Orthopedics

Feature Article Supplemental Data

Coagulopathies Are a Risk Factor for Adverse Events Following Total Hip and Total Knee Arthroplasty

Rohil Malpani, BS; Ryan P. McLynn, MD; Patawut Bovonratwet, BS; Paul S. Bagi, MD; Alp Yurter, BS; Michael R. Mercier, BS; Lee E. Rubin, MD; Jonathan N. Grauer, MD

Abstract

Current literature suggests a correlation between preoperative coagulopathies and postsurgical adverse events (AEs). However, this correlation has not been specifically assessed in the total hip arthroplasty (THA) and the total knee arthroplasty (TKA) populations. Patients who underwent primary THA and TKA with coagulopathy data were identified from the 2011–2015 American College of Surgeons National Surgical Quality Improvement Program database. Coagulopathies studied were low platelets, high partial thromboplastin time (PTT), high international normalized ratio (INR), and other hematological conditions. Univariate and multivariate analyses were conducted to explore the relationship between coagulopathies and 30-day AEs following surgery in these populations. In total, 39,605 THA patients and 67,685 TKA patients were identified. Of these, approximately 16% had a coagulopathy. These patients tended to be older and have a dependent functional status, American Society of Anesthesiologists score of 3 or greater, and diabetes mellitus. In the THA cohort, low platelets, high PTT, high INR, and other hematological conditions were associated with increased odds of any AE, major AEs, and minor AEs. High INR and other hematological conditions were associated with an increased odds of hospital readmission. In the TKA group, low platelets, high INR, and other hematological conditions were associated with increased odds of any AE, major AEs, and minor AEs. High PTT was associated with increased odds of major AEs and readmissions. Presence of a coagulopathy was associated with multiple AEs following both THA and TKA. This shows that special attention should be paid patients with any form of coagulopathy to minimize the potential risk of AEs. [Orthopedics. 2020;43(4):233–238.]

Abstract

Current literature suggests a correlation between preoperative coagulopathies and postsurgical adverse events (AEs). However, this correlation has not been specifically assessed in the total hip arthroplasty (THA) and the total knee arthroplasty (TKA) populations. Patients who underwent primary THA and TKA with coagulopathy data were identified from the 2011–2015 American College of Surgeons National Surgical Quality Improvement Program database. Coagulopathies studied were low platelets, high partial thromboplastin time (PTT), high international normalized ratio (INR), and other hematological conditions. Univariate and multivariate analyses were conducted to explore the relationship between coagulopathies and 30-day AEs following surgery in these populations. In total, 39,605 THA patients and 67,685 TKA patients were identified. Of these, approximately 16% had a coagulopathy. These patients tended to be older and have a dependent functional status, American Society of Anesthesiologists score of 3 or greater, and diabetes mellitus. In the THA cohort, low platelets, high PTT, high INR, and other hematological conditions were associated with increased odds of any AE, major AEs, and minor AEs. High INR and other hematological conditions were associated with an increased odds of hospital readmission. In the TKA group, low platelets, high INR, and other hematological conditions were associated with increased odds of any AE, major AEs, and minor AEs. High PTT was associated with increased odds of major AEs and readmissions. Presence of a coagulopathy was associated with multiple AEs following both THA and TKA. This shows that special attention should be paid patients with any form of coagulopathy to minimize the potential risk of AEs. [Orthopedics. 2020;43(4):233–238.]

The incidence of total hip arthroplasty (THA) and knee total knee arthroplasty (TKA) has been increasing annually, and now more than 1 million of these procedures are performed annually in the United States.1 Due to an aging population, combined with the rising demand for increased mobility and quality of life, this trend is projected to continue until joint replacements are the most common elective surgical procedures.2,3

Coagulopathy profiles are considered risk factors for perioperative adverse events (AEs). One prior study evaluating outcomes following noncardiac surgery found low and high platelet counts to be associated with an increased need of peri-operative blood transfusion and higher risk of mortality.4 Specific to total joint replacements, Bozic et al5 demonstrated increased risk of prosthetic joint infection in patients with a preoperative diagnosis of coagulopathy after THA. However, that study did not evaluate other AEs or further delineate or define the type of coagulopathy present.

The purpose of the current study was to use a large national database, the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP), to analyze the effect of various abnormal coagulation findings on postoperative AEs following THA and TKA. The goal of this work was to more accurately risk stratify patients with an abnormal preoperative coagulation profile to guide algorithms that might minimize perioperative morbidity and mortality.

