Mortality Factors Research Articles

Impact of diabetes on short-term outcomes in patients undergoing coronary artery bypass grafting surgery in acute coronary syndrome.

Diabetes mellitus (DM) is associated with concomitant comorbidities, such as atherosclerosis and cardiovascular disease. Coronary artery bypass grafting (CABG) surgery is the optimal therapy in diabetic patients with triple vessel disease. DM is also known to be a relevant risk factor for higher morbidity and mortality in patients who underwent elective CABG procedures. Data regarding outcomes in diabetic patients in acute coronary syndrome (ACS) is heterogeneous. This study aimed to investigate the impact of DM on short-term outcomes in patients who underwent CABG surgery in ACS. A retrospective propensity score matched (PSM) analysis of 1370 patients who underwent bypass surgery for ACS between June 2011 and October 2019 was conducted. All patients were divided into two groups: non-diabetic group (n = 905) and diabetic group (n = 465). In-hospital mortality was the primary outcome. Secondary outcomes were perioperative myocardial infarction, new onset dialysis, reopening for bleeding and duration of intensive care unit (ICU) stay. A subgroup analysis of patients with insulin-dependent and non-insulin dependent DM was also performed. After performing PSM analysis, baseline characteristics and the preoperative risk profile were comparable between both groups. The proportion of patients who underwent total arterial revascularization (p = .048) with the use of both internal thoracic arteries (p < .001) was significantly higher in the non-diabetic group. The incidence of perioperative myocardial infarction (p = .048) and new onset dialysis (p = .008) was significantly higher in the diabetic group. In-hospital mortality was statistically (p = .907) comparable between the two groups. DM was associated with a higher incidence of adverse outcomes, however with comparable in-hospital mortality in patients who underwent CABG procedure for ACS.

Cortisol Levels During First Admission Day Are Associated With Clinical Outcomes in Surgical Critically Ill Patients.

To explore the correlation between cortisol levels during first admission day and clinical outcomes. Although most patients exhibit a surge in cortisol levels in response to stress, some suffer from critical illness-related corticosteroid insufficiency (CIRCI). Literature remains inconclusive as to which of these patients are at greater risk of poor outcomes. A retrospective study. A surgical ICU (SICU) in a tertiary medical center. Critically ill patients admitted to the SICU who were not treated with steroids. Levels of cortisol taken within 24 hours of admission (day 1 [D1] cortisol) in 1412 eligible patients were collected and analyzed. Results were categorized into four groups: low (0-10 µg/dL), normal (10-25 µg/dL), high (25-50 µg/dL), and very high (above 50 µg/dL) cortisol levels. Primary endpoint was 90-day mortality. Secondary endpoints were the need for organ support (use of vasopressors and mechanical ventilation [MV]), ICU length of stay (LOS), and duration of MV. The majority of patients (63%) had high or very high D1 cortisol levels, whereas 7.6% had low levels and thus could be diagnosed with CIRCI. There were statistically significant differences in 90-day mortality between the four groups and very high levels were found to be an independent risk factor for mortality, primarily in patients with Sequential Organ Failure Assessment (SOFA) less than or equal to 3 or SOFA greater than or equal to 7. Higher cortisol levels were associated with all secondary endpoints. CIRCI was associated with favorable outcomes. In critically ill surgical patients D1 cortisol levels above 50 mcg/dL were associated with mortality, need for organ support, longer ICU LOS, and duration of MV, whereas low levels correlated with good clinical outcomes even though untreated. D1 cortisol level greater than 50 mcg/dL can help discriminate nonsurvivors from survivors when SOFA less than or equal to 3 or SOFA greater than or equal to 7.

Impact of Charlson Comorbidity Index on in-hospital mortality of patients with hyperglycemic crises: A propensity score matching analysis.

