risk of morbidity and mortality is of particular importance to patients . for total hip arthroplasty ( tha ) and total knee arthroplasty ( tka ) in - hospital risk of mortality has been reported to range from 0.13 to 0.46% . there is a paucity of evidence reporting on the mortality risk associated with total shoulder arthroplasty ( tsa ) . as such , surgeons counseling potential shoulder arthroplasty recipients often rely on anecdotal evidence due to a lack of published data . given the prior published literature for arthroplasty in other joints and orthopedic procedures in general , the mortality risk is perceivably small , however a quantification of the rates specific to tsa enables the shoulder surgeon to provide truly informed surgical consent . moreover , specific modifiable and nonmodifiable risk factors may affect mortality rates and aid in surgical decision - making , preoperative screening and postsurgical care and rehabilitation methods . mortality after orthopaedic procedures has traditionally been difficult to study , in large part due to a low overall incidence . as such the current evidence significantly lacks the generalizability for the end - point of interest . recent advances in electronic health records and supercomputer technology have enabled for more accurate capture and review of united states national healthcare trends . as such there are now large datasets with sufficient power to understand and abstract risks and trends associated with various procedures . databases with 100% capture of medicare data provide an opportunity for accurate reporting of in - hospital mortality rates coupled with demographic and medical factors that are associated with mortality . the purpose of this study is to quantify the in - patient mortality rates for patients undergoing a tsa as well as the associated demographics from 2005 to 2011 using a comprehensive medicare registry database . our hypothesis is that the in - hospital mortality rate after tsa is rare and that age is a significant risk factor for mortality . the pearldiver database is a publicly available , health insurance portability and accountability act - compliant national database . pearldiver captures 100% of the medicare hospital charge data for tsa between 2005 and 2011 . diagnosis and procedures are encrypted using current procedural terminology ( cpt ) and international classification of diseases , ninth revision ( icd-9 ) with codes specific to orthopedic measures . the database was queried based on hospital in - patient icd-9 procedural codes for tsa ( icd-9-p-81.80 ) . stratified sampling was conducted through pearldiver by creating a group within the data set calling for individuals with a death discharge from in - patient service centers using the procedure code icd-9-p-81.80 ( tsa ) , and compared against those with other discharge diagnoses ( home and rehab ) . note that there was no separate icd-9 code for reverse tsa ( rtsa ) prior to 2010 thus our patient sample includes a subset of patients receiving rtsa prior to 2010 . data were further analyzed for demographic parameters , assessing age , gender , and year the procedure was performed . using the database we determined the number of death discharges from in - patient service centers within the available data . we secondarily assessed the influence of demographics such as age , gender , year of procedure . we constructed a poisson regression model to look at the influence of age and year of procedure on mortality risk . statistical analyses were performed using stata v.13 ( statacorp lp , college station , texas , usa ) . a total of 101,323 patients underwent 125,813 tsas at an in - patient setting between 2005 and 2011 . the in - patient risk of mortality was 0.09% , or < 1 in 1000 surgeries . annual mortality risk was looked at as a function mortality risk per procedure performed [ table 1 ] . the annual mortality risk ranged from 0.05% ( 2011 ) to 0.11% ( 2009 ) . the year during which the procedure was performed was not a predictor of mortality ( p = 0.14 ) . we looked at mortality risk based on 5 years age group sub - analyses [ table 2 ] . the highest risk for in - hospital mortality was in patients older than 84 years old . increased age was a significant risk for in - patient mortality ( p = 0.03 ) . in - patient mortality was more common in women [ table 3 ] however there was no significant mortality risk based on gender ( p = 0.163 ) . the risk rate and risk of mortality stratified by year of procedure performed from 2005 to 2011 the mortality rate and risk of death as stratified by patient age at time of surgery the mortality rate and risk of death as stratified by gender the purpose of this study was to quantify in - hospital mortality rates for medicare patients undergoing tsa between 2005 and 2011 . we accept our null hypothesis : in - hospital mortality after tsa is a rare event ( 0.09%-<1 in 1000 operations ) and associated with increasing age . understanding surgical mortality risk is a vital component of medical - decision making , patient counseling and informed consent . in - hospital one prior study using 30 years institutional data reported a 0.58% 90 days mortality rate after tsa . in the study population , mortality risk was associated with the indication for tsa  neoplasm being the most significant risk for 90 days mortality . another study , similarly using long - term institutional data reported a 0.8% 90 days mortality risk associated with tsa . another prior study looked at 30 days mortality after tsa and the authors used a nationally representative data samples from the veterans administration national surgical quality improvement program for fiscal years 1999 - 2006 . however , our reported in - hospital mortality rate is significantly lower than previously reported 30 days and 90 days mortality rates . the lower reported rate in the present study is likely due to a smaller follow - up period ( i.e. , in - patient admission ) . our data suggests that from a mortality perspective tsa is a highly safe procedure and even safer than previously reported . furthermore , in comparison to