Abstract
Background
Chronic osteomyelitis is a debilitating bone infection, characterized by a persistent infection over months to years, poses diagnostic and therapeutic challenges due to its insidious nature and potential for severe bone and soft tissue destruction. This systematic review and meta-analysis aims to review the literature on the treatment of chronic osteomyelitis in long bones and assess cure rates in single versus two-stage surgery.
Methods
Following the PRISMA guidelines and registered with PROSPERO (ID: CRD42021231237), this review included studies that reported on the management of chronic osteomyelitis in long bones using either a planned one-stage or two-stage surgical approach in adult patients. Databases searched included Medline, Embase, Web of Science, CINAHL, HMIC, and AMED, using keywords related to osteomyelitis, long bones, and surgical management. Eligibility criteria focused on adults with chronic osteomyelitis in long bones, with outcomes reported after a minimum follow-up of 12 months. The meta-analysis utilized the random-effects model to pool cure rates.
Results
The analysis included 42 studies with a total of 1605 patients. The overall pooled cure rate was 91% (CI 95%) with no significant difference observed between single-stage and two-stage surgeries (X2 = 0.76, P > 0.05). Complications were reported in 26.6% of cases in single-stage procedures and 27.6% in two-stage procedures, with prolonged wound drainage noted as a common issue. Dead space management techniques varied across studies, with antibiotic-loaded calcium sulphate beads used in 30.4% of cases.
Conclusion
This meta-analysis reveals no significant difference in cure rates between single and two-stage surgical treatments for chronic osteomyelitis in long bones, supporting the efficacy of both approaches. The current treatment strategy should include a combination of debridement, dead space management using local and systematic antibiotics and soft tissue reconstruction if necessary.
Keywords: Osteomyelitis, Single stage, Two-stage, Bone infection, Debridement, Reconstruction
Introduction
Osteomyelitis is characterized by an infectious and destructive inflammatory process affecting the bone that stems from microorganisms' invasion. The infection's etiology varies, originating either from local spread linked to trauma and surgery or from hematogenous dissemination, particularly in the elderly and children [1, 2]. The disease is often compounded by immune, vascular, and soft tissue problems [2]. The manifestations of chronic osteomyelitis are diverse, often remaining indolent for months before symptoms become apparent. The distinction between acute and chronic osteomyelitis, however, is contentious [3]. While some define chronicity based on histopathological examination and sequestrum formation, others consider it chronic when the infection persists for months to years, an arbitrary but commonly used timeframe [1–4]. Nevertheless, chronic osteomyelitis evolves over an extended period, potentially leading to sequestrum, bone destruction, marrow infection, soft tissue involvement, and fistulous tracts [4]. The severity can vary widely, from simple, manageable infections to severe cases with extensive bone destruction, significant functional deficit and even limb loss.
The management of osteomyelitis requires a multifaceted and aggressive approach to eradicate the infection and optimize outcomes [5–7]. Treatment modalities vary, and decision-making remains challenging as it encompasses various surgical techniques, antibiotic delivery methods, duration of antibiotic treatment, and surgical staging [7]. The problems the patient may encounter are multifaceted, and has been highlighted in the classification by Cierny and Mader et al., which categorizes osteomyelitis based on anatomical location, physiological status, and high-risk factors [8]. The complexity of treating osteomyelitis depends on its location, often involving long-term and debilitating treatment regimens. Success is typically indicated by a prolonged remission period, but conclusively declaring the disease cured is often problematic due to late recurrence.
Traditionally, treatment has relied on prolonged antibiotic use and multiple surgical debridements. In two-stage procedures, the primary focus is on eliminating the infection through bone and soft tissue resection, followed by stabilization of the bone, often externally, using fixators or frames. A second stage is planned approximately 4–8 weeks later, though this period can vary. This stage occurs after a course of antibiotics and once the infection has resolved both clinically and biochemically. The second stage concentrates on restoring function, utilizing techniques like fibular grafts, the Masquelet technique, autologous cancellous bone grafts, or bone transport [9–11]. Conversely, single-stage techniques aim to eradicate the infection with appropriate debridement and both local and systemic antibiotics, managing the bone defect in the same stage using techniques similar to those used in the second stage of two-stage management [12–14].
Current approaches emphasize a single thorough debridement, effective management of dead space, both local and systemic antibiotic administration, and a multidisciplinary strategy [15–17].
Comparisons between these techniques in the literature are scarce. This systematic review and meta-analysis aim to thoroughly review the literature on the treatment of chronic osteomyelitis in long bones and assess cure rates in single versus two-stage surgery for the condition.
Methods
The search and selection process followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was prospectively registered with PROSPERO (International Prospective Register of Systematic Reviews) (ID: CRD42021231237).
Search strategy
A systematic search of Medline, Embase, Web of Science, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Healthcare Management Information Consortium (HMIC) and the Allied and Complementary Medicine (AMED) databases was performed using the following search strategy: (("osteomyelitis"[Title/Abstract] OR "bone infection"[Title/Abstract]) AND ("humerus"[Title/Abstract] OR "ulna"[Title/Abstract] OR "radius"[Title/Abstract] OR "fibula"[Title/Abstract] OR "single stage"[Title/Abstract] OR "one stage"[Title/Abstract] OR "two stage"[Title/Abstract] OR "two-stage"[Title/Abstract] OR "long bone"[Title/Abstract] OR "femur"[Title/Abstract] OR "tibia"[Title/Abstract])). Finally, reference lists of relevant articles were reviewed to identify additional articles that were potentially missed during the initial search.
Eligibility criteria
Studies that met the following criteria were included: (1) Management of chronic osteomyelitis in long bones using a planned one-stage or planned two-stage, 2) Patients aged 18 or older, 3) Follow up of at least 12 months, and 4) Clinical outcomes were reported.
Studies were excluded if they met any of the following criteria: (1) Review articles; (2) full text not available; (3) cadaveric studies; (4) Patients less than 18 years; (5) treatment of septic or infected non-unions, (6), non-bacterial osteomyelitis, (7) case series with fewer than 10 patients, (8) joint infections, (9) articles including non-long-bone osteomyelitis were excluded if they did not report outcome data separately for long bones. In addition, articles reporting outcomes on septic non-unions and osteomyelitis collectively were excluded.
Study screening
Titles and abstracts were independently screened for relevance by three authors using Covidence (AL, AE and MP) (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. www.covidence.org). Potentially relevant articles underwent full-text screening, with any conflicts between the authors being resolved by discussion and consensus with the senior authors (HS).
