Investigating Key Factors Related to the Decision of a Do-Not-Resuscitate Consent

Sociodemographic Factors Associated with Do-Not-Resuscitate Order Utilization in the Surgical Intensive Care Unit: An Observational Study

The use of a do-not-resuscitate (DNR) order is a powerful tool in outlining end-of-life care. This study explores sociodemographic factors associated with selection of a DNR order and assigning a healthcare proxy in the Surgical Intensive Care Unit (SICU). A retrospective chart review of 312 patients who expired in the SICU over a 7-year period was conducted. We analyzed the association of sociodemographic factors to selection of a DNR order and assignment of a healthcare proxy. Year of admission, age, religion, and proxy were independently associated with selection of DNR. In particular, the relative chance of a DNR selection in 2019 compared to 2012 was 3.538 (95% CL = 2.001-6.255, P < .01). There are significant sociodemographic factors that influence DNR utilization, highlighting the need to consider the social and religious backgrounds when engaging patients and their families in end-of-life care. Future studies will need to be conducted on whether these sociodemographic factors influence surviving patients as this study's findings can only be applied to those who have expired.

Analysis of Palliative Care Utilization and Medical Expenses among Patients with Chronic Diseases in Taiwan: A Population-Based Cohort Study

Palliative care (PC) is an important alternative treatment for patients with chronic diseases, particularly for those in the later stages of disease progression. This is because these diseases are often irreversible, with progressive worsening of symptoms. By encouraging the use of tranquility resources for good death and spiritual relief, PC can reduce the physical and psychological burden on patients at the end of their lives. Currently, most discussions on PC have focused on patients with cancers, and few have further discussed the differences in medical expenses between PC and emergency treatment in patients with chronic diseases at the end of their lives. This study analyzed the top three chronic diseases in patients who used PC resources in the past decade and identified the impact of emergency treatment on mean survival time and medical expenses based on the medical records from the National Health Insurance Research Database. In total, 4061 patients with chronic diseases who were admitted to hospice wards were included in this study; of them, 85 patients still received emergency treatment, including urinary catheterization, nasogastric intubation, and respirator use, at the end of their lives. The mean survival time of patients aged 50-64 years who received emergency treatment was longer than that of the same age group who did not receive emergency treatment. Different comparisons of the mean survival time and medical expenses using real-world data provides important insights regarding PC management that may assist in establishing health policies in the future.

Epidemiological characteristics of severe fever with thrombocytopenia syndrome and its relationship with meteorological factors in Liaoning Province, China

Background

Severe fever with thrombocytopenia syndrome (SFTS), one kind of tick-borne acute infectious disease, is caused by a novel bunyavirus. The relationship between meteorological factors and infectious diseases is a hot topic of current research. Liaoning Province has reported a high incidence of SFTS in recent years. However, the epidemiological characteristics of SFTS and its relationship with meteorological factors in the province remain largely unexplored.

Methods

Data on reported SFTS cases were collected from 2011 to 2019. Epidemiological characteristics of SFTS were analyzed. Spearman’s correlation test and generalized linear models (GLM) were used to identify the relationship between meteorological factors and the number of SFTS cases.

Results

From 2011 to 2019, the incidence showed an overall upward trend in Liaoning Province, with the highest incidence in 2019 (0.35/100,000). The incidence was slightly higher in males (55.9%, 438/783), and there were more SFTS patients in the 60–69 age group (31.29%, 245/783). Dalian City and Dandong City had the largest number of cases of SFTS (87.99%, 689/783). The median duration from the date of illness onset to the date of diagnosis was 8 days [interquartile range (IQR): 4–13 days]. Spearman correlation analysis and GLM showed that the number of SFTS cases was positively correlated with monthly average rainfall (r_s = 0.750, P < 0.001; β = 0.285, P < 0.001), monthly average relative humidity (r_s = 0.683, P < 0.001; β = 0.096, P < 0.001), monthly average temperature (r_s = 0.822, P < 0.001; β = 0.154, P < 0.001), and monthly average ground temperature (r_s = 0.810, P < 0.001; β = 0.134, P < 0.001), while negatively correlated with monthly average air pressure (r_s = −0.728, P < 0.001; β = −0.145, P < 0.001), and monthly average wind speed (r_s = −0.272, P < 0.05; β = −1.048, P < 0.001). By comparing both correlation coefficients and regression coefficients between the number of SFTS cases (dependent variable) and meteorological factors (independent variables), no significant differences were observed when considering immediate cases and cases with lags of 1 to 5 weeks for dependent variables. Based on the forward and backward stepwise GLM regression, the monthly average air pressure, monthly average temperature, monthly average wind speed, and time sequence were selected as relevant influences on the number of SFTS cases.

Conclusion

The annual incidence of SFTS increased year on year in Liaoning Province. Incidence of SFTS was affected by several meteorological factors, including monthly average air pressure, monthly average temperature, and monthly average wind speed.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05395-4.

