Mark D. Sullivan

The Seattle Heart Failure Model: Prediction of Survival in Heart Failure

Background— Heart failure has an annual mortality rate ranging from 5% to 75%. The purpose of the study was to develop and validate a multivariate risk model to predict 1-, 2-, and 3-year survival in heart failure patients with the use of easily obtainable characteristics relating to clinical status, therapy (pharmacological as well as devices), and laboratory parameters. Methods and Results— The Seattle Heart Failure Model was derived in a cohort of 1125 heart failure patients with the use of a multivariate Cox model. For medications and devices not available in the derivation database, hazard ratios were estimated from published literature. The model was prospectively validated in 5 additional cohorts totaling 9942 heart failure patients and 17 307 person-years of follow-up. The accuracy of the model was excellent, with predicted versus actual 1-year survival rates of 73.4% versus 74.3% in the derivation cohort and 90.5% versus 88.5%, 86.5% versus 86.5%, 83.8% versus 83.3%, 90.9% versus 91.0%, and 89.6% versus 86.7% in the 5 validation cohorts. For the lowest score, the 2-year survival was 92.8% compared with 88.7%, 77.8%, 58.1%, 29.5%, and 10.8% for scores of 0, 1, 2, 3, and 4, respectively. The overall receiver operating characteristic area under the curve was 0.729 (95% CI, 0.714 to 0.744). The model also allowed estimation of the benefit of adding medications or devices to an individual patients therapeutic regimen. Conclusions— The Seattle Heart Failure Model provides an accurate estimate of 1-, 2-, and 3-year survival with the use of easily obtained clinical, pharmacological, device, and laboratory characteristics.

Opioid Prescriptions for Chronic Pain and Overdose: A Cohort Study

BACKGROUND Long-term opioid therapy for chronic noncancer pain is becoming increasingly common in community practice. Concomitant with this change in practice, rates of fatal opioid overdose have increased. The extent to which overdose risks are elevated among patients receiving medically prescribed long-term opioid therapy is unknown. OBJECTIVE To estimate rates of opioid overdose and their association with an average prescribed daily opioid dose among patients receiving medically prescribed, long-term opioid therapy. DESIGN Cox proportional hazards models were used to estimate overdose risk as a function of average daily opioid dose (morphine equivalents) received at the time of overdose. SETTING HMO. PATIENTS 9940 persons who received 3 or more opioid prescriptions within 90 days for chronic noncancer pain between 1997 and 2005. MEASUREMENTS Average daily opioid dose over the previous 90 days from automated pharmacy data. Primary outcomes--nonfatal and fatal overdoses--were identified through diagnostic codes from inpatient and outpatient care and death certificates and were confirmed by medical record review. RESULTS 51 opioid-related overdoses were identified, including 6 deaths. Compared with patients receiving 1 to 20 mg/d of opioids (0.2% annual overdose rate), patients receiving 50 to 99 mg/d had a 3.7-fold increase in overdose risk (95% CI, 1.5 to 9.5) and a 0.7% annual overdose rate. Patients receiving 100 mg/d or more had an 8.9-fold increase in overdose risk (CI, 4.0 to 19.7) and a 1.8% annual overdose rate. LIMITATIONS Increased overdose risk among patients receiving higher dose regimens may be due to confounding by patient differences and by use of opioids in ways not intended by prescribing physicians. The small number of overdoses in the study cohort is also a limitation. CONCLUSION Patients receiving higher doses of prescribed opioids are at increased risk for overdose, which underscores the need for close supervision of these patients. PRIMARY FUNDING SOURCE National Institute of Drug Abuse.

risk factors for clinically recognized opioid abuse and dependence among veterans using opioids for chronic non-cancer pain

Abstract A central question in prescribing opioids for chronic non‐cancer pain (CNCP) is how to best balance the risk of opioid abuse and dependence with the benefits of pain relief. To achieve this balance, clinicians need an understanding of the risk factors for opioid abuse, an issue that is only partially understood. We conducted a secondary data analysis of regional VA longitudinal administrative data (years 2000–2005) for chronic users of opioids for CNCP (n = 15,160) to investigate risk factors for the development of clinically recognized (i.e., diagnosed) opioid abuse or dependence among these individuals. We analyzed four broad groups of possible risk factors: (i) non‐opioid substance abuse disorders, (ii) painful physical health disorders, (iii) mental health disorders, and (iv) socio‐demographic factors. In adjusted models, a diagnosis of non‐opioid substance abuse was the strongest predictor of opioid abuse/dependence (OR = 2.34, p < 0.001). Mental health disorders were moderately strong predictors (OR = 1.46, p = 0.005) of opioid abuse/dependence. However, the prevalence of mental health disorders was much higher than the prevalence of non‐opioid substance abuse disorders (45.3% vs. 7.6%) among users of opioids for CNCP, suggesting that mental health disorders account for more of the population attributable risk for opioid abuse than does non‐opioid substance abuse. Males, younger adults, and individuals with greater days supply of prescription opioids dispensed in 2002 were more likely to develop opioid abuse/dependence. Clinicians need to carefully screen for substance abuse and mental health disorders in candidates for opioid therapy and facilitate appropriate treatment of these disorders.