Materials and Methods

Database and Patient Population

Overview of the ACS NSQIP Database. The ACS NSQIP database collects more than 250 variables for each surgical case from more than 600 hospitals, mostly based in the United States.6 The variables collected include defined patient demographics, comorbidities, postoperative AEs, and readmissions data. Prior studies have validated the use of ACS NSQIP in surgical outcomes research and its popularity in this regard, including in the total joint replacement literature.7–10 The authors' institutional review board granted an exemption for studies using this dataset.

Inclusion/Exclusion Criteria and Details on Missing Data. Patients who underwent primary THA and TKA between 2011 and 2015 were identified in ACS NSQIP using the Current Procedural Terminology (CPT) codes 27130 and 27447, respectively. Those with revision CPT codes (27134 for hip and 27486/27487 for knee procedures) were excluded. Cases associated with underlying preoperative neoplasms, infections, and emergency/trauma were additionally excluded.

A small number of patients (<1%) had missing data for patient demographic characteristics, including height, weight, functional status, and American Society of Anesthesiologists (ASA) score, and were excluded. In addition, those who were missing preoperative platelet counts/partial thromboplastin time (PTT)/international normalized ratio (INR) were excluded.

Patient Preoperative Characteristics. Patient preoperative characteristics that were directly extracted from the database included age, sex, height, weight, functional status prior to surgery, ASA score, diabetes mellitus status, and smoking status. Body mass index (BMI) was calculated based on the height and weight (mass [kg]/height [m2]). The ASA score was used as a marker of comorbidities.

Preoperative coagulation variables that were assessed included platelet count, PTT, INR, and “other hematological conditions.” Definitions of abnormal laboratory coagulopathy values were abstracted from the literature11: low platelet count less than 150,000/mL, high PTT greater than 35 seconds, and high INR greater than 1.2. “Other hematologic condition” was an ACS NSQIP variable defined as “patients with any condition thought to place the patient at risk for excessive bleeding requiring hospitalization due to a deficiency of blood clotting elements, for example, vitamin K deficiency, hemophilias, thrombocytopenia, or chronic anticoagulation therapy that has not been discontinued prior to surgery.”6

Surgical Variables, Postoperative Complications, and Readmissions. Operative time (measured in minutes) and length of stay (LOS; measured in days, limited to a maximum of 30 days due to ACS NSQIP limitations) were obtained from the ACS NSQIP database. Adverse events were aggregated into any, major, and minor AEs.

A major AE was characterized as the occurrence of any one of the following events: cardiac arrest, acute renal failure, deep venous thrombosis, pulmonary embolism, wound infection, return to the operating room, 30-day readmission occurrence, ventilator use of more than 48 hours, unplanned intubation, stroke/cerebrovascular accident, sepsis/septic shock, return to the operating room, and death. A minor AE was characterized as the occurrence of any of the following events: urinary tract infection, blood transfusion, pneumonia, wound dehiscence, and progressive renal insufficiency. Any AE was defined as the occurrence of either a major or minor AE.

Statistical Analysis

Univariate Analysis. Univariate chi-square tests were performed on preoperative patient characteristics (age, sex, BMI, ASA score, functional status prior to surgery, diabetes mellitus status, and smoking status) and coagulopathy category. In addition, chi-square tests were performed between postsurgical AEs (any, major, and minor AEs and readmissions). Furthermore, 2-sample, 2-tailed t test was used to test the relation between having a coagulopathy and operative times and postoperative LOS. Statistical significance was maintained at alpha=0.05 independent of type of test.

Multivariate Analysis. Logistic regressions were performed for the different types of AEs and readmissions for all 4 predefined categories of coagulopathies in both the THA and TKA populations. Statistical significance was set at alpha=0.05, and 95% confidence intervals (CIs) are reported. The preoperative demographic variables accounted for in this regression were age, sex, BMI, ASA score, and functional status categories. Similar statistical tests and significance values were used.

Statistical analysis was performed using Stata version 13.1 (StataCorp, LP, College Station, Texas).

Results

Patient Population

Initially, 91,066 THA patients and 147,876 TKA patients were identified. After excluding patient records with and missing coagulopathy data, the population was narrowed to 39,605 THA and 67,685 TKA patients.

When comparing pre-drop and post-drop populations for the THA (Table 1) and TKA (Table 2) groups, the remaining patients had a clinically similar profile. The removal of THA patients with incomplete data resulted in an average difference in data values of only 0.32% across all of the demographic variables. The exclusion of TKA patients with incomplete data resulted in an average difference in data values of only 0.12% across all of the demographic variables.

