1.Scar Wars: Preferences in Breast Surgery.
Cormac W JOYCE ; Siun MURPHY ; Stephen MURPHY ; Jack L KELLY ; Colin M MORRISON
Archives of Plastic Surgery 2015;42(5):596-600
BACKGROUND: The uptake of breast reconstruction is ever increasing with procedures ranging from implant-based reconstructions to complex free tissue transfer. Little emphasis is placed on scarring when counseling patients yet they remain a significant source of morbidity and litigation. The aim of this study was to examine the scarring preferences of men and women in breast oncoplastic and reconstructive surgery. METHODS: Five hundred men and women were asked to fill out a four-page questionnaire in two large Irish centres. They were asked about their opinions on scarring post breast surgery and were also asked to rank the common scarring patterns in wide local excisions, oncoplastic procedures, breast reconstructions as well as donor sites. RESULTS: Fifty-eight percent of those surveyed did not feel scars were important post breast cancer surgery. 61% said that their partners' opinion of scars were important. The most preferred wide local excision scar was the lower lateral quadrant scar whilst the scars from the deep inferior epigastric artery perforator (DIEP) flap were most favoured. The superior gluteal artery perforator flap had the most preferred donor site while surprisingly, the DIEP had the least favourite donor site. CONCLUSIONS: Scars are often overlooked when planning breast surgery yet the extent and position of the scar needs to be outlined to patients and it should play an important role in selecting a breast reconstruction option. This study highlights the need for further evaluation of patients' opinions regarding scar patterns.
Arteries
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Breast Neoplasms
;
Breast*
;
Cicatrix*
;
Counseling
;
Epigastric Arteries
;
Female
;
Humans
;
Jurisprudence
;
Male
;
Mammaplasty
;
Perforator Flap
;
Tissue Donors
3.Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty
Stephen J. WALLACE ; Michael P. MURPHY ; Corey J. SCHIFFMAN ; William J. HOPKINSON ; Nicholas M. BROWN
The Journal of Korean Knee Society 2020;32(4):e63-
Background:
Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA.
Materials and methods:
A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA.Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions.
Results:
Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size.The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components.
Conclusions
A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.Level of evidence: Prospective cohort, level II.
4.Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty
Stephen J. WALLACE ; Michael P. MURPHY ; Corey J. SCHIFFMAN ; William J. HOPKINSON ; Nicholas M. BROWN
The Journal of Korean Knee Society 2020;32(4):e63-
Background:
Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA.
Materials and methods:
A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA.Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions.
Results:
Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size.The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components.
Conclusions
A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.Level of evidence: Prospective cohort, level II.