This study was designed to investigate the association between Charlson Comorbidity Index (CCI) and in-hospital mortality and other clinical outcomes among patients with hyperglycemic crises. This retrospective cohort study was conducted using data from electric medical records. A total of 1668 diabetic patients with hyperglycemic crises from six tertiary hospitals met the inclusion criteria. CCI < 4 was defined as low CCI and CCI ≥ 4 was defined as high CCI. Propensity score matching (PSM) with the 1:1 nearest neighbour matching method and the caliper value of 0.02 was used to match the baseline characteristics of patients with high CCI and low CCI to reduce the confounding bias. In-hospital mortality, ICU admission, hypoglycemia, hypokalemia, acute kidney injury, length of stay (LOS), and hospitalisation expense between low CCI and high CCI were compared and assessed. Univariate and multivariate regression were applied to estimate the impact of CCI on in-hospital and other clinical outcomes. One hundred twenty-one hyperglycemic crisis (HC) patients died with a mortality rate of 7.3%. After PSM, compared with low CCI, patients with high CCI suffered higher in-hospital mortality, ICU admission, LOS, and hospitalisation expenses. After multivariate regression, age (aOR: 1.12, 95% confidence interval [CI]: 1.06-1.18, p < 0.001), CCI(aOR: 4.42, 95% CI: 1.56-12.53, p = 0.005), uninsured (aOR: 22.32, 95% CI: 4.26-116.94, p < 0.001), shock (aOR: 10.57, 95% CI: 1.41-79.09, p = 0.022), mechanical ventilation (aOR: 75.29, 95% CI: 12.37-458.28, p < 0.001), and hypertension (aOR: 4.34, 95% CI: 1.37-13.82, p = 0.013) were independent risk factors of in-hospital mortality of HC patients. Besides, high CCI was an independent risk factor for higher ICU Admission (aOR: 5.91, 95% CI: 2.31-15.08, p < 0.001), hypoglycemia (aOR: 2.19, 95% CI:1.01-4.08, p = 0.049), longer LOS (aOR: 1.23, 95% CI: 1.19-2.27, p = 0.021), and higher hospitalisation expense (aOR: 2089.97, 95% CI: 193.33-3988.61, p = 0.031) of HC patients. CCI is associated with in-hospital mortality, ICU admission, hypoglycemia, LOS, and hospitalisation expense of HC patients. CCI could be an ideal indicator to identify, monitor, and manage chronic comorbidities among HC patients.

Analysis of factors influencing vascular calcification in peritoneal dialysis patients and their impact on long-term prognosis

BackgroundThis study aims to investigate the influencing factors of vascular calcification in peritoneal dialysis (PD) patients and its relationship with long-term prognosis.MethodsThis retrospective cohort study included chronic kidney disease patients undergoing peritoneal dialysis at the Peritoneal Dialysis Center of Beijing Luhu Hospital, Capital Medical University, from January 2019 to March 2019. Demographic and clinical laboratory data, including serum sclerostin (SOST), calcium (Ca), phosphate (P), serum albumin (ALB), and intact parathyroid hormone (iPTH) levels, were collected. Abdominal aortic calcification (AAC) was assessed using abdominal lateral X-ray examination to determine the occurrence of vascular calcification, and patients were divided into the AAC group and Non-AAC group based on the results.ResultsA total of 91 patients were included in the study. The AAC group consisted of 46 patients, while the Non-AAC group consisted of 45 patients. The AAC group had significantly older patients compared to the non-AAC group (P < 0.001) and longer dialysis time (P = 0.004). Multivariable logistic regression analysis indicated that risk factors for vascular calcification in PD patients included dialysis time, diabetes, hypertension, and SOST. Kaplan–Meier survival analysis showed that the AAC group had a significantly higher mortality rate than the non-AAC group (χ2 = 35.993, P < 0.001). Multivariable Cox regression analysis revealed that dialysis time, diabetes and AAC were risk factors for all-cause mortality in peritoneal dialysis patients.ConclusionLonger dialysis time, comorbid diabetes, comorbid hypertension, and SOST are risk factors for vascular calcification in PD patients. Additionally, AAC, longer dialysis time, and comorbid diabetes are associated with increased risk of all-cause mortality in peritoneal dialysis patients.

Clinical characteristics and the prognostic impact of acute kidney injury in critically ill patients with invasive pulmonary Aspergillosis in the intensive care unit: A retrospective, single-center study

