Ninety-Day Complications Following Total Hip Arthroplasty with Computer Navigation versus Conventional Techniques

Abstract

Background

Computer navigation is associated with improved limb alignment and implant position in total joint arthroplasty. While it is commonly used in total knee arthroplasty, adoption in the setting of total hip arthroplasty (THA) has been slower. Further, the literature is equivocal on whether computer navigation improves outcomes. The aim of this study was to assess the impact of computer navigation on outcomes in the setting of THA.

Materials and Methods

This was a retrospective cohort study. The National Readmissions Database, from 2016 to 2020, was queried via International Classification of Diseases, Tenth Revision (ICD-10) codes for all patients undergoing THA. To compare outcomes between conventional and computer-navigated THA, propensity score matching was used. In the matched cohort, logistic regression was applied to evaluate postoperative complications, while negative binomial regression was used to analyze readmissions, reoperations, and discharge disposition. Gamma regression with a log-link function was utilized to assess hospital charges and length of stay.

Results

We identified a total of 1,191,362 patients undergoing primary THA. After successful matching, there were 12,918 patients in each cohort. Computer navigation was associated with increased blood transfusions (odds ratio [OR] 2.72; p < 0.001). There were no significant differences in all-cause medical complications (p = 0.123). Computer-navigated procedures were associated with significantly reduced 90-day readmission (OR 0.85; p = 0.028); however, total charges were greater (OR 1.31; p = 0.002).

Conclusion

We found that computer-navigated THA was significantly more expensive but had reduced short-term readmission following surgery. While there were increased odds of blood transfusion, computer navigation may still be safe and beneficial in appropriately selected patients.

 

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Keywords

computer navigation - total hip arthroplasty - short-term outcomes

Hip osteoarthritis is a leading cause of disability, and due to an aging population, it is becoming more common.[1] [2] [3] [4] Total hip arthroplasty (THA) is the definitive cure for end-stage osteoarthritis and generally results in high patient satisfaction; however, as with any surgery, there is potential for devastating complications.[5] [6] Implant positioning may be a modifiable factor in preventing these complications and subsequent poor outcomes. The position of the cup and stem prosthetics is thought to directly correlate to the risk of dislocation, leg length discrepancy, articular wear, impingement, and edge-loading, all of which can lead to hardware failure and the need for revision surgery.[7] [8]

Since the 1990s, multiple methods have emerged that attempt to reduce the variability of hip prosthetic placement, such as robotic-assisted and computer-navigated surgery.[9] [10] These advancements may become increasingly important as surgeons move towards less invasive, tissue-preserving techniques that make visualization and precise placement of the implant more difficult.[7] [10]

Computer-navigated THA has consistently shown to increase the accuracy of cup positioning and stem placement.[11] [12] [13] [14] [15] However, as the technique has potential pitfalls when compared to conventional THA, such as increased costs and longer time in the operating room,[16] [17] [18] it is important to determine if it translates to better outcomes, clinically. This study aimed to evaluate short-term medical, surgical, and orthopedic-specific outcomes of THA performed using computer navigation compared to conventional techniques.

Materials and Methods

Data Source and Patient Identification

This retrospective cohort study utilized the Nationwide Readmission Database (NRD), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality (AHRQ), from 2016 to 2020. The NRD is a national database that includes discharge and readmission information, covering approximately 32 million discharges, or 60.8% of all hospitalizations.[19] It links hospitalization records and patient discharge data within a single calendar year, enabling the evaluation of patient outcomes over time.

With the database, International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10) codes were utilized to identify all adult patients undergoing THA. We then identified the subset of this population who underwent a THA with computer navigation using ICD-10 procedure codes. As the NRD tracks patients for a single calendar year, we included only those who underwent surgery between January 1 and September 30 to ensure the ability to evaluate outcomes for at least 90 days postoperatively.

