hospital mortality
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2022 ◽  
Vol 8 ◽  
Qinghao Zhao ◽  
Haiyan Xu ◽  
Xuan Zhang ◽  
Yunqing Ye ◽  
Qiuting Dong ◽  

BackgroundWith the growing burden of non-ST-elevation myocardial infarction (NSTEMI), developing countries face great challenges in providing equitable treatment nationwide. However, little is known about hospital-level disparities in the quality of NSTEMI care in China. We aimed to investigate the variations in NSTEMI care and patient outcomes across the three hospital levels (province-, prefecture- and county-level, with decreasing scale) in China.MethodsData were derived from the China Acute Myocardial Infarction Registry on patients with NSTEMI consecutively registered between January 2013 and November 2016 from 31 provinces and municipalities throughout mainland China. Patients were categorized according to the hospital level they were admitted to. Multilevel generalized mixed models were fitted to examine the relationship between the hospital level and in-hospital mortality risk.ResultsIn total, 8,054 patients with NSTEMI were included (province-level: 1,698 patients; prefecture-level: 5,240 patients; county-level: 1,116 patients). Patients in the prefecture- and county-level hospitals were older, more likely to be female, and presented worse cardiac function than those in the province-level hospitals (P <0.05). Compared with the province-level hospitals, the rate of invasive strategies was significantly lower in the prefecture- and county-level hospitals (65.3, 43.3, and 15.4%, respectively, P <0.001). Invasive strategies were performed within the guideline-recommended timeframe in 25.4, 9.7, and 1.7% of very-high-risk patients, and 16.4, 7.4, and 2.4% of high-risk patients in province-, prefecture- and county-level hospitals, respectively (both P <0.001). The use of dual antiplatelet therapy in the county-level hospitals (87.2%) remained inadequate compared to the province- (94.5%, P <0.001) and prefecture-level hospitals (94.5%, P <0.001). There was an incremental trend of in-hospital mortality from province- to prefecture- to county-level hospitals (3.0, 4.4, and 6.9%, respectively, P-trend <0.001). After stepwise adjustment for patient characteristics, presentation, hospital facilities and in-hospital treatments, the hospital-level gap in mortality risk gradually narrowed and lost statistical significance in the fully adjusted model [Odds ratio: province-level vs. prefecture-level: 1.23 (0.73–2.05), P = 0.441; province-level vs. county-level: 1.61 (0.80–3.26), P = 0.182; P-trend = 0.246].ConclusionsThere were significant variations in NSTEMI presentation and treatment patterns across the three hospital levels in China, which may largely explain the hospital-level disparity in in-hospital mortality. Quality improvement initiatives are warranted, especially among lower-level hospitals.

2022 ◽  
Vol 11 (2) ◽  
pp. 439
Giuseppe De Matteis ◽  
Marcello Covino ◽  
Maria Livia Burzo ◽  
Davide Antonio Della Polla ◽  
Francesco Franceschi ◽  

Acute Heart Failure (AHF)-related hospitalizations and mortality are still high in western countries, especially among older patients. This study aimed to describe the clinical characteristics and predictors of in-hospital mortality of older patients hospitalized with AHF. We conducted a retrospective study including all consecutive patients ≥65 years who were admitted for AHF at a single academic medical center between 1 January 2008 and 31 December 2018. The primary outcome was all-cause, in-hospital mortality. We also analyzed deaths due to cardiovascular (CV) and non-CV causes and compared early in-hospital events. The study included 6930 patients, mean age 81 years, 51% females. The overall mortality rate was 13%. Patients ≥85 years had higher mortality and early death rate than younger patients. Infections were the most common condition precipitating AHF in our cohort, and pneumonia was the most frequent of these. About half of all hospital deaths were due to non-CV causes. After adjusting for confounding factors other than NYHA class at admission, infections were associated with an almost two-fold increased risk of mortality, HR 1.74, 95% CI 1.10–2.71 in patients 65–74 years (p = 0.014); HR 1.83, 95% CI 1.34–2.49 in patients 75–84 years (p = 0.001); HR 1.74, 95% CI 1.24–2.19 in patients ≥85 years (p = 0.001). In conclusion, among older patients with AHF, in-hospital mortality rates increased with increasing age, and infections were associated with an increased risk of in-hospital mortality. In contemporary patients with AHF, along with the treatment of the CV conditions, management should be focused on timely diagnosis and appropriate treatment of non-CV factors, especially pulmonary infections.