prior published in - hospital mortality data for tka ( 0.21 - 0.51% ) and tha ( 0.29 - 0.33% ) , tsa appears to be have lower mortality risk . a major strength of our study compared to prior studies is the reporting of data from a national sample that is complete . in quantifying the risk of a rare - event , supercomputer technology has introduced the ability to review large databases accurately and cost - effectively . this study was able to gather a large cohort of patients undergoing tsa and to capture those with a discharge diagnosis of death , thereby capturing in - hospital , perioperative mortality risk . we were able to further breakdown this data between demographic variables of age , gender and year of surgery to appropriately stratify for the risk factors of mortality . found that there was no increased risk of mortality in tsas performed in patients older than 80 . however , the authors used a retrospective case control study design to assess 43 tsas in patients older than 80 years . as such , the study was likely underpowered to detect mortality as a rare event . the tka and tha evidence base suggests that age is an independent risk factor for postoperative complication and mortality . our findings support the previous nonshoulder total joints literature and identify advanced age as an important risk factor for mortality . the significance of the in - patient mortality risk after tsa identified in this study should be evaluated in concert with the general risks associated with hospitalization and undergoing medical intervention of any kind . the micromort concept is a useful notion for conceptualizing the in - patient mortality risk presented in the present study . the micromort concept was first articulated by stanford university professor ron howard in 1968 and has been used when discussing risk trade - offs . a micromort is a 1 in a million chance of death . the risk of mortality has thus been quantified to other medical and even leisurely activities based on the micromort concept . based on our calculations , this makes this surgery nearly 5 times more dangerous than giving birth in the united states ( 170 micromorts ) and 100 times more dangerous than undergoing general anesthesia alone ( 10 micromorts ) . a night in the hospital equates to 75 micromorts , thus , the mortality risk associated with hospitalization alone may be a contributing factor in the mortality risk for tsa . there are certain limitations to the findings of the present study . because our study utilizes cpt coding data , we are not able to differentiate between rtsa versus tsa . now for rtsa , more work needs to be done in order to understand the demographics for this procedure , as well as the associated mortality risk . the database is subject to a lack of detailed patient - level data that is often absent in large patient databases . as such we can not report on certain demographic and epidemiologic factors , such as height , weight , body mass index , activity level , race and socioeconomic status . previous work on outcomes after total joint arthroplasty suggests that these demographics are important modifiers of outcome . in addition to the absence of certain patient demographics , we are unable to abstract causes of death from the database . furthermore , as with any retrospective database investigation , the accuracy of coding within the system is critical to the validity of the findings . moreover , we did not include the patients who underwent surgery at an outpatient center . this was a very limited number of patients that are assumed to be healthy enough where the risk is unlikely to be any higher than the patients who undergo the procedure as an impatient . we also acknowledge that the scope of our mortality risk assessment is limited to in - hospital . as such , we do not capture perioperative and early mortality ( i.e. , 30 - 90 days mortality ) . the utilization of  death discharges  allows us to capture with reasonable certainty all in - patient deaths after tsa . 30 - 90 days mortality estimates using the same dataset would introduce significant estimation errors and weaken the conclusions of this study . finally , because the nature of our study was a database study , we were unable to conduct a multivariate analysis to control for increasing comorbidities with age . as such , we can not conclude that age is an independent risk factor for mortality . the incidence of in - patient mortality for medicare patients undergoing tsa between 2005 and 2011 was < 1 in 1000 surgeries .
introduction : the in - hospital mortality rate after total shoulder arthroplasty ( tsa ) is unknown . the purpose of this study is to quantify the in - patient mortality rates and associated demographic risk factors for patients undergoing a tsa from 2005 to 2011 using a comprehensive medicare registry database.materials and methods : we conducted a retrospective review of the medicare database within the pearldiver database . 
 the pearldiver database is a publicly available health insurance portability and accountability act - compliant national database that captures 100% of the medicare hospital data for tsa between 2005 and 2011 . using international classification of diseases , ninth revision codes for tsa we identified a dataset of patients undergoing tsa as well as a subset of those for whom 
 there was a death discharge ( i.e. , in - patient death ) . 
 risk for this outcome was further quantified by age , gender and year . 
 linear regression was performed to identify risk factors for the primary outcome.results:a total of 101,323 patients underwent 125,813 tsas between 2005 and 2011 . 
 there were 113 in - patient mortalities during this period . 
 thus the incidence of death was 0.09% . 
 increasing age was a significant risk factor for mortality ( p = 0.03 ) . 
 gender and year of procedure were not significant risk factors for mortality.conclusion:the incidence of in - patient mortality for medicare patients undergoing tsa between 2005 and 2011 was < 1 in 1000 surgeries . 
 increased age is a significant predictor of mortality.level 4:retrospective analysis