 

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Preoperative Variables Collected

We collected several preoperative variables, including patient demographics such as sex, age, household income level, and insurance status. Additionally, using ICD-10 codes, we calculated a weighted modified Elixhauser Comorbidity Index score to summarize each patient's overall comorbidity burden.[20] This index has been validated as a strong predictor of outcomes in total joint arthroplasty.[21]

 

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Propensity Score Matching

To minimize confounding and create balanced comparison groups, propensity score matching was used. The propensity scores were generated through a logistic regression model that included age, Elixhauser Comorbidity Index, sex, socioeconomic status, and insurance status as covariates. Patients who underwent computer-navigated THA were matched 1:1 to those who underwent conventional THA using nearest-neighbor matching without replacement, ensuring a caliper width of 0.2 of the standard deviation of the logit of the propensity score ([Fig. 1]).

Fig. 1 Love plot showing variation in patient demographics before and after propensity matching.

 

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Postoperative Outcomes Assessed

With respect to outcomes, we assessed both postoperative complications and hospital-associated outcomes. Complications assessed included both medical and surgical complications. Medical complications include respiratory failure, pulmonary embolism, pneumonia, cardiac arrest, heart failure, myocardial infarction, deep vein thrombosis, acute kidney injury, urological infections, stroke, plegia and paresis, osteomyelitis, and sepsis. Surgical complications include wound disruption, postoperative infection, joint infections, dislocations, periprosthetic fracture, blood transfusion, postoperative neurological complications, postoperative vascular complications, and postoperative shock. Hospital-associated outcomes include mortality, 90-day readmission, 90-day reoperation, length of hospital stay (LOS), discharge disposition (discharge to home is a routine discharge, while non-home discharges were recorded as an adverse discharge disposition), and total charges.

 

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Data Analyses

To ensure the validity of our analysis, we verified that the assumptions for valid logistic and linear regression models were satisfied. For logistic regression, we confirmed that the dependent variable was dichotomous, there was no multicollinearity among predictor variables, and the logit was linear for each continuous independent variable. For linear regression, we assessed the normality of residuals, the independence of observations, the homoscedasticity of residuals, and the linearity of the relationship between each independent variable and the dependent variable.

Categorical results are reported as counts with column percentages. Continuous data are reported as means and standard deviations, with standard errors given where appropriate. Comparison of normally distributed data was performed with independent sample t tests. For non-normally distributed data, the Wilcoxon rank-sum test was performed. Categorical variables were assessed with Fisher's exact test or chi-square test with Rao-Scott second order correction. Where applicable, residuals were assessed for normal distribution and no multicollinearity was observed.

In the matched cohort, logistic regression was applied to evaluate postoperative complications, while negative binomial regression was used to analyze readmissions, reoperations, and discharge disposition. Gamma regression with a log-link function was utilized to assess total hospital charges and length of stay. Confidence intervals were set to 95%, and p-values of 0.05 or less were considered significant. R Foundation for Statistical Computing software version 4.3.1 was used for all analyses.

No Institutional Review Board (IRB) approval was required for this study; the IRB exemption number is 20230793NRR. This study did not require informed consent.

 

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Results

Demographics

We identified a total of 1,191,362 patients undergoing primary THA. About 1,170,427 (98.24%) underwent a conventional, unassisted procedure, while 20,935 (1.76%) underwent computer navigation. Postmatch, there were 12,918 patients in each cohort. The mean age was 66.20 (SD 10.44), and 14,894 (58%) were women. Full demographics, with counts and proportions prematch and postmatch can be seen in [Tables 1] and [2].

