Impact of more variations on in-hospital mortality among patients with confirmed COVID-19.
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ABSTRACT:
SUBMITTER: Jia N
PROVIDER: S-EPMC8989748 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
Impact of more variations on in-hospital mortality among patients with confirmed COVID-19.
Jia Na N Zeng Ping P Xia Jun J Liu Deping D
Journal of clinical hypertension (Greenwich, Conn.) 20220321 4
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Project description:Measuring mortality has been a challenge during the COVID-19 pandemic. Here, we compared the results from the Spanish daily mortality surveillance system (MoMo) of excess mortality estimates, using a time series analysis, with those obtained for the confirmed COVID-19 deaths reported to the National Epidemiological Surveillance Network (RENAVE). The excess mortality estimated at the beginning of March 2020 was much greater than what has been observed in previous years, and clustered in a very short time. The cumulated excess mortality increased with age. In the first epidemic wave, the excess mortality estimated by MoMo was 1.5 times higher than the confirmed COVID-19 deaths reported to RENAVE, but both estimates were similar in the following pandemic waves. Estimated excess mortality and confirmed COVID-19 mortality rates were geographically distributed in a very heterogeneous way. The greatest increase in mortality that has taken place in Spain in recent years was detected early by MoMo, coinciding with the spread of the COVID-19 pandemic. MoMo is able to identify risk situations for public health in a timely manner, relying on mortality in general as an indirect indicator of various important public health problems.
| S-EPMC8703729 | biostudies-literature
Project description:BackgroundTo date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk.MethodsIn this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery.Results1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes.ConclusionOur competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.
| S-EPMC7997038 | biostudies-literature
Project description:PurposeThis study aims to investigate risk indicators of in-hospital mortality and severity of coronavirus disease-2019 (COVID-19) in patients with diabetes mellitus (DM).MethodsIn this retrospective study, we studied patients with COVID-19 referred to Sina Hospital, Tehran, Iran, from February 20 to May 14, 2020. Patients with either a positive real-time reverse-transcriptase polymerase-chain-reaction test of swab specimens or high clinical suspicion according to the World Health Organization interim guidance were included. We accurately divided all patients into two groups based on diabetes affection and followed-up patients with DM based on incurring death, severe COVID-19, and in-hospital complications.ResultsWe enrolled 574 patients with COVID-19 in the final analysis, of whom 176 (30.7%) patients had DM. In this study, 104 (18.1%) patients deceased, and 380 (66.2%) patients incurred severe COVID-19. We found that COVID-19 patients with DM had a significantly higher mortality rate (P value<0.001), severe disease (P value<0.001), and in-hospital complications (all P values<0.05). Besides that, in patients with DM, admission temperature (odds ratio (OR): 1.69, P value: 0.024), oxygen saturation (OR: 0.92, P value: 0.004), and urea (OR: 1.01, P value: 0.048) were independent risk indicators of in-hospital mortality. In addition, subgroup analysis of diabetic patients based on admission glucose level showed significant differences between these groups regarding acute cardiac injury (P value: 0.044) and acute liver injury (P value: 0.002).ConclusionsPatients with DM admitted with lower oxygen saturation, elevated temperature, and higher urea are more susceptible to progress to more severe COVID-19 and poor prognosis. This indicates a necessity for more precise care during hospitalization for these patients.Supplementary informationThe online version contains supplementary material available at 10.1007/s40200-020-00701-2.