Demographics of Patients Undergoing THAa

Table 1:

Demographics of Patients Undergoing THA

Demographics of Patients Undergoing TKAa

Table 2:

Demographics of Patients Undergoing TKA

Of the 39,605 included THA patients, there were no coagulopathies for 33,239 (83.93%), low platelets for 1948 (4.92%), high PTT for 3213 (8.11%), high INR for 1818 (4.59%), and other hematological conditions for 1028 (2.60%) patients. For the 67,685 included TKA patients, there were no coagulopathies for 56,908 (84.08%), low platelets for 3426 (5.06%), high PTT for 5289 (7.81%), high INR for 3001 (4.43%), and other hematologic conditions for 1825 (2.70%) patients.

The sum of the number of patients in the control group and the various coagulopathy groups was greater than the total number of patients. This was because some patients were in multiple coagulopathy categories (eg, a patient who had both low platelets and an elevated INR) and were counted in both categories.

The THA demographics are stratified by coagulopathy in Table A (available in the online version of the article), and the TKA demographics are stratified by coagulopathy in Table B (available in the online version of the article).

Demographics of patients undergoing THA focusing on coagulation status

Table A:

Demographics of patients undergoing THA focusing on coagulation status

Demographics of patients undergoing TKA focusing on coagulation status

Table B:

Demographics of patients undergoing TKA focusing on coagulation status

Perioperative Outcomes

The THA perioperative complications are displayed in Table C (available in the online version of the article). Of the overall THA group, 7090 (17.90%) patients experienced a postoperative complication. On univariate analysis, low platelets, high PTT, high INR, and other hematological conditions were associated with significantly greater rates of any AEs, major AEs, minor AEs, and hospital readmission (P<.001).

Adverse event outcomes of patients undergoing THA focusing on Coagulation Status

Table C:

Adverse event outcomes of patients undergoing THA focusing on Coagulation Status

The TKA perioperative complications are reported in Table D (available in the online version of the article). Of the entire TKA group, 10,307 (15.23%) patients experienced a postoperative complication. On univariate analysis, the aggregated TKA coagulopathy group had a significantly greater length of stay (3.4 days vs 3 days, P<.001). Additionally, low platelets, high PTT, high INR, and other hematological conditions were associated with significantly greater rates of any AE, major AEs, minor AEs, and hospital readmission (P<.001).

Adverse event outcomes of patients undergoing TKA focusing on Coagulation Status

Table D:

Adverse event outcomes of patients undergoing TKA focusing on Coagulation Status

Multivariate Analysis

Controlling for age, sex, BMI, ASA score, and functional status, the multivariate odds ratios (ORs) of an AE for the different coagulopathy groups (ie, low platelets, high PTT, high INR, or other hematological conditions) relative to the control group were calculated and are shown in Figure A and Figure B (available in the online version of the article).

Odds ratio of any adverse event for various coagulopathies.

Figure A:

Odds ratio of any adverse event for various coagulopathies.

Odds ratio of hospital readmission for various coagulopathies.

Figure B:

Odds ratio of hospital readmission for various coagulopathies.

In THA, low platelets were associated with statistically increased odds of any AE (OR=1.49, P<.001), major AEs (OR=1.37, P<.001), minor AEs (OR=1.60, P<.001), and hospital re-admission (OR=1.27, P=.023). High INR was associated with statistically increased odds of any AE (OR=1.60, P<.001), major AEs (OR=1.53, P<.001), minor AEs (OR=1.66, P<.001), and hospital readmission (OR=1.50, P<.001). High PTT was associated with statistically increased odds of any AE (OR=1.35, P<.001), major AEs (OR=1.21, P=.009), and minor AEs (OR=1.40, P<.001), but not hospital readmission. Other hematological conditions were associated with statistically increased odds of any AE (OR=1.70, P<.001), major AEs (OR=1.75, P<.001), minor AEs (OR=1.67, P<.001), and hospital readmission (OR=1.77, P<.001).

In TKA, low platelets were associated with statistically increased odds of any AE (OR=1.28, P<.001), major AEs (OR=1.24, P=.002), minor AEs (OR=1.31, P<.001), and hospital readmission (OR=1.23, P=.011). High INR was associated with statistically increased odds of any AE (OR=1.34, P<.001), major AEs (OR=1.49, P<.001), minor AEs (OR=1.28, P<.001), and hospital readmission (OR=1.67, P<.001). High PTT was associated with statistically increased odds of major AEs (OR=1.19, P=.002) and hospital readmission (OR=1.34, P<.001), but not of any AE or minor AEs. Other hematological conditions were associated with statistically increased odds of any AE (OR=1.45, P<.001), major AEs (OR=1.78, P<.001), minor AEs (OR=1.26, P=.001), and hospital readmission (OR=1.96, P<.001).

