Citations

Summary There are few data regarding postoperative hyperglycaemia in non‐diabetic compared with diabetic patients following postoperative nausea and vomiting prophylaxis with dexamethasone. Eighty‐five non‐diabetic patients and patients with type‐2 diabetes were randomly allocated to receive intravenous dexamethasone (8 mg) or ondansetron (4 mg). Blood glucose levels were measured at baseline and then 2, 4 and 24 h following induction of anaesthesia. In non‐diabetic patients, the mean ( SD ) maximum blood glucose was higher in those who received dexamethasone compared with ondansetron (9.1 (2.2) mmol.l −1 vs. 7.8 (1.4) mmol.l −1 , p = 0.04). In diabetic patients, the mean ( SD ) maximum blood glucose was also higher in those who received dexamethasone compared with ondansetron (14.0 (2.5) mmol.l −1 vs. 10.7 (2.4) mmol.l −1 , p < 0.01). Multivariate analysis demonstrated that dexamethasone administration was a significant predictor of maximum postoperative blood glucose increase (p < 0.01) after adjusting for potential confounders. There was no interaction between baseline blood glucose level, or presence or absence of diabetes, and dexamethasone administration. We conclude that dexamethasone increases postoperative blood glucose levels in both non‐diabetics and diabetics.

Objective Assess the effects of linezolid on hematologic outcomes in newly diagnosed patients with acute myeloid leukemia ( AML ) following induction chemotherapy. Design Single‐center, retrospective, observational, cohort study. Setting Large, tertiary care academic medical center. Patients A total of 225 patients ≥ 18 years admitted between December 2010 and 2013 with newly diagnosed AML were assessed for inclusion. Patients were identified through the use of ICD ‐9 codes and chemotherapy ordered via the computerized physician order entry system. Sixty‐eight patients met inclusion criteria and were grouped into two arms based on antimicrobial treatment: LZD group (linezolid plus gram‐negative antimicrobial, n=21) or control group (vancomycin or daptomycin plus gram‐negative antimicrobial, n=47). Interventions The LZD group received linezolid ≥ 72 hours. The control group received vancomycin or daptomycin ≥ 72 hours. If patients switched extended gram‐positive therapy, they were included in the LZD group as long as they had received ≥ 72 hours of linezolid. Measurements/Results The primary end point of time to neutrophil recovery was not statistically different (28 days for LZD group vs 26 days for control group; p=0.675). The preplanned subgroup analysis of patients who received ≥ 14 days of linezolid demonstrated statistically similar median times to neutrophil recovery (29 days for LZD group vs 26 days for control group; p=0.487). Total duration of extended gram‐positive antimicrobial therapy was significantly longer in the LZD group (27 days vs 16 days; p<0.001). Secondary end points not found to be statistically significant included platelet count at time of neutrophil recovery, duration of neutropenia, and length of hospital stay. Conclusions There were no significant differences in hematologic outcomes in newly diagnosed AML patients who received linezolid for extended gram‐positive antimicrobial coverage following induction chemotherapy. This study provides new insight with a primary focus on the effects of hematologic outcomes when using linezolid in a well‐defined acute leukemia population. Further study is warranted with larger populations to assess the potential adverse effects linezolid may have in patients with acute leukemia.

New Findings What is the central question of this study? Is lower body negative pressure a useful surrogate to study white blood cell responses to haemorrhage in humans? What is the main finding and its importance? We found that lower body negative pressure appears to be a useful surrogate to study the early white blood cell mobilization response during blood loss. Hypovolaemia has been associated with an immune response that might be secondary to sympathoexcitation. We tested the hypothesis that simulated hypovolaemia using lower body negative pressure (LBNP) and real hypovolaemia induced via experimental blood loss (BL) cause similar increases in the white blood cell concentration ([WBC]). We measured [WBC] and catecholamine concentrations in 12 men who underwent an LBNP and a BL protocol in a randomized order. We compared 45 mmHg of LBNP with 1000 ml of BL; therefore, [WBC] and catecholamine concentrations were plotted against central venous pressure to obtain stimulus–response relationships using the linear regression line slopes for both protocols. Mean regression line slopes were similar for total [WBC] (LBNP 183 ± 4 μl−1 mmHg−1 versus BL 155 ± 109 μl−1 mmHg−1, P = 0.15), neutrophils (LBNP 110 ± 2 μl−1 mmHg−1 versus BL 96 ± 72 μl−1 mmHg−1, P = 0.15) and lymphocytes (LBNP 65 ± 21 μl−1 mmHg−1 versus BL 59 ± 38 μl−1 mmHg−1, P = 0.90). Mean regression line slopes for adrenaline were similar (LBNP 15 ± 5 pg ml−1 mmHg−1 versus BL 16 ± 4 pg ml−1 mmHg−1, P = 0.84) and were steeper during LBNP for noradrenaline (LBNP 28 ± 6 pg ml−1 mmHg−1 versus BL 9 ± 6 pg ml−1 mmHg−1, P = 0.01). These data indicate that central hypovolaemia elicits a relative leucocytosis with a predominantly neutrophil‐based response. Additionally, our results indicate that LBNP models the stimulus–response relationship between central venous pressure and [WBC] observed during BL.

Background/Aims: Due to the progressive nature of type 2 diabetes mellitus (T2DM), deterioration in a patient’s general health is inevitable. Hence, the overall health of a T2DM patient is poor. Markers of worsening overall health such as metabolic abnormalities are predominant in the progression to any of the T2DM complications, which mask patterns of progression to individual complications, thereby making it difficult to predict which particular complication a patient will progress to (i.e. direction of progression). We aim to unmask the patterns and develop the most distinctive and predictive markers of progression to each individual complication. Methods: We take a two-step modeling approach using 94,536 T2DM patients’ 10-year, de-identified data from the OptumLabs™ Data Warehouse, a database that includes retrospective administrative claims data on commercially insured and Medicare Advantage enrollees, as well as electronic medical record data from a nationwide network of provider groups. First, we build a “general progression” model that predicts development of any new complication and captures markers of general health deterioration. Next, we develop “differential progression” models that predict progression to individual complications. We use least absolute shrinkage and selection operator (LASSO)-penalized Cox regressions to select variables and penalize the “differential progression” models against the “general progression” model such that “differential progression” patterns become unmasked. Significance of markers is determined via permutation test and predictive performance is evaluated through bootstrap estimation. Results: For a 6-year follow-up period, 31,968 (34%) of all patients progressed to at least one complication: chronic kidney disease (12%), ischemic heart disease (11%), cerebrovascular disease (8%), congestive heart failure (5%), peripheral vascular disease (5%), and renal failure (1%). In this ongoing research, we anticipate our predictive model to demonstrate improved interpretation of progression to each individual complication without causing reduced predictive performance. Conclusion: We study the progression of T2DM to multiple complications systematically and comprehensively by applying data mining techniques on the large amount of claims and clinical data from the OptumLabs Data Warehouse. By unmasking previously masked patterns and developing markers that suggest progression to a specific target complication, our study findings will assist clinicians in the management and treatment of T2DM.