Table 1 Demographics, prematch weighted

Demographics	Overall N = 1,191,362[a]	Conventional N = 1,170,427[a]	Computer-navigated N = 20,935[a]	p-Value[b]
Age (years)	65.95 (10.75)	65.95 (10.76)	66.09 (10.51)	0.3
Age category (years)				0.042
< 50	77,903 (6.5%)	76,604 (6.5%)	1,300 (6.2%)
50–64	424,776 (36%)	417,363 (36%)	7,413 (35%)
65–79	570,422 (48%)	560,171 48%)	10,251 (49%)
≥ 80	118,261 (9.9%)	116,289 (9.9%)	1,971 (9.4%)
Gender				0.001
Female	664,844 (56%)	652,853 (56%)	11,991 (57%)
Male	526,517 (44%)	517,574 (44%)	8,944 (43%)
Household income by zip code				<0.001
0–25th percentile	229,594 (19%)	226,564 (19%)	3,030 (14%)
26th–50th percentile	318,392 (27%)	313,265 (27%)	5,127 (24%)
51st–75th percentile	332,557 (28%)	327,494 (28%)	5,063 (24%)
76th–100th percentile	310,817 (26%)	303,102 (26%)	7,715 (37%)
Payer				<0.001
Medicaid	52,942 (4.4%)	52,055 (4.4%)	887 (4.2%)
Medicare	671,443 (56%)	660,070 (56%)	11,373 (54%)
Other	30,953 (2.6%)	30,541 (2.6%)	412 (2.0%)
Private insurance	428,731 (36%)	420,553 (36%)	8,177 (39%)
Self-pay	7,294 (0.6%)	7,207 (0.6%)	87 (0.4%)
Time to procedure	0.00 (2.84)	0.00 (2.86)	−0.02 (1.42)	<0.001
Length of stay	2.00 (2.05)	2.00 (2.06)	1.66 (1.56)	<0.001
Total charge	62,546.46 (40,326.54)	62,198.56 (40,071.61)	81,996.23 (48,859.31)	<0.001
Discharge disposition				<0.001
Adverse discharge	2,358 (0.2%)	2,325 (0.2%)	34 (0.2%)
Home discharge with care	531,917 (45%)	520,572 (44%)	11,345 (54%)
Routine discharge	517,598 (43%)	509,578 (44%)	8,020 (38%)
Transfer to a skilled facility	139,462 (12%)	137,925 (12%)	1,537 (7.3%)
Elixhauser Comorbidity Index				<0.001
0	305,336 (26%)	299,463 (26%)	5,873 (28%)
1–2	564,521 (47%)	554,772 (47%)	9,749 (47%)
3–4	99,882 (8.4%)	98,222 (8.4%)	1,660 (7.9%)
5+	221,623 (19%)	217,970 (19%)	3,653 (17%)
90-day readmission	41,102 (3.4%)	40,532 (3.5%)	570 (2.7%)	<0.001
90-day reoperation	14,146 (1.2%)	13,937 (1.2%)	209 (1.0%)	0.052

^a Mean (standard deviation); n (percentage).

^b Design-based Kruskal–Wallis test; Pearson's χ²: Rao and Scott adjustment.

