CoChat
Sign Up
Cited by 58

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Association between guideline recommended drugs and death in older adults with multiple chronic conditions: population based cohort study

Tinetti, Mary E, McAvay, Gail, Trentalange, Mark, Cohen, Andrew B, Allore, Heather G·2015·BMJ
DOI 10.1136/bmj.h4984PMC PMC4591503
Open this paper in CoChat — free account

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1136/bmj.h4984

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig 1 Adjusted hazard ratios of death associated with guideline recommended cardiovascular drugs for older adults with chronic conditions. AF=atrial fibrillation; CAD=coronary artery disease; DEP=depression; DM=diabetes; HF=heart failure; HL=hyperlipidemia; HTN=hypertension. Hazard ratios are adjusted for the covariates described in the Methods section,as well as number of drugs other than the study drugs, and all coexisting study conditions and drugs
Fig 1 Adjusted hazard ratios of death associated with guideline recommended cardiovascular drugs for older adults with chronic conditions. AF=atrial fibrillation; CAD=coronary artery disease; DEP=depression; DM=diabetes; HF=heart failure; HL=hyperlipidemia; HTN=hypertension. Hazard ratios are adjusted for the covariates described in the Methods section,as well as number of drugs other than the study drugs, and all coexisting study conditions and drugsCC BY-NC · PubMed Central
Fig 2 Adjusted hazard ratios of death associated with commonly used guideline recommended drugs for older adults with chronic conditions. AF=atrial fibrillation; CAD=coronary artery disease; DEP=depression; DM=diabetes; HF=heart failure; HL=hyperlipidemia; HTN=hypertension; SSRIs= selective serotonin reuptake inhibitors; SNRIs=serotonin norepinephrine reuptake inhibitors. Hazard ratios are adjusted for the covariates described in the Methods section as well asnumber of drugs other than the study drug and all coexisting study conditions and drugs
Fig 2 Adjusted hazard ratios of death associated with commonly used guideline recommended drugs for older adults with chronic conditions. AF=atrial fibrillation; CAD=coronary artery disease; DEP=depression; DM=diabetes; HF=heart failure; HL=hyperlipidemia; HTN=hypertension; SSRIs= selective serotonin reuptake inhibitors; SNRIs=serotonin norepinephrine reuptake inhibitors. Hazard ratios are adjusted for the covariates described in the Methods section as well asnumber of drugs other than the study drug and all coexisting study conditions and drugsCC BY-NC · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 41

