The ratio and difference of urine protein-to-creatinine ratio and albumin-to-creatinine ratio facilitate risk prediction of all-cause mortality.

The role of the difference and ratio of albuminuria (urine albumin-to-creatinine ratio, uACR) and proteinuria (urine protein-to-creatinine ratio, uPCR) has not been systematically evaluated with all-cause mortality. We retrospectively analyzed 2904 patients with concurrently measured uACR and uPCR from the same urine specimen in a tertiary hospital in Taiwan. The urinary albumin-to-protein ratio (uAPR) was derived by dividing uACR by uPCR, whereas urinary non-albumin protein (uNAP) was calculated by subtracting uACR from uPCR. Conventional severity categories of uACR and uPCR were also used to establish a concordance matrix and develop a corresponding risk matrix. The median age at enrollment was 58.6 years (interquartile range 45.4-70.8). During the 12,391 person-years of follow-up, 657 deaths occurred. For each doubling increase in uPCR, uACR, and uNAP, the adjusted hazard ratios (aHRs) of all-cause mortality were 1.29 (95% confidence interval [CI] 1.24-1.35), 1.12 (1.09-1.16), and 1.41 (1.34-1.49), respectively. For each 10% increase in uAPR, it was 1.02 (95% CI 0.98-1.06). The linear dose-response association with all-cause mortality was only observed with uPCR and uNAP. The 3 × 3 risk matrices revealed that patients with severe proteinuria and normal albuminuria had the highest risk of all-cause mortality (aHR 5.25, 95% CI 1.88, 14.63). uNAP significantly improved the discriminative performance compared to that of uPCR (c statistics: 0.834 vs. 0.828, p-value = 0.032). Our study findings advocate for simultaneous measurements of uPCR and uACR in daily practice to derive uAPR and uNAP, which can provide a better mortality prognostic assessment.

Long-term exposure to fine particulate matter and osteoporotic fracture: A case-control study in Taiwan.

Few studies have explored the relationship between long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 µm (PM2.5) and osteoporotic fracture, particularly in high PM2.5 level areas. The aim of this study was to assess the association between long-term exposure to PM2.5 and osteoporotic fracture. We performed a matched case-control study of 16,175 participants obtained from a hospital registry during 2005-2014 in Taiwan. A major osteoporotic fracture was defined as a fracture of the spine, hip, proximal humerus, and forearm. We applied satellite-based spatiotemporal models with 1-km resolution to individually calculate the 1-year average PM2.5 concentration before the index date which was defined as the first visit date for the osteoporotic fracture. Logistic regression models with and without potential confounding factors were used to estimate odds ratios (OR) and 95% confidence intervals (CI) between PM2.5 and osteoporotic fracture, whereas a restricted cubic spline model was used to estimate the dose-response relationship. The sample's median age was 44.7 years (interquartile range: 30.7, 63.1 years). We observed that long-term PM2.5 exposure was associated with osteoporotic fracture, the OR was 1.12 (95% CI: 1.03, 1.22) per 10-µg/m3 increase in PM2.5 in women. In the dose-response association, the OR of osteoporotic fracture was significantly increased for PM2.5 exposures more than 41 µg/m3. We did not find a significant association between PM2.5 (per 10-µg/m3 increase) and osteoporotic fracture among overall population (adjusted OR, 1.02 [95% CI, 0.97 to 1.08]) and men (adjusted OR, 0.94 [95% CI, 0.86 to 1.02]). The results of the stratified analysis showed that women were more sensitive to the adverse impact of PM2.5 that were men, and evidence was obtained of sex-based effect modification (P for interaction = 0.002). Our findings suggest that long-term exposure to PM2.5 is associated with osteoporotic fracture, particularly among women.

Particulate Air Pollution and Progression to Kidney Failure With Replacement Therapy: An Advanced CKD Registry-Based Cohort Study in Taiwan.