The Impact of Signing Do-Not-Resuscitate Orders on the Use of Non-Beneficial Life-Sustaining Treatments for Intensive Care Unit Patients: A Retrospective Study

Background: Intensive care medical technology increases the survival rate of critically ill patients. However, life-sustaining treatments also increase the probability of non-beneficial medical treatments given to patients at the end of life. Objective: This study aimed to analyse whether patients with a do-not-resuscitate (DNR) order were more likely to be subject to the withholding of cardiac resuscitation and withdrawal of life-sustaining treatment in the ICU. Methods: This retrospective study collected data regarding the demographics, illness conditions, and life-sustaining treatments of ICU patients who were last admitted to the ICU between 1 January 2016 and 31 December 2017, as determined by the hospital’s electronic medical dataset. Results: We identified and collected data on 386 patients over the two years; 319 (82.6%) signed a DNR before the end. The study found that DNR patients were less likely to receive cardiac resuscitation before death than non-DNR patients. The cardiac resuscitation treatments included chest compressions, electric shock, and cardiotonic drug injections (p < 0.001). However, the life-sustaining treatments were withdrawn for only a few patients before death. The study highlights that an early-documented DNR order is essential. However, it needs to be considered that promoting discussions of time-limited trials might be the solution to helping ICU terminal patients withdraw from non-beneficial life-sustaining treatments.

Exploratory Study of Palliative Care Utilization and Medical Expense for Inpatients at the End-of-Life

Background: Previous research mostly analyzed the utilization of palliative care for patients with cancer, and data regarding non-cancer inpatients are limited. Objectives: This research aimed to investigate the current situation regarding palliative care and the important factors that influence its utilization by inpatients (including inpatients with and without cancer) at the end of their lives. We also explored the feasibility of establishing a prediction model of palliative care utilization for inpatients at the end of their lives. These findings will allow medical staff to monitor and focus on those who may require palliative care, resulting in more end-of-life patients receiving palliative care and thereby reducing medical expense and improving their quality of life. Methods: This was a retrospective study based on real-world health information system (HIS) data from 5 different branches of Taipei City Hospital between 1 January 2018 and 31 December 2018 that enrolled a total of 1668 deceased inpatients. To explore palliative care utilization at the end of life, we used 5-fold cross-validation in four different statistical models to obtain the performance of predictive accuracy: logistic regression (LGR), classification and regression tree (CART), multivariate adaptive regression spline (MARS), and gradient boosting (GB). The important variables that may affect palliative care utilization by inpatients were also identified. Results: The results were as follows: (1) 497 (29.8%) inpatients received palliative care; (2) the average daily hospitalization cost of patients with cancer who received palliative care (NTD 5789 vs. NTD 12,115; p ≤ 0.001) and all patients who received palliative care (NTD 91,527 vs. NTD 186,981; p = 0.0037) were statistically significantly lower than patients who did not receive palliative care; (3) diagnosis, hospital, and length of stay (LOS) may affect palliative care utilization of inpatient; diagnosis, hospitalization unit, and length of hospitalization were statistically significant by LGR; (4) 51.5% of patients utilized palliative consultation services, and 48.5% utilized palliative care units; and (5) MARS had the most consistent results; its accuracy was 0.751, and the main predictors of palliative care utilization are hospital, medical expense, LOS, diagnosis, and Palliative Care Screening Tool-Taiwan version (TW-PCST) scores. Conclusions: The results reveal that palliative care utilization by inpatients remains low, and it is necessary to educate patients without cancer of the benefits and advantages of palliative care. Although data were limited, the predictability of the MARS model was 0.751; a better prediction model with more data is necessary for further research. Precisely predicting the need for palliative care may encourage patients and their family members to consider palliative care, which may balance both physical and mental care. Therefore, unnecessary medical care can be avoided and limited medical resources can be allocated to more patients in need.

The association between hypertriglyceridemic-waist phenotype and chronic kidney disease: a cohort study and meta-analysis

Evidence on the association between hypertriglyceridemic-waist phenotype (HTGW) and chronic kidney disease (CKD) is limited and inconsistent. We aimed to explore such association among 7406 Chinese aged ≥ 45 years in a cohort setting, followed by a meta-analysis. Participants were categorized into four phenotypes: NTNW (normal triglycerides and normal waist circumference), NTGW (isolated enlarged waist circumference), HTNW (isolated high triglycerides), and HTGW (high triglycerides and enlarged waist circumference). We used multivariate logistic regression to determine the association between different phenotypes and risk of CKD in the cohort study. For meta-analysis, we searched relevant studies from Embase, Medline, PubMed, and Web of Science from dataset inception up to May 1, 2021. A random-effect model was used to estimate the pooled effect and I² statistic was applied to evaluate heterogeneity. In the cohort study, compared to the NTNW phenotype, HTGW (OR 1.82, 95% CI 1.32 to 2.51, p < 0.01) and NTGW (OR 1.48, 95% CI 1.13 to 1.94, p = 0.004) were significantly associated with CKD risk after 4 years follow-up, but not for the HTNW phenotype. The meta-analysis also showed a positive association between HTGW phenotype and CKD risk (pooled OR 1.53, 95% CI 1.31 to 1.79, I² = 62.4%). Assessment of triglyceridemic-waist phenotypes might help to identify individuals with high-risk of developing CKD.