Related Articles

Need for tailored strategies to diagnose venous thrombo-embolism in older primary care patients. Extension of a keynote presentation at the 2012 Wonca Europe conference.

Eur J Gen Pract. 2013 Jan 22;

Authors: Schouten HJ, Koek HL, Moons KG, van Delden JJ, Oudega R, Geersing GJ

Abstract
Venous thrombo-embolism (VTE, pulmonary embolism and deep vein thrombosis) is common in the elderly and short-term mortality risk increases with age. Hence, notably in older patients, accurately diagnosing VTE can be lifesaving. However, most clinically suspected individuals turn out to have no VTE after imaging examination. Therefore, many physicians would feel reluctant to refer older patients as this can be very burdensome for these patients. Consequently, it is possible that elderly patients are often not referred for diagnostic work-up (risk of under diagnosis), or that treatment for VTE is initiated without confirmation by further testing (risk of overtreatment). Moreover, anticoagulation treatment of VTE is associated with a higher bleeding risk in the elderly. This bleeding risk might even outweigh the potential benefits in some of these patients. Therefore, availability of an accurate diagnostic strategy to safely exclude, and timely diagnose VTE without the need of burdening referrals in many patients might better serve the needs of older patients. Such strategies have been derived and validated in both primary and secondary care patients suspected of VTE. However, the generalizability of these strategies to older patients may be hampered, and their accuracy has never been tested in elderly populations; this in spite of the high prevalence of VTE and the potential for misdiagnosis and thus mistreatment in these patients. Therefore, we advocate validation and adaptation of current diagnostic strategies for VTE for application in elderly patients.

PMID: 23339596 [PubMed - as supplied by publisher]

Related Articles

Management of Patients With Unprovoked Venous Thromboembolism: An Evidence-Based and Practical Approach.

Curr Treat Options Cardiovasc Med. 2013 Jan 24;

Authors: Marcucci M, Iorio A, Douketis J

Abstract
OPINION STATEMENT: The management of patients with unprovoked venous thromboembolism is a common and challenging clinical problem. Although the initial antithrombotic management is well-established, there is uncertainty about the optimal long-term anticoagulant management, specifically whether patients should receive a short (i.e., 3- to 6-month) duration of anticoagulant therapy or indefinite anticoagulation. Factors that may be considered to estimate patients' risk for recurrent thromboembolism include the mode of initial clinical presentation, as deep vein thrombosis or pulmonary embolism, patient sex, antecedent hormonal therapy use, thrombophilia, D-dimer levels, and residual vein occlusion in patients with deep vein thrombosis. Many of these factors have been integrated into clinical prediction guides which stratify patients with unprovoked venous thromboembolism according to their risk for disease recurrence and, thereby, can assist clinicians in decisions about the duration of anticoagulation. The objective of this review is to consider the evidence relating to the clinical significance of purported risk factors and provide a practical case-based approach to guide decisions on duration of anticoagulation for patients with unprovoked venous thromboembolism.

PMID: 23344704 [PubMed - as supplied by publisher]

Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm.

Br J Gen Pract. 2013 Jan;63(606):1-10

Authors: Hippisley-Cox J, Coupland C

Abstract
BACKGROUND: Early diagnosis of cancer could improve survival so better tools are needed.
AIM: To derive an algorithm to estimate absolute risks of different types of cancer in men incorporating multiple symptoms and risk factors.
DESIGN AND SETTING: Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation.
METHOD: Included patients were males aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, renal, blood, prostate, testicular, other cancer). Factors examined were: 'red flag' symptoms such as weight loss, abdominal distension, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms such as tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation score and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort.
RESULTS: There were 22 521 cancers from 1 263 071 males in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, COPD, diabetes, family history, alcohol, smoking, deprivation); 22 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operator curve statistics values were: lung (0.92), colorectal (0.92), gastro-oesophageal (0.93), pancreas (0.89), renal (0.94), prostate (0.90) blood (0.83, testis (0.82); other cancers (0.86). The 10% of males with the highest risks contained 59% of all cancers diagnosed over 2 years.
CONCLUSION: The algorithm has good discrimination and could be used to identify those at highest risk of cancer to facilitate more timely referral and investigation.

PMID: 23336443 [PubMed - in process]

Symptoms and risk factors to identify women with suspected cancer in primary care: derivation and validation of an algorithm.

Br J Gen Pract. 2013 Jan;63(606):11-21

Authors: Hippisley-Cox J, Coupland C

Abstract
BACKGROUND: Early diagnosis of cancer could improve survival so better tools are needed.
AIM: To derive an algorithm to estimate absolute risks of different types of cancer in women incorporating multiple symptoms and risk factors. Design and setting: Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation.
METHOD: Included patients were females aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal, pancreatic, ovarian, renal tract, breast, blood, uterine, cervix, other). Factors examined were: 'red flag' symptoms including weight loss, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms including tiredness, constipation; and risk factors including age, family history, smoking, alcohol intake, deprivation, body mass index (BMI), and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort.
RESULTS: There were 23 216 cancers from 1 240 864 females in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, chronic obstructive pulmonary disease, diabetes, family history, alcohol, smoking, deprivation); 23 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination. The receiver operating curve statistics were lung (0.91), colorectal (0.89), gastro-oesophageal (0.90), pancreas (0.87), ovary (0.84), renal (0.90), breast (0.88), blood (0.79), uterus (0.91), cervix (0.73), other cancer (0.82). The 10% of females with the highest risks contained 54% of all cancers diagnosed over 2 years.
CONCLUSION: The algorithm has good discrimination and could be used to identify those at highest risk of cancer to facilitate more timely referral and investigation.

PMID: 23336450 [PubMed - in process]