Medical symptoms without identified pathology: relationship to psychiatric disorders, childhood and adult trauma, and personality traits.

In the past two decades, carefully designed studies examining the biopsychosocial causes of common physical symptoms have shown that most health care visits are made because of common symptoms for which no identified pathology is found (1). In this paper, we summarize the relationship between common medical symptoms without identified pathology and a range of psychosocial variables, such as stressful life events, psychological distress, psychiatric disorders, and predisposing emotional vulnerabilities. We also review the association between psychiatric illness and specific clusters of physical symptoms (such as the chronic fatigue syndrome) that are considered syndromes with ill-defined pathologic mechanisms. Medical symptoms without identified pathology are defined as physical symptoms appearing in patients who do not have proportional tissue abnormalities. In most studies reviewed here, a symptom was considered to have no identified pathology when a patient visited a medical physician and was told that 1) no structural changes could be found to explain the symptom or 2) the symptom was secondary to stress or psychiatric illness. Our medical language to describe these symptoms is imperfect; advances in research suggest that many medical symptoms without identified pathology may actually be caused by problems in psychophysiologic or brainbody pathways, such as abnormalities in smooth-muscle tone in the gastrointestinal tract during stress in patients with the irritable bowel syndrome (2). Recent research also suggests that links between perturbations in brain physiology and physical symptoms are bidirectional. Changes in brain physiology secondary to stressful life events cause functional abnormalities in the body (such as abnormalities in smooth-muscle tone in the gut), and these functional abnormalities in the body are also associated with changes in brain physiology (3). The identification of medical symptoms and syndromes without identified pathology may be broken down into a four-part process (4, 5). First, a person has a symptom (presumably, a neurophysiologic event brings it to awareness). Second, the person uses his or her knowledge, experience, and beliefs about the symptom and its cause to assign the symptom a level of medical importance. Most symptoms do not lead to medical visits because patients assign them a relatively low level of medical importance. Third, the person with the symptom seeks care. Whether a person will seek care can be predicted by that persons beliefs about the symptoms significance and by his or her attitude toward the medical system. The fourth and final step is the interaction of the patients beliefs and expectations with those of the physician. This step may be associated with decreased worry about the symptoms medical implications when the patientphysician interaction goes well, or it may lead to frustration and doctor-shopping when the interaction is problematic. The litigious nature of western society may also lead the physician to order tests because of anxiety about missing a medical problem. This may inadvertently reinforce the patients worry over having a medical illness. Spectrum of Severity The fourth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) has developed dichotomous classifications of patients with unexplained symptoms, such as somatization disorder, conversion disorder, hypochondriasis, and pain disorder. In general, these dichotomous diagnoses apply to only a small percentage of primary care patients and do not point to specific treatment regimens. Most primary care patients who have medical symptoms without identifiable pathology have associated stressful life events or anxiety and depressive diagnoses (or both) and do not have the severity or the chronicity needed to qualify for diagnosis with the somatoform disorders mentioned above (6-8). Several research groups have shown that there is not a sharp dichotomy between patients with multiple somatic symptoms (such as those with the somatization disorder) and patients with medical symptoms without identified pathology but actually a spectrum of severity of somatization (9). As the number of medical symptoms without identified pathology increases, the number of psychological distress symptoms, the number of anxiety and depressive diagnoses, and the degree of functional impairment increase linearly (9-13). Thus, increasing numbers of medically unexplained symptoms have been found to be proxy measures of the degree of psychological distress and functional impairment (9-11). Longitudinal studies that have examined predictors of chronicity in patients who have medical symptoms without identified pathology have found the baseline number of physical symptoms to be the best predictor of persistent impairment (14). Epidemiology Physical symptoms are common among community respondents and are responsible for approximately 50% of all physician visits (1). Epidemiologic surveys of community respondents