This research includes a comprehensive examination of PPCs after THAR, with a focus on the associated health-economic implications. Our research conducted the first national-scale investigation into the incidence of PPCs after THAR at the national level. The incidence of PPCs fluctuated between 2.40% and 2.70% from 2010 to 2014. The lowest rate was observed in 2015, after which there was an increase in the incidence, with the highest incidence in 2019 (3.12%). The change in ICD codes may explain the lower incidence of PPCs in 2015. After October 2015, ICD-CM-10 replaced ICD-CM-9, which may result in missing records of patients with PPCs in some institutions [12]. From 2016 to 2019, the incidence of PPCs and ARF increased simultaneously. One possible explanation is that ICD-CM-10 further subdivides ARF into “ARF with hypoxia” (J9601) and “ARF with hypercapnia” (J9602), implying a more definitive diagnosis of ARF, which may result in the increasing number of patients with ARF and PPCs after 2015.

A previous study of PPCs following THA based on the NIS database found that the incidence of PPCs was no more than 2% between 2004 and 2014 [10]. In comparison with THA patients, THAR patients had a higher incidence of PPCs, which may be attributed to the complexity of THAR surgery in dealing with surgical approach, prosthesis fracture and other issues [13, 14]. This complexity will result in a prolonged procedure time which is a main cause to PPCs [14].

In terms of demographic characteristics, patients with PPCs exhibited a statistically significant age difference of 7 years compared to those without the condition. Additionally, from the age distribution, a clinical observation revealed that the PPCs group had a higher proportion of older patients. Moreover, logistic regression analysis identified an independent risk factor for PPCs as being over 65 years old. Undeniably, numerous studies have consistently demonstrated that advanced age is widely acknowledged as a predictive factor for PPCs [15, 16]. A solid explanation is that several changes occurring with age in the respiratory system, such as chest wall compliance progressively decline and diminished ventilatory response to hypoxia and hypercapnia, can make elderly individuals more susceptible to PPCs [4].

The number of comorbidities for patients with PPCs was significantly higher. This finding is acceptable, as a higher prevalence of comorbidities signifies a comparatively diminished state of health prior to surgery, which could elevate the likelihood of experiencing postoperative consequences, including PPCs. Previous studies have reported that PPCs exhibit a correlation with extended durations of hospitalization, escalated healthcare expenditures, and elevated rates of death [9, 17]. Our study yielded similar results, showing that due to PPCs, the median hospital stay was extended by 6 days, the mortality rate was over 30-fold higher, as well as the overall hospitalization cost per admission rose by $66,095.

Several studies of PPCs have indicated that preoperative screening, appropriate management, and risk stratification are crucial for improving outcomes [4, 6, 18]. To effectively reduce and mitigate the incidence of PPCs after THAR surgery, it is essential to identify individuals with elevated risk prior to the operation [4,5,6, 19, 20].

Notably, we found that circulatory system diseases were important risk factors for PPCs, including pulmonary circulation disorders (OR = 4.88), DVT (OR = 5.17), and coagulopathy (OR = 1.99). Joyce J et al. have pointed out that coagulopathy due to surgical trauma is a non-negligible risk factor for complications after THAR, leading to an increase in complications such as DVT, pneumonia, and AMI [21]. Previous studies have identified DVT as a trigger for the development of PE [22]. The shedding and metastasis of the thrombus will directly lead to the occurrence of PE and affect other tissues in the lung, causing other PPCs. Pulmonary circulation is regarded as a highly dynamic system. Pulmonary circulation disorders will greatly increase the risk of insufficient blood supply to the lung and hypoxia, resulting in serious surgical outcomes [23].

