ABSTRACT
BACKGROUND@#Red-cell transfusion is critical for surgery during the peri-operative period; however, the transfusion threshold remains controversial mainly owing to the diversity among patients. The patient's medical status should be evaluated before making a transfusion decision. Herein, we developed an individualized transfusion strategy using the West-China-Liu's Score based on the physiology of oxygen delivery/consumption balance and designed an open-label, multicenter, randomized clinical trial to verify whether it reduced red cell requirement as compared with that associated with restrictive and liberal strategies safely and effectively, providing valid evidence for peri-operative transfusion.@*METHODS@#Patients aged >14 years undergoing elective non-cardiac surgery with estimated blood loss > 1000 mL or 20% blood volume and hemoglobin concentration <10 g/dL were randomly assigned to an individualized strategy, a restrictive strategy following China's guideline or a liberal strategy with a transfusion threshold of hemoglobin concentration <9.5 g/dL. We evaluated two primary outcomes: the proportion of patients who received red blood cells (superiority test) and a composite of in-hospital complications and all-cause mortality by day 30 (non-inferiority test).@*RESULTS@#We enrolled 1182 patients: 379, 419, and 384 received individualized, restrictive, and liberal strategies, respectively. Approximately 30.6% (116/379) of patients in the individualized strategy received a red-cell transfusion, less than 62.5% (262/419) in the restrictive strategy (absolute risk difference, 31.92%; 97.5% confidence interval [CI]: 24.42-39.42%; odds ratio, 3.78%; 97.5% CI: 2.70-5.30%; P <0.001), and 89.8% (345/384) in the liberal strategy (absolute risk difference, 59.24%; 97.5% CI: 52.91-65.57%; odds ratio, 20.06; 97.5% CI: 12.74-31.57; P <0.001). No statistically significant differences were found in the composite of in-hospital complications and mortality by day 30 among the three strategies.@*CONCLUSION@#The individualized red-cell transfusion strategy using the West-China-Liu's Score reduced red-cell transfusion without increasing in-hospital complications and mortality by day 30 when compared with restrictive and liberal strategies in elective non-cardiac surgeries.@*TRIAL REGISTRATION@#ClinicalTrials.gov, NCT01597232.
Subject(s)
Humans , Adult , Postoperative Complications , Erythrocyte Transfusion/adverse effects , Blood Transfusion , Hospitals , Hemoglobins/analysisABSTRACT
Objective:To establish a IgA nephropathy (IgAN) standard dataset for the structured and standardization of IgAN clinical information, which will be beneficial to the integration and utilization of clinical information among different medical institutions. Therefore, the IgAN Expert Collaboration Group composed the "IgA Nephropathy Standard Dataset".Methods:Referring to the domestic information standards, guidelines, data standard and consensus of related fields, based on electronic medical history, the patient identification number was used as the primary key of the system to collect information. By standardizing each data element in the data set, the standardization of the management system in data and information exchange, data collaboration and sharing was ensured, and a quality control system was developed.Results:This standard dataset included 607 data elements and 8 business domains, which were patient information, medical history information, physical examination, laboratory examination, assistant examination, renal pathology, drug treatment, and follow-up, respectively. Each module was composed of module name, data element name, English name, definition, range, reference standard, etc. At the same time, a corresponding quality control system was formulated to evaluate data quality from multiple dimensions such as completeness, standardization, accuracy, timeliness, and security for ensuring the high quality and security of the data.Conclusion:The IgAN standard dataset is established, which will contribute to the structuration and standardization of clinical information of IgAN patients.
ABSTRACT
BackgroundChina has experienced an outbreak of a novel human coronavirus (SARS-CoV-2) since December 2019, which quickly became a worldwide pandemic in early 2020. There is limited evidence on the mortality risk effect of pre-existing comorbidities for coronavirus disease 2019 (COVID-19), which has important implications for early treatment. ObjectiveEvaluate the risk of pre-existing comorbidities on COVID-19 mortality, and provide clinical suggestions accordingly. MethodThis study used a nested case-control design. A total of 94 publicly reported deaths in locations outside of Hubei Province, China, between December 18th, 2019 and March 8th, 2020 were included as cases. Each case was matched with up to three controls, based on gender and age {+/-} 1 year old (94 cases and 181 controls). The inverse probability weighted Cox proportional hazard model was performed. ResultsHistory of comorbidities significantly increased the death risk of COVID-19: one additional pre-existing comorbidity led to an estimated 40% higher risk of death (p<0.001). The estimated mortality risk in patients with CHD was three times of those without CHD (p<0.001). The estimated 30-day survival probability for a profile patient with pre-existing CHD (65-year-old female with no other comorbidities) was 0.53 (95% CI [0.34-0.82]), while it was 0.85 (95% CI [0.79-0.91]) for those without CHD. Older age was also associated with increased death risk: every 5-year increase in age was associated with a 20% increased risk of mortality (p<0.001). ConclusionExtra care and early medical intervention are needed for patients with pre-existing comorbidities, especially CHD.
ABSTRACT
We extend the shared frailty model of recurrent events and a dependent terminal event to allow for a nonparametric covariate function. We include a Gaussian random effect (frailty) in the intensity functions of both the recurrent and terminal events to capture correlation between the two processes. We employ the penalized cubic spline method to describe the nonparametric covariate function in the recurrent events model. We use Laplace approximation to evaluate the marginal penalized partial likelihood without a closed form. We also propose the variance estimates for regression coefficients. Numerical analysis results show that the proposed estimates perform well for both the nonparametric and parametric components. We apply this method to analyze the hospitalization rate of patients with heart failure in the presence of death.
