Pub Date : 2012-11-12DOI: 10.1001/2013.jamainternmed.592
Peter A Boling
{"title":"Aligning prognosis, patient goals, policy, and care models for palliative care in nursing homes.","authors":"Peter A Boling","doi":"10.1001/2013.jamainternmed.592","DOIUrl":"https://doi.org/10.1001/2013.jamainternmed.592","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1580-1"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/2013.jamainternmed.592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30945879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-12DOI: 10.1001/2013.jamainternmed.613
William Cunningham
{"title":"HIV racial disparities: time to close the gaps.","authors":"William Cunningham","doi":"10.1001/2013.jamainternmed.613","DOIUrl":"https://doi.org/10.1001/2013.jamainternmed.613","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1599-600"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/2013.jamainternmed.613","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30961240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-12DOI: 10.1001/archinternmed.2012.4508
Edgar P Simard, Mesfin Fransua, Deepa Naishadham, Ahmedin Jemal
Background: Overall declines in human immunodeficiency virus (HIV) mortality may mask patterns for subgroups, and prior studies of disparities in mortality have used area-level vs individual-level socioeconomic status measures. The aim of this study was to examine temporal trends in HIV mortality by sex, race/ethnicity, and individual level of education (as a proxy for socioeconomic status).
Methods: We examined HIV deaths among non-Hispanic white, non-Hispanic black, and Hispanic men and women aged 25 to 64 years in 26 states (1993-2007; N=91 307) reported to the National Vital Statistics System. The main outcome measures were age-standardized HIV death rates, rate differences, and rate ratios by educational attainment and between the least- and the most-educated (≤12 vs ≥16 years) individuals.
Results: Between 1993-1995 and 2005-2007, mortality declined for most men and women by race/ethnicity and educational levels, with the greatest absolute decreases for nonwhites owing to their higher baseline rates. Among men with the most education, rates per 100 000 population decreased from 117.89 (95% CI, 101.08-134.70) to 15.35 (12.08-18.62) in blacks vs from 26.42 (24.93-27.92) to 1.79 (1.50-2.08) in whites. Rates were unchanged for the least-educated black women (26.76; 95% CI, 24.30-29.23; during 2005-2007) and remained high for similarly educated black men (52.71; 48.96-56.45). Relative declines were greater with increasing levels of education (P < .001), resulting in widening disparities. Among men, the disparity rate ratio (comparing the least and the most educated) increased from 1.04 (95% CI, 0.89-1.21) during 1993-1995 to 3.43 (2.74-4.30) during 2005-2007 for blacks and from 0.98 (0.91-1.05) to 2.82 (2.34-3.40) for whites.
Conclusion: Although absolute declines in HIV mortality were greatest for nonwhites, rates remain high among blacks, especially in the lowest educated groups, underscoring the need for additional interventions.
{"title":"The influence of sex, race/ethnicity, and educational attainment on human immunodeficiency virus death rates among adults, 1993-2007.","authors":"Edgar P Simard, Mesfin Fransua, Deepa Naishadham, Ahmedin Jemal","doi":"10.1001/archinternmed.2012.4508","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.4508","url":null,"abstract":"<p><strong>Background: </strong>Overall declines in human immunodeficiency virus (HIV) mortality may mask patterns for subgroups, and prior studies of disparities in mortality have used area-level vs individual-level socioeconomic status measures. The aim of this study was to examine temporal trends in HIV mortality by sex, race/ethnicity, and individual level of education (as a proxy for socioeconomic status).</p><p><strong>Methods: </strong>We examined HIV deaths among non-Hispanic white, non-Hispanic black, and Hispanic men and women aged 25 to 64 years in 26 states (1993-2007; N=91 307) reported to the National Vital Statistics System. The main outcome measures were age-standardized HIV death rates, rate differences, and rate ratios by educational attainment and between the least- and the most-educated (≤12 vs ≥16 years) individuals.</p><p><strong>Results: </strong>Between 1993-1995 and 2005-2007, mortality declined for most men and women by race/ethnicity and educational levels, with the greatest absolute decreases for nonwhites owing to their higher baseline rates. Among men with the most education, rates per 100 000 population decreased from 117.89 (95% CI, 101.08-134.70) to 15.35 (12.08-18.62) in blacks vs from 26.42 (24.93-27.92) to 1.79 (1.50-2.08) in whites. Rates were unchanged for the least-educated black women (26.76; 95% CI, 24.30-29.23; during 2005-2007) and remained high for similarly educated black men (52.71; 48.96-56.45). Relative declines were greater with increasing levels of education (P < .001), resulting in widening disparities. Among men, the disparity rate ratio (comparing the least and the most educated) increased from 1.04 (95% CI, 0.89-1.21) during 1993-1995 to 3.43 (2.74-4.30) during 2005-2007 for blacks and from 0.98 (0.91-1.05) to 2.82 (2.34-3.40) for whites.