Introduction: The incidence and impact of acute kidney injury (AKI) in patients with invasive pulmonary aspergillosis (IPA) admitted to the intensive care unit (ICU) are unknown. Methods: This retrospective study included 140 patients who were diagnosed IPA and admitted to the medical ICU of China–Japan Friendship Hospital in Beijing, China. AKI was defined according to the kidney disease improving global outcomes guidelines. Data on demographic characteristics, comorbidities, laboratory tests, treatments, and prognosis at ICU admission were collected. Results: The rate of AKI was 71.4% (n = 100), and approximately 30% of the patients had preadmission acute kidney dysfunction. Of the 100 patients with AKI, 19, 8, and 73 patients had stage I, II, and III AKI, respectively, and 64 (87.6%) patients required continuous renal replacement therapy. Overall ICU mortality rate was 52.1%. Irreversible AKI was a strong independent risk factor for ICU mortality (odds ratio 13.36, 95% confidence interval 4.52–39.48, p &amp;lt; 0.001), followed by chronic lung disease, use of intermittent positive-pressure ventilation, and long-term corticosteroid treatment within 1 year prior to ICU admission. Higher cardiac troponin I levels at admission and worse volume control during the first 7 days of ICU stay were potential predictive factors of irreversible kidney dysfunction. Patients with irreversible AKI and those who died during the ICU stay had greater volume overload during the first 14 days of ICU stay. Patients who survived received earlier renal replacement therapy support after ICU admission compared to those who died (median, 2 vs. 5 days; p = 0.026). Conclusion: Compared to the patients with IPA in the absence of AKI, those with AKI presented with more volume overload, worse disease burden, and required stronger respiratory support, while experiencing worse prognosis. Irreversible AKI was a strong predictor of mortality in patients with critical IPA. Better volume control and earlier CRRT initiation should be considered key points in AKI management and prognostic improvement.

Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model based on real endometrial cancer patients.

This study aimed to construct a competing risk prediction model for predicting specific mortality risks in endometrial cancer patients from the SEER database based on their demographic characteristics and tumor information. We collected relevant clinical data on patients with histologically confirmed endometrial cancer in the SEER database between 2010 and 2015. Univariate and multivariate competing risk models were used to analyze the risk factors for endometrial cancer-specific death, and a predictive nomogram was constructed. C-index and receiver operating characteristic curve (ROC) at different time points were used to verify the accuracy of the constructed nomogram. There were 26 109 eligible endometrial cancer patients in the training cohort and 11 189 in the validation cohort. Univariate and multivariate analyses revealed that Age, Marriage, Grade, Behav, FIGO, Size, Surgery, SurgOth, Radiation, ParaAortic_Nodes, Peritonea, N positive, DX_liver, and DX_lung were independent prognostic factors for specific mortality in endometrial cancer patients. Based on these factors, a nomogram was constructed. Internal validation showed that the nomogram had a good discriminative ability (C-index = 0.883 [95% confidence interval [CI]: 0.881-0.884]), and the 1-, 3-, and 5-year AUC values were 0.901, 0.886 and 0.874, respectively. External validation indicated similar results (C-index = 0.883 [95%CI: 0.882-0.883]), and the 1-, 3-, and 5- AUC values were 0.908, 0.885 and 0.870, respectively. We constructed a competing risk model to predict the specific mortality risk among endometrial cancer patients. This model has favorable accuracy and reliability and can provide a reference for the development and update of endometrial cancer prognostic risk assessment tools.

Influence of elevated liver enzyme level on 30-day mortality rates in patients undergoing nonemergency orthopedic surgery

BackgroundThe effect of elevated preoperative liver enzyme levels on postoperative outcomes is a topic of concern to clinicians. This study explored the association between elevated preoperative liver enzyme levels and surgical outcomes in patients undergoing orthopedic surgery.MethodsUsing the American College of Surgeons National Surgical Quality Improvement Program database, we obtained data on adult patients who received nonemergency orthopedic surgery under general anesthesia between 2011 and 2021.ResultsWe evaluated the data of 477,524 patients, of whom 6.1% (24 197 patients) had elevated preoperative serum glutamic oxaloacetic transaminase (SGOT) levels. An elevated SGOT level was significantly associated with 30-day postoperative mortality (adjusted hazard ratio, 1.62; 95% confidence interval, 1.39 to 1.90). We determined that the mortality rate rose with SGOT levels. The results remained unchanged after propensity score matching.ConclusionElevated preoperative SGOT levels constitute an independent risk factor for 30-day postoperative mortality and are proportionately associated with the risk of 30-day postoperative mortality.

Lipid risk factors for cardiovascular mortality and chronic inflammation in functionally dependent elderly persons

Lipid risk factors for cardiovascular mortality and chronic inflammation in functionally dependent elderly persons

Sepsis mortality among patients with haematological malignancy admitted to intensive care 2000–2022: a binational cohort study