Discussion

As total joint arthroplasty moves toward placing an increased emphasis on quality improvement and enhancing the value of care, there is substantial impetus to identify patients at increased risk of experiencing complications to potentially avoid such events.12,13 With a relatively high rate of overall complications and a high rate of bleeding and blood transfusion,14–18 coagulopathies are important to consider as potential risk factors for transfusions and other complications in the acute perioperative period. The current study aimed to characterize the prevalence of common coagulation abnormalities in a large national sample of total joint arthroplasty patients and determine whether such abnormalities are independently associated with postoperative complications.

Previous studies have noted significant associations of the blanket term coagulopathies with AEs,19 readmission,20 and increased costs.21 However, these studies have used administrative databases and International Classification of Diseases (ICD) codes to identify patients with a coagulopathy and do not allow these to be quantified. Further, prior research has demonstrated that ICD codes frequently suffer from poor sensitivity,22 which may bias the results of administrative database studies.23

The current study found that approximately 16% of both THA and TKA patients had a laboratory abnormality or previous diagnosis of a coagulopathy (Tables A and B). In both groups, these patients were significantly older, had greater incidence of diabetes mellitus, and were assigned higher ASA scores, suggesting a greater level of overall medical comorbidity. The association of such patient-level factors with coagulation abnormalities had previously yielded mixed results, as one prior investigation in the spine literature found a similar pattern among patients with coagulation disorders,11 whereas a separate study found no significant differences in terms of age or comorbidities.24 In addition, the presence of a coagulation abnormality was associated with increased operative time, although the effects were relatively small, which may further contribute to subsequent transfusion requirement and other complications.

For both THA and TKA, the presence of a coagulopathy or laboratory abnormality was associated with a significant increase in perioperative blood transfusion, which is consistent with prior findings in other orthopedic surgeries.11,24,25 Although the association of a diagnosed coagulopathy with AEs and readmission has been previously noted,19,20 the current findings also demonstrate a similar increase in AEs for patients with low platelets, high PTT, and high INR (Tables C and D).

To account for baseline difference seen in patients with coagulation abnormalities that may augment the risk of AEs, patient demographics, functional status, and ASA score were controlled for. After applying these controls, low platelet count, elevated INR, and other hematological conditions were independently associated with all major outcomes studied for both THA and TKA patients. The current findings demonstrate that coagulopathies and laboratory abnormalities are associated not only with increased postoperative bleeding but also increased incidence of other complications and readmissions after THA and TKA.

Although the ACS NSQIP database provided several advantages to the current study over prior investigations, it also presented several limitations. As a retrospective analysis, it is impossible to determine causality, and it is possible that confounding variables are not collected in the database. Additionally, there is a relatively high rate of missing values for the variables of interest, leading to a large number of cases being dropped. To better understand potential discrepancies between patients with complete or missing data, the 2 groups were compared on the basis of demographics, functional status, and medical comorbidity (Tables 12), and there were generally no significant differences. Although the patients used in the study and those dropped from analysis appear to be very similar overall, there is nevertheless potential to introduce bias by dropping patients with missing data.26 Additionally, the current study could not address the risks or costs of measuring coagulation laboratory values preoperatively or the benefits and costs of intervening based on such values or a history of coagulopathy, either preoperatively or postoperatively.

Currently, although abnormalities in laboratory testing values for platelets, PT, PTT, and INR can be identified prospectively during preoperative patient testing, there is a lack of consensus concerning the relevance of preoperative measurement of these values in the surgical literature, and treatment of mildly abnormal values is not clear. Whereas some studies have found an association between laboratory abnormalities and AEs,4,11 others have found no evidence for routine measurement of these values for all patients in the absence of known bleeding or other risk factors.27–29 The current findings suggest that such laboratory values may provide relevant information to physicians prior to total joint arthroplasty. However, given the growing importance on providing low-cost and high-value care, further investigation is needed to better characterize the benefits of obtaining this laboratory data to make informed decisions vs the risks and costs of phlebotomy. At the authors' institution in particular, although complete blood counts and comprehensive metabolic panel values are routinely collected preoperatively, coagulation studies are no longer routinely collected for elective arthroplasties unless there is a known history of coagulopathy or liver disease.

Conclusion

The current study used a large sample to offer unique insights into the risk profile for complications and readmissions following these procedures for patients with various coagulopathies (eg, low platelets, high PTT, high INR). With the higher rates of readmissions and postoperative complications in this at-risk patient population, these results suggest that greater perioperative medical optimization and post-discharge care may be able to lower the risks of readmissions in this group, thereby reducing cost and improving care metrics. These findings also suggest that preoperative laboratory values can in fact be useful in evaluating patients for THA and TKA and inform postoperative management.

