A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study

Purpose Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algorithms to develop a prediction model for the prognosis of patients with long bone sarcoma. Methods Data of patients with long bone sarcoma in the extremities was collected from the Surveillance, Epidemiology, and End Results Program database from 2004 to 2014. Univariate and multivariate analyses were performed to select possible prediction features. DeepSurv, a deep learning model, was constructed for predicting cancer-specific survival rates. In addition, the classical cox proportional hazards model was established for comparison. The predictive accuracy of our models was assessed using the C-index, Integrated Brier Score, receiver operating characteristic curve, and calibration curve. Results Age, tumor extension, histological grade, tumor size, surgery, and distant metastasis were associated with cancer-specific survival in patients with long bone sarcoma. According to loss function values, our models converged successfully and effectively learned the survival data of the training cohort. Based on the C-index, area under the curve, calibration curve, and Integrated Brier Score, the deep learning model was more accurate and flexible in predicting survival rates than the cox proportional hazards model. Conclusion A deep learning model for predicting the survival probability of patients with long bone sarcoma was constructed and validated. It is more accurate and flexible in predicting prognosis than the classical CoxPH model (AU)

Calcium phosphate coating enhances osteointegration of melt electrowritten scaffold by regulating macrophage polarization.

The osteoimmune microenvironment induced by implants plays a significant role in bone regeneration. It is essential to efficiently and timely switch the macrophage phenotype from M1 to M2 for optimal bone healing. This study examined the impact of a calcium phosphate (CaP) coating on the physiochemical properties of highly ordered polycaprolactone (PCL) scaffolds fabricated using melt electrowritten (MEW). Additionally, it investigated the influence of these scaffolds on macrophage polarization and their immunomodulation on osteogenesis. The results revealed that the CaP coated PCL scaffold exhibited a rougher surface topography and higher hydrophilicity in comparison to the PCL scaffold without coating. Besides, the surface morphology of the coating and the release of Ca2+ from the CaP coating were crucial in regulating the transition of macrophages from M1 to M2 phenotypes. They might activate the PI3K/AKT and cAMP-PKA pathways, respectively, to facilitate M2 polarization. In addition, the osteoimmune microenvironment induced by CaP coated PCL could not only enhance the osteogenic differentiation of bone marrow-derived mesenchymal stem cells (BMSCs) in vitro but also promote the bone regeneration in vivo. Taken together, the CaP coating can be employed to control the phenotypic switching of macrophages, thereby creating a beneficial immunomodulatory microenvironment that promotes bone regeneration.

Unraveling T cell exhaustion in the immune microenvironment of osteosarcoma via single-cell RNA transcriptome.

Osteosarcoma (OS) represents a profoundly invasive malignancy of the skeletal system. T cell exhaustion (Tex) is known to facilitate immunosuppression and tumor progression, but its role in OS remains unclear. In this study, single-cell RNA sequencing data was employed to identify exhausted T cells within the tumor immune microenvironment (TIME) of OS. We found that exhausted T cells exhibited substantial infiltration in OS samples. Pseudotime trajectory analysis revealed a progressive increase in the expression of various Tex marker genes, including PDCD1, CTLA4, LAG3, ENTPD1, and HAVCR2 in OS. GSVA showed that apoptosis, fatty acid metabolism, xenobiotic metabolism, and the interferon pathway were significantly activated in exhausted T cells in OS. Subsequently, a prognostic model was constructed using two Tex-specific genes, MYC and FCGR2B, which exhibited exceptional prognostic accuracy in two independent cohorts. Drug sensitivity analysis revealed that OS patients with a low Tex risk were responsive to Dasatinib and Pazopanib. Finally, immunohistochemistry verified that MYC and FCGR2B were significantly upregulated in OS tissues compared with adjacent tissues. This study investigates the role of Tex within the TIME of OS, and offers novel insights into the mechanisms underlying disease progression as well as the potential treatment strategies for OS.

A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study.