</p><p><strong>Conclusion: </strong>Although absolute declines in HIV mortality were greatest for nonwhites, rates remain high among blacks, especially in the lowest educated groups, underscoring the need for additional interventions.</p>","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1591-8"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.4508","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30961594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-12DOI: 10.1001/2013.jamainternmed.99
Kishore M Gadde, Mariko F Kopping, H Ryan Wagner, Gretchen M Yonish, David B Allison, George A Bray
BACKGROUND Obese individuals who have failed to achieve adequate weight loss with lifestyle changes have limited nonsurgical therapeutic options. We evaluated the efficacy and tolerability of zonisamide, an antiepileptic drug, for enhancing weight loss in obese patients receiving diet and lifestyle guidance. METHODS This was a 1-year, randomized, double-blind, placebo-controlled trial conducted from January 9, 2006, through September 20, 2011, at Duke University Medical Center. A total of 225 obese (mean [SD] body mass index, 37.6 [4.9]) participants included 134 women (59.6%) and 91 men (40.4%) without diabetes mellitus. (Body mass index is calculated as weight in kilograms divided by height in meters squared.) Interventions were daily dosing with placebo (n = 74), 200 mg of zonisamide (n = 76), or 400 mg of zonisamide (n = 75), in addition to diet and lifestyle counseling by a dietitian for 1 year. Primary outcome was change in body weight at 1 year. RESULTS Of the 225 randomized patients, 218 (96.9%) provided 1-year follow-up assessments. Change in body weight was -4.0 kg (95% CI, -5.8 to -2.3 kg; least squares mean, -3.7%) for placebo, -4.4 kg (-6.1 to -2.6 kg; -3.9%; P = .79 vs placebo) for 200 mg of zonisamide, and -7.3 kg (-9.0 to -5.6 kg; -6.8%; P = .009 vs placebo) for 400 mg of zonisamide. In the categorical analysis, 23 (31.1%) assigned to placebo, 26 (34.2%; P = .72) assigned to 200 mg of zonisamide, and 41 (54.7%; P = .007) assigned to 400 mg of zonisamide achieved 5% or greater weight loss; for 10% or greater weight loss, the corresponding numbers were 6 (8.1%), 17 (22.4%; P = .02), and 24 (32.0%; P < .001). Gastrointestinal, nervous system, and psychiatric adverse events occurred at a higher incidence with zonisamide than with placebo. CONCLUSION Zonisamide at the daily dose of 400 mg moderately enhanced weight loss achieved with diet and lifestyle counseling but had a high incidence of adverse events. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00275834
{"title":"Zonisamide for weight reduction in obese adults: a 1-year randomized controlled trial.","authors":"Kishore M Gadde, Mariko F Kopping, H Ryan Wagner, Gretchen M Yonish, David B Allison, George A Bray","doi":"10.1001/2013.jamainternmed.99","DOIUrl":"https://doi.org/10.1001/2013.jamainternmed.99","url":null,"abstract":"BACKGROUND\u0000Obese individuals who have failed to achieve adequate weight loss with lifestyle changes have limited nonsurgical therapeutic options. We evaluated the efficacy and tolerability of zonisamide, an antiepileptic drug, for enhancing weight loss in obese patients receiving diet and lifestyle guidance.\u0000\u0000\u0000METHODS\u0000This was a 1-year, randomized, double-blind, placebo-controlled trial conducted from January 9, 2006, through September 20, 2011, at Duke University Medical Center. A total of 225 obese (mean [SD] body mass index, 37.6 [4.9]) participants included 134 women (59.6%) and 91 men (40.4%) without diabetes mellitus. (Body mass index is calculated as weight in kilograms divided by height in meters squared.) Interventions were daily dosing with placebo (n = 74), 200 mg of zonisamide (n = 76), or 400 mg of zonisamide (n = 75), in addition to diet and lifestyle counseling by a dietitian for 1 year. Primary outcome was change in body weight at 1 year.\u0000\u0000\u0000RESULTS\u0000Of the 225 randomized patients, 218 (96.9%) provided 1-year follow-up assessments. Change in body weight was -4.0 kg (95% CI, -5.8 to -2.3 kg; least squares mean, -3.7%) for placebo, -4.4 kg (-6.1 to -2.6 kg; -3.9%; P = .79 vs placebo) for 200 mg of zonisamide, and -7.3 kg (-9.0 to -5.6 kg; -6.8%; P = .009 vs placebo) for 400 mg of zonisamide. In the categorical analysis, 23 (31.1%) assigned to placebo, 26 (34.2%; P = .72) assigned to 200 mg of zonisamide, and 41 (54.7%; P = .007) assigned to 400 mg of zonisamide achieved 5% or greater weight loss; for 10% or greater weight loss, the corresponding numbers were 6 (8.1%), 17 (22.4%; P = .02), and 24 (32.0%; P < .001). Gastrointestinal, nervous system, and psychiatric adverse events occurred at a higher incidence with zonisamide than with placebo.