Post-operative protein supplementation following orthopaedic surgery: A systematic review

Decreased mechanical loading after orthopaedic surgery predisposes patients to develop muscle atrophy.The purpose of this review was to assess whether the evidence supports oral protein supplementation can help decrease postoperative muscle atrophy and/or improve patient outcomes following orthopaedic surgery.A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and MetaAnalysis(PRISMA).PubMed(MEDLINE),Embase,Scopus,and Web of Science were searched for randomized controlled trials that assessed protein or amino acid supplementation in patients undergoing orthopaedic surgery.Two investigators independently conducted the search using relevant Boolean operations.Primary outcomes included functional or physiologic measures of muscle atrophy or strength.Fourteen studies including 611 patients(224 males,387 females)were analyzed.Three studies evaluated protein supplementation after ACL reconstruction(ACLR),3 after total hip arthroplasty(THA),5 after total knee arthroplasty(TKA),and 3 after surgical treatment of hip fracture.Protein supplementation showed beneficial effects across all types of surgery.The primary benefit was a decrease in muscle atrophy compared to placebo as measured by muscle cross sectional area.Multiple authors also demonstrated improved functional measures and quicker achievement of rehabilitation benchmarks.Protein supplementation has beneficial effects on mitigating muscle atrophy in the postoperative period following ACLR,THA,TKA,and surgical treatment of hip fracture.These effects often correlate with improved functional measures and quicker achievement of rehabilitation benchmarks.Further research is needed to evaluate long-term effects of protein supplementation and to establish standardized population-specific regimens that maximize treatment efficacy in the postoperative period.

A novel non-invasive method for predicting bone mineral density and fracture risk using demographic and anthropometric measures

Fractures are costly to treat and can significantly increase morbidity.Although dual-energy x-ray absorptiometry(DEXA)is used to screen at risk people with low bone mineral density(BMD),not all areas have access to one.We sought to create a readily accessible,inexpensive,high-throughput prediction tool for BMD that may identify people at risk of fracture for further evaluation.Anthropometric and demographic data were collected from 492 volunteers(♂275,♀217;[44-20]years;Body Mass Index(BMI)=[27.6-6.0]kg/m^(2))in addition to total body bone mineral content(BMC,kg)and BMD measurements of the spine,pelvis,arms,legs and total body.Multiple-linear-regression with step-wise removal was used to develop a two-step prediction model for BMC followed by BMC.Model selection was determined by the highest adjusted R2,lowest error of estimate,and lowest level of variance inflation(α=0.05).Height(HTcm),age(years),sex^(m=1,f=0),%body fat(%fat),fat free mass(FFMkg),fat mass(FMkg),leg length(LLcm),shoulder width(SHWDTHcm),trunk length(TRNKLcm),and pelvis width(PWDTHcm)were observed to be significant predictors in the following two-step model(p<0.05).Step1:BMC(kg)=(0.0063×HT)+(-0.0024×AGE)+(0.1712×SEX^(m=1,f=0))+(0.0314×FFM)+(0.001×FM)+(0.0089×SHWDTH)+(-0.0145×TRNKL)+(-0.0278×PWDTH)-0.5073;R^(2)=0.819,SE-0.301.Step2:Total body BMD(g/cm^(2))=(-0.0028×HT)+(-0.0437×SEX^(m=1,f=0))+(0.0008×%FAT)+(0.2970×BMC)+(-0.0023×LL)+(0.0023×SHWDTH)+(-0.0025×TRNKL)+(-0.0113×PWDTH)+1.379;R^(2)=0.89,SE-0.054.Similar models were also developed to predict leg,arm,spine,and pelvis BMD(R^(2)=0.796-0.864,p<0.05).The equations developed here represent promising tools for identifying individuals with low BMD at risk of fracture who would benefit from further evaluation,especially in the resource or time restricted setting.