Table 2 Demographics, postmatch

Demographics	Overall N = 25,836[a]	Conventional N = 12,918[a]	Computer-navigated N = 12,918[a]	p-Value[b]
Age (years)	66.20 (10.44)	66.20 (10.44)	66.20 (10.45)	>0.9
Age category (years)				>0.9
< 50	1,540 (6.0%)	770 (6.0%)	770 (6.0%)
50–64	9,104 (35%)	4,552 (35%)	4,552 (35%)
65–79	12,738 (49%)	6,369 (49%)	6,369 (49%)
≥ 80	2,454 (9.5%)	1,227 (9.5%)	1,227 (9.5%)
Gender				>0.9
Female	14,894 (58%)	7,447 (58%)	7,447 (58%)
Male	10,942 (42%)	5,471 (42%)	5,471 (42%)
Household income by zip code				>0.9
0–25th percentile	3,468 (13%)	1,734 (13%)	1,734 (13%)
26th–50th percentile	5,618 (22%)	2,809 (22%)	2,809 (22%)
51st–75th percentile	6,120 (24%)	3,060 (24%)	3,060 (24%)
76th–100th percentile	10,630 (41%)	5,315 (41%)	5,315 (41%)
Payer				>0.9
Medicaid	1,124 (4.4%)	562 (4.4%)	562 (4.4%)
Medicare	13,988 (54%)	6,994 (54%)	6,994 (54%)
Other	494 (1.9%)	247 (1.9%)	247 (1.9%)
Private insurance	10,130 (39%)	5,065 (39%)	5,065 (39%)
Self-pay	100 (0.4%)	50 (0.4%)	50 (0.4%)
Length of stay	1.75 (1.92)	1.83 (2.21)	1.67 (1.57)	<0.001
Total charge	75,753.97 (47,512.12)	66,175.15 (41,768.64)	85,332.80 (50,860.95)	<0.001
Discharge disposition
Adverse discharge	46 (0.2%)	24 (0.2%)	22 (0.2%)
Home discharge with care	13,345 (52%)	6,073 (47%)	7,272 (56%)
Routine discharge	10,196 (39%)	5,529 (43%)	4,667 (36%)
Transfer to a skilled facility	2,248 (8.7%)	1,291 (10.0%)	957 (7.4%)
Elixhauser Comorbidity Index				>0.9
0	7,338 (28%)	3,669 (28%)	3,669 (28%)
1–2	12,064 (47%)	6,032 (47%)	6,032 (47%)
3–4	2,052 (7.9%)	1,026 (7.9%)	1,026 (7.9%)
5+	4,382 (17%)	2,191 (17%)	2,191 (17%)
90-day readmission	777 (3.0%)	435 (3.4%)	342 (2.6%)	<0.001
90-day reoperation	284 (1.1%)	156 (1.2%)	128 (1.0%)	0.095

^a Mean (standard deviation); n (percentage).

^b Wilcoxon rank-sum test. Pearson's chi-square test.

 

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Medical and Surgical Complications

We found that patients in the computer-navigated cohort did not have a significant difference in all-cause medical complications (odds ratio [OR] 0.92 [95% CI 0.83–1.02]; p = 0.123). However, they had reduced odds of respiratory failure (OR 0.70 [95% CI 0.56–0.89]; p = 0.003) and pneumonia (OR 0.71 [95% CI 0.53–0.95]; p = 0.02). Patients in the computer-navigated cohort had increased all-cause surgical complications (OR 1.92 [95% CI 1.34–2.75]; p < 0.001), specifically blood transfusions (OR 2.72 [95% CI 1.78–4.18]; p < 0.001). There was no significant difference between any other surgical complications evaluated. We found no difference in rates of dislocation (p = 0.102), joint infection (p = 0.366), postoperative infection (p = 0.447), or periprosthetic fracture (p = 0.378). Results of univariate analysis, and counts and proportions prematch and postmatch, can be seen in [Tables 3] and [4]. Results of multivariate analysis can be seen in [Fig. 2].

Fig. 2 Forest plot comparing adverse events. Odds of outcomes are given as computer-assisted relative to conventional total hip arthroplasty. OR, odds ratio.