Quality assessment and risk of bias
Study quality assessment was conducted using the methodological index for non-randomized studies (MINORS) tool. Methodological quality was categorized prior as follows: a score of 0–8 or 0–12 was considered poor quality, 9–12 or 13–18 was considered fair quality, and 13–16 or 19–24 was considered excellent quality, for non-comparative and comparative studies, respectively. For randomized controlled trials, the Cochrane risk of bias-2 (RoB-2) tool was used to assess study quality. Quality assessment measurements are denoted after each study in Table 1.
Table 1.
Baseline demographics and patient characteristics
| Study | Study design | MINORS | Sample size | Meeting criteria | Females | Age (yr) | Follow up (mth) | Stage |
|---|---|---|---|---|---|---|---|---|
| Ochsner 1990 [30] | R.cohort | 8 | 25 | 12 | 4 (16%) | 54 (23–82) | 26 (2–60) | One |
| Philandrianos 1992 [31] | R.cohort | 7 | 11 | 10 | 1 (9%) | 51.3 (29–82) | 40.5 (12–82) | One |
| Guelinckx 1995 [32] | R.cohort | 8 | 16 | 10 | 2 (12.5%) | 41 (24–73) | 24 (6–120) | One |
| Pfeiffenberger 1996 [33] | R.cohort | 7 | 28 | 5 | NR | 47 (6–83) | 66 (24–156) | One |
| Yamashita 1998 [34] | R.cohort | 9 | 18 | 13 | 8 (44.4%) | 38.7 (14–77) | 55 (24–75) | One |
| Simpson 2001 [35] | P.comparative | 15 | 50 | 43 | 11 (22%) | 49 (13–82) | 26 (12–48) | One |
| Kuokkanen 2002 [36] | R.cohort | 7 | 21 | 16 | 3 (14.3%) | 34 (30–69) | 30 (7–78) | One |
| Hashmi 2004 [37] | P.cohort | 10 | 17 | 8 | 0 (0%) | 37 (17–53) | 75 (56–95) | One |
| Chang 2007 [38] | R.comparative | 13 | 65 | 65 | 29 (44.6%) | 39.8 (18–69) | 75 (36–334) | One |
| Rao 2007 [39] | P.cohort | 12 | 51 | 7 | 27 (52.9%) | 55.4 (17–83) | 24.9 (3–53) | One |
| Khan 2012 [40] | R.cohort | 7 | 20 | 20 | 3 (15%) | 44.5 (6–73) | 22.5 (19–36) | One |
| Romanò 2014 [41] | R.comparative | 14 | 76 | 76 | 27 (25.5%) | 45.7 (19–80) | 21.8 (12–36) | One |
| Ferrando 2017 [26] | R.comparative | 13 | 25 | 20 | 5 (20%) | 49 (16–86) | 23 (16–33) | One |
| Badie 2019 [42] | P.cohort | 11 | 30 | 30 | 5 (16.7%) | 26.3 (17–53) | min. 12 | One |
| Oosthuysen 2019 [43] | R.cohort | 9 | 24 | 14 | 4 (28.6%) | 34.8 (16–45) | 18.1 (12–29) | One |
| Zhou 2020 [27] | R.cohort | 9 | 42 (43 limbs) | 42 | 19 (45.2%) | 43.7 (23–74) | 42.8 (12.8–77.5) | One |
| Al-Mousawi 2020 [44] | R. Cohort | 7 | 12 | 12 | 5 (41.7%) | 63 (35–74) | 16 (12–24) | One |
| Hotchen 2020 [45] | P. Cohort | 13 | 71 | 63 | 17 (23.9%) | 48.8 (19.9–82.9) | Min. 24 | One |
| Lorentzen 2020 [46] | R.cohort | 7 | 11 | 9 | 3(27.3%) | 62 (39–79) | 26.4 (15–42) | One |
| Bor 2022 [47] | R. cohort | 9 | 16 | 15 | 3 (18.6%) | 49 (13–71) | 72 (18–192) | One |
| Elhessy 2022 [48] | R. Cohort | 9 | 14 | 14 | 4 (28.6%) | 43.4 (17–73) | 30.1 (20–49) | One |
| Jagadeesh 2022 [13] | R.Review of P.Data (comparative) | 16 | 100 | 100 | 31 (31%) | 40.35 | 32.2 (24–63) | One |
| Luo 2022 [49] | R.cohort | 8 | 17 | 16 | 1 (5.9%) | 41.9 (8–70) | > 2 yr | One |
| McNally 2022 [24] | P.cohort | 12 | 100 | 70 | 35 (35%) | 51.6 (23–88) | 72.6 (50.4–100.8) | One |
| Jiamton 2023 [50] | P. Cohort | 9 | 62 | 59 | 13 (21%) | 47.2 | 12 | One |
| Langit 2023 [51] | R. Cohort | 9 | 53 (54 bones) | 53 | 14 (26%) | 45.5 | 29 (12–59) | One |
| Sambri 2023 [52] | R. Cohort | 10 | 93 | 93 | 25 (26.9%) | 40 (4–73) | 21 (12–84) | One |
| Ferguson 2023 [14] | R.Review of P.Data (comparative) | 17 | 359 | 315 | NR | 49.6 (16–89) | 57 (12–126) | One |
| Perry 1986 [53] | R.cohort | 7 | 14 | 8 | NR | 37.7 (23–59) | 14.6 (7–18) | two |
| McNally 1993 [54] | R.cohort | 8 | 37 | 37 | 9 | 42 (18–75) | 49 (12–121) | two |
| Ueng 1994 [25] | R.cohort | 8 | 13 | 5 | 3 (23%) | 35 (17–59) | 37 (24–54) | two |
| Emara 2002 [29] | R.cohort | 9 | 20 | 20 | 2 (10%) | 24 (18–39) | 34 (30–48) | two |
| Alonge 2003 [55] | R.cohort | 8 | 25 | 20 | 9 (36%) | 22.4 (9–44) | 46 (19–80) | Two |
| Zweifel-Schlatter 2006 [56] | R.cohort | 8 | 14 | 10 | 1 (7.7%) | 39 (16–69) | 31.4 (12–52) | Two |
| Wu 2007 [57] | R.cohort | 8 | 23 | 7 | 7 (30.4%) | 48.3 (16–82) | 55 (24–156) | Two |
| Wu 2017 [11] | R.cohort | 9 | 36 | 36 | 6 (16.7%) | 41 (21–68) | 29.5 (21–45) | Two |
| Yu 2017 [9] | R.cohort | 9/ | 13 | 13 | 4 (30.8%) | 39 (16–69) | 17.8 (12–24) | Two |
| Qiu 2017 [10] | R. Comparative | 16 | 40 | 40 | 7 (17.5%) | 37.75 (20–71) | 30.6 (18–54) | Two |
| Buono 2018 [58] | R.comparative | 12 | 24 | 24 | 6 (25%) | 41 (16–75) | 30 (12–144) | Two |
| Wu 2019 [59] | R. Review of P.data | 9 | 28 | 28 | 12 (42.9%) | 41 (21–68) | 29.5 (24–45) | Two |
| Finelli 2019 [60] | RCT | **Some Concerns | 45 | 45 | 7 (15.5%) | 34.8 (> 18) | 24 | Both |
| Zhou 2021 [12] | R.comparative | 15 | 102 | 102 | 7 (6.7%) | 38 (17–63) | NR | Both |
| Aggregates | 1861 | 1605 | 379 (23%) | Mean: 42.7 ± 8.5 | 36 ± 18 | One stage: 28 | ||
| Two stages: 12 | ||||||||
| Comparing: 2 |
*R. (Retrospective), P. (Prospective), ** ROB-2
Data extraction
Three authors independently extracted relevant data from the included studies to a previously piloted Microsoft Excel spreadsheet (Microsoft, Redmond, Washington, USA). These data included general article information, patient demographic and surgical procedure details, and relevant outcome measures.