RATIONALE & OBJECTIVE: Limited evidence concerns fine particulate matter (with aerodynamic diameter ≤ 2.5µm [PM2.5]) exposure and the risk for kidney failure with replacement therapy (KFRT). This study assessed whether PM2.5 exposure was associated with progression of chronic kidney disease (CKD) to KFRT. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 6,628 adult patients with CKD were recruited from the Advanced CKD Program in Taiwan between 2003 and 2015. EXPOSURE: Satellite-based spatiotemporal models were used to calculate each individual's 1-year PM2.5 exposure before the date of enrollment into the Advanced CKD Program. OUTCOMES: Time to KFRT (defined as initiation of maintenance hemodialysis, peritoneal dialysis, or kidney transplantation) and time to all-cause mortality. ANALYTICAL APPROACH: Multivariable proportional hazard regression analyses were used to estimate the association of PM2.5 with KFRT and all-cause mortality. Restricted cubic splines were used to explore dose-response relationships. RESULTS: The study population included 6,628 adult patients with CKD who were aged 20 to 90 years. 941 KFRT events and 1,653 deaths occurred during follow-up. The adjusted HR for progression to KFRT was 1.19 (95% CI, 1.08-1.31) per 7.8µg/m3 greater PM2.5, an amount spanning the interquartile range. There was evidence of a dose-response relationship (adjusted HRs of 1.16 [95% CI, 0.90-1.51], 1.19 [95% CI, 0.94-1.52], and 1.42 [95% CI, 1.12-1.80] for low, medium, and high PM2.5 levels). There was no significant association between PM2.5 and all-cause mortality (adjusted HR, 1.01 [95% CI, 0.95-1.08]). LIMITATIONS: Misclassification of PM2.5 exposure assessment and the potential for residual confounding. CONCLUSIONS: Our findings suggest that long-term exposure to PM2.5 is associated with increased risk for progression to KFRT in patients with CKD.

24-hour Serum Creatinine Variation Associates with Short- and Long-Term All-Cause Mortality: A Real-World Insight into Early Detection of Acute Kidney Injury.

Real-world evidence describing the variation in serum creatinine (S-Cre) within 24 hours and its prognostic value is unknown. We enrolled 14 912 adults who received two S-Cre measurements within 24 hours at a tertiary hospital between 2003 and 2016. The study population was divided into four groups according to the hospital service settings where the baseline and second S-Cre were measured: Group 1, Outpatient-to-Outpatient; Group 2, Outpatient-to-ED (emergency department) or Inpatient; Group 3, ED-to-ED or Inpatient; and Group 4, Inpatient-to-Inpatient. The main predictors were the difference between the two S-Cre measurements (ΔS-Cre) and the percent change (ΔS-Cre%). The main outcomes were 30-day, 1-year, or 3-year all-cause mortality. A total of 6753 and 8159 patients with an increase and a decrease within-day ΔS-Cre, respectively. Among 6753 patients who had deteriorating ΔS-Cre or ΔS-Cre%, the adjusted hazard ratio (aHR) for 1-year all-cause mortality for each 0.1 mg/dL or 5% change in S-Cre was 1.09 (95% confidence interval [CI]: 1.07, 1.11) and 1.03 (95% CI: 1.03, 1.04). In 8159 patients with improving ΔS-Cre%, the aHR was 0.97 (95% CI: 0.94, 1.00). Groups 3 and 4 had statistically significant positive linear relationships between deteriorating ΔS-Cre% and 30-day and 3-year mortality. The optimal cut-offs for deteriorating ΔS-Cre% for predicting 30-day mortality were approximately 22% for Group 3 and 20% for Group 4. Inpatient within-day deteriorating ΔS-Cre or ΔS-Cre% above 0.2 mg/dL or 20%, respectively, is associated with all-cause mortality. Monitoring 24-hour S-Cre variation identifies acute kidney injury earlier than the conventional criteria.

Validation and Comparison of the 2003 and 2016 Diastolic Functional Assessments for Cardiovascular Mortality in a Large Single-Center Cohort.