Table 3 Adverse events prematch

Characteristic	Overall N = 1,191,362[a]	Conventional N = 1,170,427[a]	Computer-navigated N = 20,935[a]	p-Value[b]
Medical complications	103,857 (8.7%)	102,282 (8.7%)	1,575 (7.5%)	0.018
Respiratory failure	15,152 (1.3%)	14,977 (1.3%)	174 (0.8%)	<0.001
Pulmonary embolism	5,146 (0.4%)	5,059 (0.4%)	87 (0.4%)	0.8
Pneumonia	9,652 (0.8%)	9,543 (0.8%)	109 (0.5%)	0.002
Cardiac arrest	979 (<0.1%)	965 (<0.1%)	14 (<0.1%)	0.6
Heart failure	40,746 (3.4%)	40,085 (3.4%)	661 (3.2%)	0.4
Myocardial infarction	5,099 (0.4%)	5,023 (0.4%)	76 (0.4%)	0.3
Transfusion	26,762 (2.2%)	25,753 (2.2%)	1,009 (4.8%)	<0.001
Deep vein thrombosis	5,010 (0.4%)	4,947 (0.4%)	64 (0.3%)	0.041
Acute kidney disease	33,198 (2.8%)	32,733 (2.8%)	464 (2.2%)	0.005
Urological infections	22,594 (1.9%)	22,265 (1.9%)	328 (1.6%)	0.024
Stroke	3,115 (0.3%)	3,082 (0.3%)	32 (0.2%)	0.017
Plegia and paresis	2,738 (0.2%)	2,704 (0.2%)	34 (0.2%)	0.11
Osteomyelitis	996 (<0.1%)	976 (<0.1%)	20 (<0.1%)	0.7
Sepsis	12,842 (1.1%)	12,669 (1.1%)	173 (0.8%)	0.009
Surgical	45,684 (3.8%)	44,431 (3.8%)	1,253 (6.0%)	0.001
Wound disruption	4,825 (0.4%)	4,769 (0.4%)	56 (0.3%)	0.013
Postop infection	5,911 (0.5%)	5,838 (0.5%)	73 (0.4%)	0.025
Joint infection	375 (<0.1%)	371 (<0.1%)	3 (<0.1%)	0.3
Dislocation	375 (<0.1%)	363 (<0.1%)	12 (<0.1%)	0.15
Periprosthetic fracture	9,325 (0.8%)	9,169 (0.8%)	156 (0.7%)	0.7
Postop shock	4,300 (0.4%)	4,246 (0.4%)	54 (0.3%)	0.056
Postop vascular	4,439 (0.4%)	4,389 (0.4%)	50 (0.2%)	0.020

^a n (percentage).

^b Pearson's χ²: Rao and Scott adjustment.

Table 4 Adverse events postmatch

Adverse events (postmatch)	Overall N = 25,836[a]	Conventional N = 12,918[a]	Computer-navigated N = 12,918[a]	p-Value[b]
Medical complications	2,016 (7.8%)	1,088 (8.4%)	928 (7.2%)	<0.001
Respiratory failure	285 (1.1%)	182 (1.4%)	103 (0.8%)	<0.001
Pulmonary embolism	116 (0.4%)	65 (0.5%)	51 (0.4%)	0.2
Pneumonia	189 (0.7%)	123 (1.0%)	66 (0.5%)	<0.001
Cardiac arrest	14 (<0.1%)	7 (<0.1%)	7 (<0.1%)	>0.9
Heart failure	803 (3.1%)	421 (3.3%)	382 (3.0%)	0.2
Myocardial infarction	105 (0.4%)	58 (0.4%)	47 (0.4%)	0.3
Transfusion	1,004 (3.9%)	358 (2.8%)	646 (5.0%)	<0.001
Deep vein thrombosis	98 (0.4%)	60 (0.5%)	38 (0.3%)	0.026
Acute kidney disease	619 (2.4%)	344 (2.7%)	275 (2.1%)	0.005
Urological infections	413 (1.6%)	216 (1.7%)	197 (1.5%)	0.3
Stroke	48 (0.2%)	29 (0.2%)	19 (0.1%)	0.15
Plegia and paresis	42 (0.2%)	21 (0.2%)	21 (0.2%)	>0.9
Osteomyelitis	23 (<0.1%)	11 (<0.1%)	12 (<0.1%)	0.8
Sepsis	257 (1.0%)	150 (1.2%)	107 (0.8%)	0.007
Surgical	1,390 (5.4%)	590 (4.6%)	800 (6.2%)	<0.001
Wound disruption	86 (0.3%)	50 (0.4%)	36 (0.3%)	0.13
Postop infection	115 (0.4%)	70 (0.5%)	45 (0.3%)	0.019
Joint infection	5 (<0.1%)	3 (<0.1%)	2 (<0.1%)	>0.9
Dislocation	9 (<0.1%)	2 (<0.1%)	7 (<0.1%)	0.2
Periprosthetic fracture	213 (0.8%)	120 (0.9%)	93 (0.7%)	0.063
Postop shock	96 (0.4%)	61 (0.5%)	35 (0.3%)	0.008
Postop vascular	97 (0.4%)	64 (0.5%)	33 (0.3%)	0.002

^a n (percentage).