Outcomes
Outcomes included the cure rate (%). A meta-analysis of proportions using the random-effects model was used to pool the cure rate (%) estimates from different studies. Without appropriate data transformation, the accompanying meta-analyses experience threats to statistical conclusion validity [18], such as confidence limits falling outside of the established zero-to-one range and variance instability [19]. While the logit transformation solves the problem of confidence interval estimates falling outside the zero to one range, it does not necessarily resolve the issues regarding variance from extreme proportional datasets. As the double arcsine transformation (Freeman-Tukey transformation) addresses both problems listed above, it is the preferred transformation method and was implemented in the current analysis. Once the meta-analysis had been performed on the transformed proportions, a back-transformation was performed. There is still no consensus about the back-transformation method that should be used with the Freeman-Tukey double arcsine method, although the harmonic mean was suggested for back-transformation [20]. Secondary outcomes included types of treatments used, complications, dead space management techniques, length of hospital stay, data on cost and the need for secondary interventions.
Meta-analysis
Statistical analysis was performed using R v 3.6.3 (R Core Team, Vienna, Austria). The random-effects model (using the maximum likelihood estimator for tau) was used to pool the effect sizes from the included studies. The underlying hypothesis for adopting the random-effects model is that heterogeneity or observed variance of effect is a sum of sampling error and variation in true-effect sizes stemming from inter-population variability. The generic inverse variance method was used to weigh each trial’s per-protocol population. Subgroup analysis was performed based on the stage. The overall proportion was calculated as well as the proportion within each subgroup. Forest plots were used to visualize the results. P values < 0.05 were considered statistically significant.
Prediction interval
The prediction interval was used to assess the treatment effect that may be predicted in future analyses, considering the different settings across different studies. It captures the variability in the true treatment effect across different settings. With substantial heterogeneity, prediction intervals will be broader than confidence intervals and might be considered a more conservative technique to integrate uncertainty in the analysis [21].
Sensitivity analysis
Sensitivity analysis was performed using the leave-one-out method to assess the effect of the different studies on the estimate and heterogeneity. Sensitivity analysis was performed to assess whether the pooled estimate and between-study heterogeneity were significantly affected by the exclusion of certain studies.
Publication bias and heterogeneity between studies
Funnel plots were used to assess publication bias. Egger’s test was used to test the asymmetry of funnel plots [22]. The trim-and-fill method was also used to detect and adjust for publication bias [23]. The I2 statistic was used to explore the percentage of heterogeneity attributed to variation in true-effect sizes secondary to inter-population variation. Estimates from subgroups within the same study were pooled using a fixed-effects model and used in the meta-analysis. The 95% confidence interval (CI) and Z-statistic were calculated and used for hypothesis testing. Heterogeneity between studies was quantified using the I2 statistic. In the case of high heterogeneity, the cause was investigated, the outlier was removed, and a new result was presented.
Results
After the removal of duplicates from the initial search, a total of 3398 references were retrieved for title and abstract screening (Fig. 1). A total of 3237 articles were excluded after the initial title/abstract screening. Next, 161 studies underwent full-text review. A total of 42 studies were included in the final analysis.
Fig. 1.
PRISMA flowchart illustrating inclusion of studies into the review
Sample data
The pooled patient demographics are outlined in Table 1. Among the included studies, all but one were retrospective, encompassing both cohort and retrospective comparative studies. A total of 1605 patients were analyzed, predominantly male (77%), with an average age of 42.7 ± 8.5 years. The mean follow-up duration was 36 ± 18 months. The studies predominantly focused on one-stage management (28 studies), while twelve opted for planned two-stage management, and two studies offered comparisons between single and two-stage management.
Characteristics of osteomyelitis
The infection characteristics, host status, anatomical regions involved, and organisms are detailed in Table 2. The Cierny-Mader (CM) classification, reported in most studies, identified CM type III as the most common (60%) with host type B prevailing (51%). The etiology was primarily post-traumatic (64%, n = 812), followed by hematogenous origins (23%, n = 295). The tibia was the most affected site (57%, n = 819), with the femur (27%, n = 392) and humerus (6.8%, n = 98) following. Methicillin-susceptible Staphylococcus aureus (MSSA) was the predominant organism (28.5%, n = 357), with Methicillin-resistant Staphylococcus aureus (MRSA) found in 8.7% (109) of cases. Notably, 24.8% (n = 310) of cases showed no growth.
Table 2.