BackgroundSepsis occurs in 12–27% of patients with haematological malignancy within a year of diagnosis. Sepsis mortality has improved in non-cancer patients in the last two decades, but longitudinal trends in patients with haematological malignancy are not well characterised. We aimed to compare outcomes, including temporal changes, in patients with and without a haematological malignancy admitted to ICU with a primary diagnosis of sepsis in Australia and New Zealand over the past two decades.MethodsWe performed a retrospective cohort study of 282,627 patients with a primary intensive care unit (ICU) admission diagnosis of sepsis including 17,313 patients with haematological malignancy, admitted to 216 intensive care units (ICUs) in Australia or New Zealand between January 2000 and December 2022. Annual crude and adjusted in-hospital mortality were reported. Risk factors for in-hospital mortality were determined using a mixed methods logistic regression model and were used to calculate annual changes in mortality.ResultsIn-hospital sepsis mortality decreased in patients with haematological malignancy, from 55.6% (95% CI 46.5–64.6%) in 2000 to 23.1% (95% CI 20.8–25.5%) in 2021. In patients without haematological malignancy mortality decreased from 33.1% (95% CI 31.3–35.1%) to 14.4% (95% CI 13.8–14.8%). This decrease remained significant after adjusting for mortality predictors including age, SOFA score and comorbidities, as estimated by adjusted annual odds of in-hospital death. The reduction in odds of death was of greater magnitude in patients with haematological malignancy than those without (OR 0.954, 95% CI 0.947–0.961 vs. OR 0.968, 95% CI 0.966–0.971, p < 0.001). However, absolute risk of in-hospital mortality remained higher in patients with haematological malignancy. Older age, higher SOFA score, presence of comorbidities, and mechanical ventilation were associated with increased mortality. Leukopenia (white cell count < 1.0 × 109 cells/L) was not associated with increased mortality in patients with haematological malignancy (p = 0.60).ConclusionsSepsis mortality has improved in patients with haematological malignancy admitted to ICU. However, mortality remains higher in patients with haematological malignancy than those without.Graphical abstract

Presence of Epstein-Barr virus in cerebrospinal fluid is associated with increased mortality in HIV-negative cryptococcal meningitis.

Cryptococcus neoformans is the most common cause of fungal meningitis and is associated with a high mortality. The clinical significance of concurrent Epstein-Barr virus (EBV) in the cerebrospinal fluid (CSF) of human immunodeficiency virus (HIV)-negative patients with cryptococcal meningitis (CM) remains unclear. A retrospective cohort study was performed by analyzing CSF samples from 79 HIV-negative Chinese Han patients with confirmed CM. We identified CSF viral DNA in these patients by metagenomic next-generation sequencing (mNGS) and compared 10-week survival rates among those with and without EBV DNA in CSF. Of 79 CSF samples tested, 44.3% (35/79) had detectable viral DNA in CSF, while 55.7% (44/79) were virus-negative. The most frequent viral pathogen was EBV, which was detected in 22.8% (18/79) patients. The median number of CSF-EBV DNA reads was 4 reads with a range from 1 to 149 reads. The 10-week mortality were 22.2% (4/18) in those with positive-CSF-EBV and 2.3% (1/44) in those with negative-CSF-virus (hazard ratio 8.20, 95% confidence interval [CI] 1.52-81.80; p=0.014), which remained significant after a multivariate adjustment for the known risk factors of mortality (adjusted hazard ratio 8.15, 95% CI 1.14-92.87; p=0.037). mNGS can identify viruses that coexist in CSF of HIV-negative patients with CM. EBV DNA is most commonly found together with Cryptococcus neoformans in CSF and its presence is associated with increased mortality in HIV-negative CM patients.

Predictive factors of 90-day mortality after curative hepatic resection for hepatocellular carcinoma: a western single-center observational study

PurposeThe aim of this study was to identify predictive risk factors associated with 90-day mortality after hepatic resection (HR) in hepatocellular carcinoma (HCC).MethodsAll patients undergoing elective resection for HCC from a single- institutional and prospectively maintained database were included. Multivariate regression analysis was conducted to identify pre- and intraoperative as well as histopathological predictive factors of 90-day mortality after elective HR.ResultsBetween August 2004 and October 2021, 196 patients were enrolled (148 male /48 female). The median age of the study cohort was 68.5 years (range19-84 years). The rate of major hepatectomy (≥ 3 segments) was 43.88%. Multivariate analysis revealed patient age ≥ 70 years [HR 2.798; (95% CI 1.263–6.198); p = 0.011], preoperative chronic renal insufficiency [HR 3.673; (95% CI 1.598–8.443); p = 0.002], Child–Pugh Score [HR 2.240; (95% CI 1.188–4.224); p = 0.013], V-Stage [HR 2.420; (95% CI 1.187–4.936); p = 0.015], and resected segments ≥ 3 [HR 4.700; (95% 1.926–11.467); p = 0.001] as the major significant determinants of the 90-day mortality.ConclusionAdvanced patient age, pre-existing chronic renal insufficiency, Child–Pugh Score, extended hepatic resection, and vascular tumor involvement were identified as significant predictive factors of 90-day mortality. Proper patient selection and adjustment of treatment strategies could potentially reduce short-term mortality.