PURPOSE: Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algorithms to develop a prediction model for the prognosis of patients with long bone sarcoma. METHODS: Data of patients with long bone sarcoma in the extremities was collected from the Surveillance, Epidemiology, and End Results Program database from 2004 to 2014. Univariate and multivariate analyses were performed to select possible prediction features. DeepSurv, a deep learning model, was constructed for predicting cancer-specific survival rates. In addition, the classical cox proportional hazards model was established for comparison. The predictive accuracy of our models was assessed using the C-index, Integrated Brier Score, receiver operating characteristic curve, and calibration curve. RESULTS: Age, tumor extension, histological grade, tumor size, surgery, and distant metastasis were associated with cancer-specific survival in patients with long bone sarcoma. According to loss function values, our models converged successfully and effectively learned the survival data of the training cohort. Based on the C-index, area under the curve, calibration curve, and Integrated Brier Score, the deep learning model was more accurate and flexible in predicting survival rates than the cox proportional hazards model. CONCLUSION: A deep learning model for predicting the survival probability of patients with long bone sarcoma was constructed and validated. It is more accurate and flexible in predicting prognosis than the classical CoxPH model.

Deciphering the heterogeneity and immunosuppressive function of regulatory T cells in osteosarcoma using single-cell RNA transcriptome.

Osteosarcoma (OS) is a highly invasive malignant neoplasm with poor prognosis. The tumor microenvironment (TME) plays an essential role in the occurrence and development of OS. Regulatory T cells (Tregs) are known to facilitate immunosuppression, tumor progression, invasion, and metastasis. However, the effect of Tregs in the TME of OS remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) data was used to identify Tregs and various other cell clusters in the TME of OS. Gene set variation analysis (GSVA) was used to investigate the signaling pathways in Tregs from OS and adjacent tissues. The CellChat and iTALK packages were used to analyze cellular communication. In addition, a prognostic model was established based on the Tregs-specific genes using bulk RNA-seq from the TARGET database, and it was verified using a Gene Expression Omnibus dataset. The pRRophetic package was used to predict drug sensitivity. Immunohistochemistry was used to verify the expression of candidate genes in OS. Based on the above methods, we showed that the OS samples were highly infiltrated with Tregs. GSVA revealed that oxidative phosphorylation, angiogenesis and mammalian target of rapamycin complex 1 (mTORC1) were highly activated in Tregs from OS compared with those from adjacent tissues. Using cellular communication analysis, we found that Tregs interacted with osteoblastic, endothelial, and myeloid cells via C-X-C motif chemokine ligand (CXCL) signaling; particularly, they strongly affected the expression of C-X-C motif chemokine receptor 4 (CXCR4) and interacted with other cell clusters through CXCL12/transforming growth factor ß1 (TGFB1) to collectively enable tumor growth and progression. Subsequently, two Tregs-specific genes-CD320 and MAF-were screened through univariate, least absolute shrinkage and selection operator regression (LASSO) and multivariate analysis to construct a prognostic model, which showed excellent prognostic accuracy in two independent cohorts. In addition, drug sensitivity analysis demonstrated that OS patients at high Tregs risk were sensitive to sunitinib, sorafenib, and axitinib. We also used immunohistochemistry to validate that CD320 and MAF were significantly upregulated in OS tissues compared with adjacent tissues. Overall, this study reveals the heterogeneity of Tregs in the OS TME, providing new insights into the invasion and treatment of this cancer.

Deep-Learning-Based Model for the Prediction of Cancer-Specific Survival in Patients with Spinal Chordoma.

OBJECTIVE: Spinal chordomas are locally aggressive and frequently recurrent tumors with a poor prognosis. Previous studies focused on a Cox regression model to predict the survival of patients with spinal chordoma. We aimed to develop a more effective model based on deep learning for prognosis prediction in spinal chordoma. METHODS: Patients with spinal chordoma were gathered from the SEER database. Cox regression analysis was conducted to compare the influence of different clinical characteristics on cancer-specific survival. Two deep learning models, namely, DeepSurv and NMTLR, were developed, alongside 2 classic models, for the purpose of comparison. Performance of these models was evaluated by concordance index, Integrated Brier Score, receiver operating characteristic curves, Kaplan-Meier curves, and calibration curves. RESULTS: A total of 258 spinal chordoma patients were included in the current study. The median follow-up time was 94 ± 52 months. Variables used for prognosis prediction consisted of age, primary site, tumor size, histologic grade, extension of surgery, tumor invasion, and metastasis. Comparing with conventional models, each deep learning model showed superior predictive performance, the C-index on the test cohort is 0.830 for DeepSurv and 0.804 for NMTLR, respectively. The DeepSurv model represented the best performance, with area under the curve of 0.843 in predicting 5-year survival and 0.880 in predicting 10-year survival. CONCLUSIONS: We successfully constructed a deep learning model to predict the CSS of spinal chordoma patients and proved that it was more accurate and practical than conventional prediction model. Our deep learning model has the potential to guide clinicians in better care planning and decision-making.