Characteristics of the osteomyelitis according to classification, location and organisms
| Study | Cierny Mader | Host type | Pathology | Bones | Organisms |
|---|---|---|---|---|---|
| Ochsner 1990 [30] | NR | NR | Post-traumatic 11, Hematogenous 1 | Femur 7, Tibia 5 | MSSA 7, Mixed 2, Pseudomonas 2, Coag-ve staph 1 |
| Philandrianos 1992 [31] | NR | NR | Post traumatic 8, Contiguous 2 | Tibia 5, femur 4, phalanx 1 | MSSA 6, Coag-ve staph 1, proteus 1, E.coli 1, Salmonella 1 |
| Guelinckx 1995 [32] | NR | NR | NR | Tibia 10 | NR |
| Pfeiffenberger 1996 [33] | NR | NR | NR | Humerus 5 | MSSA 4, No growth/unknown 1 |
| Yamashita 1998 [34] | NR | NR | Hematogenous 12, Post-traumatic 4, iatrogenic 2 | Tibia 9, humerus 2, femur 2 | MSSA 4, MRSA 2, No growth/unknown 3, coag-'ve staph 1, Pseudomonas 2, streptococcus 1 |
| Simpson 2001 [35] | CMI 2, CMII 3, CMIII 28, CMIV 8 | A: 21, B: 16, C: 4 | Hematogenous: 8, Post-traumatic: 29, Contiguous 4 | Tibia 17, femur 16, humerus 5, radius 1, metatarsal 1, phalanx 1 | MRSA 2, Coag-'ve staph 5, Mixed 15, MSSA 15, Diptheroids 1, Streptoccous 2, Proteus 1, |
| Kuokkanen 2002 [36] | NR | NR | Post-traumatic 16 | Tibia 16 | NR |
| Hashmi 2004 [37] | CMIII 6, CMIV: 11 | A:16, B:1 | Post-traumatic 8 | Femur 4, Tibia 4 | MSSA 4, Mixed 1, Coag- ‘ve staph 1, Pseudomonas 2 |
| Chang 2007 [38] | CMI: 44, CMII: 2, CMIII: 16, CMIV: 3 | A 55, B 9, C 1 | Hematogenous 41, iatrogenic 13, post-traumatic 11 | Femur 26, tibia 32, humerus 5, radius/ulna 2 | MSSA 22, Pseudomonas 7, MRSA 6, Coag- ‘ve staph 4, Enterobacter cloacae 2, Micrococcus 1, No growth/unknown 23 |
| Rao 2007 [39] | NR | NR | NR | tibia 3, tibia/fibula 2, femur 1, leg 1 | VRE 3, coag-ve staph 2, Mixed 1, MSSA 1 |
| Khan 2012 [40] | NR | NR | Post-traumatic 20 | Tibia 20 | NR |
| Romanò 2014 [41] | CMI 21, CMII 4, CMIII 46, CMIV 5 | A: 29, B: 44, C: 3 | Iatrogenic 31, post-traumatic 25, Hematogenous 20 | Tibia 37, Femur 25, Humerus 3, Tibia/femur 1, Other 1 | MRSA 28, MSSA 20, No growth/unknown 14, Coag-ve staph 13, Mixed 13, Enterococcus 8, Pseudomonas 8, Strep 2 |
| Ferrando 2017 [26] | NR | NR | Iatrogenic 15, post-traumatic 8, Hematogenous 2 | Tibia 13, femur 6, humerus 1 | MSSA 11, MRSA 3, Pseudomonas 6, E.Coli 1, Finegoldia magna 1, streptococcus 1, Mixed 1 |
| Badie 2019 [42] | CM I to III | C excluded | Hematogenous 17, post-traumatic 13 | Ulna 1, radius 2, humerus 2, femur 11, tibia 14 | MSSA 15, MRSA 3, Klebsiella 2, E.Coli 2, Proteus 2, Salmonella 1, Streptococcus 1, mixed 2, No growth/unknown 2 |
| Oosthuysen 2019 [43] | CMIII 14 | A: 7, B: 7 | Post-traumatic 9, Hematogenous 4, Contiguous 1 | Femur 3, Tibia 8, Radius 1, ulna 1, humerus 1 | MSSA 3, No growth/unknown 3, Mixed 2, MRSA 2, Bifidobacterium 1, Enterobacter 1, Pseudomonas 1, Strep 1 |
| Zhou 2020 [27] | CMIII 43 | A: 36, BS:6, BL: 1 | post-traumatic 31, hematogenous 10, contiguous 2 | Tibia 43 | No growth/unknown 22, MSSA 11, Enterococcus 2, Pseudomonas 2, Acinetobacter baumannii 1, Aeromonas hydrophilia 1, Coag-ve staph 1, E.coli 1, Klebsiella 1, Mixed 1 |
| Al-Mousawi 2020 [44] | CMII 7, CMIII 5 | NR | Post-traumatic 9, Contiguous 3 | Femur 3, tibia 7, fibula 2 | S.aureus 8, E.coli 3 |
| Hotchen 2020 [45] | NR | NR | NR | Tibia 34, Femur 22, Humerus 8, Fibula 3, Radius 3, ulna 1 | NR |
| Lorentzen 2020 [46] | NR | NR | Post-traumatic 8, iatrogenic 1 | tibia 5, humerus 1, fibula 1, tibia/fibula 1, ulna 1 | NR |
| Bor 2022 [47] | CMI 2, CMIII 12, CMIV 1 | A: 9, B: 6 | Post-traumatic 9, Hematogenous 3, iatrogenic 3 | Tibia 7, Femur 4, humerus 2, fibula 1 | Unspecified 4, MSSA 8, Pseudomonas 1, Serratia 1, Provedencia rettgeri 1 |
| Elhessy 2022 [48] | CMI 14 | A: 6, B: 8 | NR | Tibia 11, femur 3 | MRSA 8, MSSA 2, Pseudomonas 1, No growth/unknown 3 |
| Jagadeesh 2022 [13] | CMI 21, CMIII 70, CMIV 7 | A: 74, B: 26 | NR | Tibia 74, femur 22, humerus 3, radius/ulna 1 | No growth/unknown 30, mixed 9, MSSA 21, MRSA 9, Staph epidermidis 5, E.coli 4, Pseudomonas 7, others 15 |
| Luo 2022 [49] | CMIII 11, CMIV 5 | NR | Post-traumatic 16 | Fibula 16 | NR |
| McNally 2022 [24] | CMIII: 72, CMIV: 18 | A: 19, B: 71 | post-traumatic 71, hematogenous 19, iatrogenic 6, contiguous 4 | Tibia 38, femur 24, humerus 16, radius/ulna 10, femur/tibia 1, fibula 1 | MSSA 30, Mixed 21, Pseudomonas 7, Enterococcus 6, MRSA 6, Coag-ve staph 5, Enterobacter 5, E.Coli 5, Strep. 5, Cornyebacteria 4, Klebsiella 4, Proteus 4, Achromobacter 3, Morganella morganii 3, Bacillus 2, Citrobacter 2, Bacteroides 1, Clostridia 1, Propionobacter 1, Salmonella 1, Serratia 1 |