have found high rates of such symptoms as headache (15), fatigue (16), and abdominal pain (17). One health care diary study (18) reported that participants had a new physical symptom every 5 to 7 days, and more than 90% of these symptoms were not brought to a physicians attention. Another study found that 85% to 95% of community respondents had at least one symptom every 2 to 4 days (19). People in the United States have been found to restrict activities because of symptoms an average of 9.7 days per year and to visit physicians an average of 2.7 times per year (20). Researchers have sought to understand factors predicting medical visits for common physical symptoms, such as headache or fatigue. Studies of community participants with migraine headaches (15), fatigue (16), and common gastrointestinal symptoms (17) have shown that compared with persons who do not seek health care, persons who do seek health care have significantly more stressful life events (21, 22), have psychological distress, and are significantly more likely to meet the criteria for a DSM-IV anxiety or depressive disorder. Epidemiologic studies have found that 25% to 35% of primary care patients meet the criteria for a DSM psychiatric disorder, most often an anxiety or depressive disorder (8, 23). Researchers have shown that approximately half of patients with a DSM anxiety or depressive disorder do not receive an accurate diagnosis by primary care physicians (7, 8, 23). This may be because 50% to 80% of patients with a DSM anxiety or depressive disorder initially present with physical symptoms (7, 8). Compared with patients with psychiatric illness who present with psychological symptoms, significantly more patients with psychiatric illness who present with physical symptoms do not receive an accurate diagnosis by a primary care physician (7, 8). Patients with common anxiety and depressive disorders have significantly more medical symptoms without identified pathology than do patients without psychiatric illness (24, 25). In the Epidemiologic Catchment Area study (25), 50% of community respondents with five or more medically unexplained symptoms over a 6-month period met the criteria for a DSM-III psychiatric disorder; only 5% of respondents without these symptoms met the criteria. Spitzer and colleagues, in the Primary Care Evaluation of Mental Disorders (PRIME-MD) 1000 study (26), showed that as the number of medical symptoms increased, so did the percentage of patients who met the criteria for a DSM-III-R anxiety or depressive disorder (10). This was true both for symptoms that the primary care physician rated as not explained by medical pathology and for symptoms that the physician labeled as probably due to a medical illness. Two other large primary care studies (9, 11) also found a relationship between more medical symptoms without identified pathology and a higher likelihood of a DSM-IV anxiety or depressive disorder. This relationship between the number of medical symptoms and psychiatric disorders holds true for patients with subsyndromal psychiatric disorders. Mental health researchers (27, 28) have shown that as the number of self-rated psychological symptoms increases, so does the number of self-rated physical symptoms, with a correlation of about 0.5 between psychological scales of distress and self-rated physical symptom checklists. Health Care Utilization Patients with depressive and anxiety disorders are often high utilizers of medical services, perhaps because they have an increased number of physical symptoms. In the Epidemiologic Catchment Area Study of five United States cities (29), community respondents with one or more with psychiatric disorders were significantly more likely than respondents without psychiatric disorders to be high utilizers of medical services. A study in a large health maintenance organization (HMO) (30) found that patients with depression who were treated with antidepressants incurred about twice the health care costs of age- and sex-matched patients without depression, even after adjustment for comorbid chronic medical illness. These differences in medical costs were found in every component measured, including primary care, medical specialty, and mental health visits; in-patient medical days; laboratory costs; emergency department costs; and radiography (30). Elderly patients in an HMO who had positive results on screening tests for depression were found to incur 30% to 50% more overall costs than did nondepressed elderly persons after adjustment for comorbidity (31). A retrospective casecontrol study (32) showed that patients with a specific type of anxietypanic disorderhad increased medical costs in every year over a 10-year period compared with age- and sex-matched controls. This association between psychiatric disorders and health care utilization is also evident if patients are identified by utilization patterns. High utilizers of medical services have been shown to h

Trends in long-term opioid therapy for chronic non-cancer pain

To report trends and characteristics of long‐term opioid use for non‐cancer pain.

