Smoking Dependent Alterations in Bone Formation and Inflammation Represent Major Risk Factors for Complications Following Total Joint Arthroplasty

Abstract

Numerous studies have described a correlation between smoking and reduced bone mass. This not only increases fracture risk but also impedes reconstruction/fixation of bone. An increased frequency of complications following surgery is common. Here, we investigate the effect of smoking on the clinical outcome following total joint arthroplasty (TJA). 817 patients receiving primary or revision (including clinical transfers) TJA at our level-one trauma center have been randomly interviewed twice (pre- and six months post-surgery). We found that 159 patients developed complications (infections, disturbed healing, revisions, thrombosis, and/or death). Considering nutritional status, alcohol and cigarette consumption as possible risk factors, OR was highest for smoking. Notably, mean age was significantly lower in smokers (59.2 ± 1.0a) than non-smokers (64.6 ± 0.8; p < 0.001). However, the number of comorbidities was comparable between both groups. Compared to non-smokers (17.8 ± 1.9%), the complication rate increases with increasing cigarette consumption (1⁻20 pack-years (PY): 19.2 ± 2.4% and >20 PY: 30.4 ± 3.6%; p = 0.002). Consequently, mean hospital stay was longer in heavy smokers (18.4 ± 1.0 day) than non-smokers (15.3 ± 0.5 day; p = 0.009) or moderate smokers (15.9 ± 0.6 day). In line with delayed healing, bone formation markers (BAP and CICP) were significantly lower in smokers than non-smokers 2 days following TJA. Although, smoking increased serum levels of MCP-1, OPG, sRANKL, and Osteopontin as well as bone resorption markers (TRAP5b and CTX-I) were unaffected. In line with an increased infection rate, smoking reduced 25OH vitamin D3 (immune-modulatory), IL-1β, IL-6, TNF-α, and IFN-γ serum levels. Our data clearly show that smoking not only affects bone formation after TJA but also suppresses the inflammatory response in these patients. Thus, it is feasible that therapies favoring bone formation and immune responses help improve the clinical outcome in smokers following TJA.

Keywords: bone metabolism; cigarettes; complications; delayed wound healing; infection; pack-years (PY); revision surgery; smoking; total joint arthroplasty (TJA).

Figure 1

Overview on the study population. (A) Flow chart on the patient recruitment: Between June 2016 and January 2018, a total of 817 patients with total joint arthroplasties (TJA) were interviewed for our study. However, 29 patients had to be excluded from the study because of missing data sets. Of the remaining 788 patients, 510 (62.4%) received primary TJA and 284 (37.6%) had a revision TJA. Of the patients with primary TJA, 431 (84.5%) had no complications and 79 (15.5%) had complications up to six months following surgery. Of the patients with revision TJA, 189 (71.2%) had no complications and 80 (28.8%) had complications up to six months following surgery. Venn diagrams on the complications, with the number in patients affected (N) and the relative occurrence (in %) with regard to (B) the patients with primary TJA and (D) the patients with revision TJA. Duration of hospital stay (in days) of the study participants with (C) primary TJA and (E) revision TJA.

Figure 2

Nutritional status and alcohol and cigarette consumption in patients receiving (A–C) primary TJA or (D–F) revision TJA. (A,D) Nutritional status was obtained with the help of the nutrition risk screening 2002, which defines a nutritional risk for obtained scores ≥3. The data are presented as box blot Tukey to mark ouliers (*). (B,E) Pie diagrams showing the alcohol consumption in the study population. Alcohol consumption was defined as never/rarely, occasionally, daily (one glass of wine or beer), and abuse (daily more than one glass of wine, beer and/or hard liquor). (C,F) Pie diagrams showing the smoking behavior of the study population. Cigarette consumption was measured in pack-years (PY), with the number of PY being ((number of cigarettes smoked per day/20) × (number of years smoked)).

Figure 3

Description of the study population based on the smoking behavior. The analysis differentiated between non-smokers (0 PY; N = 381), moderate smokers (1–20 PY; N = 253) and heavy smokers (>20 PY; N = 154). (A) Complication rate is given in % and total numbers (N). (B) Time of hospitalization was documented in days. (C) Patients’ age is given in years. (D) Gender distribution within the groups is given in % and total numbers (N). (E) Patients’ BMI is given in kg/m². (F) Number of comorbidities. * p < 0.05, ** p < 0.01, and *** p < 0.001 as indicated.

Figure 4

Effect of smoking on blood circulating factors. Relative cytokine levels in (pre-surgical) serum samples from non-smokers (0 PY), light smokers (1–10 PY), moderate smokers (11–20 PY) and heavy smokers (>20 PY) were determined with the help of the RayBio® Human Cytokine Array C5 (N = 5 per group). For the heat map, signal intensities were first normalized to the internal (positive) control followed by a second normalization to the mean signal intensity of each cytokine. Under-represented cytokines are colored green; over-represented cytokines are colored red.

Figure 5

Effect of smoking on serum levels of markers for bone formation and resorption. The analysis differentiated between non-smokers (0 PY; N = 14), moderate smokers (1–20 PY; N = 16) and heavy smokers (>20 PY; N = 12). All ELISAs were performed in duplicates. As bone formation markers, serum levels of (A) bone specific alkaline phosphatase (BAP) and (B) type I C-terminal collagen pro-peptide (CICP) were determined. As bone resorption markers, serum levels of (C) tartrate-resistant acidic phosphatase (TRAP5b) and (D) C-terminal telo-peptide of type I collagen (CTX-I) were determined. As regulators for osteoclastogenesis, serum levels of (E) soluble receptor activator of nuclear factor kappa-B ligand (sRANKL), (F) Osteoprotegerin (OPG), (G) the resulting OPG:sRANKL ratio, and (H) the regulatory 25OH vitamin D3 were determined. (I) Osteopontin serum levels were determined as a marker for osteoclast adherence. (J) Monocyte chemoattractant protein-1 (MCP-1/CCL2) serum levels were determined as a stress marker. In addition, serum levels of the tissue inhibitor of metalloproteinases (K) TIMP-1 and (L) TIMP-2 were determined as an indicator for tissue turnover. * p < 0.05, ** p < 0.01, and *** p < 0.001 as indicated.

Figure 6

Effect of smoking on serum levels of inflammatory markers. The analysis differentiated between non-smokers (0 PY; N = 14), moderate smokers (1–20 PY; N = 16) and heavy smokers (>20 PY; N = 12). All ELISAs were performed in duplicates. Serum levels of (A) interleukin 1 beta (IL-1β), (B) interleukin 6 (IL-6), (C) tumor necrosis factor alpha (TNF-α), and (D) interferon gamma (IFN-γ) were determined. * p < 0.05, ** p < 0.01, and *** p < 0.001 as indicated.