| Jiamton 2023 [50] | CMI 11, CMII 3, CMIII 37, CMIV 11 | A: 47, B: 15 | Post-traumatic 48, hematogenous 14 | Tibia 34, femur 19, humerus 4, calcaneus 2, clavicle 1, forearm 1, fibula 1 | No growth/unknown 28, Mixed 7, Pseudomonas 9, MSSA 4, MRSA 1, Aerococcus viridans 1, Coag-'ve staph 2, Enterobacter 1, Enterococcus 1, Serratia 1, Staph cohnii 1, staph hemolyticus 1, staph hominis 1 |
| Langit 2023 [51] | CMI 10, CMIII 39, CMIV 5 | A: 23, B: 31 | Post-traumatic 46, hematogenous 7, iatrogenic 1 | Tibia 27, femur 10, humerus 9, fibula 5, ulna 2, radius 1 | Mixed 12, No growth/unknown 13, MSSA 19, Enterobacter 2, salmonella 1, coag-ve staph 2, streptococcus 1, staph mitis 1, staph lugdunesis 1, anaerobes 1, pseudomonas 1 |
| Sambri 2023 [52] | CMI: 31, CMII 13, CMIII 21, CMIV 28 | A: 67, B: 26 | Post-traumatic 25, Hematogenous 47, iatrogenic 21 | Femur 24, Tibia 52. Humerus 6, radius 4, others 7 | Negative 32, MRSA 18, MSSA 21, mixed 5, coag-'ve staph 10, enterobacter 7 |
| Ferguson 2023 [14] | CMIII 284, CMIV 75 | A: 99, B: 260 | Post-traumatic 222, Hematogenous 83, iatrogenic 43, contiguous 11 | Tibia 165, Femur 101, forearm 20, foot 11, Others 33 | Mixed 73, No growth/unknown 106, MSSA 90, MRSA 12, coag-'ve staph 21, Pseudomonas 16, E.Coli 4, Enterobacter 8, Diphtheroids 2, Enterococcus 2, Proteus 3, Candida 2, Klebsiella 1, Bacteroids 1, Mycobacterium 3, Corynebacterium 3, serratia 3, strep 2, achromobacter 2, bacillus 2, salmonella 2, Cutibacterium acne 1, C.difficile 1 |
| Perry 1986 [53] | NR | NR | Hematogenous 3, post-traumatic 5 | Tibia 3, femur 4, radius 1 | MSSA 5, Mixed 3 |
| McNally 1993 [54] | NR | NR | post-traumatic 31, haematogenous 5, iatrogenic 1 | Tibia 25,, femur 9, radius 2, humerus 1 | NR |
| Ueng 1994 [25] | CMIII: 5 | A: 5 | Post-traumatic 5 | Tibia 5 | mixed 2, pseudomonas 2, serratia 1 |
| Emara 2002 [29] | CMIII: 8, CMIV: 12 | A:20 | Post-traumatic 19, Hematogenous 1 | Tibia 20 | NR |
| Alonge 2003 [55] | NR | NR | Post-traumatic 4, Iatrogenic 5, Contiguous 2, NR 9 | Tibia 7, femur 10, Humerus 1, ulna 2 | MSSA 8, No growth/unknown 10, Proteus 2 |
| Zweifel-Schlatter 2006 [56] | CMIII:10 | B: 10 | Post-traumatic 10 | Tibia 10 | MSSA 8, mixed 2, No growth/unknown 2 |
| Wu 2007 [57] | CMIII 7 | A: 6, B:1 | Post-traumatic 7 | Femur 7 | No growth/unknown 1, Pseudomonas 1, Mixed 2, acinetobacter 1, enterobacter 1, MRSA 1, |
| Wu 2017 [11] | CMIV 36 | B: 36 | post-traumatic 35, hematogenous 1 | femur 19, tibia 16, fibula 1 | Mixed 13, MSSA 12, No growth/unknown 6, MRSA 5 |
| Yu 2017 [9] | NR | NR | NR | Femur 13 | Mixed 3, No growth/unknown 3, Citrobacter 1, MRSA 6 |
| Qiu 2017 [10] | NR | NR | Post-traumatic 40 | Tibia 40 | MSSA 14, Coag-ve staph 3, Strept 2, Enterococcus 4, enterobacter 4, E.Coli 3, Klebsiella 3, Proteus 1, Pseudomonas 1, Citrobacter 1, acinetobacter 3, |
| Buono 2018 [58] | CMIII or IV: 24 | NR | post-traumatic 23, iatrogenic 1 | Tibia 24 | NR |
| Wu 2019 [59] | CMI 8, CMIII 11, CMIV 9 | A: 8, B: 20 | post-traumatic 12, hematogenous 16 | Humerus 28 | MSSA 14, No growth/unknown 8, MRSA 6 |
| Finelli 2019 [60] | CMI: 45 | NR | Post-traumatic 45 | tibia 29, femur 16 | MSSA 23, Coag-ve staph 13, Enterococcus 5, Enterobacter 4, Strep 4, pseudomonas 3, Klebsiella 2, proteus 1, Providencia 1, serratia 1 |
| Zhou 2021 [12] | NR | NR | NR | Tibia 76, femur 26 | NR |
| Aggregates |
CMI: CMII: 32 (2.9%) 207 (18.6%) CMIII: 667 (60%) CMIV: 205 (18.5%) |
A: 547 (47.6%) B: 594 (51.7%) C: 8 (0.7%) |
Post-traumatic: 812 (63.8%) Hematogenous: 295 (23.2%) Contiguous: 29 (2.8%) Iatrogenic: 137 (10.8%) |
Tibia: 819 (57.2%) Femur: 392 (27.4%) Humerus: 98 (6.8%) Radius/ulna: 23 (1.6%) Fibula: 27 (1.9%) Others: 73 (5%) |
MSSA: 357 (28.5%) MRSA: 109 (8.7%) Pseudomonas 66 (5.3%) Coag—‘ve staph: 85 (6.8%) Enterococcus: 22 (1.8%) Klebsiella: 9 (0.7%) Enterobacter: 30 (2.4%) E.coli: 18 (1.4%) Polymicrobial: 163 (13%) No growth/unknown: 310 (24.8%) Others: 83 (6.6%) |
MSSA: Methicillin-Sensitive Staphylococcal Aureus, Methicillin-Resistant Staphylococcus Aureus
Management strategies
The surgical treatment strategies are categorized in Table 3, including debridement, dead space management, soft tissue coverage, bone graft, and osseous stabilization. Dead space management techniques varied, with antibiotic-loaded calcium sulphate (CaSO4) beads (e.g., Stimulan, Osteoset T) used in 30.4% (n = 469) of cases. Polymethyl methacrylate (PMMA) cement was utilized in 15% (n = 236) of cases, employed as beads, spacers, and in Masquelet techniques. Other treatments included Cerament G (CaSO4 + hydroxyapatite), S53P4 bioactive glass, and others as described in Table 3. Flaps were required in 21.6% (n = 332) of cases, and bone grafts were used in 17% (n = 274), incorporating autologous, allograft, and reamer aspirate autograft.