| S-EPMC7788281 | biostudies-literature
Project description:Decreased total CO2 (tCO2) is significantly associated with all-cause mortality in critically ill patients. Because of a lack of data to evaluate the impact of tCO2 in patients with COVID-19, we assessed the impact of tCO2 on all-cause mortality in this study. We retrospectively reviewed the data of hospitalized patients with COVID-19 in two Korean referral hospitals between February 2020 and September 2021. The primary outcome was in-hospital mortality. We assessed the impact of tCO2 as a continuous variable on mortality using the Cox-proportional hazard model. In addition, we evaluated the relative factors associated with tCO2 ≤ 22 mmol/L using logistic regression analysis. In 4,423 patients included, the mean tCO2 was 24.8 ± 3.0 mmol/L, and 17.9% of patients with tCO2 ≤ 22 mmol/L. An increase in mmol/L of tCO2 decreased the risk of all-cause mortality by 4.8% after adjustment for age, sex, comorbidities, and laboratory values. Based on 22 mmol/L of tCO2, the risk of mortality was 1.7 times higher than that in patients with lower tCO2. This result was maintained in the analysis using a cutoff value of tCO2 24 mmol/L. Higher white blood cell count; lower hemoglobin, serum calcium, and eGFR; and higher uric acid, and aspartate aminotransferase were significantly associated with a tCO2 value ≤ 22 mmol/L. Decreased tCO2 significantly increased the risk of all-cause mortality in patients with COVID-19. Monitoring of tCO2 could be a good indicator to predict prognosis and it needs to be appropriately managed in patients with specific conditions.
| S-EPMC10550989 | biostudies-literature
Project description:The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has led to widespread use of hydroxychloroquine and azithromycin despite the lack of conclusive evidence for their safety and efficacy. We evaluated the association between treatment with hydroxychloroquine and/or azithromycin and hospital mortality as the primary outcome. We compared the hospital mortality of patients treated with hydroxychloroquine alone, azithromycin alone, or their combination to the mortality of patients who received neither drug. A logistic multivariate model with overlap weight propensity score was used for estimation of odds ratios (ORs) with 95% confidence intervals (95% CIs). One thousand four hundred and three patients with SARS-CoV-2 infection were admitted to the hospital. At the time of the analysis, the outcome was available for 1376 (98%) of them. Five hundred and eighty-seven patients (42%) received azithromycin and 377 patients (27%) received hydroxychloroquine, alone or in combination. In-hospital mortality was 26%. After the adjusted analysis, azithromycin alone was associated with lower mortality (OR 0.60, 95% CI 0.42-0.85) compared to no treatment. Hydroxychloroquine alone (OR 0.76, 95% CI 0.53-1.08) and the combination of azithromycin and hydroxychloroquine (OR 1.13, 95% CI 0.77-1.69) were not associated with hospital mortality. In this cohort of patients, azithromycin alone was associated with lower hospital mortality but hydroxychloroquine was not associated with increased or reduced mortality. While we await randomized clinical trials, these data support the use of azithromycin in novel coronavirus disease 2019 (COVID-19) and can contribute to better understanding of its role in further meta-analyses.
| S-EPMC7563535 | biostudies-literature
Project description:ObjectiveTo develop predictive models for in-hospital mortality and length of stay (LOS) for coronavirus disease 2019 (COVID-19)-positive patients.Patients and methodsWe performed a multicenter retrospective cohort study of hospitalized COVID-19-positive patients. A total of 764 patients admitted to 14 different hospitals within the Cleveland Clinic from March 9, 2020, to May 20, 2020, who had reverse transcriptase-polymerase chain reaction-proven coronavirus infection were included. We used LightGBM, a machine learning algorithm, to predict in-hospital mortality at different time points (after 7, 14, and 30 days of hospitalization) and in-hospital LOS. Our final cohort was composed of 764 patients admitted to 14 different hospitals within our system.ResultsThe median LOS was 5 (range, 1-44) days for patients admitted to the regular nursing floor and 10 (range, 1-38) days for patients admitted to the intensive care unit. Patients who died during hospitalization were older, initially admitted to the intensive care unit, and more likely to be white and have worse organ dysfunction compared with patients who survived their hospitalization. Using the 10 most important variables only, the final model's area under the receiver operating characteristics curve was 0.86 for 7-day, 0.88 for 14-day, and 0.85 for 30-day mortality in the validation cohort.ConclusionWe developed a decision tool that can provide explainable and patient-specific prediction of in-hospital mortality and LOS for COVID-19-positive patients. The model can aid health care systems in bed allocation and distribution of vital resources.