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Tung Phi Nguyen ◽  
Xuan Thi Phan ◽  
Tuan Huu Nguyen ◽  
Dai Quang Huynh ◽  
Linh Thanh Tran ◽  

Background. Major bleeding has been a common and serious complication with poor outcomes in ECMO patients. With a novel, less-invasive cannulation approach and closer coagulation monitoring regime, the incidence of major bleeding is currently not determined yet. Our study aims to examine the incidence of major bleeding, its determinants, and association with mortality in peripheral-ECMO patients. Method. We conducted a single-center retrospective study on adult patients undergoing peripheral-ECMO between January 2019 and January 2020 at a tertiary referral hospital. Determinants of major bleeding were defined by logistic regression analysis. Risk factors of in-hospital mortality were determined by Cox proportional hazard regression analysis. Results. Major bleeding was reported in 33/105 patients (31.4%) and was associated with higher in-hospital mortality [adjusted hazard ratio (aHR) 3.56, 95% confidence interval (CI) 1.63–7.80, p < 0.001 ). There were no significant difference in age, sex, ECMO indications, ECMO modality, pre-ECMO APACHE-II and SOFA scores between two groups with and without major bleeding. Only APTT >72 seconds [adjusted odds ratio (aOR) 7.10, 95% CI 2.60–19.50, p < 0.001 ], fibrinogen <2 g/L [aOR = 7.10, 95% CI 2.60–19.50, p < 0.001 ], and ACT >220 seconds [aOR = 3.9, 95% CI 1.20–11.80, p = 0.017 ] on days with major bleeding were independent predictors. Conclusions. In summary, major bleeding still had a fairly high incidence and poor outcome in peripheral-ECMO patients. APTT > 72 seconds, fibrinogen < 2 g/L were the strongest predicting factors for major bleeding events.

2022 ◽  
Vol 7 (4) ◽  
pp. 301-305
Thomas Iype ◽  
Dileep Ramachandran ◽  
Praveen Panicker ◽  
Sunil D ◽  
Manju Surendran ◽  

Worldwide stroke care was affected by COVID 19 pandemic and the majority of the literature was on ischemic stroke. Intracerebral hemorrhage (ICH) accounts for about one-fourth of strokes worldwide and has got high mortality and morbidity. We aimed to study the effect of the Pandemic on ICH outcomes and flow metrics during the first wave compared to the pre-pandemic period and how that experience was made used in managing ICH during the second wave. Ours was a single-center observational study, where consecutive patients with non-COVID spontaneous ICH aged more than 18 years who presented within 24 hours of last seen normal were included in the study. We selected the months of June, July, and August in 2021 as the second wave of the pandemic, the same months in 2020 as the first wave of the pandemic, and the same months in 2019 as the pre-pandemic period. We compared the 3-month functional outcomes, in hospital mortality and workflow metrics during the three time periods. We found poor three-month functional outcomes and higher hospital mortality during the first wave of the COVID 19 pandemic, which improved during the second wave. In-hospital time metrics measured by the door to CT time which was delayed during the first wave improved to a level better than the pre-pandemic period during the second wave. ICH volume was more during the first and second waves compared to the pre-pandemic period. Other observations of our study were younger age during the second wave and higher baseline systolic BP at admission during both pandemic waves. Our study showed that functional outcomes and flow metrics in ICH care improved during the second wave of the pandemic through crucial re-organization of hospital stroke workflows. We are sharing this experience because we may have to do further rearrangements in future as the upcoming times are challenging due to new variants emerging.

Maria Elena Laino ◽  
Elena Generali ◽  
Tobia Tommasini ◽  
Giovanni Angelotti ◽  
Alessio Aghemo ◽  

IntroductionIdentifying SARS-CoV-2 patients at higher risk of mortality is crucial in the management of a pandemic. Artificial intelligence techniques allow to analyze big amount of data to find hidden patterns. We aimed to develop and validate a mortality score at admission for COVID-19 based on high-level machine learning.Material and methodsWe conducted a retrospective cohort study on hospitalized adults COVID-19 patients between March and December 2020. The primary outcome was in-hospital mortality. A machine learning approach on vital parameters, laboratory values, and demographic features was applied to develop different models. Then, a feature importance analysis was performed to reduce the number of variables included in the model, to develop a risk score with good overall performance, that was finally evaluated in terms of discrimination and calibration capabilities. All results underwent cross-validation.Results1,135 consecutive patients (median age 70 years, 64% males) were enrolled, 48 patients were excluded, the cohort was randomly divided in training (760) and test (327). During hospitalization, 251 (22%) patients died. After feature selection, the best performing classifier was random forest (AUC 0.88±0.03). Based on the relative importance of each variable, a pragmatic score was developed, showing good performances (AUC 0.85, ±0.025), and three levels were defined that correlated well with in-hospital mortality.ConclusionsMachine learning techniques were applied in order to develop an accurate in-hospital mortality risk score for COVID-19 based on ten variables. The application of the proposed score has utility in clinical settings to guide the management and prognostication of COVID-19 patients.

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