ObjectiveTo analyze the influencing factors of acute exacerbation readmission in elderly patients with chronic obstructive pulmonary disease (COPD) within 30 days, construct and validate the risk prediction model.MethodsA total of 1120 elderly patients with COPD in the respiratory department of 13 general hospitals in Ningxia from April 2019 to August 2020 were selected by convenience sampling method and followed up until 30 days after discharge. According to the time of filling in the questionnaire, 784 patients who entered the study first served as the modeling group, and 336 patients who entered the study later served as the validation group to verify the prediction effect of the model.ResultsEducation level, smoking status, number of acute exacerbations of COPD hospitalizations in the past 1 year, regular use of medication, rehabilitation and exercise, nutritional status and seasonal factors were the influencing factors of patients’ readmission to hospital. The risk prediction model was constructed: Z=–8.225–0.310×assignment of education level+0.564×assignment of smoking status+0.873×assignment of number of acute exacerbations of COPD hospitalizations in the past 1 year+0.779×assignment of regular use of medication+0.617×assignment of rehabilitation and exercise +0.970×assignment of nutritional status+assignment of seasonal factors [1.170×spring (0, 1)+0.793×autumn (0, 1)+1.488×winter (0, 1)]. The area under ROC curve was 0.746, the sensitivity was 75.90%, and the specificity was 64.30%. Hosmer-Lemeshow test showed that P=0.278. Results of model validation showed that the sensitivity, the specificity and the accuracy were 69.44%, 85.71% and 81.56%, respectively.ConclusionsEducation level, smoking status, number of acute exacerbations of COPD hospitalizations in the past 1 year, regular use of medication, rehabilitation and exercise, nutritional status and seasonal factors are the influencing factors of patients’ readmission to hospital. The risk prediction model is constructed based on these factor. This model has good prediction effect, can provide reference for the medical staff to take preventive treatment and nursing measures for high-risk patients.
Patient priority evaluation has been studied and applied abroad for a long time, which is a mature theory and widely used in practice now. This article uses the priority, patients, waiting list and criteria as keywords to search Wiley Inter Science, Web of Science, Scopus Pub Med, The Cochrane Library, Science Direct, Springer, and Jstor database (searching time is up to December 2017), to collect relevant indicators for patient admission priority evaluation. In addition, relevant citations and grey literature were searched, and experts from relevant fields in China were consulted to obtain more comprehensive research literature. On this basis, this article describes the concept of patient admission priority evaluation, and describes the meanings of the indicators and the countries of application from the three dimensions of clinical indicators, expected results, and social factors. It is considered that the research and implementation of the evaluation of the priority of patient admission has been relatively many. However, there are only a few related researches in the country and without unity. There is no systematic patient-related priority evaluation. It is necessary to use foreign mature theory research to establish a hospital admission priority evaluation system suitable for China’s national conditions.
Objective To determine the trend in the causes of admission among diabetic patients in West China Hospital from 1996 to 2005. Methods The medical records of diabetic inpatients from January 1996 to December 2005 were retrieved, and half of them were randomly selected. A questionnaire was completed and SPSS13.0 software was used for statistical analyses. Results The most common causes of admission for diabetic patients were diabetic chronic complications (20.2%), infection (19.5%), hyperglycemic symptoms (11.7%), malignant tumor (8.9%) and diabetic acute complications (5.8%). The constituent ratios of diabetic macrovascular disease and malignant tumor as the admission causes tended to increase, while the constituent ratios of diabetic microvascular disease, hyperglycemic symptoms and diabetic acute complications tended to decrease. Infection remained as one of the main causes of admission among diabetic patients. Conclusion The main cause of admission to West China Hospital for diabetic patients from 1996 to 2005 was diabetic chronic complications.