BACKGROUND: The prognostic performance of the diastolic dysfunction (DD) algorithms published by the Mayo Clinic research group in 2003 and the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI) in 2016 in association with cardiovascular (CV) mortality was compared in this study. METHODS: A retrospective hospital cohort comprising 57,630 adults who had undergone comprehensive echocardiographic examinations between 2008 and 2016 was analyzed. All echocardiographic parameters were measured according to appropriate guidelines, and dates of CV death were verified using the national mortality database. The prognostic performance of the Mayo 2003 and ASE/EACVI 2016 algorithms in association with 3-year CV mortality was systematically investigated. RESULTS: The adjusted hazard ratio (aHR) for severe DD defined by Mayo 2003 (1.64; 95% CI, 1.02-2.64; P = .04) was less than that defined by ASE/EACVI 2016 (aHR, 2.46; 95% CI, 1.58-3.84; P < .001) compared with patients with normal diastolic function. According to the ASE/EACVI 2016 algorithm, the cumulative 3-year CV mortality rate was 2.4% (95% CI, 1.8%-3.0%) for normal diastolic function, 4.7% (95% CI, 4.0%-5.4%) for mild DD, 5.8% (95% CI, 5.0%-6.7%) for moderate DD, 8.3% (95% CI, 6.1%-10.5%) for severe DD, and 3.8% (95% CI, 2.8%-4.8%) for indeterminate DD, respectively (P < .001). The dose-mortality patterns following DD severity were observed only in the ASE/EAVCI 2016 classification. The risk for 3-year CV mortality in patients with concomitant left ventricular ejection fraction < 40% and severe DD was 7 times (aHR, 7.81 [95% CI, 3.81-16.0; P < .05] for Mayo 2003; aHR, 7.67 [95% CI, 4.61-12.8; P < .05] for ASE/EACVI 2016) higher than that in patients with left ventricular ejection fractions ≥ 60% and normal diastolic function. The absolute number of patients who were correctly reclassified by ASE/EAVCI 2016 was 23,181, corresponding to 42% of the absolute net reclassification index. CONCLUSIONS: DD and impaired left ventricular ejection fraction increased CV mortality risk in a mutually independent manner. The severity of DD on the basis of ASE/EACVI 2016 has a graded relationship with CV mortality in a large population cohort.

First-4-week erythrocyte sedimentation rate variability predicts erythrocyte sedimentation rate trajectories and clinical course among patients with pyogenic vertebral osteomyelitis.

BACKGROUND: The trajectory pattern of erythrocyte sedimentation rate (ESR) in patients with pyogenic vertebral osteomyelitis (PVO) and its clinical significance is unclear. We further evaluated whether the first-4-week ESR variability can predict the trajectory pattern, treatment duration and recurrence of PVO. METHODS: The longitudinal ESR patterns of adults with PVO within the first 6 months were characterized through group-based trajectory modeling (GBTM). The ESR variability within the first 4 weeks was defined using the absolute difference (AD), coefficient of variation, percent change, and slope change. The first-4-week ESR variabilities were analyzed using ordinal logistic regression to predict the 6-month ESR trajectory and using logistic regression to predict treatment duration and recurrence likelihood. The discrimination and calibration of the prediction models were evaluated. RESULTS: Three ESR trajectory patterns were identified though GBTM among patients with PVO: Group 1, initial moderate high ESR with fast response; Group 2, initial high ESR with fast response; Group 3, initial high ESR with slow response. Group 3 patients (initial high ESR with slow response) were older, received longer antibiotic treatment, and had more comorbidities and higher recurrence rates than patients in the other two groups. The initial ESR value and ESR - AD could predict the 6-month ESR trajectory. By incorporating the first-4-week ESR variabilities and the clinical features of patients, our models exhibited moderate discrimination performance to predict prolonged treatment (≥12 weeks; C statistic, 0.75; 95% confidence interval [CI], 0.70 to 0.81) and recurrence (C statistic, 0.69; 95% CI, 0.61 to 0.78). CONCLUSIONS: The initial ESR value and first-4-week ESR variability are useful markers to predict the treatment duration and recurrence of PVO. Future studies should validate our findings in other populations.