\u0000\u0000\u0000CONCLUSION\u0000Zonisamide at the daily dose of 400 mg moderately enhanced weight loss achieved with diet and lifestyle counseling but had a high incidence of adverse events.\u0000\u0000\u0000TRIAL REGISTRATION\u0000clinicaltrials.gov Identifier: NCT00275834","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1557-64"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/2013.jamainternmed.99","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31045745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-12DOI: 10.1001/archinte.172.20.1532
{"title":"About this journal.","authors":"","doi":"10.1001/archinte.172.20.1532","DOIUrl":"https://doi.org/10.1001/archinte.172.20.1532","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1532"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31496060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-11-12DOI: 10.1001/archinternmed.2012.3758
Tyler N A Winkelman, Ryan M Antiel, Cynthia S Davey, Jon C Tilburt, John Y Song
{"title":"Medical students and the Affordable Care Act: uninformed and undecided.","authors":"Tyler N A Winkelman, Ryan M Antiel, Cynthia S Davey, Jon C Tilburt, John Y Song","doi":"10.1001/archinternmed.2012.3758","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.3758","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1603-5"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.3758","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30929003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T elemonitoring is often proposed as an efficient way to provide health care. The recent study by Takahashi et al examining telemonitoring in vulnerable patients with mixed chronic diseases clearly reflects the need for meticulous scientific approaches to study these types of interventions. Telemonitoring aims at early detection and prompt action in the case of health deterioration. Although patients reported high satisfaction and a sense of safety, telemonitoring failed to reduce hospital admissions and emergency department visits. Surprisingly, it resulted in a 4-fold increase in mortality risk (relative risk, 3.8; 95% CI, 1.3-11.0). This suggests that telemonitoring in frail elderly patients is hazardous, causing more harm than good. However, one can question the validity of this conclusion. A well-considered interpretation of the observed increased risk of mortality among patients receiving telemonitoring requires crucial information on timing and causes of death, which is currently lacking. The combined end point analysis ignores the true time-related impact of the exposure on mortality and health care utilization. In addition, it would have been informative to compare between-group characteristics of fatal cases vs nonfatal cases and indications for hospital admissions and emergency department visits. Despite randomization, it is not clear if both groups were comparable regarding their baseline mortality risk. An important constraint to obtain unbiased effect estimates in a randomized controlled trial (RCT) is that comparison groups are equivalent in terms of prognosis. It is well-established in statistical literature that hypothesis testing is inappropriate to evaluate differences in the distribution of baseline patient characteristics between treatment groups in RCTs. Nevertheless, the authors decided, based on P values, that both groups were balanced and adjustment of potential confounders was not necessary. It needs to be emphasized that even nonsignificant (P .05) imbalances of strong prognostic factors may still result in substantial bias and therefore requires adjustment. For example, chronic obstructive pulmonary disease, diabetes mellitus, and congestive heart failure were not statistically imbalanced between the treatment groups and yet are important risk factors of mortality and hence potentially confounding the effects of telemonitoring. These questions actually reflect the largest drawback of the study: the lack of substantial insight in the assumed relation between patient characteristics, intervention, and outcome. In intervention testing, the RCT is the final step, following a sequence of steps from initial preclinical research through phase 1 and phase 2 studies. The study by Takahashi et al warrants careful consideration of the benefits of telehealth interventions. Moreover, it shows the need of careful development and testing of nonpharmaceutical interventions.
