Intensive renal support in critically ill patients with acute kidney injury did not decrease mortality, improve recovery of kidney function, or reduce the rate of nonrenal organ failure as compared with less-intensive therapy involving a defined dose of intermittent hemodialysis three times per week and continuous renal-replacement therapy at 20 ml per kilogram per hour. (ClinicalTrials.gov number, NCT00076219.)
Objectives To estimate the prevalence of specific comorbid conditions (CCs) and multiple comorbid conditions (MCCs) among adult patients with hyperkalemia and examine the associations between MCCs and healthcare resource utilization (HRU) and costs. Methods This retrospective observational cohort study was conducted using a large administrative claims database. We identified patients with hyperkalemia (ICD-10-CM: E87.5; or serum potassium >5.0 mEq/L; or NDC codes for either patiromer or sodium polystyrene sulfonate) during the study period (1/1/2016–6/30/2019). The earliest service/claim date with evidence of hyperkalemia was identified as index date. Qualified patients had ≥12 months of enrolment before and after index date, ≥18 years of age. Comorbid conditions were assessed using all data within 12 months prior to the index date. Healthcare resource utilization and costs were estimated using all data within 12 months after the index date. Association rule mining was applied to identify MCCs. Generalized linear models were used to examine the associations between MCCs and HRU and costs. Results Of 22,154 patients with hyperkalemia, 94% had ≥3 CCs. The most common individual CCs were chronic kidney disease (CKD, 85%), hypertension (HTN, 83%), hyperlipidemia (HLD, 81%), and diabetes mellitus (DM, 47%). The most common dyad combination of CCs was CKD+HTN (71%). The most common triad combination was CKD+HTN+HLD (62%). The most common quartet combination was CKD+HTN+HLD+DM (36%). The increased number of CCs were significantly associated with increased ED visits, length of hospital stays, and total healthcare costs (all p-value < 0.0001). Conclusions MCCs are very prevalent among patients with hyperkalemia and are strongly associated with HRU and costs.
Methods for estimating the regional variance in emission tomography images which arise from the Poisson nature of the raw data are discussed. The methods are based on the bootstrap and jackknife methods of statistical resampling theory. The bootstrap is implemented in time-of-flight PET (positron emission tomography); the same techniques can be applied to non-time-of-flight PET and SPECT (single-photon-emission computed tomography). The estimates are validated by comparing them to those obtained by repetition of emission scans, using data from a time-of-flight positron emission tomograph. Simple expressions for the accuracy of the estimates are given. The present approach is computationally feasible and can be applied to any reconstruction technique as long as the data are acquired in a raw, uncorrected form.
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