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Development and validation of a risk calculator for postoperative diplopia following orbital fracture repair in adults
被引:0
|作者:
Hassan, Bashar
[1
,2
]
Hricz, Nicholas
[3
]
Er, Seray
[3
]
Yoon, Joshua
[4
]
Resnick, Eric
[3
]
Liang, Fan
[2
]
Yang, Robin
[2
]
Manson, Paul N.
[2
]
Grant, Michael P.
[1
,5
]
机构:
[1] Univ Maryland, Med Ctr, Div Plast & Reconstruct Surg, R Adams Cowley Shock Trauma Ctr, Baltimore, MD 21201 USA
[2] Johns Hopkins Univ Hosp, Dept Plast & Reconstruct Surg, Baltimore, MD USA
[3] Univ Maryland, Sch Med, Baltimore, MD USA
[4] George Washington Univ, Dept Surg, Washington, DC USA
[5] Univ Maryland, Med Ctr, R Adams Cowley Shock Trauma Ctr, Div Plast & Reconstruct Surg, 110 S Paca St,Suite 4-S-124, Baltimore, MD 21201 USA
关键词:
SURGICAL REPAIR;
BLOWOUT FRACTURES;
FLOOR FRACTURES;
CALIBRATION;
INDEX;
SURGERY;
MODELS;
D O I:
10.1038/s41598-024-54121-w
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Postoperative diplopia is the most common complication following orbital fracture repair (OFR). Existing evidence on its risk factors is based on single-institution studies and small sample sizes. Our study is the first multi-center study to develop and validate a risk calculator for the prediction of postoperative diplopia following OFR. We reviewed trauma patients who underwent OFR at two high-volume trauma centers (2015-2019). Excluded were patients < 18 years old and those with postoperative follow-up < 2 weeks. Our primary outcome was incidence/persistence of postoperative diplopia at >= 2 weeks. A risk model for the prediction of postoperative diplopia was derived using a development dataset (70% of population) and validated using a validation dataset (remaining 30%). The C-statistic and Hosmer-Lemeshow tests were used to assess the risk model accuracy. A total of n = 254 adults were analyzed. The factors that predicted postoperative diplopia were: age at injury, preoperative enophthalmos, fracture size/displacement, surgical timing, globe/soft tissue repair, and medial wall involvement. Our predictive model had excellent discrimination (C-statistic = 80.4%), calibration (P = 0.2), and validation (C-statistic = 80%). Our model rules out postoperative diplopia with a 100% sensitivity and negative predictive value (NPV) for a probability < 8.9%. Our predictive model rules out postoperative diplopia with an 87.9% sensitivity and a 95.8% NPV for a probability < 13.4%. We designed the first validated risk calculator that can be used as a powerful screening tool to rule out postoperative diplopia following OFR in adults.
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页数:9
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