{"title":"Increased mortality following telemonitoring in frail elderly patients: look before you leap!","authors":"Jaap Trappenburg, Rolf Groenwold, Marieke Schuurmans","doi":"10.1001/archinternmed.2012.4421","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.4421","url":null,"abstract":"T elemonitoring is often proposed as an efficient way to provide health care. The recent study by Takahashi et al examining telemonitoring in vulnerable patients with mixed chronic diseases clearly reflects the need for meticulous scientific approaches to study these types of interventions. Telemonitoring aims at early detection and prompt action in the case of health deterioration. Although patients reported high satisfaction and a sense of safety, telemonitoring failed to reduce hospital admissions and emergency department visits. Surprisingly, it resulted in a 4-fold increase in mortality risk (relative risk, 3.8; 95% CI, 1.3-11.0). This suggests that telemonitoring in frail elderly patients is hazardous, causing more harm than good. However, one can question the validity of this conclusion. A well-considered interpretation of the observed increased risk of mortality among patients receiving telemonitoring requires crucial information on timing and causes of death, which is currently lacking. The combined end point analysis ignores the true time-related impact of the exposure on mortality and health care utilization. In addition, it would have been informative to compare between-group characteristics of fatal cases vs nonfatal cases and indications for hospital admissions and emergency department visits. Despite randomization, it is not clear if both groups were comparable regarding their baseline mortality risk. An important constraint to obtain unbiased effect estimates in a randomized controlled trial (RCT) is that comparison groups are equivalent in terms of prognosis. It is well-established in statistical literature that hypothesis testing is inappropriate to evaluate differences in the distribution of baseline patient characteristics between treatment groups in RCTs. Nevertheless, the authors decided, based on P values, that both groups were balanced and adjustment of potential confounders was not necessary. It needs to be emphasized that even nonsignificant (P .05) imbalances of strong prognostic factors may still result in substantial bias and therefore requires adjustment. For example, chronic obstructive pulmonary disease, diabetes mellitus, and congestive heart failure were not statistically imbalanced between the treatment groups and yet are important risk factors of mortality and hence potentially confounding the effects of telemonitoring. These questions actually reflect the largest drawback of the study: the lack of substantial insight in the assumed relation between patient characteristics, intervention, and outcome. In intervention testing, the RCT is the final step, following a sequence of steps from initial preclinical research through phase 1 and phase 2 studies. The study by Takahashi et al warrants careful consideration of the benefits of telehealth interventions. Moreover, it shows the need of careful development and testing of nonpharmaceutical interventions.","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 20","pages":"1612; author reply 1613"},"PeriodicalIF":0.0,"publicationDate":"2012-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.4421","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"31045748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1001/archinternmed.2012.4268
Jacqueline Baras Shreibati, Laurence C Baker, Mark A Hlatky, Matthew W Mell
Background: Since January 1, 2007, Medicare has covered abdominal aortic aneurysm (AAA) screening for new male enrollees with a history of smoking under the Screening Abdominal Aortic Aneurysms Very Efficiently (SAAAVE) Act. We examined the association between this program and abdominal ultrasonography for AAA screening, elective AAA repair, hospitalization for AAA rupture, and all-cause mortality.
Methods: We used a 20% sample of traditional Medicare enrollees from 2004 to 2008 to identify 65-year-old men eligible for screening and 3 control groups not eligible for screening (70-year-old men, 76-year-old men, and 65-year-old women). We used logistic regression to examine the change in outcomes at 365 days for eligible vs ineligible beneficiaries before and after SAAAVE Act implementation, adjusting for comorbidities, state-level smoking prevalence, geographic variation, and time trends.