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Demographics of Patients Undergoing THAa

CharacteristicTHA: All EntriesTHA: Patients Without Missing Coagulopathy Data


No.%No.%
Total91,066100.0039,605100.00
Age, yAverage: 64.7Average: 64.8
  18–5416,52118.14712718.00
  55–6427,37430.0612,022b30.35b
  65–7428,021b30.77b11,95630.19
  ≥7519,15021.03850021.46
Sex
  Male41,04245.0718,08845.67
  Female50,024b54.93b21,517b54.33b
BMI, kg/m2Average: 30.2Average: 30.2
  <2530,889b33.92b13,592b34.32b
  25–3023,11425.3810,01425.28
  30–3518,36920.17790319.95
  >3518,69420.53809620.44
Functional status prior to injury
  Independent89,165b97.91b38,692b97.69b
  Partially dependent18282.018792.22
  Totally dependent730.08340.09
ASA scoreAverage: 2.4Average: 2.4
  138384.2116534.17
  250,235b55.16b21,507b54.30b
  335,46238.9415,76239.80
  ≥415571.716831.72
Smoker
  Yes12,08213.27544613.75
  No78,984b86.73b34,159b86.25b
Diabetes mellitus
  Insulin23362.5710092.55
  Non-insulin8007b8.79b3646b9.21b

Demographics of Patients Undergoing TKAa

TKA: All EntriesTKA: Patients Without Missing Coagulopathy Data


CharacteristicNo.%No.%
Total147,876100.0067,685100.00
Age, yAverage: 66.6Average: 66.7
  18–5415,95510.79717810.61
  55–6444,86230.3420,60430.44
  65–7454,654b36.96b24,875b36.75b
  ≥7532,40521.9115,02822.20
Sex
  Male56,16737.9825,73338.02
  Female91,709b62.02b41,952b61.98b
BMI, kg/m2Average: 33.0Average: 33.0
  <2540,30327.2518,63927.54
  25–3042,12228.4819,29228.50
  30–3550,451b34.12b23,028b34.02b
  >3515,00010.1467269.94
Functional status prior to injury
  Independent145,792b98.59b66,795b98.69b
  Partially dependent18631.268621.27
  Totally dependent710.05280.04
ASA scoreAverage: 2.5Average: 2.5
  131202.1115462.28
  274,419b50.33b33,854b50.02b
  368,00545.9931,24846.17
  ≥423321.5810371.53
Smoker
  Yes12,7598.6358268.61
  No135,117b91.37b61,859b91.39b
Diabetes
  Insulin65074.4029774.40
  Non-insulin19,873b13.44b9355b13.82b