  1. [1]Gorina Y, Lentzer H. Multiple causes of death in old age. Aging Trends 2008;(9):1-9. 19174856
  2. [3]Hoyert DL, Xu JQ. Deaths: preliminary data for 2011. National Vital Statistics Reports; Vol 61 No 6. National Center for Health Statistics; 2012. 24984457
  3. [4]Tinetti ME, McAvay G, Murphy T, Allore H, Gross, C, Lin H. Contribution of individual diseases to death in older adults with multiple diseases. J Am Geriatr Soc 2012; 60: 1448-56. 22734792 PMC3419332
  4. [5]Tinetti ME, McAvay G, Chang SS, et al. Contribution of multiple chronic conditions to universal health outcomes. J Am Geriatr Soc 2011; 59: 1686-91. 21883118 PMC3622699
  5. [6]Smith SC Jr, Benjamin EJ, Bonow RO, et al. AHA/ACCF secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease: 2011 update: a guideline from the American Heart Association and American College of Cardiology Foundation. Circulation 2011; 124: 2458-73. 22052934
  6. [8]January CT, Wann LS, Alpert JS. 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society. Circulation 2014; 130: 2071-104. 24682348
  7. [9]Yancy CW, Jessup M, Bozkurt B, et al. 2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2013; 62: e147-239. 23747642
  8. [11]James PA, Oparil S, Carter BL, et al. 2014 Evidence-based guideline for the management of high blood pressure in adults. Report From the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014; 311: 507-20. 24352797
  9. [12]Bajcar JM, Li Wang L, Moineddin R, Nie JX, Tracy CS, Upshur REG. From pharmaco-therapy to pharmaco-prevention: trends in prescribing to older adults in Ontario, Canada, 1997-2006. BMC Fam Pract 2010; 11: 75. 20929561 PMC2958963
  10. [13]National Center for Health Statistics. Health, United States, 2013: with special feature on prescription drugs. CDC, 2014. www.cdc.gov/nchs/data/hus/hus13.pdf. 24967476
  11. [14]Tran VT, Harrington M, Montori VM, Barnes C, Wicks P, Ravaud P. Adaptation and validation of the Treatment Burden Questionnaire (TBQ) in English using an internet platform. BMC Med 2014; 12: 109. 24989988 PMC4098922
  12. [15]Taché SV, Sönnichsen A, Ashcroft DM. Prevalence of adverse drug events in ambulatory care: a systematic review. Ann Pharmacother 2011; 45: 977-89. 21693697
  13. [16]Hakkarainen KM, Hedna K, Petzold M, Hägg S. Percentage of patients with preventable adverse drug reactions and preventability of adverse drug reactions: a meta-analysis. PLoS One 2012; 7: e33236. 22438900 PMC3305295
  14. [20]Healthcare Cost and Utilization Project (HCUP). Clinical classification system. Agency for Healthcare Research and Quality. 2012. www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. 21413206
  15. [21]Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation 2014; 129(25 Suppl 2): S1-45. 24222016
  16. [22]Guyatt GH, Akl EA, Crowther M, Gutterman DD, Schuünemann HJ, for the American College of Chest Physicians Antithrombotic Therapy and Prevention of Thrombosis Panel. Executive Summary: Antithrombotic Therapy and Prevention of Thrombosis, 9th ed: American College of Chest Physicians Evidence-Based Clinical Practice Guidelines. Chest 2012; 141(2_suppl): 7S-47S. 22315257 PMC3278060
  17. [24]Nagi SZ. An epidemiology of disability among adults in the United States. Milbank Mem Fund Q Health Soc 1976; 54: 439-67. 137366
  18. [25]Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care 1998; 36: 8-27. 9431328
  19. [26]Quan H, Sundararajan V, Halfon P, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care 2005; 43: 1130-9. 16224307
  20. [27]Therneau TM, Grambsch PM. Modeling survival data: extending the Cox model. Springer-Verlag; 2000.
  21. [28]Sturmer T, Joshia M, Glynn RJ, et al. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. J Clin Epidemiol 2006; 59: 437-47. 16632131 PMC1448214
  22. [29]O’Brien EC, Kim S, Hess PL. Effect of the 2014 atrial fibrillation guideline revisions on the proportion of patients recommended for oral anticoagulation. JAMA Intern Med 2015; 175: 848-50. 25730606
  23. [30]The AFFIRM Investigators. Relationships Between Sinus Rhythm, Treatment, and Survival in the Atrial Fibrillation Follow-Up Investigation of Rhythm Management (AFFIRM) Study. Circulation 2004; 109: 1509-13. 15007003
