Arthur R. Williams

Intensive Intraoperative Insulin Therapy versus Conventional Glucose Management during Cardiac Surgery: A Randomized Trial

Context Intensive insulin therapy used to maintain normoglycemia during intensive care after cardiac surgery improves perioperative outcomes. Its effect during cardiac surgery is unknown. Contributions The authors randomly assigned 400 cardiac surgical patients to tight glycemic control (blood glucose level, 4.4 to 5.6 mmol/L [80 to 100 mg/dL]) during surgery or usual intraoperative care. All patients received tight glycemic control in the cardiac intensive care unit. The groups had the same risk for perioperative adverse events (risk ratio, 1.0 [95% CI, 0.8 to 1.2]). The intensive treatment group had more strokes (8 vs. 1) and more deaths (4 vs. 0) than the conventional treatment group. Caution The authors performed the study at a single center. Implications Maintaining normoglycemia during cardiac surgery does not improve outcomes and might worsen them. The Editors Hyperglycemia occurs frequently in patients with and without diabetes during cardiac surgery, especially during cardiopulmonary bypass surgery (1, 2). In a study by Van den Berghe and colleagues (3), intensive insulin therapy after surgery reduced morbidity and death in critically ill patients, most of whom underwent cardiac surgery. As a result, professional organizations have recommended rigorous glycemic control in hospitalized patients (4) and strict glycemic control is now routine practice during the postoperative period in cardiac surgical patients. However, no consensus exists on the optimal management of intraoperative hyperglycemia in cardiac surgical patients because of the lack of evidence from randomized trials. Researchers are increasingly extrapolating evidence from studies that assess the role of strict postoperative glycemic control in critically ill patients to advocate for intravenous insulin therapy for patients in the operating room (3, 57). Evidence, strictly from observational studies, suggests that tight intraoperative glycemic control may reduce postoperative complications (810). We recently reported, in a retrospective, observational study of 409 cardiac surgical patients, that intraoperative hyperglycemia was an independent risk factor for perioperative complications, including death, after adjustment for postoperative glucose concentrations. Each 1.1-mmol/L (20 mg/dL) increase in glucose concentration greater than 5.6 mmol/L (>100 mg/dL) during surgery was associated with a 34% increase in the likelihood of postoperative complications (8). An association between intraoperative hyperglycemia and adverse outcomes based on observational studies does not prove causality. Because hyperglycemia can adversely affect immunity, wound healing, and vascular function, the concept that normoglycemia be maintained during the relatively brief duration of cardiac surgery seems plausible (1116). On the other hand, the degree of intraoperative hyperglycemia may merely reflect the severity of underlying stress. If so, prevention of hyperglycemia might not reduce perioperative complications, and the risks and costs of intensive intraoperative glycemic management may outweigh the benefits. Simple, safe, and effective insulin infusion algorithms that achieve rigorous intraoperative glycemic control are lacking. To address these questions, we conducted a randomized, controlled trial at 1 center to determine whether maintenance of near normoglycemia during cardiac surgery by using intraoperative intravenous insulin infusion reduced perioperative death and morbidity when added to rigorous postoperative glycemic control. Methods Design Overview This was a randomized, open-label, controlled trial with blinded assessment. We randomly assigned patients to receive intensive insulin therapy to maintain intraoperative glucose levels between 4.4 (80 mg/dL) and 5.6 mmol/L (100 mg/dL) or conventional treatment. By design, both groups were postoperatively treated with strict glycemic control to ensure that the observed difference in outcome could be attributed to the effects of intraoperative glycemic control. Setting We performed the study at St. Marys Hospital, Rochester, Minnesota, which is a tertiary care teaching hospital with 1157 beds and an average of more than 41000 admissions per year. Participants Adults undergoing elective cardiac surgery between July 2004 and April 2005 were eligible for enrollment in our study. We excluded patients who had off-pump cardiopulmonary bypass procedures. The Mayo Foundation Institutional Review Board, Rochester, Minnesota, approved the protocol. Randomization and Interventions Before we enrolled patients in our randomized trial, we enrolled 20 patients in a 2-week pilot trial to ensure that the anesthesiologists in the operating room and the nursing staff in the intensive care units (ICUs) had adequate experience with the study insulin infusion algorithm. The 20 patients received intensive insulin therapy during surgery and for 24 hours after