Demographics of patients undergoing THA focusing on coagulation status

TotalLow Platelets (<150,000 ×103 /mL3)High PTT (>35 s)High INR (>1.2)Other Hematological ConditionsNo CoagulopathiesP-value
# of Patients39,6051,9483,2131,8181,02833,239
General Variables: N (%)100.00%4.92%8.11%4.59%2.60%83.93%
Age<0.001
  18 – 547,127 (18.00%)267 (13.71%)507 (15.78%)215 (11.83%)107 (10.41%)6,212 (18.69%)
  55 – 6412,022 (30.35%)517 (26.54%)830 (25.83%)375 (20.63%)228 (22.18%)10,393 (31.27%)
  65 – 7411,956 (30.19%)590 (30.29%)982 (30.56%)527 (28.99%)337 (32.78%)10,016 (30.13%)
  ≥ 758,500 (21.46%)574 (29.47%)894 (27.82%)701 (38.56%)356 (34.63%)6,618 (19.91%)
Sex<0.001
  Male18,088 (45.67%)1,341 (68.84%)1,517 (47.21%)1,035 (56.93%)551 (53.60%)14,641 (44.05%)
  Female21,517 (54.33%)607 (31.16%)1,696 (52.79%)783 (43.07%)477 (46.40%)18,598 (55.95%)
BMI0.083
  < 258,096 (20.44%)379 (19.46%)715 (22.25%)381 (20.96%)216 (21.01%)6,764 (20.35%)
  25 – 3013,592 (34.32%)700 (35.93%)1,030 (32.06%)574 (31.57%)336 (32.68%)11,466 (34.50%)
  30 – 3510,014 (25.28%)517 (26.54%)759 (23.62%)483 (26.57%)252 (24.51%)8,435 (25.38%)
  > 357,903 (19.95%)352 (18.07%)709 (22.07%)380 (20.90%)224 (21.79%)6,574 (19.78%)
Functional Status (prior to surgery):<0.001
  Independent38,692 (97.69%)1,876 (96.30%)3,082 (95.92%)1,723 (94.77%)953 (92.70%)32,589 (98.04%)
  Partially dependent879 (2.22%)71 (3.64%)123 (3.83%)90 (4.95%)72 (7.00%)629 (1.89%)
  Totally Dependent34 (0.09%)1 (0.05%)8 (0.25%)5 (0.28%)3 (0.29%)21 (0.06%)
ASA<0.001
   11,653 (4.17%)55 (2.82%)84 (2.61%)27 (1.49%)3 (0.29%)1,494 (4.49%)
   221,507 (54.30%)744 (38.19%)1,291 (40.18%)488 (26.84%)206 (20.04%)19,109 (57.49%)
   315,762 (39.80%)1,056 (54.21%)1,714 (53.35%)1,196 (65.79%)729 (70.91%)12,234 (36.81%)
  ≥ 4683 (1.72%)93 (4.77%)124 (3.86%)107 (5.89%)90 (8.75%)402 (1.21%)
Diabetes4,655 (11.75%)309 (15.86%)438 (13.63%)282 (15.51%)191 (18.58%)3,730 (11.22%)<0.001
  Insulin1,009 (2.55%)94 (4.83%)94 (2.93%)70 (3.85%)54 (5.25%)769 (2.31%)
  Non-insulin3,646 (9.21%)215 (11.04%)344 (10.71%)212 (11.66%)137 (13.33%)2,961 (8.91%)
Smoker5,446 (13.75%)263 (13.50%)526 (16.37%)166 (9.13%)140 (13.62%)4,540 (13.66%)0.224

Demographics of patients undergoing TKA focusing on coagulation status

TotalLow Platelets (<150,000 ×103 /mL3)High PTT (>35 s)High INR (>1.2)Other Hematological ConditionsNo CoagulopathiesP-value
# of Patients67,6853,4265,2893,0011,82556,908
General Variables: N (%)100.00%5.06%7.81%4.43%2.70%84.08%
Age<0.001
  18 – 547,178 (12.61%)207 (0.36%)505 (0.89%)194 (0.34%)131 (0.23%)6,307 (11.08%)
  55 – 6420,604 (36.21%)831 (1.46%)1,446 (2.54%)657 (1.15%)402 (0.71%)17,826 (31.32%)
  65 – 7424,875 (43.71%)1,272 (2.24%)1,910 (3.36%)1,043 (1.83%)666 (1.17%)20,959 (36.83%)
  ≥ 7515,028 (26.41%)1,116 (1.96%)1,428 (2.51%)1,107 (1.95%)626 (1.10%)11,816 (20.76%)
Sex<0.001
  Male25,733 (45.22%)2,158 (3.79%)2,286 (4.02%)1,584 (2.78%)919 (1.61%)20,390 (35.83%)
  Female41,952 (73.72%)1,268 (2.23%)3,003 (5.28%)1,417 (2.49%)906 (1.59%)36,518 (64.17%)
BMI0.771
  < 256,726 (11.82%)353 (0.62%)529 (0.93%)284 (0.50%)186 (0.33%)5,648 (9.92%)
  25 – 3018,639 (32.75%)1,025 (1.80%)1,372 (2.41%)798 (1.40%)474 (0.83%)15,703 (27.59%)
  30 – 3519,292 (33.90%)1,004 (1.76%)1,495 (2.63%)862 (1.51%)555 (0.98%)16,181 (28.43%)
  > 3523,028 (40.47%)1,044 (1.83%)1,893 (3.33%)1,057 (1.86%)610 (1.07%)19,376 (34.05%)
Functional Status (prior to surgery):<0.001
  Independent66,795 (117.37%)3,361 (5.91%)5,184 (9.11%)2,926 (5.14%)1,781 (3.13%)56,229 (98.81%)
  Partially dependent862 (1.51%)62 (0.11%)102 (0.18%)70 (0.12%)42 (0.07%)659 (1.16%)
  Totally Dependent28 (0.05%)3 (0.01%)3 (0.01%)5 (0.01%)2 (0.00%)20 (0.04%)
ASA<0.001
   11,546 (2.72%)55 (0.10%)86 (0.15%)34 (0.06%)15 (0.03%)1,375 (2.42%)
   233,854 (59.49%)1,291 (2.27%)1,973 (3.47%)792 (1.39%)445 (0.78%)29,925 (52.58%)
   331,248 (54.91%)1,969 (3.46%)3,053 (5.36%)2,025 (3.56%)1,285 (2.26%)24,929 (43.81%)
  ≥ 41,037 (1.82%)111 (0.20%)177 (0.31%)150 (0.26%)80 (0.14%)679 (1.19%)
Diabetes12,312 (21.63%)761 (1.34%)1,023 (1.80%)636 (1.12%)436 (0.77%)10,109 (17.76%)<0.001
  Insulin2,977 (5.23%)233 (0.41%)305 (0.54%)194 (0.34%)122 (0.21%)2,322 (4.08%)
  Non-insulin9,335 (16.40%)528 (0.93%)718 (1.26%)442 (0.78%)314 (0.55%)7,787 (13.68%)
Smoker5,826 (10.24%)278 (0.49%)522 (0.92%)222 (0.39%)155 (0.27%)4,871 (8.56%)0.305