  24. [31]Afilalo DJ, Duque G, Russell Steele R, et al. Statins for secondary prevention in elderly patients; a hierarchical bayesian meta-analysis. Am Coll Cardiol 2008; 51: 437-51. 18174034
  25. [32]Pfeffer MA, Swedberg K, Granger CB, et al. Effects of candesartan on mortality and morbidity in patients with chronic heart failure: the CHARM-Overall programme. Lancet 2003; 362: 759-66. 13678868
  26. [34]Cleland JG, Tendera M, Adamus J, Freemantle N, Polonski L, Taylor J. The Perindopril in elderly people with chronic heart failure (PEP-CHF) study. Eur Heart J 2006; 27: 2338-2345. 16963472
  27. [35]Yusuf S, Pfeffer MA, Swedberg K, et al. Effects of candesartan in patients with chronic heart failure and preserved left-ventricular ejection fraction: the CHARM-Preserved Trial. Lancet 2003; 362: 777-81. 13678871
  28. [36]Bogner HR, Morales KH, Post EP, Bruce ML. Diabetes, depression, and death. A randomized controlled trial of a depression treatment program for older adults based in primary care (PROSPECT). Diabetes Care 2007; 30: 3005-10. 17717284 PMC2803110
  29. [37]Bhatt DL, Fox KA, Hacke W, et al Clopidogrel and aspirin versus aspirin alone for the prevention of atherothrombotic events. N Engl J Med 2006; 354: 1706-17. 16531616
  30. [38]Dogliotti A, Paolasso E, Giuliano RP. Current and new oral antithrombotics in non-valvular atrial fibrillation: a network meta-analysis of 79808 patients. Heart 2014; 100: 396-405. 24009224
  31. [39]Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HAW. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008; 359: 1577-89. 18784090
  32. [40]Roussel R, Tavert F, Pasquet B. Metformin use and mortality among patients with diabetes and atherothrombosis. Arch Intern Med 2010; 170: 1892-9. 21098347
  33. [41]Dhruva SS, Redberg RF. Variations between clinical trial participants and Medicare beneficiaries in evidence used for Medicare national coverage decisions. Arch Intern Med 2008; 168: 136-40. 18227358
  34. [42]American Geriatrics Society expert panel on the care of older adults with multimorbidity. Patient-centered care for older adults with multiple chronic conditions: a stepwise approach from the American Geriatrics Society. J Am Geriatr Soc 2012; 60: 1957-68. 22994844 PMC4459791
  35. [44]Pilotto A, Addante F, Ferrucci L, et al. The multidimensional prognostic index predicts short- and long-term mortality in hospitalized geriatric patients with pneumonia. J Gerontol A Biol Sci Med Sci 2009; 64: 880-7. 19349589 PMC2981465
  36. [45]Klabunde CN, Harlan LC, Warren JL. Data sources for measuring comorbidity. A comparison of hospital records and Medicare claims data for cancer patients. Med Care 2006; 44: 921-8. 17001263
  37. [46]Lentine KL, Schnitzler MA, Abbott KC, Bramesfeld K, Buchanan PM, Brennan DC. Sensitivity of billing claims for cardiovascular disease events among kidney transplant recipients. Clin J Am Soc Nephrol 2009; 4: 1213-21. 19541817 PMC2709516
  38. [47]Noyes K, Liu H, Lyness JM, Friedman B. Medicare beneficiaries with depression: Comparing diagnoses in claims data with the results of screening. Psychiatr Serv 2011; 62: 1159-66. 21969642
  39. [49]Johnson ES, Bartman BA, Briesacher BA, et al. The incident user design in comparative effectiveness research. Pharmacoepidemiol Drug Saf 2012; 22: 1-6. 23023988
  40. [50]Shrank WH, Patrick AR, Brookhart MA. Healthy user and related biases in observational studies of preventive interventions: a primer for physicians. J Gen Intern Med 2011; 26: 546-50. 21203857 PMC3077477
  41. [51]Fried TR, McGraw S, Agostini JV, Tinetti ME. Views of older persons with multiple conditions on competing outcomes and clinical decision-making. J Am Geriatr Soc 2008; 56: 1839-44. 18771453 PMC2596278

Cited by

Sorted by citations

See all 58

Metadata

Authors
Tinetti, M. E., McAvay, G., Trentalange, M., Cohen, A. B., & Allore, H. G.
Venue
BMJ
Publisher
BMJ
Published
2015-10-02
Pages
h4984
ISSN
1756-1833
DOI
10.1136/bmj.h4984
PMC
PMC4591503
Cited by
58
References
5
Language
en
Licence
www.bmj.org/licenses/tdm/1.0/terms-and-conditions.html (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review