The short-term effects of individual and mixed ambient air pollutants on suicide mortality: A case-crossover study

It is critical to explore intervenable environmental factors in suicide mortality. Based on 30,688 suicide cases obtained from the Mortality Surveillance System of the Jiangsu Provincial Centre for Disease Control and Prevention, we utilized a case-crossover design, and found that the OR of suicide deaths increased by a maximum of 0.71 % (95 % CI: 0.09 %, 1.32 %), 0.68 % (95 % CI: 0.12 %, 1.25 %), 0.77 % (95 % CI: 0.19 %, 1.37 %), 2.95 % (95 % CI: 1.62 %, 4.29 %), 4.18 % (95 % CI: 1.55 %, 6.88 %), and 0.93 % (95 % CI: 0.10 %, 1.77 %), respectively, for per 10 μg/m3 increase in the particulate matter (PM) with diameters ≤ 2.5 µm (PM2.5), PM with diameters ≤ 10 µm (PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and per 0.1 mg/m3 increase in carbon monoxide (CO) concentrations with the conditional logistic regression analysis. People living in county-level cities were more susceptible. Particularly, a significant positive association was found between air pollutant mixture exposure and suicide deaths (OR=1.04,95 % CI: 1.01, 1.06). The excess fraction of suicide deaths due to air pollution reached a maximum of 8.07 %. In conclusion, we found associations between individual and mixed ambient air pollutants and suicide deaths, informing the development of integrated air pollution management and targeted measures for suicide prevention and intervention. Environmental ImplicationAs a major contributor to the global burden of disease, air pollution was confirmed by accumulating studies to have adverse impact on mental health, and potentially lead to suicide deaths. However, systematic studies on the association between air pollution and suicide mortality are lacking. We explored the associations of multiple air pollutants and pollution mixtures with suicide deaths and assessed excess suicide mortality due to air pollution, emphasizing the importance of air pollution control on suicide prevention. Our study provides evidence to support mechanistic studies on the association between air pollution and suicide, and informs comprehensive air pollution management.

A physiologically-based digital twin for alcohol consumption—predicting real-life drinking responses and long-term plasma PEth

Alcohol consumption is associated with a wide variety of preventable health complications and is a major risk factor for all-cause mortality in the age group 15-47 years. To reduce dangerous drinking behavior, eHealth applications have shown promise. A particularly interesting potential lies in the combination of eHealth apps with mathematical models. However, existing mathematical models do not consider real-life situations, such as combined intake of meals and beverages, and do not connect drinking to clinical markers, such as phosphatidylethanol (PEth). Herein, we present such a model which can simulate real-life situations and connect drinking to long-term markers. The new model can accurately describe both estimation data according to a χ2 -test (187.0 < Tχ2 = 226.4) and independent validation data (70.8 < Tχ2 = 93.5). The model can also be personalized using anthropometric data from a specific individual and can thus be used as a physiologically-based digital twin. This twin is also able to connect short-term consumption of alcohol to the long-term dynamics of PEth levels in the blood, a clinical biomarker of alcohol consumption. Here we illustrate how connecting short-term consumption to long-term markers allows for a new way to determine patient alcohol consumption from measured PEth levels. An additional use case of the twin could include the combined evaluation of patient-reported AUDIT forms and measured PEth levels. Finally, we integrated the new model into an eHealth application, which could help guide individual users or clinicians to help reduce dangerous drinking.

Establishment of a mortality risk nomogram for predicting in-hospital mortality of sepsis: cohort study from a Chinese single center.