Adverse event outcomes of patients undergoing THA focusing on Coagulation Status

# of PatientsTotalLow Platelets (<150,000 x103 /mL3)High PTT (>35 s)High INR (>1.2)Other Hematological ConditionsNo CoagulopathiesP-value
39,6051,9483,2131,8181,02833,239
General Variables: N (%)100.00%4.92%8.11%4.59%2.60%83.93%
Any Adverse Event7,090 (17.90%)485 (24.90%)785 (24.43%)534 (29.37%)335 (32.59%)5,541 (16.67%)<0.001
Major Adverse Event2,196 (5.54%)166 (8.52%)241 (7.50%)189 (10.40%)128 (12.45%)1,691 (5.09%)<0.001
Death69 (0.17%)11 (0.56%)9 (0.28%)12 (0.66%)8 (0.78%)49 (0.15%)
Sepsis/Septic shock148 (0.37%)9 (0.46%)20 (0.62%)19 (1.05%)10 (0.97%)108 (0.32%)
Unplanned Intubation76 (0.19%)10 (0.51%)10 (0.31%)5 (0.28%)6 (0.58%)56 (0.17%)
Ventilator >48 hrs33 (0.08%)8 (0.41%)5 (0.16%)2 (0.11%)5 (0.49%)23 (0.07%)
Stroke33 (0.08%)3 (0.15%)4 (0.12%)5 (0.28%)1 (0.10%)25 (0.08%)
Cardiac Arrest29 (0.07%)3 (0.15%)6 (0.19%)3 (0.17%)2 (0.19%)20 (0.06%)
MI98 (0.25%)7 (0.36%)7 (0.22%)5 (0.28%)10 (0.97%)80 (0.24%)
Acute Renal Failure15 (0.04%)2 (0.10%)3 (0.09%)2 (0.11%)1 (0.10%)9 (0.03%)
PE108 (0.27%)3 (0.15%)5 (0.16%)5 (0.28%)2 (0.19%)96 (0.29%)
DVT169 (0.43%)9 (0.46%)21 (0.65%)13 (0.72%)9 (0.88%)129 (0.39%)
Wound Infection537 (1.36%)50 (2.57%)53 (1.65%)41 (2.26%)27 (2.63%)409 (1.23%)
Return to OR809 (2.04%)53 (2.72%)80 (2.49%)60 (3.30%)42 (4.09%)642 (1.93%)
Readmission1,475 (3.72%)107 (5.49%)155 (4.82%)129 (7.10%)91 (8.85%)1,137 (3.42%)<0.001
Minor Adverse Event5,564 (14.05%)395 (20.28%)641 (19.95%)434 (23.87%)266 (25.88%)4,310 (12.97%)<0.001
Wound Dehiscence42 (0.11%)6 (0.31%)4 (0.12%)2 (0.11%)2 (0.19%)32 (0.10%)
UTI389 (0.98%)18 (0.92%)48 (1.49%)30 (1.65%)17 (1.65%)308 (0.93%)
Pneumonia146 (0.37%)12 (0.62%)24 (0.75%)19 (1.05%)11 (1.07%)102 (0.31%)
Progressive Renal Insufficiency45 (0.11%)9 (0.46%)6 (0.19%)5 (0.28%)7 (0.68%)25 (0.08%)
Transfusion5,119 (12.93%)368 (18.89%)585 (18.21%)400 (22.00%)250 (24.32%)3,966 (11.93%)
T-tests comparing differences in surgical outcomes in patients depending on presence of Coagulopathies
No CoagulopathiesAny coagulopathiesP-value
Operating Time<0.001
  Mean93.9296.72
  SD41.5044.65
Length of Stay<0.001
  Mean3.003.42
  SD4.894.02