^b Pearson's chi-square test; Fisher's exact test.

 

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Hospital-Associated Outcomes

With respect to hospital-associated outcomes, the computer-navigated procedure was associated with significantly reduced 90-day readmission (OR 0.85 [95% CI 0.74–0.98]; p = 0.05) and LOS (OR 0.86 [95% CI 0.80–0.92]; p < 0.001); however, total charges were greater (OR 1.31 [95% CI 1.11–1.54]; p = 0.002). The computer-navigated cohort averaged $85,332.80 of total charges, while the conventional cohort averaged $66,175.15. There was no difference in 90-day reoperation (p = 0.906). Results of multivariate analysis for hospital-associated outcomes can be seen in [Fig. 3].

Fig. 3 Forest plot comparing hospital outcomes. Odds of outcomes are given as computer-assisted relative to conventional total hip arthroplasty. OR, odds ratio.

 

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Discussion

This study compared short-term outcomes between conventional and computer-navigated THA. We found that computer-navigated THA had reduced odds of respiratory failure and pneumonia, but increased odds of transfusion. With respect to hospital-associated outcomes, computer-navigated THA had reduced length of stay and 90-day readmission, but there was no difference in 90-day reoperation. We found no difference in dislocation, infection, or periprosthetic fracture between the two procedures. Total charges were significantly greater for the computer-navigated procedure.

Multiple studies report that computer-navigated THA leads to more consistently accurate acetabular component positioning than conventional techniques.[11] [12] [13] [14] A study by Najarian et al. analyzed outcomes of imageless computer navigation compared to conventional THA done by a single surgeon and found that computer navigation reduced positional errors of the acetabular component.[7] Specifically, regarding the degree of abduction and anteversion, the standard deviation and number of “outliers” from ideal placement were significantly decreased with computer-navigated surgery.[7] Moskal and Capps found that, while there was no difference in the mean acetabular abduction and anteversion angles, computer-navigated surgery led to significantly more placements within the “safe zone” than the conventional procedure.[22] “Safe zones,” previously described by Lewinnek et al., are the degree of anteversion and abduction that surgeons aim for when positioning the acetabular component.[23] Whether prosthetic positioning within these designated zones translates to better clinical results remains contested.[7] [24] [25] [26]

The literature is divided regarding whether computer navigation is associated with improved orthopedic-specific outcomes.[12] [27] [28] In a retrospective study comparing the results of conventional, unassisted THA with computer-navigated THA, Bohl et al. found that computer navigation was associated with a lower rate of dislocation and aseptic revision of the acetabular component.[11] Our study, however, did not find any difference in dislocations between the two procedures. Of note, the study by Bohl et al. utilized the 100% Medicare Part A claims dataset, which is limited to adults 65 years of age or older. Considering 42.2% of our dataset was younger than 65, this could have had a significant impact on outcomes. Also, their study had a much longer follow-up of 2 to 3 years, while we only assessed short-term outcomes. Similarly to our study, a meta-analysis by Xu et al. found no difference in postoperative dislocation between computer-navigated and conventional groups, although they did report a significant reduction in the number of cups implanted beyond the safe zone with computer navigation.[12] A randomized control study by Parratte et al. found that, upon evaluation during a 10-year follow-up, patients with computer-navigated versus conventional THA had no difference in functional outcome, acetabular linear wear, or survivorship free from aseptic loosening.[29]