Relationship Between Baseline Glycemic Control and Cognitive Function in Individuals With Type 2 Diabetes and Other Cardiovascular Risk Factors: The Action to Control Cardiovascular Risk in Diabetes-Memory in Diabetes (ACCORD-MIND) trial

OBJECTIVE—Diabetes is associated with cognitive decline and dementia. However, the relationship between the degree of hyperglycemia and cognitive status remains unclear. This was explored using baseline cognitive measures collected in the ongoing Memory in Diabetes (MIND) substudy of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. RESEARCH DESIGN AND METHODS—The relationship of A1C and fasting plasma glucose (FPG) levels to performance on four cognitive tests was assessed, adjusting for age and other determinants of cognitive status. The tests were the Digit Symbol Substitution Test (DSST), Mini Mental Status Examination (MMSE), Rey Auditory Verbal Learning Test, and Stroop Test. RESULTS—A statistically significant age-adjusted association was observed between the A1C level and the score on all four cognitive tests. Specifically, a 1% higher A1C value was associated with a significant 1.75-point lower DSST score (95% CI −1.22 to −2.28; P < 0.0001), a 0.20-point lower MMSE score (−0.11 to −0.28; P < 0.0001), a 0.11-point lower memory score (−0.02 to −0.19, P = 0.0142), and a worse score (i.e., 0.75 s more) on the Stroop Test (1.31–0.19, P = 0.0094). The association between the DSST score and A1C persisted in all multiple linear regression models. FPG was not associated with test performance. CONCLUSIONS—Higher A1C levels are associated with lower cognitive function in individuals with diabetes. The effect of glucose lowering on cognitive function will be determined by the ongoing ACCORD-MIND trial.

Trends in use of opioids for non-cancer pain conditions 2000-2005 in commercial and Medicaid insurance plans: The TROUP Study

&NA; Opioids are widely prescribed for non‐cancer pain conditions (NCPC), but there have been no large observational studies in actual clinical practice assessing patterns of opioid use over extended periods of time. The TROUP (Trends and Risks of Opioid Use for Pain) study reports on trends in opioid therapy for NCPC in two disparate populations, one national and commercially insured population (HealthCore plan data) and one state‐based and publicly‐insured (Arkansas Medicaid) population over a six year period (2000–2005). We track enrollees with the four most common NCPC conditions: arthritis/joint pain, back pain, neck pain, headaches, as well as HIV/AIDS. Rates of NCPC diagnosis and opioid use increased linearly during this period in both groups, with the Medicaid group starting at higher rates and the HealthCore group increasing more rapidly. The proportion of enrollees receiving NCPC diagnoses increased (HealthCore 33%, Medicaid 9%), as did the proportion of enrollees with NCPC diagnoses who received opioids (HealthCore 58%, Medicaid 29%). Cumulative yearly opioid dose (in mg. morphine equivalents) received by NCPC patients treated with opioids increased (HealthCore 38%, Medicaid 37%) due to increases in number of days supplied rather than dose per day supplied. Use of short‐acting Drug Enforcement Administration Schedule II opioids increased most rapidly, both in proportion of NCPC patients treated (HealthCore 54%, Medicaid 38%) and in cumulative yearly dose (HealthCore 95%, Medicaid 191%). These trends have occurred without any significant change in the underlying population prevalence of NCPC or new evidence of the efficacy of long‐term opioid therapy and thus likely represent a broad‐based shift in opioid treatment philosophy.

Psychosocial factors in fibromyalgia compared with rheumatoid arthritis: II. Sexual physical and emotional abuse and neglect.

Objective Two recent reports have found associations between fibromyalgia and sexual victimization, but had methodologic characteristics that limited their interpretation. Method We compared 36 patients with fibromyalgia and 33 patients with rheumatoid arthritis by using structured interviews for sexual, physical, and emotional victimization histories, as well as dimensional self-report measures of victimization severity. Results Compared with the patients with rheumatoid arthritis, those with fibromyalgia had significantly higher lifetime prevalence rates of all forms of victimization, both adult and childhood, as well as combinations of adult and childhood trauma. Although childhood maltreatment was found to be a general risk factor for fibromyalgia, particular forms of maltreatment (eg, sexual abuse per se) did not have specific effects. Experiences of physical assault in adulthood, however, showed a strong and specific relationship with unexplained pain. Trauma severity was correlated significantly with measures of physical disability, psychiatric distress, illness adjustment, personality, and quality of sleep in patients with fibromyalgia but not in those with rheumatoid arthritis. Conclusions Fibromyalgia seems to be associated with increased risk of victimization, particularly adult physical abuse. Sexual, physical, and emotional trauma may be important factors in the development and maintenance of this disorder and its associated disability in many patients.

