Objective: To estimate and compare the burdens of opportunistic infections and herpes zoster in real-world practice among patients with various systemic rheumatic diseases. Methods: This 13-year cohort study used national health insurance data to compare the incidence rates (IRs) of nine opportunistic infections among patients with five rheumatic diseases. The analyses were stratified according to follow-up duration using Poisson regression, and Cox models were used to compare the risk of first opportunistic infection. Results: During 2000–2013, we identified 76,966 patients who had polymyositis/dermatomyositis (PM/DM, 2270 cases), systemic lupus erythematosus (SLE, 15,961 cases), systemic sclerosis (SSc, 2071 cases), rheumatoid arthritis (RA, 38,355 cases), or primary Sjögren’s syndrome (pSS, 18,309 cases). The IR of opportunistic infections was highest for PM/DM cases (61.3/1000 person-years, 95% confidence interval [CI] 56.6–66.2), followed by SLE cases (43.1/1000 person-years, 95% CI 41.7–44.5), SSc cases (31.6/1000 person-years, 95% CI 28.3–35.1), RA cases (25.0/1000 person-years, 95% CI 24.4–25.7), and pSS cases (24.1/1000 person-years, 95% CI 23.1–25.2). Multivariable Cox analysis revealed that, relative to SLE, PM/DM was associated with a significantly higher risk of opportunistic infections (hazard ratio 1.18, 95% CI 1.08–1.29). The risk of opportunistic infections was highest during the first year after the diagnosis of all five rheumatic diseases. Conclusions: The risk of opportunistic infection was highest for PM/DM, followed by SLE, SSc, RA, and pSS. Careful observation and preventive therapy for opportunistic infections may be warranted in selected PM/DM patients, especially during the first year after the diagnosis.

Background and Objectives: In the intensive care unit (ICU), renal failure and respiratory failure are two of the most common organ failures in patients with systemic inflammatory response syndrome (SIRS). These clinical symptoms usually result from sepsis, trauma, hypermetabolism or shock. If this syndrome is caused by septic shock, the Surviving Sepsis Campaign Bundle suggests that vasopressin be given to maintain mean arterial pressure (MAP) > 65 mmHg if the patient is hypotensive after fluid resuscitation. Nevertheless, it is important to note that some studies found an effect of various mean arterial pressures on organ function; for example, a MAP of less than 75 mmHg was associated with the risk of acute kidney injury (AKI). However, no published study has evaluated the risk factors of mortality in the subgroup of acute kidney injury with respiratory failure, and little is known of the impact of general risk factors that may increase the mortality rate. Materials and Methods: The objective of this study was to determine the risk factors that might directly affect survival in critically ill patients with multiple organ failure in this subgroup. We retrospectively constructed a cohort study of patients who were admitted to the ICUs, including medical, surgical, and neurological, over 24 months (2015.1 to 2016.12) at Chiayi Chang Gung Memorial Hospital. We only considered patients who met the criteria of acute renal injury according to the Acute Kidney Injury Network (AKIN) and were undergoing mechanical ventilator support due to acute respiratory failure at admission. Results: Data showed that the overall ICU and hospital mortality rate was 63.5%. The most common cause of ICU admission in this cohort study was cardiovascular disease (31.7%) followed by respiratory disease (28.6%). Most patients (73%) suffered sepsis during their ICU admission and the mean length of hospital stay was 24.32 ± 25.73 days. In general, the factors independently associated with in-hospital mortality were lactate > 51.8 mg/dL, MAP ≤ 77.16 mmHg, and pH ≤ 7.22. The risk of in-patient mortality was analyzed using a multivariable Cox regression survival model. Adjusting for other covariates, MAP ≤ 77.16 mmHg was associated with higher probability of in-hospital death [OR = 3.06 (1.374–6.853), p = 0.006]. The other independent outcome predictor of mortality was pH ≤ 7.22 [OR = 2.40 (1.122–5.147), p = 0.024]. Kaplan-Meier survival curves were calculated and the log rank statistic was highly significant. Conclusions: Acute kidney injury combined with respiratory failure is associated with high mortality. High mean arterial pressure and normal blood pH might improve these outcomes. Therefore, the acid–base status and MAP should be considered when attempting to predict outcome. Moreover, the blood pressure targets for acute kidney injury in critical care should not be similar to those recommended for the general population and might prevent mortality.

End-stage renal disease (ESRD) patients experience oxidative stress due to excess exogenous or endogenous oxidants and insufficient antioxidants. Hence, oxidative stress and inflammation cause endothelial damage, contributing to vascular dysfunction and atherosclerosis. Therefore, ESRD patients suffer more cardiovascular and hospitalization events than healthy people. This study aims to test the correlations between ROS, SOD3, IL-2, IL-6, and IL-18 and the first kidney disease-related hospitalization or death events in ESRD patients undergoing regular hemodialysis. A total of 212 participants was enrolled, including 45 normal healthy adults and 167 ESRD patients on regular dialysis. Blood samples from all participants were collected for ROS, SOD3, IL-2, IL-6, and IL-18 measurement at the beginning of the study, and every kidney disease-related admission or death was recorded for the next year. Multivariate analysis was conducted by fitting a linear regression model, logistic regression model, and Cox proportional hazards model to estimate the adjusted effects of risk factors, prognostic factors, or predictors on continuous, binary, and survival outcome data. The results showed that plasma SOD3 and serum IL-18 were two strong predictors of the first kidney disease-related hospitalization or death. In the Cox proportional hazards models (run in R), higher IL-18 concentration (>69.054 pg/mL) was associated with a hazard ratio of 3.376 for the first kidney disease-related hospitalization or death (95% CI: 1.2644 to 9.012), while log(SOD3) < 4.723 and dialysis clearance (Kt/V; 1.11 < value < 1.869) had a hazard ratio = 0.2730 (95% CI: 0.1133 to 0.6576) for reducing future kidney disease-related hospitalization or death. Other markers, including body mass index (BMI), transferrin saturation, total iron binding capacity, and sodium and alkaline phosphate, were also found to be significant in our study. These results reveal the new predictors SOD3 and IL-18 for the medical care of end-stage renal disease patients.

This study evaluated the effect of early anti-tumor necrosis factor (TNF) therapy in patients with severe rheumatoid arthritis (RA) on the subsequent risk of total knee replacement (TKR) surgery. This retrospective observational study included a hospital-based cohort of 200 patients diagnosed with severe RA who received treatment with anti-TNF therapy between 2003 and 2014. Clinical parameters including age, sex, body mass index, and the time from the diagnosis of RA to the initiation of anti-TNF therapy were analyzed. Of the 200 enrolled patients, 84 underwent an early intervention (≤3 years from the diagnosis of RA to the initiation of anti-TNF therapy), and 116 underwent a late intervention(>3 years from the diagnosis of RA to the initiation of anti-TNF therapy). Five (6.0%) patients in the early intervention group underwent TKR compared to 31 (26.7%) in the late intervention group (p = 0.023). After adjusting for confounding factors, the late intervention group still had a significantly higher risk of TKR (p = 0.004; odds ratio, 5.572; 95% confidence interval, 1.933–16.062). Those receiving treatment including methotrexate had a lower risk of TKR (p = 0.004; odds ratio, 0.287; 95% confidence interval, 0.122–0.672). Delayed initiation of anti-TNF therapy in the treatment of severe RA was associated with an increased risk of TKR surgery. Adding methotrexate treatment decreased the risk of future TKR.