surgery. The pilot period data allowed us to modify the graded insulin infusion to achieve desired glucose concentration goals. We built safety features into our infusion protocol to minimize hypoglycemia. We discontinued the infusion when glucose levels were less than 4.4 mmol/L (<80 mg/dL) and initiated dextrose infusion. When glucose levels decreased to less than 3.3 mmol/L (<60 mg/dL), we treated hypoglycemia according to a standardized hypoglycemia protocol. Per protocol, patients treated in the pilot phase were not included in the analyzed cohort. Study coordinators obtained written informed consent from all patients who met eligibility criteria. We randomly assigned patients to receive intensive or conventional intraoperative insulin therapy. Randomization was computer-generated with permuted blocks of 4, with stratification according to surgeon, surgical procedure (coronary artery bypass grafting [CABG] with or without other procedures and no CABG), and diabetes. The randomization assignments were concealed in opaque, sealed, tamper-proof envelopes that were opened sequentially by study personnel after participants signed the patient consent form. We could not possibly know, before obtaining consent, the few patients who would not have intraoperative hyperglycemia (glucose concentration of 5.6 mmol/L or more [100 mg/dL]). Therefore, per protocol, patients who gave consent were randomly assigned, and those whose glucose levels were less than 5.6 mmol/L (<100 mg/dL) during surgery were not included in the final analyses. Intraoperative Period Intensive Treatment Patients in the intensive treatment group received a continuous intravenous insulin infusion, 250 units of NovoLin R (Novo Nordisk, Princeton, New Jersey) in 250 mL of 0.45% sodium chloride, when their blood glucose levels exceeded 5.6 mmol/L (>100 mg/dL). We adjusted the infusions to maintain blood glucose levels between 4.4 (80 mg/dL) and 5.6 mmol/L (100 mg/dL). We adjusted the dose according to a standardized algorithm used by anesthesiologists (Appendix Table 1). Appendix Table 1. Insulin Infusion Protocol* Conventional Treatment Patients in the conventional treatment group did not receive insulin during surgery unless their glucose levels exceeded 11.1 mmol/L (200 mg/dL). If glucose concentration was between 11.1 (200 mg/dL) and 13.9 mmol/L (250 mg/dL), patients received an intravenous bolus of 4 units insulin every hour until the glucose concentration was less than 11.1 mmol/L (<200 mg/dL). If the intraoperative glucose concentration was greater than 13.9 mmol/L (>250 mg/dL), patients received an intravenous infusion of insulin that was continued until the glucose level was less than 8.3 mmol/L (<150 mg/dL). In both study groups, we measured arterial plasma glucose concentration every 30 minutes, starting just before anesthetic induction by using hexokinase method on a Double P Modular System (Roche Diagnostics, Indianapolis, Indiana). Intraoperative procedures, including cardiopulmonary bypass, monitoring, laboratory testing, and treatment, were left to the discretion of anesthesiologists and cardiac surgeons. There was no standard protocol for monitoring and managing intraoperative potassium levels. Postoperative Period Intravenous insulin infusion was started in patients in the conventional treatment group on their arrival in the ICU. Thereafter, both study groups were treated identically, with the intravenous insulin infusion rates adjusted by a nursing staff that was not involved with the study according to a standard protocol. The target blood glucose range was 4.4 (80 mg/dL) to 5.6 mmol/L (100 mg/dL) (Appendix Table 1). Arterial blood glucose levels were measured every 1 to 2 hours by using the Accu-Check Inform blood glucose monitoring system (glucometer) (Roche Diagnostics). During the first 24 hours after surgery, patients were given only clear liquids by mouth; we did not administer subcutaneous insulin or oral diabetic medications during this time. Thereafter, the hospital diabetes consulting service saw all patients and provided individualized recommendations for ongoing care. Outcomes and Measurements The primary outcome variable was a composite of death, sternal wound infections, prolonged pulmonary ventilation, cardiac arrhythmias (new-onset atrial fibrillation, heart block requiring permanent pacemaker, or cardiac arrest), stroke, and acute renal failure within 30 days after surgery. Secondary outcome measures were length of stay in the ICU and hospital. Trained study personnel identified the occurrence of a complication through chart abstraction by using confirmable, objective criteria in accordance with standardized definitions from the Society of Thoracic Surgeons (STS) database committee (17). Personnel who assessed outcomes were not aware of patient treatment assignment or of the study hypothesis. Follow-up Procedures We contacted patients by telephone and used a standardized telephone survey at 30 days after surgery to assess outcomes that occurred after discharge. We considered pat