Deciphering the crosstalk of immune dysregulation between COVID-19 and idiopathic inflammatory myopathy.

Background: The coronavirus disease (COVID-19) pandemic is a serious threat to public health worldwide. Growing evidence reveals that there are certain links between COVID-19 and autoimmune diseases; in particular, COVID-19 and idiopathic inflammatory myopathies (IIM) have been observed to be clinically comorbid. Hence, this study aimed to elucidate the molecular mechanisms of COVID-19 and IIM from a genomic perspective. Methods: We obtained transcriptome data of patients with COVID-19 and IIM separately from the GEO database and identified common differentially expressed genes (DEGs) by intersection. We then performed functional enrichment, PPI, machine learning, gene expression regulatory network, and immune infiltration analyses of co-expressed genes. Results: A total of 91 common genes were identified between COVID-19 and IIM. Functional enrichment analysis revealed that these genes were mainly involved in immune dysregulation, response to external stimuli, and MAPK signaling pathways. The MCODE algorithm recognized two densely linked clusters in the common genes, which were related to inflammatory factors and interferon signaling. Subsequently, three key genes (CDKN1A, IFI27, and STAB1) were screened using machine learning to predict the occurrence of COVID-19 related IIM. These key genes exhibited excellent diagnostic performance in both training and validation cohorts. Moreover, we created TF-gene and miRNA-gene networks to reveal the regulation of key genes. Finally, we estimated the relationship between key genes and immune cell infiltration, of which IFI27 was positively associated with M1 macrophages. Conclusion: Our work revealed common molecular mechanisms, core genes, potential targets, and therapeutic approaches for COVID-19 and IIM from a genomic perspective. This provides new ideas for the diagnosis and treatment of COVID-19 related IIM in the future.

Item-specific control of attention capture: An eye movement study.

Measures of attentional capture are sensitive to attentional control settings. Recent research suggests that such control settings can be linked associatively to specific items. Rapid item-specific retrieval of these control settings can then modulate measures of attentional capture. However, the processes that produce this item-specific control of attentional capture are unclear. The current study addressed this issue by examining eye-movement patterns associated with the item-specific proportion congruency effect (ISPC). Participants searched for a shape singleton target in search displays that also contained a colour singleton-the colour singleton was either the same item as the shape singleton (congruent trials) or a different item (incongruent trials). The relative proportions of congruent and incongruent trials were manipulated separately for two distinct item types that were randomly intermixed. Response times (RTs) were faster on congruent than incongruent trials, and this congruency effect was larger for high-proportion congruent (HPC) than low-proportion congruent (LPC) items. Eye movement data revealed a higher proportion of saccades towards the distractor and longer dwell times on the distractor in the HPC condition. These results suggest that item-specific associative learning can influence the strength of representation of the task goal (e.g., find the odd shape), a form of selection history effect in visual search.

Processing directional information in stimuli inhibits the spatial association of luminance levels.

Previous studies have found that the spatial-numerical association of the response codes (SNARC) effect automatically occurred when processing both numbers and non-symbolic magnitudes. However, this conclusion was challenged by several recent studies that found no SNARC effect when processing non-symbolic magnitudes with a directional cue. In the present study, we hypothesized that automatic spatial association of non-symbolic magnitudes would be inhibited by directional cues; thus, we utilized left and right arrow stimuli with different luminance levels to systematically investigate the spatial association of luminance. To ensure that participants could effectively discriminate the luminance stimuli, we first replicated the SNARC effect in Experiment 1, by presenting rectangles with different luminance levels. Then, arrows with the same luminance levels as the rectangles were randomly presented to participants on the centre of a screen; participants completed direction classification (Experiment 2), colour classification (Experiment 3), or luminance classification (Experiment 4) tasks with these arrow stimuli. We found that (1) the SNARC effect was present when processing rectangles with different luminance levels (Experiment 1); however, (2) the Simon-like effect rather than the spatial association of luminance was observed when processing arrows with different luminance levels in the luminance-irrelevant classification tasks (Experiments 2 and 3) and the luminance-relevant classification task (Experiment 4). These results indicate that processing of a directional cue inhibited the spatial association of luminance in both luminance-relevant and luminance-irrelevant classification tasks.

