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Biomedical subjects

T G Nick

Publications and source records attributed to T G Nick.

40 records · Page 3Linked to original sources
PubMedDate not supplied

Results following trapeziometacarpal arthroplasty of the thumb.

A retrospective follow-up study was performed on patients with degenerative joint disease (DJD) who underwent trapeziometacarpal arthroplasty of the thumb with 3-week immobilization and without the use of K-wire fixation. Pre- and post-operative pain, activities of daily living (ADLs), grip strength, and pinch strength were compared. Data were collected on 25 hands in 23 patients, 7 hands with full trapezium resections and 18 with hemi-trapezium resections. The median age was 60 years, with a range of 39 to 73 years, and the median follow-up period was 1 year 11 months, with a range of 3 months to 11 years. Grip and pinch strength were measured pre- and postoperatively. Pain was assessed on a visual analog scale (VAS), and ADLs were assessed by means of a 15-item survey. Both pain and ADLs were evaluated postoperatively with recall of preoperative status. Following surgery, all thumbs were immobilized in a static splint for 3 weeks and then allowed progressive use. Median improvements in hemi-trapezium resections included grip, 22.5 lb; pinch, 4.7 lb; and ADLs, 33%. Pain was reduced a median of 7.0 cm on the VAS. Median improvements in full trapezium resection included grip, 29.5 lb; pinch, 0 lb; ADLs, 60%; and pain reduction, 8 cm on the VAS. This follow-up study suggests that satisfactory results can be achieved in pain reduction, strength, and ADLs with an immobilization period of only 3 weeks and without the use of K-wires following carpometacarpal (CMC) arthroplasty.

Activities of Daily Living↗
PubMedDate not supplied

The out-of-hospital use of a domestic violence screen for assessing patient risk.

OBJECTIVES: To determine the following: 1) whether a Domestic Violence Scene Assessment Screen (DVSAS) is accurate at predicting domestic violence (DV) when compared with results on the validated Abuse Assessment Screen (AAS), and 2) whether EMTs can perform accurately on a DVSAS after they have finished a transport so as not to interfere with routine care. METHODS: All patients transported by ambulance from domestic environments (i.e., home) by an urban EMS system were included in the study. A ten-question screen was developed to assess whether a domestic environment had a high risk of having DV (DVSAS). A positive answer to any of the questions was considered to be a positive result on the screen. A trained observer with no clinical duties rode on the ambulance for randomized shifts during a two-month period. The observer completed the DVSAS while at the scene, then the patient, if able, completed the AAS. After finishing the transport, the EMT completed the DVSAS based on his or her memory of the scene. Results of the observer DVSAS were compared with the results of the EMT DVSAS and with the AAS. RESULTS: A total of 43 transports from domestic scenes were included in the study. The observer DVSAS alone was positive in five cases (12%), the EMT DVSAS alone was positive in five cases (12%), and both were positive in seven cases (17%). Agreement between the EMT and the observer yielded a kappa of 0.56 adjusted for chance. Of 15 (42%) patients able to complete the AAS, one (7%) was positive on the AAS alone, four (27%) were positive on the observer DVSAS alone, and three (29%) were positive on both. The observer DVSAS agreed with the AAS results in ten of 15 (66%) of cases. When compared with the AAS, the observer DVSAS had a sensitivity of 75%, specificity of 55%, positive predictive value of 38%, and negative predictive value of 86%. CONCLUSION: Emergency medical technicians can complete the DVSAS at the end of a transport with good agreement with results obtained by an independent observer at the scene. The DVSAS is able to reflect the results of the AAS with moderate to good agreement.

Ambulances↗
PubMedDate not supplied

Regression modeling strategies: an illustrative case study from medical rehabilitation outcomes research.

The practice of outcomes research is growing in all segments of the health care industry, yet few practitioners and researchers are prepared to deal with the completion of statistical analyses that characterize the new focus on results. This article discusses basic model formulation and interpretation. It also encourages the use of statistical models that study the simultaneous effects of many variables on an outcome and gives examples of relationships among variables that are not simple and linear. The methods are illustrated with a dataset consisting of stroke rehabilitation inpatients discharged during a 3-year period with an admission date that is within 1 year after stroke.

Forecasting↗