Systematic Review: Treatment Agreements and Urine Drug Testing to Reduce Opioid Misuse in Patients With Chronic Pain

BACKGROUND Experts recommend opioid treatment agreements and urine drug testing to reduce opioid analgesia misuse, but evidence of their effectiveness has not been systematically reviewed. PURPOSE To synthesize studies of the association of treatment agreements and urine drug testing with opioid misuse outcomes in outpatients with chronic noncancer pain. DATA SOURCES MEDLINE, PsycINFO, EMBASE, Cochrane Central Register of Controlled Clinical Trials (January 1966 to June 2009), reference lists, and expert contacts. STUDY SELECTION Original research addressing opioid medications, chronic pain, and treatment agreements or urine drug testing, with a sample size of 50 participants or more and published in English, Spanish, or French. DATA EXTRACTION Two investigators independently identified eligible studies, extracted data, and assessed study quality. The outcome of opioid misuse was defined as drug abuse, drug misuse, aberrant drug-related behavior, diversion, or addiction. DATA SYNTHESIS Of 102 eligible studies, 11 met inclusion criteria; 6 were in pain clinics and 5 were in primary care settings. Four primary care studies examined multicomponent strategies that included interdisciplinary support. All studies were observational and rated as poor to fair quality. In 4 studies with comparison groups, opioid misuse was modestly reduced (7% to 23%) after treatment agreements with or without urine drug testing. In the other 7 studies, the proportion of patients with opioid misuse after treatment agreements, urine drug testing, or both varied widely (3% to 43%). LIMITATIONS Diversity of interventions and opioid misuse measures precluded meta-analysis. Most studies evaluated combinations of interventions. CONCLUSION Relatively weak evidence supports the effectiveness of opioid treatment agreements and urine drug testing in reducing opioid misuse by patients with chronic pain. Further research on effective ways to monitor and reduce opioid misuse is needed, especially in primary care settings. PRIMARY FUNDING SOURCE Substance Abuse and Mental Health Services Administration, National Institute on Drug Abuse, and Robert Wood Johnson Foundation.

A comparison of hospital adverse events identified by three widely used detection methods

OBJECTIVE Determine the degree of congruence between several measures of adverse events. DESIGN Cross-sectional study to assess frequency and type of adverse events identified using a variety of methods. SETTING Mayo Clinic Rochester hospitals. PARTICIPANTS All inpatients discharged in 2005 (n = 60 599). INTERVENTIONS Adverse events were identified through multiple methods: (i) Agency for Healthcare Research and Quality-defined patient safety indicators (PSIs) using ICD-9 diagnosis codes from administrative discharge abstracts, (ii) provider-reported events, and (iii) Institute for Healthcare Improvement Global Trigger Tool with physician confirmation. PSIs were adjusted to exclude patient conditions present at admission. MAIN OUTCOME MEASURE Agreement of identification between methods. RESULTS About 4% (2401) of hospital discharges had an adverse event identified by at least one method. Around 38% (922) of identified events were provider-reported events. Nearly 43% of provider-reported adverse events were skin integrity events, 23% medication events, 21% falls, 1.8% equipment events and 37% miscellaneous events. Patients with adverse events identified by one method were not usually identified using another method. Only 97 (6.2%) of hospitalizations with a PSI also had a provider-reported event and only 10.5% of provider-reported events had a PSI. CONCLUSIONS Different detection methods identified different adverse events. Findings are consistent with studies that recommend combining approaches to measure patient safety for internal quality improvement. Potential reported adverse event inconsistencies, low association with documented harm and reporting differences across organizations, however, raise concerns about using these patient safety measures for public reporting and organizational performance comparison.

Interrelationships among Variables Affecting Well Siblings and Mothers in Families of Children with a Chronic Illness or Disability

A structural equation model (SEM) examined interrelationships among psychosocial variables known to affect the health and development of well siblings and parents when a child with a chronic illness or disability is a member of the family. Using dyads of 252 well children and parents, socioeconomic status (SES) and family cohesion were associated with the parent-reported behavior of the well sibling. SES also influenced the mood of the mother that in turn influenced family cohesion. The well siblings knowledge about the illness of the brother or sister, attitude toward the illness, mood, self-esteem, and feelings of social support were interrelated and related to the behavior of the well sibling. The SEM suggests that interventions may be directed at several points in these interactions including boosting knowledge levels of the well sibling, improving family cohesion, and assuring adequate “income” support to the family through income transfers or in-kind services.