Table 3.
Management strategies and cure rates within the included studies
| Study | Management Protocol | Cure rate | Dead space Mx | Flaps | Bone graft | |
|---|---|---|---|---|---|---|
| Onestage | Ochsner 1990 [30] | IM reaming + Abx loaded PMMA beads | 7/8 (87.5%) | PMMA beads 8 | None | None |
| IM reaming + Suction irrigation drainage | 4/4 (100%) | |||||
| Philandrianos 1992 [31] | Debridement + Laser sterilisation + suction drainage + ABx loaded haemostatic device ± flap | 10/10 (100%) | hemostatic device 9 | local skin 4, Muscle 1 | None | |
| Guelinckx 1995 [32] | Debridement + free muscle flap | 10/10 (100%) | - | None | None | |
| Pfeiffenberger 1996 [33] | Debridment + Abx loaded PMMA beads | 2/3 (66.6%) | PMMA beads 3 | None | None | |
| Debridement only | 1/2 (50%) | |||||
| Yamashita 1998 [34] | Debridement + Abx loaded calcium-hydroxyapatite | 13/13 (100%) | Ca-HA ceramic blocks 13 | None | None | |
| Simpson 2001 [35] | Debridement + Abx loaded PMMA beads | 24/30 (80%) | PMMA beads 30 | Free 3, local 1, free fibula 1 | None | |
| Debridement + free or local flap | 3/3 (100%) | |||||
| Minimal Debridement: drainage, tissue debulking, removal of sequestra and lavage | 0/4 (0%) | |||||
| Kuokkanen 2002 [36] | Debridement + muscle flap | 15/16 (93.8%) | - | Muscle 16 | 3 | |
| Debridement + bone graft + muscle flap | 3/3 (100%) | |||||
| Hashmi 2004 [37] | Debridment + IM suction irrigation drainage (Lautenbach technique) | 8/8 (100%) | - | None | None | |
| Chang 2007 [38] | Debridement only | 24/40 (60%) | CaSO4 beads 65 | None | None | |
| Debridement + ABx loaded CaSO4 | 20/25 (80%) | |||||
| Rao 2007 [39] | Debridement + Abx loaded PMMA beads | 7/7 (100%) | PMMA beads 7 | None | None | |
| Khan 2012 [40] | Debridement + free radial forearm fasciocutaneous flap | 12/12 (100%) | - | Fasciocutaneous 20 | None | |
| Debridement + autogenic bone graft + free radial forearm fasciocutaneous flap | 8/8 (100%) | |||||
| Romanò 2014 [41] | Debridement + hydroxyapatite & CaSO4 | 24/27 (99.9%) | CaSO4 beads 27, tricalcium PO4 beads 22, Bioglass 27 | None | Bone matrix 22 | |
| Debridement + s53p4 bioglass | 25/27 (92.6%) | |||||
| Debridement + tricalcium phosphate & ABx-loaded demineralised bone matrix | 19/22 (86.4%) | |||||
| Ferrando 2017 [26] | Debridement + Reamer-Irrigator-Aspirator + s53p4 bioglass | 9/9 (100%) | CaSO4 beads 9, Bioglass s53p4 11 | Muscle 3 | None | |
| Debridement + Reamer-Irrigator-Aspirator + s53p4 bioglass + ALT flap | 2/2 (100%) | |||||
| Debridement ± Reamer-Irrigator-Aspirator + CaSO4 ± ALT flap | 8/9 (89%) | |||||
| Badie 2019 [42] | Debridement + Abx loaded CaSO4 mixed with bone marrow aspirate autograft ± flap | 23/30 (77%) | CaSO4 beads 30 | None | Bone marrow aspirate 30 | |
| Oosthuysen 2019 [43] | Debridment + s53p4 bioglass | 13/14 (92.9%) | Bioglass 14 | None | None | |
| Zhou 2020 [27] | Debridement + Abx loaded CaSO4 | 37/41 (90.2%) | CaSO4 beads 43 | Unspecified 2 | None | |
| Debridement + Abx loaded CaSO4 + flap | 1/2 (50%) | |||||
| Al-Mousawi 2020 [44] | Debridment + keystone perforator island flap | 11/12 (91.7%) | - | Fasciocutaneous 12 | None | |
| Hotchen 2020 [45] | Debridement ± (Abx loaded CaSO4 with CaCO3) OR (abx loaded CaSO4 with hydroxyapatite) ± flap | 61/63 (96.8%) | CaSO4 + CaCO3 beads, CaSO4 beads + HA. Numbers NR | Unspecified 54 | None | |
| Lorentzen 2020 [46] | Debridement + Abx loaded CaSO4 with hydroxyapatite ± flap | 8/9 (88.9%) | CaSO4 + HA 9 | Muscle 9 | None | |
| Bor 2022 [47] | Debridement + removal of metal + Abx loaded PMMA cement | 15/15 (100%) | PMMA beads 1, IM nail/rod 3, cemented rod 2, Cement blocks 8 | None | None | |
| Elhessy 2022 [48] | Debridement + IM reaming and irrigation + Abx loaded CaSO4 | 14/14 (100%) | CaSO4 beads 14 | None | None | |
| Jagadeesh 2022 [13] | Debridement + Abx loaded CaSO4 | 44/50 (88%) | CaSO4 pellet 50 | Unspecified 10 | 50 | |
| Debridement + bone graft | 32/50 (64%) | |||||
| Luo 2022 [49] | Debridement + distally based peroneal artery perforator + fasciocutaneous flap | 16/16 (100%) | - | Fasciocutaneous 16 | None | |
| McNally 2022 [24] | Abx loaded CaSO4 hydroxyapatite ± flap | 66/70 (94.3%) | CaSO4 + HA 70 | NR* | None | |
| Jiamton 2023 [50] | Debridement + Abx loaded microporous nanohydroxyapatite (nHA-ATB) beads ± flap | 52/53 (98.11%) | Nanohydroxyapatite beads 62 | None | None | |
| Langit 2023 [51] | Debridement ± IM reaming & irrigation + stimulan or cerament G ± flap | 45/53 (85%) | - | Unspecified 11 | None | |