Patients in the computer-navigated cohort had reduced odds of pneumonia and respiratory failure, but there was no difference between the two cohorts for any other medical complications assessed. The computer-navigated cohort also had decreased LOS; while these findings were statistically significant, the difference between the two cohorts was 0.16 days, which is not clinically significant. Finally, the computer-navigated cohort had reduced odds of 90-day readmission. A retrospective database study by Hamilton et al. had similar findings; patients undergoing computer-assisted fluoroscopy-based hip navigation had lower readmission rates at both 90 and 365 days.[30]

We found that the total charges of hospitalization were significantly higher for patients undergoing the computer-navigated procedure; this is in agreement with much of the current literature.[17] [18] [31] Brown et al. found computer navigation to be $1,100 more per case than conventional THA due to increased operating time and costly single-use components.[32] Like our own results, these findings did not include the initial investment required for computer navigation software and equipment. However, we could not assess for any added costs associated with readmission and reoperation, which may result in the two procedures being comparatively cost-neutral. A study by de Palma et al. found that an early dislocation (within 6 weeks) could increase the cost of THA by up to 342%.[33] Importantly, we found no difference in odds of dislocation, suggesting that the benefits of computer navigation may not offset these costs, at least not in the short term.

Along with the added costs of computer-navigated THA, the procedure is also typically longer than conventional surgery and could result in a higher risk of blood transfusion. While we were unable to assess and compare operative times, much of the literature reports that computer navigation leads to more time in the OR.[7] [28] [34] [35] Conversely, a study by Singh et al. found that computer-navigated THA had the shortest operating time when compared to both conventional and robot-assisted THA, although the study was performed at a single institution and did not use propensity matching.[36] Longer duration of surgery has been associated with increased incidence of wound complications, deep surgical site infection, and DVT in THA.[37] [38] Additionally, the added surgical time predisposes patients to higher blood loss and increased odds of receiving a blood transfusion.[39] We found that patients undergoing computer-navigated THA had significantly higher odds of needing a transfusion. These additional risks should be considered when debating whether computer navigation is worth the potential benefits.

Limitations

Our study had multiple limitations. This was a retrospective study and, therefore, had inherent bias. For one, we could not control for where these procedures were taking place, and whether or not the conventional cohort had the same overall resources as the computer-navigated one. The centers that perform high volumes of computer-navigated surgery likely have more institutional volume overall, potentially leading to better outcomes.[40] We also could not control for surgeon experience; there is clearly a learning curve for utilizing computer navigation, and as this is a relatively new technique, our results could be impacted.[7] [41] Additionally, we could not account for surgical approach, which may influence the risk of various complications. Further, we could not assess the actual placement of the prostheses to confirm superior positioning in the computer-navigated cohort, although a great deal of evidence supports our stated assumptions. Another limitation was that, similar to studies on individual implants, studies of technology are product-specific; our data do not account for which individual products may perform better than others. Also, our study relied on ICD-10 codes, which are subject to human error. Finally, we had a short-term follow-up of only 90 days, and as orthopedic-specific complications can occur months to years after THA, we likely did not capture the full array of outcomes.

 

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Conclusion

This study found that computer-navigated THA is associated with greater odds of transfusion, is more costly, and has no difference in orthopedic-specific complications when compared to conventional, unassisted THA. However, computer-navigated THA was associated with reduced odds of pneumonia and respiratory failure, shorter LOS, and reduced odds of 90-day readmission. These findings suggest that, while computer navigation is not the outright superior technique, it may be both safe and beneficial in appropriately selected patients, warranting further consideration of its role in improving THA outcomes. Future research should focus on optimizing the cost-effectiveness of computer navigation in THA and further exploring its long-term benefits in reducing complications and improving patient recovery.

 

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Conflict of Interest

None declared.

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Publication History

Received: 23 January 2025

Accepted: 11 July 2025

Article published online:
01 August 2025