upon admission. These findings underscore the importance of targeted prevention to improve patient outcomes after ischemic stroke.

Predictors of early mortality after lung transplantation for idiopathic pulmonary arterial hypertension.

Lung transplantation remains an important therapeutic option for idiopathic pulmonary arterial hypertension (IPAH),yet short-term survival is the poorest among the major diagnostic categories. We sought to develop a prediction model for 90-day mortality using the United Network for Organ Sharing database for adults with IPAH transplanted between 2005 and 2021. Variables with a pvalue ≤ 0.1 on univariate testing were included in multivariable analysis to derive the best subset model. The cohort comprised 693 subjects, of whom 71 died (10.2%) within 90 days of transplant. Significant independent predictors of early mortality were: extracorporeal circulatory support and/or mechanical ventilation at transplant (OR:3; CI: 1.4-5), pulmonary artery diastolic pressure (OR:1.3 per 10 mmHg; CI: 1.07-1.56), forced expiratory volume in the first second percent predicted (OR:0.8 per 10%; CI: 0.7-0.94), recipient total bilirubin >2 mg/dL (OR:3; CI: 1.4-7.2) and ischemic time >6 h (OR: 1.7, CI: 1.01-2.86). The predictive model was able to distinguish 25% of the cohort with a mortality of ≥20% from 49% with a mortality of ≤5%. We conclude that recipient variables associated with increasing severity of pulmonary vascular disease, including pretransplant advanced life support, and prolonged ischemic time are important risk factors for 90-day mortality after lung transplant for IPAH.

Influence of lymphopenia on long-term mortality in septic shock, a retrospective observational study

Background and objectiveThe diagnosis of infection, to diagnose septic shock, has been qualified by leukocyte counts and protein biomarkers. Septic shock mortality is persistently high (20%–50%), and rising in the long term. The definition of sepsis does not include leukocyte count, and lymphopenia has been associated with its mortality in the short term. Immunosuppression and increased mortality in the long term due to sepsis have not been demonstrated. The aim is to relate the occurrence of lymphopenia and its lack of recovery during septic shock with mortality at 2 years. Patients and methodsCohort of 332 elderly patients diagnosed with septic shock. Mortality at 28 days and 2 years was analysed according to leukocyte, neutrophil, and lymphocyte counts, and the ability to recover from lymphopenia (LRec). ResultsA total of 74.1% of patients showed lymphopenia, and 73.5% did not improve during ICU stay. Mortality was 31.0% and 50.3% at 28 days and 2 years, respectively. Lymphopenia was a predictor of early mortality (OR 2.96) and LRec of late mortality (OR 3.98). Long-term mortality was associated with LRec (HR 1.69). ConclusionsIn elderly patients with septic shock, 28-day mortality is associated with lymphopenia and neutrophilia, and LRec with 2-year mortality; this may represent 2 distinct phenotypes of behaviour after septic shock.

Masticatory function and mortality among older adults living in long-term care facilities in Brazil.

To investigate the association between mortality and masticatory function in older adults living in long-term care facilities (LTCFs), controlling for demographic and health covariates. Poor oral health has been associated with mortality; however, no previous study investigated whether objective and self-reported poor masticatory function is a predictor of early mortality in LTCFs. Baseline characteristics of 295 participants were collected, including age, sex, polypharmacy, mobility, activities of daily living, frailty, nutritional status, and objective (masticatory performance - chewing gum) and self-reported masticatory function. The participants were followed-up with for 4 years to record the mortality data. Cox regression models were run to analyse the data (α = .05). During the 4-year follow-up, 124 (42.0%) participants died. Older adults with poor masticatory performance (hazard ratio [HR] = 1.59, 95% confidence interval [95% CI] = 1.07-2.36) and those who self-reported masticatory dysfunction (HR = 1.48, 95% CI = 1.01-2.16) were at higher risk of early death than those with good mastication. However, in a multivariate model including both objective and self-reported masticatory function, only the objective measurement remained associated with early death (HR = 1.52, 95% CI = 1.02-2.27). Poor masticatory performance seems to be associated with early death in older adults living in LTCFs, but they may have shared risk factors accumulated throughout life that were not covered by the study period.

Functional Status Associations With Treatment Receipt and Outcomes Among Older Adults Newly Diagnosed With Multiple Myeloma.

Multiple myeloma (MM) is a prevalent hematologic malignancy in older adults, who often experience physical disability, increased health care usage, and reduced treatment tolerance. Home health (HH) services are frequently used by this group, but the relationship between disability, HH use, and MM treatment receipt is unclear. This study examines the connections between disability, treatment receipt, and survival outcomes in older adults with newly diagnosed MM using a nationwide data set. The SEER-Medicare data set was used to identify adults aged 66 years and older diagnosed with MM from 2010 to 2017, who used HH services the year before diagnosis. Disability was assessed with the Outcome and Assessment Information Set, using a composite score derived from items related to ability to complete activities of daily living. Mortality, therapy receipt, and health care utilization patterns were evaluated. Of 37,280 older adults with MM, 6,850 (18.2%) used HH services before diagnosis. Moderate disability at HH assessment resulted in similar MM-directed therapy receipt as mild disability, with comparable health care usage after diagnosis to severe disability. HH users had a higher comorbidity burden and higher mortality (adjusted risk ratio for 3-year mortality: 1.59 [95% CI, 1.55 to 1.64]). Severe functional disability before diagnosis was strongly related to postdiagnosis mortality. Among older adults with MM receiving HH services, disability is a predictor of early mortality. Moderately disabled individuals undergo similar therapy intensity as the mildly disabled but experience increased acute care utilization. Previous HH use could identify patients with MM requiring intensive support during therapy initiation.

Magnesium levels and mortality relationship in patients with Acinetobacter baumannii detected in the Intensive Care Unit.

Acinetobacter baumannii (A. baumannii) causes serious nosocomial infections, especially in Intensive Care Units (ICU). Studies have shown that magnesium (Mg) levels change in sepsis. This study aimed to investigate the effect of Mg levels on mortality in patients with A. baumannii sepsis in the ICU. 140 patients who were hospitalized in the tertiary ICU between January 2018 and March 2020 and who were found to have A. baumannii sepsis in their culture follow-ups were included in the study. Demographic information of the patients, Mg levels during hospitalization and follow-up, and various data in the ICU were recorded. The factors that predicted one-month mortality were old age, APACHE II score, CCIS, A. baumannii detection in the early stages of ICU admission, and high Mg level on day A. baumannii was detected, and the lowest Mg level after A. baumannii was detected in the early period. According to the multivariate logistic regression analysis, age increase [OR (95% CI): 1.062 (1.009-1.117)], APACHE II increase [OR (95% CI): 1.251 (1.141-1.372)], and early detection of A. baumannii during ICU admission [OR (95% CI): 0.902 (0.845-0.962)] were found to be factors that increase one-month mortality. Hypermagnesemia in patients with A. baumannii indicates longer-term mortality, while a rapid decrease in Mg levels is a predictor of early mortality. Keeping Mg levels of patients within the reference range with frequent Mg measurement reduces mortality. Knowing colonized patients during admission to the ICU may be useful as an indicator of A. baumannii infection development and mortality risk.