ObjectiveTo explore the distribution of multidrug resistant organism in neonates admitted to the hospital through various ways, and analyze the risk factors in order to avoid cross infection of multidrug resistant organism in neonatology department. MethodsA total of 2 124 neonates were monitored from January 2012 to July 2013, among which 1 119 were admitted from outpatient department (outpatient group), 782 were transferred from other departments (other department group), and 223 were from other hospitals (other hospital group). We analyzed their hospital stays, weight, average length of stay, and drug-resistant strains, and their relationship with nosocomial infection. ResultsAmong the 105 drug-resistant strains, there were 57 from the outpatient group, 27 from the other department group, and 21 from the other hospital group. The positive rate in the patients transferred from other hospitals was the highest (9.42%). Neonates with the hospital stay of more than 14 days and weighing 1 500 g or less were the high-risk groups of drug-resistant strains in nosocomial infection. Drug-resistant strains of nosocomial infection detected in the patients admitted through different ways were basically identical. ConclusionWe should strengthen screening, isolation, prevention and control work in the outpatient neonate. At the same time, we can't ignore the prevention and control of the infection in neonates from other departments or hospitals, especially the prevention and control work in neonates with the hospital stay of more than 14 days and weighing 1 500 g or less to reduce the occurrence of multiple drug-resistant strains cross infection.
ObjectiveTo investigate the influencing factors of unplanned readmission in patients with chronic obstructive pulmonary disease (COPD) within 1 year, construct a risk prediction model and evaluate its effect. MethodsClinical data of 403 inpatients with COPD were continuously collected from January 2023 to May 2023, including 170 cases in the readmission group and 233 cases in the non readmission group. LASSO regression was applied to screen the optimized variables and multivariate logistic regression analyses were applied to explore the risk factors of unplanned readmission in patients with COPD within 1 year. After that a nomogram prediction model was constructed and evaluated its discrimination, calibration, and clinical applicability. ResultsThe incidence of unplanned readmission in patients with COPD within 1 year was 42.2%. Respiratory failure, number of acute exacerbation in the last year, creatinine and white blood cell count were risk factors for unplanned admission of patients with COPD within one year (P<0.05). Creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid were included in the nomogram model, the area under curve (AUC) and its 95% confidential interval (CI) of the nomogram model was 0.687 (0.636 - 0.739), with the sensitivity, specificity, and accuracy were 0.824, 0.742 and 0.603, respectively. The AUC of the nomogram after re-sampling 1 000 times was 0.687 (0.634 - 0.739). The calibration curve showed a high degree of three line overlap and the clinical decision curve showed that the nomogram model provided better net benefits than the treat-all tactics or the treat-none tactics with threshold probabilities of 15.0% - 55.0%. ConclusionThe nomogram model constructed based on creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid has good predictive value for unplanned readmission in patients with COPD within 1 year.
Objective To investigate the impact of nutritional risk on unplanned readmissions in elderly patients with chronic obstructive pulmonary disease (COPD), to provide evidence for clinical nutrition support intervention. Methods Elderly patients with COPD meeting the inclusive criteria and admitted between June 2014 and May 2015 were recruited and investigated with nutritional risk screening 2002 (NRS 2002) and unplanned readmission scale. Meanwhile, the patients’ body height and body weight were measured for calculating body mass index (BMI). Results The average score of nutritional risk screening of the elderly COPD patients was 4.65±1.33. There were 456 (40.07%) patients who had no nutritional risk and 682 (59.93%) patients who had nutritional risk. There were 47 (4.13%) patients with unplanned readmissions within 15 days, 155 (13.62%) patients within 30 days, 265 (23.28%) patients within 60 days, 336 (29.53%) patients within 180 days, and 705 (61.95%) patients within one year. The patients with nutritional risk had significantly higher possibilities of unplanned readmissions within 60 days, 180 days and one year than the patients with no nutritional risk (all P<0.05). The nutritional risk, age and severity of disease influenced unplanned readmissions of the elderly patients with COPD (all P<0.05). Conclusions There is a close correlation between nutritional risk and unplanned readmissions in elderly patients with COPD. Doctors and nurses should take some measures to reduce the nutritional risk so as to decrease the unplanned readmissions to some degree.
The implantation of left ventricular assist device (LVAD) has significantly improved the quality of life for patients with end-stage heart failure. However, it is associated with the risk of complications, with unplanned readmissions gaining increasing attention. This article reviews the influencing factors, prediction methods and models, and intervention measures for unplanned readmissions in LVAD patients, aiming to provide scientific guidance for clinical practice, assist healthcare professionals in accurately assessing patients' conditions, and develop rational care plans.