Effect of discharge instructions on readmission of hospitalised patients with heart failure: do all of the Joint Commission on Accreditation of Healthcare Organizations heart failure core measures reflect better care?

Background: Most nationally standardised quality measures use widely accepted evidence-based processes as their foundation, but the discharge instruction component of the United States standards of Joint Commission on Accreditation of Healthcare Organizations heart failure core measure appears to be based on expert opinion alone. Objective: To determine whether documentation of compliance with any or all of the six required discharge instructions is correlated with readmissions to hospital or mortality. Research design: A retrospective study at a single tertiary care hospital was conducted on randomly sampled patients hospitalised for heart failure from July 2002 to September 2003. Participants: Applying the Joint Commission on Accreditation of Healthcare Organizations criteria, 782 of 1121 patients were found eligible to receive discharge instructions. Eligibility was determined by age, principal diagnosis codes and discharge status codes. Measures: The primary outcome measures are time to death and time to readmission for heart failure or readmission for any cause and time to death. Results: In all, 68% of patients received all instructions, whereas 6% received no instructions. Patients who received all instructions were significantly less likely to be readmitted for any cause (p = 0.003) and for heart failure (p = 0.035) than those who missed at least one type of instruction. Documentation of discharge instructions is correlated with reduced readmission rates. However, there was no association between documentation of discharge instructions and mortality (p = 0.521). Conclusions: Including discharge instructions among other evidence-based heart failure core measures appears justified.

A community-based intervention for siblings and parents of children with chronic illness or disability: the ISEE study.

OBJECTIVE Siblings of children with chronic illness or disability have been reported to have a 1.6 to 2.0 risk for behavioral and mental health problems. Our objective was to examine the effects of an intervention for siblings (age 7-15 years) of children with chronic illness or disability. METHOD A randomized, three-group repeated-measures design was used: full intervention (n=79), partial intervention (n=71), and a waiting list control group (n=102). Outcomes were sibling knowledge about illness, behavior problems, social support, self-esteem, attitude, and mood measured over four postintervention periods. Covariates were family cohesion, maternal mood, socioeconomic status, and well sibling age. The full intervention included structured teaching and psychosocial sessions at a 5-day residential summer camp. The partial intervention included camp only. Treatment effects were estimated by using generalized estimating equation panel analyses. RESULTS The full treatment group showed significant improvements on all six outcomes over most periods, the partial treatment group on three outcomes, and the control group on two outcomes. Improvements in outcomes ranged from 5% to 25% increases over baseline measures. CONCLUSIONS A dose-response relationship to intervention was found. Treatment gains were sustained over a period of 12 months.

Impact of a Guideline on Management of Children Hospitalized With Community-Acquired Pneumonia

OBJECTIVES: We sought to describe the impact a clinical practice guideline (CPG) had on antibiotic management of children hospitalized with community-acquired pneumonia (CAP). PATIENTS AND METHODS: We conducted a retrospective study of discharged patients from a children’s hospital with an ICD-9-CM code for pneumonia (480–486). Eligible patients were admitted from July 8, 2007, through July 9, 2009, 12 months before and after the CAP CPG was introduced. Three-stage least squares regression analyses were performed to examine hypothesized simultaneous relationships, including the impact of our institution\x{2019}s antimicrobial stewardship program (ASP). RESULTS: The final analysis included 1033 patients: 530 (51%) before the CPG (pre-CPG) and 503 (49%) after the CPG (post-CPG). Pre-CPG, ceftriaxone (72%) was the most commonly prescribed antibiotic, followed by ampicillin (13%). Post-CPG, the most common antibiotic was ampicillin (63%). The effect of the CPG was associated with a 34% increase in ampicillin use (P < .001). Discharge antibiotics also changed post-CPG, showing a significant increase in amoxicillin use (P < .001) and a significant decrease in cefdinir and amoxicillin/clavulanate (P < .001), with the combined effect of the CPG and ASP leading to 12% (P < 0.001) and 16% (P < .001) reduction, respectively. Overall, treatment failure was infrequent (1.5% vs 1%). CONCLUSIONS: A CPG and ASP led to the increase in use of ampicillin for children hospitalized with CAP. In addition, less broad-spectrum discharge antibiotics were used. Patient adverse outcomes were low, indicating that ampicillin is appropriate first-line therapy for otherwise healthy children admitted with uncomplicated CAP.

Cancer treatment, symptom monitoring, and self-care in adults: pilot study.