Inversion Effect of Hand Postures: Effect of Visual Experience Over Long and Short Term.

Some researchers argue that holistic processing is unique to face recognition supported by the face inversion effect. However, findings such as the body inversion effect challenge the face processing-specificity hypothesis, thus supporting the expertise hypothesis. Few studies have explored a possible hand inversion effect which could involve special processing similar to the face and body. We conducted four experiments to investigate the time course and flexibility of the hand posture inversion effect. We utilized a same/different discrimination task (Experiments 1 and 2), an identification task (Experiment 3), and a training paradigm involving the exposure of different hand orientations (Experiment 4). The results show the hand posture inversion effect (with fingers up as upright orientation) was not initially observed during the early phase of testing, but occurred in later phases. This suggests that both lifetime experience and recent exposure affect the hand posture inversion effect. We also found the hand posture inversion effect, once established, was stable across days and remained consistent across different tasks. In addition, the hand posture inversion effect for specific orientations could be obtained with short-term training of a given orientation, indicating the cognitive process is flexible.

The Influence of Growth Mindset on the Mental Health and Life Events of College Students.

Growth mindset refers to our core belief that our talents can be developed through practice, which may influence our thoughts and behaviors. Growth mindset has been studied in a variety of fields, including education, sports, and management. However, few studies have explored whether differences in individuals' growth mindsets influence college students' self-reported mental health. Using the Growth Mindset Scale, Adolescent Self-rating Life Events Checklist, and SCL-90 Scale, data was collected from 2,505 freshmen in a University in China. Findings revealed that the students within the growth mindset group scored significantly lower on "mental health issues" and "stress due to life events" than the students in the fixed mindset group. Our findings suggest that individuals with a growth mindset are less prone to mental health problems than individuals with a fixed mindset.

Encoding Numbers in the Context of Multiple Overlapping Cues: Evidence from a Chinese Finger Number Cognition Study.

How people encode numbers in the context of multiple overlapping encoded cues remains unclear. In this study, we explored Chinese finger numbers, which contain both a numerical magnitude cue and a left-right hand cue offered by the expressing hand, to investigate the number encoding mechanism in the context of multiple overlapping cues. Chinese finger numbers expressed by the left or right hand were randomly and centrally presented on a computer screen to participants who were asked to perform a hand classification task (Experiment 1), a magnitude classification task (Experiment 2), a parity classification task (Experiment 3) and a magnitude classification or ring classification task (Experiment 4). We discovered (a) only an association effect between the pressed key and the expressing hand in hand classification and parity classification tasks, (b) the SNARC effect only on the magnitude classification task, (c) the association effect between the pressed key and the expressing hand on the larger, Chinese finger number, magnitude classification task in Experiment 2, and (d) the SNARC effect and the association between the pressed key and the expressing hand were reversed on the ring classification task. From these results, we concluded that people can flexibly choose appropriate number encoding cues and how numbers are encoded in the context of multiple overlapping cues depending on (a) which cognition task individuals perform and (b) the character of the numbers involved.

Interaction mechanism between location and sequence in letter cognition.

A previous study used days as a sequence symbol to investigate the interaction mechanism between location and sequence in sequence symbol cognition; the study findings suggested that the spatial stimulus-response compatibility effect and the Simon effect could not co-exist with the SNARC-like effect when processing sequence symbols. The previous study did not include the influence of the difficulty of identifying sequence symbols on the Simon effect in the investigation, so it is unclear whether the conclusion about processing sequence symbols with considerable identification difficulty can be extended to the processing of sequence symbols with less identification difficulty. Therefore, the present study explored letters that have a low level of identification difficulty to investigate the interaction mechanism between location and sequence in sequence symbol cognition. Participants were asked to classify a probe letter, which was randomly displayed on the left or right side of the screen, according to its location (Experiment 1), its sequence (Experiment 2) or its colour (Experiment 3). The results indicated that (1) only the spatial stimulus-response compatibility effect and Simon effect were present in the letter location classification task and letter colour classification task, respectively. (2) The Simon effect co-existed with the SNARC-like effect, and these two effects interacted with each other in the letter sequence classification task. From these results, it can be concluded that the task determines whether the Simon effect and the SNARC-like effect can co-exist, with differences presented across sequence symbols.