Cardiac-related complications are one of the significant challenges that cannot be overlooked after THAR surgery. In our study, congestive heart failure (OR = 2.77) was identified as one of the preoperative risk factors for PPCs, which is associated with an increased risk of postoperative pneumonia (OR = 2.69) and (OR = 3.62). As a chronic disease, congestive heart failure has the risk of deterioration into acute heart failure under the action of risk factors such as age and surgery [24]. acute heart failure aggravates cardiac congestion and affects cardiac ejection, which leads to pulmonary circulation obstruction, resulting in severe PPCs such as pulmonary edema, pneumonia, and ARF [25]. Similar to acute heart failure, AMI and cardiac arrest are likewise pivotal risk factors correlated with cardiac complications subsequent to THAR. According to previous studies, cardiac arrest during surgical anesthesia, although rare, is associated with extremely high mortality (70%) [26, 27]. In our study, when cardiac arrest occurred, the risks for both ARF and PE were more than 4-fold higher, which illustrated the importance of guarding against PPCs after cardiac arrest.

Likewise, the contribution of neurological disorders to the development of PPCs in THAR patients merited close consideration. In our study, we identified other neurological disorders as a risk factor for PPCs (OR = 2.04). Neurological system disorders were closely associated with cardiovascular complications, commonly manifesting as heart failure, respiratory failure, and metabolic disorders [28]. Concurrent with cardiovascular dysregulation, patients’ pulmonary function is inevitably compromised. Additionally, previous studies have reported the relationship between intraoperative anesthesia and neurological disorders [29]. Consequently, controlling anesthesia time and optimizing anesthesia strategy were essential ways to reduce the incidence of PPCs in THAR patients [30].

Among the variables examined in our study, continuous trauma ventilation emerged as the most potent predictor for the development of PPCs after THAR (OR = 11.30). Previous studies have reported several ventilator-associated pulmonary events, including pneumonia, ARF, and PE [31, 32]. Notably, an intimate association between continuous trauma ventilation and ARF (OR = 17.06) was observed in our study, indicating an impairment in patients’ respiratory function when utilizing trauma ventilation. Therefore, non-invasive ventilation is one of the critical ways to reduce PPCs during surgery [31].

Matthew Sloan et al. reported a significantly elevated risk of PE in patients with metastatic cancer (OR = 3.07), such a risk factor was identified in our study (OR = 3.69) [33]. In addition, we observed that blood transfusion was associated with an increased risk of developing PPCs (OR = 1.62), especially pneumonia (OR = 1.91) and PE (OR = 1.44). One plausible explanation is that blood transfusion may indicate a disturbance of the patient’s circulatory system during the perioperative period, such as anemia, hypotension and even heart failure [34,35,36]. Patients with these circulatory disorders may face a higher risk of developing PPCs after THAR surgery.

Previous research has demonstrated a significant association between fluid-electrolyte abnormalities and PPCs [10], which was observed in our study (OR = 3.43). Similarly, as one of the manifestations of fluid imbalance, weight loss is an important risk factor for PPCs (OR = 2.83). It is suggested that fluid-electrolyte imbalances and weight loss may serve as indicators of underlying chronic diseases such as diabetic nephropathy, chronic gastritis, or hypertensive renal damage [10, 37]. Given these findings, patients’ fluid-electrolyte status and weight changes should be closely monitored and managed, thereby optimizing patient outcomes after THAR [37].

There are inherent limitations associated with using NIS databases that should be acknowledged: firstly, it is a retrospective assessment conducted on a national database, which makes it challenging in the examination of particular patient features and factors that influence treatment decision-making; secondly, due to the exclusive reliance on medical billing data in the NIS database, it is possible that coding inconsistencies exist, which could compromise the robustness of multivariate models in accurately capturing observed trends in the development of complications; thirdly, other known risk factors associated with PPCs such as skin moisture, immobility, level of serum albumin, BMI and duration of surgery, are not available within the NIS database [4, 6, 19]. However, the utilization of such an extensive and representative national database like the NIS remains advantageous for identifying trends and demographics due to its widespread use as a reliable research tool [8, 10]. The validity of the NIS database has been confirmed through validation with other databases for accurately identifying patients undergoing specific orthopedic surgeries [8].