Total knee replacement; minimal clinically important differences and responders.

OBJECTIVE: To provide new data on minimally clinical important difference (MCID) and percentages of responders on pain and functional dimensions of Western Ontario and McMaster Osteoarthritis Index (WOMAC) in patients who have undergone total knee replacement (TKR). METHODS: 1-year prospective multicentre study with two different cohorts. Consecutive patients on the waiting list were recruited. There were 415 and 497 patients included. Pain and function were collected by the reverse scoring option of the WOMAC (0-100, worst to best). Transition items (five point scale) were collected at 1-year and MCID was calculated through mean change in patients somewhat better, Receiver Operating Characteristic (ROC) and two other questions about satisfaction. Analysis was performed in the whole sample and by tertiles of baseline severity. Likewise were calculated the percentages of patients who attained cut-off values. RESULTS: Global MCID for pain were about 30 in both cohorts and 32 for. By ROC these values were about 20 and 24 respectively. According to the other two transitional questions these values were for pain 27 and 20 for function. By tertiles the worst the baseline score the higher the cut-off values. Percentage of responders does not change when comparing responders to the global MCID with their own tertile MCID and were about 61% for pain and 50% for function. CONCLUSION: Due to the wide variations, MCID estimates should be calculated and used according to the baseline severity score.

Patient acceptable symptom state and OMERACT-OARSI set of responder criteria in joint replacement. Identification of cut-off values.

OBJECTIVE: To identify new cut-off values beyond which patients can be considered as satisfied or as responders through patient acceptable symptom state (PASS) and OMERACT-OARSI (Outcome Measures in Rheumatology-Osteoarthritis Research Society International) set of responder criteria in total joint replacement. METHODS: Secondary analysis of a 1-year prospective multicenter study of 861 patients, 510 with total knee replacement (TKR) and 351 with total hip prosthesis (THR). Pain and function data were collected by the reverse scoring option of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). PASS values were identified with the 25th centile estimation using an anchoring question about satisfaction with actual symptoms. OMERACT-OARSI set of responder criteria was based on a combination of absolute and relative change of pain, function and global patient's assessment. Receiver operating characteristic (ROC) analysis was used as a complementary approach. RESULTS: The values for PASS were about 80 and 69 for pain and function in THR, while these values were 80 and 68 when using OMERACT-OARSI criteria. Regarding TKR, PASS values were about 75 and 67 in pain and function with both criteria. ROC values were slightly lower in all cases. PASS and OMERACT-OARSI values varied moderately across tertiles of baseline severity. CONCLUSION: With the provided data we can establish when a patient can be considered as satisfied/responder in joint replacement. The scores achieved at 1 year were very similar according to both criteria.

Total knee replacement: Are there any baseline factors that have influence in patient reported outcomes?

BACKGROUND: There is conflicting evidence about what factors influence outcomes after total knee replacement (TKR). The objective is to identify baseline factors that differentiate patients who achieve both, minimal clinically important difference (MCID) and a patient acceptable symptom state (PASS) in pain and function, measured by WOMAC, after TKR from those who do not attain scores above the cutoff in either of these dimensions. METHODS: One-year prospective multicentre study. Patients completed WOMAC, SF-12, EQ-5D, expectations, other joint problems and sociodemographic data while in the waiting list, and 1-year post-TKR. Dependent variable was a combination of MCID and PASS in both dimensions (yes/no). Univariate analysis was performed to identify variables associated. Exploratory factor analysis (EFA) was performed to study how these variables grouped into different factors. RESULTS: Total sample comprised 492 patients. Mean (SD) age was 71.3 (6.9), and there were a 69.7% of women. Of the total, 106 patients did not attain either MCID or PASS in either dimension, and 230 exceeded both thresholds in both dimensions. In the univariate analysis, 13 variables were associated with belonging to one group or another. These 13 variables were included in EFA; 3 factors were extracted: expectations, mental health, and other joints problems. The percentage of variance explained by the 3 factors was 80.4%. CONCLUSION: We have found 2 modifiable baseline factors, expectations and mental health, that should be properly managed by different specialist. Indication of TKR should take into account these modifiable factors for improving outcomes after TKR.

[Nursing professionals' reading habits; a study in a hospital in Granada]. / Hábitos de lectura en enfermería: estudio en un hospital de granada.

In all the hospital library standards, as well as in the existing Accreditation Norms for hospitals, a section is included which cites the distinct professionals who work at the institution which the library services must attend to provide for their scientific information needs. Among the sanitary collectives, nursing professionals are explicitly listed. Nonetheless, since the creation of hospital library services in Spain, many librarians have noticed that the nursing professionals, which compose the most numerous group in a hospital, have a very low library visitation rate in relationship to other collectives such as doctors in particular. Desiring to have objective data regarding library use, and not merely perceptions, the authors planned out a study in a large, 1.200 bed, hospital where more than 1.000 professionals comprise the nursing staff. The authors wanted to verify the nursing staff's needs for scientific information, their habits regarding their scientific information needs, and the possible difficulties which they encounter trying to acquire this type of information; furthermore, the authors wanted to know the nursing professionals' attitude towards this issue.

Automated segmentation of cell nuclei in fine needle aspirates of the breast.

OBJECTIVE: To achieve a classifier of breast lesions to discriminate between benign and malignant cases of cytologic smears with automated segmentation image analysis techniques. STUDY DESIGN: The techniques were applied to images of epithelial cell nuclei from cytologic smears obtained by fine needle aspiration. The images of the nuclei were taken from 95 cases of malignant lesions and 47 benign (approximately 25 nuclei per case), and 28 nuclear variables were measured. The data were analyzed by a double methodology, discriminant analysis and classification and regression trees (CART), to determine which provided the best results. RESULTS: CART selected the SD of the nuclear area with correct classification of 85.1% of benign and 94.7% malignant aspirates. Discriminant analysis selected the group of variables formed by axis lengths, SD of the longest axis, sphericity and variance of gray levels, with results similar to those of CART. CONCLUSION: Automated segmentation image analysis techniques were effective, and the classifier was quick, simple and efficacious in malignant-benign discrimination.

Diagnosis of breast cancer by measuring nuclear disorder using planar graphs.

OBJECTIVE: To achieve a classifier of breast lesions to distinguish benign from malignant mammary lesions by quantifying nuclear disorder in epithelial cell groups from smears obtained by fine needle aspiration. STUDY DESIGN: The study included 95 cases of breast cancer (289 groups) and 47 of benign breast lesions (150 groups), diagnosed by cytology. Information from planar graphs (mean of nuclear distances, standard deviation, maximum and minimum distance between nuclei) was used, and an algorithm constructed for this purpose was applied. The data were classified by double methodology--discriminant analysis, and classification and regression trees (CART)--to determine which achieved the best results. RESULTS: CART selected the standard deviation of nuclear distances with accurate classification in 95.7% of benign lesions and 97.9% of malignant. Discriminant analysis constructed the discriminant function using the mean of nuclear distances and its standard deviation, with results similar to those of CART. CONCLUSION: The classifier based on nuclear disorder that we constructed proved to be rapid, simple and effective for malignant-benign discrimination in breast lesions and should be of diagnostic assistance.