Body-Posture Recognition by Undergraduate Students Majoring in Physical Education and Other Disciplines.

Humans are more proficient at processing visual display of body posture when the body is in upright orientation, compared to when inverted (inversion effect). Here we investigated whether extensive exposure or expertise on body posture recognition would affect the efficiency with which body-posture is processed. Using whole-body and piecemeal-body postures as stimuli, we performed two experiments to investigate whether body-posture recognition differed between two groups of participants: undergraduates majoring in physical education (PE) and those in other subjects (non-PE), respectively. These two groups differed significantly in the frequency and intensity of exercise per day and/or accumulated exercise time. In our experiments, following initial presentation of an image of a body posture, participants were shown the same or a different stimulus and were asked to report whether or not they had been previously shown the same image. The orientations of the body postures were also varied between trials. Our results showed that, in Experiment 1, for whole-body posture recognition, both the PE and non-PE groups showed a robust body-inversion effect in terms of both error rate and reaction time (RT), but the magnitude of the body-inversion effect in the RT measure was greater in the PE than the non-PE group. In Experiment 2, for piecemeal-body postures, both groups showed the inversion effect in terms of both error rate and RT measures and the PE group made fewer overall errors than the non-PE group. These cumulative results suggest that a superiority effect exists for PE participants compared with non-PE participants. Our results are generally consistent with the expertise hypothesis.

Face recognition and memory in congenital amusia.

Congenital amusia, commonly known as tone deafness, is a lifelong impairment of music perception and production. It remains a question of debate whether the impairments in musical domain observed in congenital amusia are paralleled in other non-musical perceptual abilities. Using behavioral measures in two experiments, the current study explored face perception and memory in congenital amusics. Both congenital amusics and matched controls performed a face perception task (Experiment 1) and an old/novel object memory task (for both faces and houses, Experiment 2). The results showed that the congenital amusic group had significantly slower reaction times than that in matched control group when identifying whether two faces presented together were the same or different. For different face-pairs, the deficit was greater for upright faces compared with inverted faces. For object memory task, the congenital amusic group also showed worse memory performance than the control group. The results of the present study suggest that the impairment attributed to congenital amusia is not only limited to music, but also extends to visual perception and visual memory domain.

Preoperative intravenous flurbiprofen reduces postoperative pain and inflammatory cytokines in elderly patients after hip arthroplasty.

Effect of flurbiprofen on the postoperative cognition and inflammatory cytokines in elderly patients after hip arthroplasty was investigated. Elderly patients undergoing replacement of total hip were randomly divided into three groups of equal size (n=60). A control group (control) received no treatment before or at the end of surgery. The other two groups, PRE and INTRA, received 50 mg flurbiprofen intravenously 15 min before the surgery and 30 min before the end of surgery, respectively. The pain score was evaluated by a visual analog scale (VAS) at the following time-points: 24 h before surgery (T0), and 3 h (T1), 12 h (T2) and 24 h (T3) after surgery. Peripheral venous blood was collected at T0, T1, T2 and T3. Cognitive function was assessed by mini-mental state examination (MMSE) at the time of T0, T1, T2 and T3. The serum concentration of tumor necrosis factor α (TNF-α), interleukin-1ß (IL-1ß), IL-6, and Cox-2 were measured using enzyme linked immunosorbent assay (ELISA). The VAS scores and the release of pro-inflammatory cytokines in the PRE and INTRA groups were less than those in the control group at T1, T2 and T3. The MMSE scores in PRE and INTRA groups were significantly higher than those in the control group at T1, T2 and T3. The PRE group showed a lower VAS score, release of pro-inflammatory cytokines and higher MMSE scores at T1, T2 and T3 than the control and INTRA groups. Intravenous flurbiprofen administration reduces postoperative pain and flammatory response after hip arthroplasty. Moreover, flurbiprofen is more effective when given preoperatively than intraoperatively.