To establish a mortality risk nomogram for predicting in-hospital mortality of sepsis patients in the Chinese population. Data were obtained from the medical records of sepsis patients enrolled at the Affiliated Huadu Hospital, Southern Medical University, between 2019 and 2021. A total of 696 sepsis patients were initially included in our research, and 582 cases were finally enrolled after screening and divided into the survival group (n = 400) and the non-survival group (n = 182) according to the incidence of mortality during hospitalization. Twenty-eight potential sepsis-related risk factors for mortality were identified. Least absolute shrinkage and selection operator (LASSO) regression was used to optimize variable selection by running cyclic coordinate descent with k-fold (tenfold in this case) cross-validation. We used binary logistic regression to build a model for predicting mortality from the variables based on LASSO regression selection. Binary logistic regression was used to establish a nomogram based on independent mortality risk factors. To validate the prediction accuracy of the nomogram, receiver operating characteristic curve (ROC) analysis, decision curve analysis (DCA) and restricted cubic spline (RCS) analysis were employed. Eventually, the Hosmer-Lemeshow test and calibration curve were used for nomogram calibration. LASSO regression identified a total of ten factors, namely, chronic heart disease (CHD), lymphocyte count (LYMP), neutrophil-lymphocyte ratio (NLR), red blood cell distribution width (RDW), C reactive protein (CRP), Procalcitonin (PCT), lactic acid, prothrombin time (PT), alanine aminotransferase (ALT), total bilirubin (Tbil), interleukin-6 (IL6), that were incorporated into the multivariable analysis. Finally, a nomogram including CHD, LYMP, NLR, RDW, lactic acid, PT, CRP, PCT, Tbil, ALT, and IL6 was established by multivariable logistic regression. The ROC curves of the nomogram in the training and validation sets were 0.9836 and 0.9502, respectively. DCA showed that the nomogram could be applied clinically if the risk threshold was between 29.52 and 99.61% in the training set and between 31.32 and 98.49% in the testing set. RCS showed that when the value of independent risk factors from the predicted model exceeded the median, the mortality hazard ratio increased sharply. The results of the Hosmer-Lemeshow test (χ2 = 0.1901, df = 2, p = 0.9091) and the calibration curves of the training and validation sets showed good agreement with the actual results, which indicated good stability of the model. Our nomogram, including CHD, LYMP, NLR, RDW, lactic acid, PT, CRP, PCT, Tbil, ALT, and IL6, exhibits good performance for predicting mortality risk in adult sepsis patients.

Bronchiectasis in Türkiye: Data from a Multicenter Registry (Turkish Adult Bronchiectasis Database).

Bronchiectasis is a chronic lung disease characterized by permanent bronchial wall dilatation. Although it has been known as an orphan disease, it has recently gained attention because of registry-based studies and drug research. We aimed to use a multicenter database to analyze and compare data regarding the etiology, associated comorbidities, microbiological characteristics, and preventive strategies of bronchiectasis in Türkiye to those of other countries. A multicenter prospective cohort study. The multicenter, prospective cohort study was conducted between March 2019 and January 2022 using the Turkish Adult Bronchiectasis Database, in which 25 centers in Türkiye participated. Patients aged > 18 years who presented with respiratory symptoms such as cough, sputum, and dyspnea and were diagnosed with non-cystic fibrosis bronchiectasis using computed tomography were included in the study. Demographic information, etiologies, comorbidities, pulmonary functions, and microbiological, radiological, and clinical data were collected from the patients. Of the 1,035 study participants, 518 (50%) were females. The mean age of the patients was 56.1 ± 16.1 years. The underlying etiology was detected in 565 (54.6%) patients. While postinfectious origin was the most common cause of bronchiectasis (39.5%), tuberculosis was identified in 11.3% of the patients. An additional comorbidity was detected in 688 (66.5%) patients. The most common comorbidity was cardiovascular disease, and chronic obstructive pulmonary disease (COPD) and bronchiectasis was identified in 19.5% of the patients. The most commonly detected microbiological agent was Pseudomonas aeruginosa (29.4%). Inhaled corticosteroids (ICS) were used in 70.1% of the patients, and the frequency of exacerbations in the last year was significantly higher in patients using ICS than in nonusers (p < 0.0001). Age [odds ratio (OR): 1.028; 95% confidence interval (CI): 1.005-1.051], cachexia (OR: 4.774; 95% CI: 2,054-11,097), high modified medical research council dyspnea scale score (OR: 1,952; 95% CI: 1,459-2,611), presence of chronic renal failure (OR: 4,172; 95% CI: 1,249-13,938) and use of inhaled steroids (OR: 2,587; 95% CI: 1,098-6,098) were significant risk factors for mortality. Mortality rates were higher in patients with COPD than in those with no COPD (21.7-9.1%, p = 0.016). Patients with bronchiectasis and COPD exhibited more frequent exacerbations, exacerbation-related hospitalizations, and hospitalization in the intensive care unit in the previous year than patients without COPD. This is the first multicenter study of bronchiectasis in Türkiye. The study results will provide important data that can guide the development of health policies in Türkiye on issues such as infection control, vaccination, and the unnecessary use of antibiotics and steroids.

Cerebral hemodynamics and optic nerve sheath diameter acquired via neurosonology in critical patients with severe coronavirus disease: experience of a national referral hospital in Peru.