| S-EPMC8114764 | biostudies-literature
Project description: Not available
| S-EPMC7527144 | biostudies-literature
Project description:It remains unknown to what degree resource prioritization toward SARS-CoV-2 (2019-nCoV) coronavirus (COVID-19) cases had disrupted usual acute care for non-COVID-19 patients, especially in the most vulnerable populations such as patients with schizophrenia. The objective was to establish whether the impact of the COVID-19 pandemic on non-COVID-19 hospital mortality and access to hospital care differed between patients with schizophrenia versus without severe mental disorder. We conducted a nationwide population-based cohort study of all non-COVID-19 acute hospitalizations in the pre-COVID-19 (March 1, 2019 through December 31, 2019) and COVID-19 (March 1, 2020 through December 31, 2020) periods in France. We divided the population into patients with schizophrenia and age/sex-matched patients without severe mental disorder (1:10). Using a difference-in-differences approach, we performed multivariate patient-level logistic regression models (adjusted odds ratio, aOR) with adjustment for complementary health insurance, smoking, alcohol and substance addiction, Charlson comorbidity score, origin of the patient, category of care, intensive care unit (ICU) care, major diagnosis groups and hospital characteristics. A total of 198,186 patients with schizophrenia were matched with 1,981,860 controls. The 90-day hospital mortality in patients with schizophrenia increased significantly more versus controls (aOR = 1.18; p < 0.001). This increased mortality was found for poisoning and injury (aOR = 1.26; p = 0.033), respiratory diseases (aOR = 1.19; p = 0.008) and for both surgery (aOR = 1.26; p = 0.008) and medical care settings (aOR = 1.16; p = 0.001). Significant changes in the case mix were noted with reduced admission in the ICU and for several somatic diseases including cancer, circulatory and digestive diseases and stroke for patients with schizophrenia compared to controls. These results suggest a greater deterioration in access to, effectiveness and safety of non-COVID-19 acute care in patients with schizophrenia compared to patients without severe mental disorders. These findings question hospitals' resilience pertaining to patient safety and underline the importance of developing specific strategies for vulnerable patients in anticipation of future public health emergencies.
| S-EPMC9542474 | biostudies-literature
Project description:ObjectivesThe extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19.DesignThis is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics.SettingShort-term acute care hospitals and critical access hospitals in the USA.ParticipantsHospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021.Intervention/exposurePre-COVID-19 hospital quality.OutcomesRisk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs).ResultsIn-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p<0.0001; 30 days -0.38, p<0.0001). Correlations with in-hospital RSMRs were strongest for patient experience (-0.39, p<0.0001) and timely and effective care (-0.30, p<0.0001) group scores; 30-day RSMRs were strongest for patient experience (-0.34, p<0.0001) and mortality (-0.33, p<0.0001) groups. Patients admitted to 1-star hospitals had higher odds of mortality (in-hospital OR 1.87, 95% CI 1.83 to 1.91; 30-day OR 1.46, 95% CI 1.43 to 1.48) compared with 5-star hospitals. If all hospitals performed like an average 5-star hospital, we estimate 38 000 fewer COVID-19-related deaths would have occurred between April 2020 and September 2021.ConclusionsHospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies.
| S-EPMC10982775 | biostudies-literature
Project description:ObjectiveTo determine the association between chronic kidney disease (CKD) and mortality in persons with a confirmed coronavirus disease 2019 (COVID-19) diagnosis.MethodsCross-sectional secondary baseline study. The study population consisted of 243,065 patients confirmed to have COVID-19 during May-December 2020. Stata 16.0 was used for statistical analysis, Chi-square test was used for bivariate analysis, and Poisson regression with robust variances was used for multiple analysis.ResultsThe prevalence of patients with a confirmed COVID-19 diagnosis who had CKD and died was 1.42 times the prevalence of mortality in those without CKD. The comorbidities combined with CKD that presented the highest probability of mortality were diabetes mellitus and hypertension.ConclusionsCKD is associated with a high mortality rate in patients with a confirmed COVID-19 diagnosis. Patients with CKD, diabetes mellitus, and arterial hypertension have a higher prevalence of mortality than those without comorbidities.
| S-EPMC9205307 | biostudies-literature