| Sambri 2023 [52] | Debridement + PerOssal beads ± flap | 70/93 (74.5%) | PerOssal beads 93 | local 2, free 5 | None | |
| Ferguson 2023 [14] | Debridement + osteoset T ± flap | 159/179 (88.8%) | CaSO4 beads 179, CaSO4 + HA 180 | Muscle 98 | None | |
| Debridement + cerament G ± flap | 172/180 (96.6%) | |||||
| Two stage | Perry 1986 [53] | Stage 1: Debridement + Abx loaded implantable pump. Stage 2: pump removal | 5/8 (62.5%) | Implantable pump 8 | None | None |
| McNally 1993 [54] | Stage 1: Debridement + Abx loaded PMMA beads or muscle flap; Stage 2: redebridment ± removal of beads + autogenous bone transplant | 28/32 (92%) | PMMA beads 23 | Muscle 14 | 37 | |
| Ueng 1994 [25] | Stage 1: Debridment + Abx PMMA beads; Stage 2: Removal of beads, autogenous bone graft | 5/5 (100%) | PMMA beads: 5 | None | 5 | |
| Emara 2002 [29] | Stage 1: Debridement + corticotomy; Stage 2: corticotomy + Segment transfer | 19/20 (95%) | - | None | None | |
| Alonge 2003 [35] | Stage 1: Debridement + Abx loaded PMMA beads + flap; Stage 2: redebridment + removal of beads + autogenous bone graft | 17/20 (85%) |
PMMA beads 19 (3 patients had 1 stage with retained PMMA) |
Fasciocutaneous 2, cross-leg 1 | 3 | |
| Zweifel-Schlatter 2006 [56] | Stage 1: Debridement ± continous irrigation/drainage; Stage 2: Debridement + free fasciocutaneous flap | 6/6 (100%) | - | Fasciocutaneous 10 | 4 | |
| Stage 1: Debridement ± continous irigation/drainage; Stage 2: Debridement + free fasciocutaneous flap + bone graft | 4/4 (100%) | |||||
| Wu 2007 [57] | Stage 1: Debridement + Abx loaded PMMA beads; Stage 2: plate + bone graft | 6/7 (85.7%) | PMMA beads 7 | None | 7 | |
| Wu 2017 [11] | Stage 1: Debridement + Abx PMMA spacer ± flap; Stage 2: Removal of spacer, bone graft | 30/36 (83.3%) | PMMA powder/spacer 36 | Unspecified 8 | 36 | |
| Yu 2017 [9] | Stage 1: Debridement, plate, PMMA spacer; Stage 2: removal of spacer, bone graft (Masquelet) | 12/13 (92.3%) | PMMA spacer 13 | None | 13 | |
| Qiu 2017 [10] | Stage 1: Debridement + Abx loaded PMMA beads; Stage 2: beads removal + bone graft | 16/18 (88.9%) | PMMA beads 18, Cement Spacer 22 | Fasciocutaneous 18 | 40 | |
| Stage 1: Debridement + Abx loaded spacer (Masquelet); Stage 2: spacer removal + bone graft | 20/22 (90.9%) | |||||
| Buono 2018 [58] | Stage 1: Debridement + Abx loaded PMMA beads; Stage 2: Bead removal + bone graft + free muscle flap | 11/13 (84.6%) | PMMA beads 24 | Muscle 13, Fasciocutaneous 11 | 11 | |
| Stage 1: Debridement + Abx loaded PMMA beads; Stage 2: Bead removal + bone graft + free fasciocutaneous flap | 10/11 (90.9%) | |||||
| Wu 2019 [59] | Stage 1: Debridement + Abx rod; Stage 2: removal of cement rod ± masquelet bone grafting | 5/8 (62.5%) | Cemented rod 8, PMMA spacer 20 | None | 13 | |
| Stage 1: Debridement + Abx PMMA spacer; Stage 2: removal of spacer ± masquelet bone grafting | 20/20 (100%) | |||||
| Compared | Finelli 2019 [60] | Debridment + IM reaming with Reamer Irrigator Aspirator | 20/23 (87%) |
One-stage: None Two-stage: PMMA spacer 22 |
None | None |
| Stage 1: Debridement + Conventional IM reaming + Abx PMMA spacer; Stage 2: removal of spacer | 21/22 (95.5%) | |||||
| Zhou 2021 [12] | Debridement + Abx loaded CaSO4 + osteotomy + bone transport | 61/70 (87.1%) | Total: CaSO4 implantation 102 | None | None | |
| Stage 1: Debridement + Abx loaded CaSO4; Stage 2: osteotomy + bone transport | 30/32 (93.8%) | |||||
| Aggregates |
PMMA implant: 236 (15.7%) CaSO4 beads (osteoset T, Stimulan): 469 (31.2%) S53P4 Bioglass: 52 (3.5%) CaSO4 + HA (Cerament G): 259 (17.2%) PerOssal beads: 93 (6.2%) Nanohydroxyapatite beads: 62 (4.1%) Others: 145 (9.6%) None: 188 (12.5%) |
Total flap use: 332 (21.6%) muscle flaps: 154 (10%) Fasciocutaneous flaps: 89 (5.8%) Unspecified/others: 89 (5.8%) |
Total Bone graft use: 274 (17%) |
*Unable to exclude cases not meeting criteria. NR, Not reported
Complications
Complications reported across studies exhibited considerable heterogeneity, detailed in Table 4. Recurrence of infection was treated as a failure, not a complication, and is thus analyzed separately under cure rates. The overall complication rates were similar for both single-stage and two-stage treatments (26.6% and 27.6%, respectively). The most frequent complication in single-stage procedures was prolonged wound drainage (13%), with stiffness and reduced range of motion also commonly reported.
Table 4.