Results: Fewer than 3% of abdominal ultrasonography claims after 2007 were for SAAAVE-specific AAA screening. There was a significantly greater increase in abdominal ultrasonography use among SAAAVE-eligible beneficiaries (2.0 percentage points among 65-year-old men, from 7.6% in 2004 to 9.6% in 2008; 0.7 points [8.9% to 9.6%] among 70-year-old men; 0.7 points [10.8% to 11.5%] among 76-year-old men; and 0.9 points [7.5% to 8.4%] among 65-year-old women) (P < .001 for all comparisons with 65-year-old men). The SAAAVE Act was associated with increased use of abdominal ultrasonography in 65-year-old men compared with 70-year-old men (adjusted odds ratio [AOR], 1.15; 95% CI, 1.11-1.19) (P < .001), and this increased use remained even when SAAAVE-specific AAA screening was excluded (AOR, 1.12; 95% CI, 1.08-1.16) (P < .001). Implementation of the SAAAVE Act was not associated with changes in rates of AAA repair, AAA rupture, or all-cause mortality.
Conclusions: The impact of the SAAAVE Act on AAA screening was modest and was based on abdominal ultrasonography use that it did not directly reimburse. The SAAAVE Act had no discernable effect on AAA rupture or all-cause morality.
{"title":"Impact of the Screening Abdominal Aortic Aneurysms Very Efficiently (SAAAVE) Act on abdominal ultrasonography use among Medicare beneficiaries.","authors":"Jacqueline Baras Shreibati, Laurence C Baker, Mark A Hlatky, Matthew W Mell","doi":"10.1001/archinternmed.2012.4268","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.4268","url":null,"abstract":"<p><strong>Background: </strong>Since January 1, 2007, Medicare has covered abdominal aortic aneurysm (AAA) screening for new male enrollees with a history of smoking under the Screening Abdominal Aortic Aneurysms Very Efficiently (SAAAVE) Act. We examined the association between this program and abdominal ultrasonography for AAA screening, elective AAA repair, hospitalization for AAA rupture, and all-cause mortality.</p><p><strong>Methods: </strong>We used a 20% sample of traditional Medicare enrollees from 2004 to 2008 to identify 65-year-old men eligible for screening and 3 control groups not eligible for screening (70-year-old men, 76-year-old men, and 65-year-old women). We used logistic regression to examine the change in outcomes at 365 days for eligible vs ineligible beneficiaries before and after SAAAVE Act implementation, adjusting for comorbidities, state-level smoking prevalence, geographic variation, and time trends.</p><p><strong>Results: </strong>Fewer than 3% of abdominal ultrasonography claims after 2007 were for SAAAVE-specific AAA screening. There was a significantly greater increase in abdominal ultrasonography use among SAAAVE-eligible beneficiaries (2.0 percentage points among 65-year-old men, from 7.6% in 2004 to 9.6% in 2008; 0.7 points [8.9% to 9.6%] among 70-year-old men; 0.7 points [10.8% to 11.5%] among 76-year-old men; and 0.9 points [7.5% to 8.4%] among 65-year-old women) (P < .001 for all comparisons with 65-year-old men). The SAAAVE Act was associated with increased use of abdominal ultrasonography in 65-year-old men compared with 70-year-old men (adjusted odds ratio [AOR], 1.15; 95% CI, 1.11-1.19) (P < .001), and this increased use remained even when SAAAVE-specific AAA screening was excluded (AOR, 1.12; 95% CI, 1.08-1.16) (P < .001). Implementation of the SAAAVE Act was not associated with changes in rates of AAA repair, AAA rupture, or all-cause mortality.</p><p><strong>Conclusions: </strong>The impact of the SAAAVE Act on AAA screening was modest and was based on abdominal ultrasonography use that it did not directly reimburse. The SAAAVE Act had no discernable effect on AAA rupture or all-cause morality.</p>","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 19","pages":"1456-62"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.4268","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30912463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1001/archinternmed.2012.4198
Andrew L Avins
{"title":"Needling the status quo.","authors":"Andrew L Avins","doi":"10.1001/archinternmed.2012.4198","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.4198","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 19","pages":"1454-5"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.4198","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30894676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-22DOI: 10.1001/archinternmed.2012.4309
Daniel J Brotman, Amir K Jaffer
{"title":"Resuming anticoagulation in the first week following gastrointestinal tract hemorrhage: should we adopt a 4-day rule?","authors":"Daniel J Brotman, Amir K Jaffer","doi":"10.1001/archinternmed.2012.4309","DOIUrl":"https://doi.org/10.1001/archinternmed.2012.4309","url":null,"abstract":"","PeriodicalId":8290,"journal":{"name":"Archives of internal medicine","volume":"172 19","pages":"1492-3"},"PeriodicalIF":0.0,"publicationDate":"2012-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/archinternmed.2012.4309","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"30912648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}