ABSTRACT
PURPOSE: Our study aimed to evaluate the effectiveness of the nursing care program on the incidence and rate of 28-day hospital readmissions among pulmonary tuberculosis (TB) patients. METHODS: We conducted a quasi-experimental study using a historical control (usual care) group. Patients diagnosed with pulmonary TB who received nursing interventions between January 28, 2021, and May 31, 2021, were categorized as an intervention group, whereas historical controls were selected from January 1, 2020, to December 31, 2020. The primary outcomes were the incidence and rates of hospital readmissions within 28 days due to TB-related complications. The secondary outcome was the change in knowledge and self-care behavior scores at discharge and 28 days postdischarge. Cox models were used to assess the intervention's impact on the incidence of hospital readmission. Rates of readmission were compared by the Poisson model. Both Cox and Poisson models were adjusted for age, sex, sputum smears at diagnosis, serum albumin level, and diabetes mellitus at baseline. RESULTS: Among 104 pulmonary TB patients included in the analysis (68 were in a historical control group and 36 were in an intervention group), 20 patients were readmitted due to TB-related complications. We found that our nursing care program resulted in a significant reduction in the incidence (adjusted hazard ratio was 0.16 [95% CI 0.03, 0.87]) and the rate of hospital readmissions (adjusted incidence rate ratio was 0.22 [95% CI 0.06, 0.85]). Furthermore, nursing interventions significantly improved knowledge and self-care behavior scores with significant score retention at 28 days postdischarge. CONCLUSIONS: The nursing care program can significantly decrease the incidence and rate of 28-day hospital readmission and improve knowledge and self-care behavior scores in pulmonary TB patients.
Subject(s)
Diabetes Mellitus , Patient Readmission , Humans , Patient Discharge , Aftercare , Incidence , Retrospective StudiesABSTRACT
Background: Mortality from multidrug-resistant (MDR) pathogens is an urgent healthcare crisis worldwide. At present we do not have any simplified screening tools to predict the risk of mortality associated with MDR infections. The aim of this study was to develop a screening tool to predict mortality in patients with multidrug-resistant organisms. Methods: A retrospective cohort study to evaluate mortality risks in patients with MDR infections was conducted at Phrae Hospital. Univariable and multivariable analyses were used to classify possible risk factors. The model performance was internally validated utilizing the mean of three measures of discrimination corrected by the optimism using a 1000-bootstrap procedure. The coefficients were transformed into item scores by dividing each coefficient with the lowest coefficient and then rounding to the most adjacent number. The area under the receiver operating characteristic curve (AuROC) was used to determine the performance of the model. Results: Between 1 October 2018 and 30 September 2020, a total of 504 patients with MDR infections were enrolled. The ICU-SEPSA score composed of eight clinical risk factors: 1) immunocompromised host, 2) chronic obstructive pulmonary disease, 3) urinary tract infection, 4) sepsis, 5) placement of endotracheal tube, 6) pneumonia, 7) septic shock, and 8) use of antibiotics within the past 3 months. The model showed good calibration (Hosmer-Lemeshow χ2 = 19.27; p-value = 0.50) and good discrimination after optimism correction (AuROC 84.6%, 95% confidence interval [Cl]: 81.0%-88.0%). The positive likelihood ratio of low risk (score ≤ 5) and high risk (score ≥ 8) were 2.07 (95% CI: 1.74-2.46) and 12.35 (95% CI: 4.90-31.13), respectively. Conclusion: A simplified predictive scoring tool wad developed to predict mortality in patients with MDR infections. Due to a single-study design of this study, external validation of the results before applying in other clinical practice settings is warranted.
ABSTRACT
BACKGROUND: Septic shock is a serious condition leading to increased mortality. Despite previous report of no benefit, thiamine has emerged as potential therapy to reduce mortality in septic shock patients. This study aimed to investigate the effect of thiamine in mortality rate in patients with septic shock. METHODS: Eight databases, including MEDLINE, EMBASE, Science Direct, Scopus, Cochrane, CINAHL, Open Grey, and Dart-Europe, were systematically searched from the inception of the database up to August 21, 2020. Studies evaluating the effectiveness of thiamine on mortality rate in septic shock patients compared between thiamine and placebo were included. We used random-effects model to analyze the mortality with risk ratio (RR) and 95% confidence interval (95% CI). The subgroup and sensitivity analysis were performed to examine the influence of variables. Publication bias was considered using funnel plot, Begg's test, and Egger's test. RESULTS: A total of 3,658 studies were retrieved and reviewed. Five studies were included for meta-analysis. In random-effects meta-analysis of the randomized controlled trials, although not statistically significant, there was a trend which suggested that thiamine may reduce mortality rate in septic shock patients (RR, 0.96; 95% CI: 0.72-1.28, P = 0.774). The result of sensitivity and subgroup analyses also supported the suggestion that thiamine may decrease mortality in septic shock patients. The Begg's test (P = 0.624) and Egger's test (P = 0.777) revealed no publication bias. CONCLUSIONS: Although not statistically significant, thiamine may reduce mortality rate in septic shock patients. Further prospective studies with larger sample size are warranted.