Representing Spatial Layout According to Intrinsic Frames of Reference: Limitations From Position Regularity and Instructions.

Mou and McNamara have suggested that object locations are represented according to intrinsic reference frames. In three experiments, we investigated the limitations of intrinsic reference frames as a mean to represent object locations in spatial memory. Participants learned the locations of seven or eight common objects in a rectangular room and then made judgments of relative direction based on their memory of the layout. The results of all experiments showed that when all objects were positioned regularly, judgments of relative direction were faster or more accurate for novel headings that were aligned with the primary intrinsic structure than for other novel headings; however, when one irregularly positioned object was added to the layout, this advantage was eliminated. The experiments further indicated that with a single view at study, participants could represent the layout from either an egocentric orientation or a different orientation, according to experimental instructions. Together, these results suggest that environmental reference frames and intrinsic axes can influence performance for novel headings, but their role in spatial memory depends on egocentric experience, layout regularity, and instructions.

MEKK1 Associated with Neuronal Apoptosis Following Intracerebral Hemorrhage.

The JNKs have been implicated in a variety of biological functions in mammalian cells, including apoptosis and the responses to stress. However, the physiological role of these pathways in the intracerebral hemorrhage (ICH) has not been fully elucidated. In this study, we identified a MAPK kinase kinase (MAPKKK), MEKK1, may be involved in neuronal apoptosis in the processes of ICH through the activation of JNKs. From the results of western blot, immunohistochemistry and immunofluorescence, we obtained a significant up-regulation of MEKK1 in neurons adjacent to the hematoma following ICH. Increasing MEKK1 level was found to be accompanied with the up-regulation of p-JNK 3, p53, and c-jun. Besides, MEKK1 co-localized well with p-JNK in neurons, indicating its potential role in neuronal apoptosis. What's more, our in vitro study, using MEKK1 siRNA interference in PC12 cells, further confirmed that MEKK1 might exert its pro-apoptotic function on neuronal apoptosis through extrinsic pathway. Thus, MEKK1 may play a role in promoting the brain damage following ICH.

Expression of CDc6 after acute spinal cord injury in adult rats.

The cell division cycle 6 (CDc6) protein has been primarily investigated as a component of the pre-replicative complex for the initiation of DNA replication. Some studies have shown that CDc6 played a critical role in the development of human carcinoma. However, the expression and roles of CDc6 in the central nervous system remain unknown. We have performed an acute spinal cord injury (SCI) model in adult rats and investigated the dynamic changes of CDc6 expression in spinal cord. Western blot have found that CDc6 protein levels first significantly increase, reach a peak at day 3, and then gradually return to normal level at day 14 after SCI. Double immunofluorescence staining showed that CDc6 immunoreactivity was found in neurons, astrocytes, and microglia. Additionally, colocalization of CDc6/active caspase-3 has been detected in neurons and colocalization of CDc6/proliferating cell nuclear antigen has been detected in astrocytes and microglial. In vitro, CDc6 depletion by short interfering RNA inhibits astrocyte proliferation and reduces cyclin A and cyclin D1 protein levels. CDc6 knockdown also decreases neuronal apoptosis. We speculate that CDc6 might play crucial roles in CNS pathophysiology after SCI.

Effect of vacuum sealing drainage in osteofascial compartment syndrome.

OBJECTIVES: To investigate the effect of vacuum sealing drainage in the patients with osteofascial compartment syndrome in comparison to conventional treatment. METHODS: Fifty-two patients diagnosed with osteofascial compartment syndrome were enrolled in this study. They were randomly divided into two groups based on treatments: vacuum sealing drainage and conventional treatment. After operation, the length of hospital stay and antibiotics administration were recorded in the two groups, as well as swelling elimination and wound closure. RESULTS: No significant difference was observed in terms of the baseline characteristics between the two groups. There are no obvious local or systemic complications in all cases. In contrast to conventional treatment group, the time of swelling elimination, wound closure, hospital stay and antibiotics application were reduced significantly in vacuum sealing drainage group. No allergic reactions or other side effects were observed after the application of vacuum sealing drainage material, indicating its safety. CONCLUSION: Vacuum sealing drainage is effective in treating osteofascial compartment syndrome with better clinical outcomes than conventional therapy.