Adverse event outcomes of patients undergoing TKA focusing on Coagulation Status

# of PatientsTotalLow Platelets (<150,000 ×103 /mL3)High PTT (>35 s)High INR (>1.2)Other Hematological ConditionsNo CoagulopathiesP-value
67,6853,4265,2893,0011,82556,908
General Variables: N (%)100.00%5.06%7.81%4.43%2.70%84.08%
Any Adverse Event10,307 (15.23%)674 (19.67%)892 (16.87%)646 (21.53%)420 (23.01%)8,322 (14.62%)<0.001
Major Adverse Event3,861 (5.70%)269 (7.85%)382 (7.22%)289 (9.63%)205 (11.23%)3,027 (5.32%)<0.001
Death86 (0.13%)5 (0.15%)12 (0.23%)10 (0.33%)9 (0.49%)58 (0.10%)
Sepsis/Septic shock176 (0.26%)15 (0.44%)18 (0.34%)15 (0.50%)18 (0.99%)133 (0.23%)
Unplanned Intubation105 (0.16%)8 (0.23%)13 (0.25%)6 (0.20%)6 (0.33%)80 (0.14%)
Ventilator >48 hrs47 (0.07%)5 (0.15%)6 (0.11%)5 (0.17%)2 (0.11%)35 (0.06%)
Stroke66 (0.10%)4 (0.12%)8 (0.15%)9 (0.30%)4 (0.22%)50 (0.09%)
Cardiac Arrest54 (0.08%)6 (0.18%)8 (0.15%)4 (0.13%)4 (0.22%)39 (0.07%)
MI135 (0.20%)6 (0.18%)13 (0.25%)7 (0.23%)8 (0.44%)107 (0.19%)
Acute Renal Failure42 (0.06%)7 (0.20%)6 (0.11%)6 (0.20%)4 (0.22%)27 (0.05%)
PE491 (0.73%)28 (0.82%)36 (0.68%)24 (0.80%)16 (0.88%)405 (0.71%)
DVT604 (0.89%)35 (1.02%)37 (0.70%)26 (0.87%)24 (1.32%)509 (0.89%)
Wound Infection581 (0.86%)39 (1.14%)60 (1.13%)49 (1.63%)26 (1.42%)459 (0.81%)
Return to OR743 (1.10%)68 (1.98%)86 (1.63%)72 (2.40%)51 (2.79%)548 (0.96%)
Readmission2,370 (3.50%)174 (5.08%)268 (5.07%)209 (6.96%)147 (8.05%)1,808 (3.18%)<0.001
Minor Adverse Event7,353 (10.86%)480 (14.01%)607 (11.48%)443 (14.76%)270 (14.79%)5,984 (10.52%)<0.001
Wound Dehiscence129 (0.19%)12 (0.35%)22 (0.42%)19 (0.63%)12 (0.66%)85 (0.15%)
UTI544 (0.80%)37 (1.08%)50 (0.95%)28 (0.93%)18 (0.99%)443 (0.78%)
Pneumonia252 (0.37%)15 (0.44%)28 (0.53%)21 (0.70%)7 (0.38%)202 (0.35%)
Progressive Renal Insufficiency85 (0.13%)5 (0.15%)8 (0.15%)14 (0.47%)10 (0.55%)61 (0.11%)
Transfusion6,519 (9.63%)421 (12.29%)524 (9.91%)372 (12.40%)235 (12.88%)5,326 (9.36%)
T-tests comparing differences in surgical outcomes in patients depending on presence of Coagulopathies
No CoagulopathiesAny coagulopathiesP-value
Operating Time<0.001
  Mean94.3296.17
  SD39.2539.11
Length of Stay<0.001
  Mean3.093.37
  SD3.694.37
Authors

The authors are from the Department of Orthopaedics and Rehabilitation, Yale School of Medicine, New Haven, Connecticut.

Mr Malpani, Dr McLynn, Mr Bovonratwet, Dr Bagi, Mr Yurter, and Mr Mercier have no relevant financial relationships to disclose. Dr Rubin is a paid consultant for DePuy Synthes and DJO Global and holds stock in 3D Surgical, Inc. Dr Grauer is a paid consultant for TIDI Products, Bioventus, Stryker, and Medtronic.

Correspondence should be addressed to: Jonathan N. Grauer, MD, Department of Orthopaedics and Rehabilitation, Yale University School of Medicine, 47 College St, New Haven, CT 06520 ( jonathan.grauer@yale.edu).

Received: April 01, 2019
Accepted: July 22, 2019

10.3928/01477447-20200624-02

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