Aggregated complications in both groups
| Complication | One stage | Two stages |
|---|---|---|
| Chronic pain | 8 | 0 |
| Complete flap failure/anastomosis thrombosis managed surgically | 2 | 3 |
| Thromboembolism (DVT, PE) | 3 | 0 |
| Fracture managed surgically | 17 | 2 |
| Hematoma managed surgically | 1 | 2 |
| Hematoma managed conservatively | 1 | 0 |
| Non-union/mail-union | 11 | 7 |
| Partial flap failure managed conservatively | 2 | 0 |
| Partial flap failure managed surgically | 2 | 0 |
| Flap edema | 1 | 0 |
| Pin site infection | 17 | 19 |
| Prolonged wound leakage | 150 | 10 |
| Reduced range of motion | 35 | 24 |
| Reduced sensation/nerve injury | 19 | 1 |
| Seroma | 1 | 0 |
| Abscess | 1 | 0 |
| Wound healing problems/superficial infections managed surgically | 13 | 4 |
| Wound healing problems/superficial infections managed conservatively | 7 | 0 |
| Deep infection managed conservatively | 4 | 0 |
| Acute on top of chronic osteomyelitis | 1 | 0 |
| Amputation | 3 | 1 |
| Kidney failure | 2 | 0 |
| Skin rash | 0 | 1 |
| Unrelated/insignificant Complications | 20 | 0 |
|
Overall complication rate (Excluding death due to disease, recurrence of COM and unrelated/insignificant Cx) |
301/1131 (26.6%) | 74/268 (27.6%) |
Meta-analysis of cure rates
The analysis included 1636 patients. Single stage method was used in 1339 patients and the two-stage method was used in 297 patients. The pooled cure rate was 91% (CI 87%; 93%). Stratifying the analysis by stage did not reveal a statistically significant difference (X2 = 0.76, P > 0.05) with similar cure rate across stages (Fig. 2). The funnel plot was symmetric indicating the absence of publication bias. Egger’s test was not statistically significant (P = 0.64).
Fig. 2.
Meta-analysis of cure rates in single and two-stage groups
Discussion
In our systematic review and meta-analysis on the treatment of osteomyelitis, we examined the evolving therapeutic strategies for this complex condition. Our findings reveal that, in terms of cure rates, or more appropriately termed, non-recurrence rates, there appears to be no significant difference when comparing single versus two-stage management of chronic osteomyelitis. This analysis is the first to collectively assess the success rates of single versus two stage management.
The decision between single-stage and multi-stage procedures is important, particularly considering the implications of lengthier hospital stays, increased costs, and operational complexities associated with two-stage management. Zhou et al. highlighted the notably higher costs and extended hospital stays associated with two-stage procedures compared to single-stage management [12]. Their findings indicate an average hospital stay of 28 days for the two-stage group, versus 18 days for those undergoing single-stage procedures. Similar trends are noted in studies by McNally, Ueng, and Qiu, reporting hospital stays of 27, 22, and 24 days respectively in two-stage treatment [10, 24, 25]. However, variability in hospital stay lengths is influenced by different institutional protocols and the possibility of outpatient management. Across studies, a comprehensive report on the costs and durations of hospital stays is generally deficient.
The surgical aspect of treatment is intricate, and our data indicates that debridement alone is associated with lower cure rates. Quantifying the extent of debridement in various studies presents another challenge, as the terminology used to describe it, such as "radical" or "adequate," is open to diverse interpretations. Consequently, the current data does not allow for distinct categorization of debridement methods.
Dead space management has become increasingly significant in recent years. Techniques such as antibiotic-coated beads and cement, muscle flaps, and bone grafts for addressing compromised soft tissue and bone loss have shown favorable outcomes based studies included in this review.. The induced membrane or Masquelet technique, though requiring a two-stage approach, has shown reliable results in our review [10, 11]. Additionally, bone defect management techniques, such as circular frames and bone segment transfers, offer stability, enabling early range of motion and weight-bearing. Jagadeesh et al.'s study reported a higher success rate with the use of calcium sulfate compared to debridement alone [13]. The current evidence suggests that the effectiveness of various local antibiotic delivery systems is comparable [14, 26].
Complication reporting varied across studies, with a notable incidence of prolonged wound drainage in single-stage procedures, often associated with calcium sulfate beads. While concerning, this drainage is not necessarily a harbinger of infection. Ferguson et al. reported high rates of wound leakage using calcium sulphate beads, but highlighted the low risk of infection associated with it [14]. Jagadeesh et al. also reported 18 out of 50 patients had ongoing serous discharge with the use of calcium sulphate that lasted up to 4 weeks resolving without treatment other than dressing changes [13]. This is in line with reports of 4–30% serous discharge while calcium sulphate is undergoing resorption. It is perhaps mitigated by adequate soft tissue coverage and judicious use of calcium sulphate [12, 14, 27, 28]
Commonly reported complications included wound issues, stiffness, and neuropathic symptoms, which could potentially be alleviated by early rehabilitation following extensive surgeries. Moreover, data on postoperative range of motion is scarce; improved reporting could reveal differences in single-stage groups, potentially allowing for earlier postoperative rehabilitation. More pin site issues were observed in the two-stage group, potentially due to longer durations of fixator use [10, 12, 29]. However, drawing definitive conclusions in this regard is difficult due to the more frequent use of fixators in two-stage management, as well as variations in the definition of pin-site infections. The occurrence of fractures in both treatment approaches necessitates cautious management, particularly regarding the introduction of implants. Systemic complications such as deep vein thrombosis, pulmonary embolism, and acute kidney injuries were also noted, albeit less frequently.
Perhaps it is key to highlight the literature's deficiencies, including the heterogeneity in antibiotic administration, inclusion criteria covering various bones and etiologies, and diverse causative organisms. These variations make it challenging to conclusively determine the superiority of specific treatments. In addition, the analysis represents single-arm comparisons, which are potential sources of bias. Although studies utilized similar techniques for both single and two-stage procedures, certain factors, such as the degree of osteomyelitis and the patient's physiological status, may indicate the use of one technique over the other. Another point of interest would be an analysis of the potential complications in both treatment groups. However, the variation in definitions of complications and the lack of clear reporting of complications arising due to disease and treatment did not allow for an accurate analysis in this regard.
Future research should focus on prospective studies, examining variables like causative organisms, patient demographics, Cierny-Mader classification, and specific treatment modalities. In addition, it will be helpful to know whether major differences exist between different preparations of antibiotic coated beads.
Conclusion
Chronic osteomyelitis is a complex condition with various treatments and interventions described. The data from our analysis suggests that single and two-stage treatment of chronic osteomyelitis yields comparably effective results. The current treatment strategies included a combination of debridement, dead space management, local and systematic antibiotics along with bone stabilization and soft tissue reconstruction if necessary. However, the indications for using either technique may play a role in predicting success rates. Higher-level studies should be conducted to provide more generalizable conclusions.
Acknowledgements
None.
Author contributions
All authors contributed to the study conception and design. Data collection and analysis were performed by AL, AE, MM, AW, BP. Supervision and administration were performed by AL and HS. The first draft of the manuscript was written by AL and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Declarations
Ethical approval
Ethical approval was not required for the purpose of this review.
Competing interest
The authors have no relevant financial or non-financial interests to disclose.
Footnotes
The original online version of this article was revised: The table 3 has been revised.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Change history
8/31/2024
A Correction to this paper has been published: 10.1186/s13018-024-04976-6
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