We aimed to describe the neurosonological findings related to cerebral hemodynamics acquired using transcranial Doppler and to determine the frequency of elevated ICP by optic nerve sheath diameter (ONSD) measurement in patients with severe coronavirus disease (COVID-19) hospitalized in the intensive care unit of a national referral hospital in Peru. We included a retrospective cohort of adult patients hospitalized with severe COVID-19 and acute respiratory failure within the first 7 days of mechanical ventilation under deep sedoanalgesia, with or without neuromuscular blockade who underwent ocular ultrasound and transcranial Doppler. We determine the frequency of elevated ICP by measuring the diameter of the optic nerve sheath, choosing as best cut-off value a diameter equal to or >5.8 mm. We also determine the frequency of sonographic patterns obtained by transcranial Doppler. Through insonation of the middle cerebral artery. Likewise, we evaluated the associations of clinical, mechanical ventilator, and arterial blood gas variables with ONSD ≥5.8 mm and pulsatility index (PI) ≥1.1. We also evaluated the associations of hemodynamic findings and ONSD with mortality the effect size was estimated using Poisson regression models with robust variance. This study included 142 patients. The mean age was 51.39 ± 13.3 years, and 78.9% of patients were male. Vasopressors were used in 45.1% of patients, and mean arterial pressure was 81.87 ± 10.64 mmHg. The mean partial pressure of carbon dioxide (PaCO2) was elevated (54.08 ± 16.01 mmHg). Elevated intracranial pressure was seen in 83.1% of patients, as estimated based on ONSD ≥5.8 mm. A mortality rate of 16.2% was reported. In the multivariate analysis, age was associated with elevated ONSD (risk ratio [RR] = 1.07). PaCO2 was a protective factor (RR = 0.64) in the cases of PI ≥ 1.1. In the mortality analysis, the mean velocity was a risk factor for mortality (RR = 1.15). A high rate of intracranial hypertension was reported, with ONSD measurement being the most reliable method for estimation. The increase in ICP measured by ONSD in patients with severe COVID-19 on mechanical ventilation is not associated to hypercapnia or elevated intrathoracic pressures derived from protective mechanical ventilation.

Trends in prevalence, mortality, and risk factors of dementia among the oldest-old adults in the United States: the role of the obesity epidemic.

The oldest-old population, those aged ≥ 80years, is the fastest-growing group in the United States (US), grappling with an increasingly heavy burden of dementia. We aimed to dissect the trends in dementia prevalence, mortality, and risk factors, and predict future levels among this demographic. Leveraging data from the Global Burden of Disease Study 2019, we examined the trends in dementia prevalence, mortality, and risk factors (with a particular focus on body mass index, BMI) for US oldest-old adults. Through decomposition analysis, we identified key population-level contributors to these trends. Predictive modeling was employed to estimate future prevalence and mortality levels over the next decade. Between 1990 and 2019, the number of dementia cases and deaths among the oldest-old in the US increased by approximately 1.37 million and 60,000 respectively. The population growth and aging were highlighted as the primary drivers of this increase. High BMI emerged as a growing risk factor. Females showed a disproportionately higher dementia burden, characterized by a unique risk factor profile, including BMI. Predictions for 2030 anticipate nearly 4 million dementia cases and 160,000 related deaths, with a marked increase in prevalence and mortality anticipated among those aged 80-89. The past 30years have witnessed a notable rise in both the prevalence and mortality of dementia among the oldest-old in the US, accompanied by a significant shift in risk factors, with obesity taking a forefront position. Targeted age and sex-specific public health strategies that address obesity control are needed to mitigate the dementia burden effectively.

Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection among Kidney Transplant Recipients: A Large Single-Center Experience.

Kidney transplant recipients (KTRs) are a vulnerable immunocompromised population at risk of severe COVID-19 disease and mortality after SARS-CoV-2 infection. We sought to characterize the post-infection sequelae in KTRs at our center. We studied all adult KTRs (with a functioning allograft) who had their first episode of SARS-CoV-2 infection between 04/2020 and 04/2022. Outcomes of interest included risk factors for hospitalization, all-cause mortality, COVID-19-related mortality, and allograft failure. Of 979 KTRs with SARS-CoV-2 infection, 381 (39%) were hospitalized. In the multivariate analysis, risk factors for hospitalization included advanced age/year (HR: 1.03, 95% CI: 1.02-1.04), male sex (HR: 1.29, 95% CI: 1.04-1.60), non-white race (HR: 1.48, 95% CI: 1.17-1.88), and diabetes as a cause of ESKD (HR: 1.77, 95% CI: 1.41-2.21). SARS-CoV-2 Vaccination was associated with decreased risk of hospitalization (HR: 0.73, 95% CI: 0.59-0.90), all-cause mortality (HR: 0.52, 95% CI: 0.37-0.74), and COVID-19-related mortality (HR: 0.47, 95% CI: 0.31-0.71) in the univariate and multivariate analyses. Risk factors for both all-cause and COVID-19-related mortality in the multivariate analyses included advanced age, hospitalization, and respiratory symptoms for hospital admission. Furthermore, additional risk factors for all-cause mortality in the multivariate analysis included being a non-white recipient and diabetes as a cause of ESKD, with being a recipient of a living donor as protective. Hospitalization due to COVID-19-associated symptoms is associated with increased mortality. Vaccination is a protective factor against hospitalization and mortality.