De Facto Long-term Opioid Therapy for Noncancer Pain

ObjectivesThis paper describes characteristics of opioid use episodes for noncancer pain and defines thresholds for de facto long-term opioid therapy. MethodsCONSORT (CONsortium to Study Opioid Risks and Trends) includes adult members of 2 health plans serving over 1% of the US population. Opioid use episodes beginning in the years 1997 to 2005 were classified as acute, episodic, long-term/lower dose, or long-term/higher dose. ResultsOn the basis of evaluation of the likelihood of opioid use continuing, long-term opioid therapy was defined by episodes lasting longer than 90 days with 10+ opioid prescriptions or 120+ days supply of opioids dispensed. Long-term/higher dose episodes (<1.5% of all opioid use episodes) were characterized by daily or near daily use, a mean duration of about 1000 days, and an average daily dose of about 55 mg. They accounted for more than half the total morphine equivalents dispensed from the years 1997 to 2006. Short-acting, non-Schedule II opioids (eg, hydrocodone with acetaminophen) were, by far, the most commonly prescribed medications for acute, episodic, and long-term episodes. Long-acting (sustained-release) opioids were the predominately prescribed medication in a minority of long-term episodes (6% to 12%). DiscussionLong-term opioid therapy was characterized by the diversity in medications prescribed, dosage levels, and frequency of use. The proposed threshold for long-term opioid therapy provides a checkpoint for physicians to review whether an explicit decision to sustain opioid therapy has been reached, and to ensure that a documented treatment plan and provisions for monitoring medication use and patient outcomes are in place.

Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): a randomised open-label substudy

Background Persons with type 2 diabetes (T2D) are at risk for cognitive impairment and brain atrophy. The ACCORD Memory in Diabetes (MIND) Study investigated whether persons randomized to an intensive glycaemic therapeutic strategy targeting HbA1c to <6% had better cognitive function and a larger brain volume at 40 months than persons randomized to a standard strategy targeting HbA1c to 7%–7.9%.BACKGROUND People with type 2 diabetes are at risk of cognitive impairment and brain atrophy. We aimed to compare the effects on cognitive function and brain volume of intensive versus standard glycaemic control. METHODS The Memory in Diabetes (MIND) study was done in 52 clinical sites in North America as part of Action to Control Cardiovascular Risk in Diabetes (ACCORD), a double two-by-two factorial parallel group randomised trial. Participants (aged 55-80 years) with type 2 diabetes, high glycated haemoglobin A(1c) (HbA(1c)) concentrations (>7·5%; >58 mmol/mol), and a high risk of cardiovascular events were randomly assigned to receive intensive glycaemic control targeting HbA(1c) to less than 6·0% (42 mmol/mol) or a standard strategy targeting HbA(1c) to 7·0-7·9% (53-63 mmol/mol). Randomisation was via a centralised web-based system and treatment allocation was not masked from clinic staff or participants. We assessed our cognitive primary outcome, the Digit Symbol Substitution Test (DSST) score, at baseline and at 20 and 40 months. We assessed total brain volume (TBV), our primary brain structure outcome, with MRI at baseline and 40 months in a subset of participants. We included all participants with follow-up data in our primary analyses. In February, 2008, raised mortality risk led to the end of the intensive treatment and transition of those participants to standard treatment. We tested our cognitive function hypotheses with a mixed-effects model that incorporated information from both the 20 and 40 month outcome measures. We tested our MRI hypotheses with an ANCOVA model that included intracranial volume and factors used to stratify randomisation. This study is registered with ClinicalTrials.gov, number NCT00182910. FINDINGS We consecutively enrolled 2977 patients (mean age 62·5 years; SD 5·8) who had been randomly assigned to treatment groups in the ACCORD study. Our primary cognitive analysis was of patients with a 20-month or 40-month DSST score: 1378 assigned to receive intensive treatment and 1416 assigned to receive standard treatment. Of the 614 patients with a baseline MRI, we included 230 assigned to receive intensive treatment and 273 assigned to receive standard treatment in our primary MRI analysis at 40 months. There was no significant treatment difference in mean 40-month DSST score (difference in mean 0·32, 95% CI -0·28 to 0·91; p=0·2997). The intensive-treatment group had a greater mean TBV than the standard-treatment group (4·62, 2·0 to 7·3; p=0·0007). INTERPRETATION Although significant differences in TBV favoured the intensive treatment, cognitive outcomes were not different. Combined with the non-significant effects on other ACCORD outcomes, and increased mortality in participants in the intensive treatment group, our findings do not support the use of intensive therapy to reduce the adverse effects of diabetes on the brain in patients with similar characteristics to those of our participants. FUNDING US National Institute on Aging and US National Heart, Lung, and Blood Institute.