METHODS: All 5616 patients, diagnosed with breast cancer in University Malaya Medical Centre from 1999 to 2013 were included. In 945 elderly patients (aged 65 years and above), multivariable logistic regression was performed to identify factors associated with treatment, following adjustment for age, ethnicity, tumor, and other treatment characteristics. The impact of lack of treatment on survival of the elderly was assessed while accounting for comorbidities.
RESULTS: One in five elderly patients had comorbidities. Compared to younger patients, the elderly had more favorable tumor characteristics, and received less loco-regional treatment and chemotherapy. Within stage I-IIIa elderly breast cancer patients, 10 % did not receive any surgery. These patients were older, more likely to be Malays, have comorbidities, and bigger tumors. In elderlies with indications for adjuvant radiotherapy, no irradiation (30 %) was associated with increasing age, comorbidity, and the absence of systemic therapy. Hormone therapy was optimal, but only 35 % of elderly women with ER negative tumors received chemotherapy. Compared to elderly women who received adequate treatment, those not receiving surgery (adjusted hazard ratio: 2.30, 95 %CI: 1.10-4.79), or radiotherapy (adjusted hazard ratio: 1.56, 95 %CI: 1.10-2.19), were associated with higher mortality. Less than 25 % of the survival discrepancy between elderly women receiving loco-regional treatment and no treatment were attributed to excess comorbidities in untreated patients.
CONCLUSION: While the presence of comorbidities significantly influenced loco-regional treatment decisions in the elderly, it was only able to explain the lower survival rates in untreated patients up to a certain extent, suggesting missed opportunities for treatment.
METHODS AND RESULTS: This was a retrospective longitudinal study of HF patients aged ≥18 years hospitalized at a tertiary healthcare center between January 1, 2009 and December 31, 2013 in Ghana. Patients were eligible if they were discharged from first admission for HF (index admission) and followed up to time of all-cause, cardiovascular, and HF mortality or end of study. Multivariable time-dependent Cox model and inverse-probability-of-treatment weighting of marginal structural model were used to estimate associations between statin treatment and outcomes. Adjusted hazard ratios were also estimated for lipophilic and hydrophilic statin compared with no statin use. The study included 1488 patients (mean age 60.3±14.2 years) with 9306 person-years of observation. Using the time-dependent Cox model, the 5-year adjusted hazard ratios with 95% CI for statin treatment on all-cause, cardiovascular, and HF mortality were 0.68 (0.55-0.83), 0.67 (0.54-0.82), and 0.63 (0.51-0.79), respectively. Use of inverse-probability-of-treatment weighting resulted in estimates of 0.79 (0.65-0.96), 0.77 (0.63-0.96), and 0.77 (0.61-0.95) for statin treatment on all-cause, cardiovascular, and HF mortality, respectively, compared with no statin use.
CONCLUSIONS: Among Africans with HF, statin treatment was associated with significant reduction in mortality.
Methods: This is a cohort study where prevalent ESRD patients' details were recorded between May 2012 and October 2012. Their records were matched with national death record at the end of year 2015 to identify the deceased patients within three years. Four models were formulated with two models were based on logistic regression models but with different number of predictors and two models were developed based on risk scoring technique. The preferred models were validated by using sensitivity and specificity analysis.
Results: A total of 1332 patients were included in the study. Majority succumbed due to cardiovascular disease (48.3%) and sepsis (41.3%). The identified risk factors were mode of dialysis (P < 0.001), diabetes mellitus (P < 0.001), chronic heart disease (P < 0.001) and leg amputation (P = 0.016). The accuracy of four models was almost similar with AUC between 0.680 and 0.711. The predictive models from logistic regression model and risk scoring model were selected as the preferred models based on both accuracy and simplicity. Besides the mode of dialysis, diabetes mellitus and its complications are the important predictors for early mortality among prevalent ESRD patients.
Conclusions: The models either based on logistic regression or risk scoring model can be used to screen high risk prevalent ESRD patients.
METHODS: We performed a meta-analysis of PEW prevalence from contemporary studies including more than 50 subjects with kidney disease, published during 2000-2014 and reporting on PEW prevalence by subjective global assessment or malnutrition-inflammation score. Data were reviewed throughout different strata: (1) acute kidney injury (AKI), (2) pediatric chronic kidney disease (CKD), (3) nondialyzed CKD 3-5, (4) maintenance dialysis, and (5) subjects undergoing kidney transplantation (Tx). Sample size, period of publication, reporting quality, methods, dialysis technique, country, geographical region, and gross national income were a priori considered factors influencing between-study variability.
RESULTS: Two studies including 189 AKI patients reported a PEW prevalence of 60% and 82%. Five studies including 1776 patients with CKD stages 3-5 reported PEW prevalence ranging from 11% to 54%. Finally, 90 studies from 34 countries including 16,434 patients on maintenance dialysis were identified. The 25th-75th percentiles range in PEW prevalence among dialysis studies was 28-54%. Large variation in PEW prevalence across studies remained even when accounting for moderators. Mixed-effects meta-regression identified geographical region as the only significant moderator explaining 23% of the observed data heterogeneity. Finally, two studies including 1067 Tx patients reported a PEW prevalence of 28% and 52%, and no studies recruiting pediatric CKD patients were identified.
CONCLUSION: By providing evidence-based ranges of PEW prevalence, we conclude that PEW is a common phenomenon across the spectrum of AKI and CKD. This, together with the well-documented impact of PEW on patient outcomes, justifies the need for increased medical attention.
METHODS: Planned analysis of data was collected during an international 7-day cohort study of adults undergoing elective in-patient surgery. AKI was defined using Kidney Disease Improving Global Outcomes criteria. Patients missing preoperative creatinine data were excluded. We used multivariable logistic regression to examine the relationships among preoperative creatinine-based estimated glomerular filtration rate (eGFR), postoperative AKI, and hospital mortality, accounting for the effects of age, major comorbid diseases, and nature and severity of surgical intervention on outcomes. We similarly modeled preoperative associations of AKI. Data are presented as n (%) or odds ratios (ORs) with 95% confidence intervals.
RESULTS: A total of 36,357 patients were included, 743 (2.0%) of whom developed AKI with 73 (9.8%) deaths in hospital. AKI affected 73 of 196 (37.2%) of all patients who died. Mortality was strongly associated with the severity of AKI (stage 1: OR, 2.57 [1.3-5.0]; stage 2: OR, 8.6 [5.0-15.1]; stage 3: OR, 30.1 [18.5-49.0]). Low preoperative eGFR was strongly associated with AKI. However, in our model, lower eGFR was not associated with increasing mortality in patients who did not develop AKI. Conversely, in older patients, high preoperative eGFR (>90 mL·minute·1.73 m) was associated with an increasing risk of death, potentially reflecting poor muscle mass.
CONCLUSIONS: The occurrence and severity of AKI are strongly associated with risk of death after surgery. However, the relationship between preoperative renal function as assessed by serum creatinine-based eGFR and risk of death dependent on patient age and whether AKI develops postoperatively.