Effect of Novel Inflammatory Biomarkers on Adverse Outcomes in Patients with Interstitial Lung Disease and Pneumonia: A Multicenter Retrospective Cohort Study.

Interstitial lung disease frequently coincides with pneumonia in clinical settings, and both conditions are closely associated with immunoinflammation. The Systemic Immune Inflammatory Index (SII) is a recently identified marker, and its connection to the prognosis of individuals suffering from interstitial lung disease and concurrent pneumonia remains unclear. The objective of this study was to scrutinize the correlation between varying SII levels and unfavorable outcomes in patients grappling with interstitial lung disease complicated by pneumonia. This study encompassed a retrospective multicenter cohort of 324 patients diagnosed with interstitial lung disease and pneumonia, all receiving glucocorticoid treatment during their hospitalization. We initially conducted ROC analysis to determine the optimal SII threshold. Subsequently, we examined disparities in clinical symptoms, physical signs, clinical test data, and other clinical attributes among patients with differing SII levels. Later, we employed the Kaplan-Meier survival curve method to assess the association between distinct SII levels and the 30-day and 90-day mortality rates in patients dealing with interstitial lung disease complicated by pneumonia. Finally, a Cox regression model was employed to identify factors influencing adverse prognosis in these patients. The findings demonstrated that the optimal SII threshold for predicting 30-day mortality was 1416.97, with an AUC of 0.633 (95% CI: 0.559-0.708) and a P value of <0.001. For 90-day mortality, the optimal SII threshold was 994.59, yielding an AUC of 0.628 (95% CI: 0.56-0.697) and a P value of <0.001. Noteworthy statistical distinctions emerged in dyspnea, cyanosis, and oxygenation index among patients with varying SII levels. Additionally, invasive mechanical ventilation, non-invasive ventilation, and extended infection duration independently constituted 30-day and 90-day mortality risk factors. Elevated heart rate and higher SII levels emerged as independent risk factors for 90-day mortality. To some extent, SII levels exhibit correlations with the clinical manifestations in patients grappling with interstitial lung disease complicated by pneumonia. Notably, a high SII level is an independent predictor for an unfavorable prognosis in these patients. Nevertheless, these findings warrant further validation through prospective cohort studies.

Demystifying COVID-19 mortality causes with interpretable data mining

While COVID-19 becomes periodical, old individuals remain vulnerable to severe disease with high mortality. Although there have been some studies on revealing different risk factors affecting the death of COVID-19 patients, researchers rarely provide a comprehensive analysis to reveal the relationships and interactive effects of the risk factors of COVID-19 mortality, especially in the elderly. Through retrospectively including 1917 COVID-19 patients (102 were dead) admitted to Xiangya Hospital from December 2022 to March 2023, we used the association rule mining method to identify the risk factors leading causes of death among the elderly. Firstly, we used the Affinity Propagation clustering to extract key features from the dataset. Then, we applied the Apriori Algorithm to obtain 6 groups of abnormal feature combinations with significant increments in mortality rate. The results showed a relationship between the number of abnormal feature combinations and mortality rates within different groups. Patients with “C-reactive protein > 8 mg/L”, “neutrophils percentage > 75.0 %”, “lymphocytes percentage < 20%”, and “albumin < 40 g/L” have a 2×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} mortality rate than the basic one. When the characteristics of “D-dimer > 0.5 mg/L” and “WBC > 9.5×109\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$9.5 \ imes 10^9$$\\end{document} /L” are continuously included in this foundation, the mortality rate can be increased to 3×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} or 4×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document}. In addition, we also found that liver and kidney diseases significantly affect patient mortality, and the mortality rate can be as high as 100%. These findings can support auxiliary diagnosis and treatment to facilitate early intervention in patients, thereby reducing patient mortality.