A descriptive study was conducted on self-reported symptoms and self-care by 37 adults receiving chemotherapy primarily for leukemia, lymphomas, or breast cancer or radiation therapy for head and neck or lung cancers. The Therapy-Related Symptom Checklist and demographic and interview forms on self-care for identified symptoms were used. Severe symptoms on the Therapy-Related Symptom Checklist subscales fatigue, eating, nausea, pain, numbness in fingers/toes, hair loss, and constipation were reported by patients on chemotherapy. Those on radiation therapy reported severe symptoms on the eating, fatigue, skin changes, oropharynx, and constipation subscales. Self-care strategies were in the following categories, using complementary medicine as framework: diet/nutrition/lifestyle change (eg, use of nutritional supplements; modifications of food and of eating habits; naps, sleep, and rest); mind/body control (eg, relaxation methods, prayer, music, attending granddaughters sports events); biologic treatments (vitamins); herbal treatments (green mint tea); and ethnomedicine (lime juice and garlic). The first category was predominantly used by patients in both treatment types. Medications were prescribed also to help control symptoms (eg, pain and nausea). Symptom monitoring and self-care for symptoms identified may be facilitated by the Therapy-Related Symptom Checklist; based on reported symptom severity, care providers may prioritize interventions. A larger study needs to be done on (a) the use of the Therapy-Related Symptom Checklist as a clinical tool to assess symptoms that oncology patients experience during therapy; (b) whether care providers, based on patient-reported symptom severity, can prioritize interventions--and how this influences the efficiency of care; (c) the self-care strategies used by patients on chemotherapy or radiation therapy or both; and (d) how useful these strategies are in alleviating symptoms.

A cost measurement study for a tele-oncology practice

Summary The costs of providing oncology services in three different ways were measured. Services were provided to a peripheral hospital by: conventional clinics, in which the oncologist worked at the hospital concerned; outreach clinics, in which an oncologist was flown in periodically from a central hospital; and telemedicine clinics, in which the oncologist at the central hospital practised via a video-link. During a one-year study period, 2400 patients were seen in conventional clinics, 81 in outreach clinics and 103 in telemedicine clinics. At these workloads the average costs per patient were 149, 897 and 812, respectively. However, the average costs cannot be compared directly without further information about the shape of the unit cost curves.

A symptom checklist for children with cancer: the Therapy-Related Symptom Checklist-Children.

Background: Symptom monitoring and alleviation are basic to the care of children and adolescents with cancer. A symptom checklist helps facilitate this process. Objectives: The primary objective of this study was to calibrate a child-friendly, clinically usable checklist capturing symptom occurrence and severity; a secondary objective was to examine age group differences: 5 to 11 years (n = 222) and 12 to 17 years (n = 163) and sex differences: males (54%) and females (46%), and correlate symptom severity, functional status, and quality of life. Methods: Three hundred eighty-five children/adolescents at 5 university-affiliated outpatient oncology clinics: central, western, eastern, southeastern United States. Diagnoses were acute lymphoblastic leukemia (45%), solid tumors (14%), nervous system tumors (18%), and others (23%). Principal component factor analysis, confirmatory factor analysis, correlational statistics, t test, Wilcoxon test were performed. Results: (a) Robust 30-item checklist, 7 factors; (b) 14 of 30 symptoms reported by at least 40% of patients. Top 5 are feeling sluggish (77%), nausea (72%), appetite loss (66%), irritable (61%), and vomiting (54%). (c) Sixteen of 30 symptoms reported at severity 2 or greater: “quite a bit.” (d) Therapy-Related Symptom Checklist–Children (TRSC-C) scores are as follows: range, 0 to 89; mean, 25.14 (SD, 18.68). (e) Cronbach &agr; = .9106. (f) Older children reported greater symptom severities: TRSC-C (t = 2.73, P = .003). (g) There were no sex differences on the TRSC-C total score. (h) Lansky correlations with TRSC-C (r = −0.32; P = .02); factors: nutrition related (r = −0.36; P = .05); oropharyngeal (r = −0.51; P = .0002); and respiratory (r = − 0.25; P = .06). (i) Pediatric Quality of Life Inventory correlation with TRSC−C (r = −0.68; P = .0001). Conclusion: The new TRSC-C has good measurement properties and is ready for use in clinics and research. Implications for Practice: Use of the TRSC-C is consistent with guidelines emphasizing self-report of patient symptoms, shared patient decision making, and improved communications among patients, clinicians, and significant others.