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Predictive Scores (predictive + score)
Selected AbstractsDiscontinuation of prophylactic therapy in severe haemophilia: incidence and effects on outcomeHAEMOPHILIA, Issue 6 2001K. Fischer A cohort study was performed to assess adherence to early prophylactic therapy and its effects on outcome in 49 patients with severe haemophilia born 1970,1980. Median age at start of prophylaxis was 5.5 years. The majority (69%) of patients interrupted prophylactic treatment one or more times of their own accord (median total interruption 2.2 years). Patients who discontinued prophylaxis at any point tended to have more arthropathy as measured by the Pettersson scale (median 8 points versus 4 points). One-third of these patients interrupted prophylaxis for longer periods and had permanently stopped taking prophylaxis at a mean age of 20.1 years (mean ± SD duration 4.1 ± 4 years) and consequently experienced 5.4 ± 3.4) joint bleeds per year. This subgroup could be identified by a predictive score based on age at start of prophylaxis, weekly dose of prophylaxis, and joint bleed frequency on prophylaxis. In conclusion, while on prophylaxis, more than two-thirds of patients with severe haemophilia try to discontinue treatment, resulting in slightly more arthropathy. One-third of these patients permanently discontinue prophylaxis in adulthood, while maintaining a low number of joint bleeds. [source] Development of a simple scoring tool in the primary care setting for prediction of recurrent falls in men and women aged 65 years and over living in the communityJOURNAL OF CLINICAL NURSING, Issue 7 2009Jean Woo Aim., We documented the number of falls and falls risk profile over two years to derive a falls risks prediction score. Background., Simple falls risk assessment tools not requiring equipment or trained personnel may be used as a first step in the primary care setting to identify older people at risk who may be referred for further falls risk assessment in special clinics. Design., Survey. Method., Men (n = 1941) and 1949 women aged 65 years and over living in the community were followed up for two years to document the number of falls. Information was collected regarding demography, socioeconomic status, medical history, functional limitations, lifestyle factors and psychosocial functioning. Measurements include body mass index, grip strength and stride length. Logistic regression was used to determine significant predictions of falls and to calculate predictive scores. Result., Twelve factors in men and nine factors in women were used to construct a risk score. The AUC of the receiver operating characteristic curve was >0·70 for both men and women and a cut off score of ,8 gave sensitivity and specificity values between 60,78%. The factors included chronic disease, drugs, functional limitation, lifestyle, education and psychosocial factors. When applied to future predictions, only low energy level and clumsiness in both hands in men and feeling downhearted in women, were significant factors. Conclusions., A risk assessment tool with a cut off score of ,8 developed from a two-year prospective study of falls may be used in the community setting as an initial first step for screening out those at low risk of falls. Relevance to clinical practice., A simple tool may be used in the community to screen out those at risk for falls, concentrating trained healthcare professionals' time on detailed falls assessment and intervention for those classified as being at risk. [source] Can the Neuropathic Pain Scale Discriminate Between Non-neuropathic and Neuropathic Pain?PAIN MEDICINE, Issue 2 2008David A. Fishbain MD, FAPA ABSTRACT Objectives., 1) To determine if the neuropathic pain scale (NPS) can be used to classify chronic pain patients (CPPs) as having primarily neuropathic vs non-neuropathic pain, and furthermore; 2) to determine what, if any, cut-off score can be used to reliably make this determination. Design., A total of 305 CPPs consecutive admissions to The Rosomoff Pain Center were administered the NPS and were assigned a diagnosis according to the physical examination and all available test results. CPPs with a diagnosis of chronic radiculopathy and spondylolysis/degenerative arthritis were segregated into two groups for the purposes of having a group representative of neuropathic pain (chronic radiculopathy) and non-neuropathic pain (spondylolysis/degenerative arthritis). Applying neuropathic pain criteria to each "of these two groups": a neuropathic pain "subtype" was identified within the chronic radiculopathy group; and, a non-neuropathic pain "subtype" was identified within the spondylolysis/degenerative arthritis group. This step was performed in order to assure that the CPPs selected for further analysis were truly representative of neuropathic and non-neuropathic pain. Discriminant function analysis was then employed to determine if NPS scoring could differentiate between these two "subtypes." Results from the discriminant function analysis model were utilized to derive an NPS cut-off score above which CPPs would be classified as having neuropathic pain. For the diagnoses of myofascial pain syndromes, spinal stenosis, epidural fibrosis, fibromyalgia, complex regional pain syndromes 1 and 2, and failed back surgery syndrome, a predicted NPS score was calculated and compared with the cut-off score. Setting., Multidisciplinary pain facility. Patients., Chronic pain patients. Results., The NPS appeared to be able to separate CPPs into neuropathic pain vs non-neuropathic pain subtypes. The derived cut-off score from the model was 5.53. Myofascial pain syndrome and spinal stenosis had predictive scores lower than this cut-off score at 3.81 and 4.26, respectively. Epidural fibrosis, fibromyalgia, complex regional pain syndromes 1 and 2, and failed back surgery syndrome had predictive scores higher than the cut-off score at 6.15, 6.35, 6.87, 9.34, and 7.19, respectively. Conclusions., The NPS appears to be able to discriminate between neuropathic and non-neuropathic pain. A debate is currently raging as to whether diagnoses, such as fibromyalgia and complex regional pain syndrome 1, can be classified as neuropathic. Our NPS cut-off score results suggest that these diagnoses may have a neuropathic pain component. The reliability and validity of our NPS method will need to be tested further in other neuropathic pain models, such as diabetic peripheral neuropathic pain. [source] Validation study of the prediction system for clinical response of M-VAC neoadjuvant chemotherapyCANCER SCIENCE, Issue 1 2007Ryo Takata To predict the efficacy of the M-VAC neoadjuvant chemotherapy for invasive bladder cancers, we previously established the method to calculate the prediction score on the basis of expression profiles of 14 predictive genes. This scoring system had clearly distinguished the responder group from the non-responder group. To further validate the clinical significance of the system, we applied it to 22 additional cases of bladder cancer patients and found that the scoring system correctly predicted clinical response for 19 of the 22 test cases. The group of patients with positive predictive scores had significantly longer survival than that with negative scores. When we compared our results with a previous report describing the prognosis of the patients with cystectomy alone, the results imply that patients with positive scores are likely to benefit from M-VAC neoadjuvant chemotherapy, but that the chemotherapy would shorten the lives of patients with negative scores. We are confident that our prediction system to M-VAC therapy should provide opportunities for achieving better prognosis and improving the quality of life of patients. Taken together, our data suggest that the goal of ,personalized medicine', prescribing the appropriate treatment regimen for each patient, may be achievable by selecting specific sets of genes for their predictive values according to the approach shown here. (Cancer Sci 2007; 98: 113,117) [source] | ||||||||||