Machine learning in orthopedics: a literature review

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose. By searching both in the Scopus and Medline databases, we retrieved, screened and analyzed the content of 70 journal articles, and coded these resources following an iterative method within a Grounded Theory approach. We report the survey findings by outlining the articles\u2019 content in terms of the main machine learning techniques mentioned therein, the orthopedic application domains, the source data and the quality of their predictive performance

Routine blood tests as an active surveillance to monitor COVID-19 prevalence. A retrospective study

Background: In Italy, one of the country most affected by the COVID-19 pandemic, the first autoch-thonous case appeared in Lombardy on February 20th, 2020. One month later, the number of COVID-19 patients in Lombardy exceeded 17000 and about 3500 had died. Because of this rapid increase in infected people scientists wonder whether SARS-CoV-2 was already highly circulating in Lombardy before such date. Plasma levels of aspartate aminotransferase (AST) and lactate dehydrogenase (LDH) were shown to be highly increased in COVID-19 patients. Monitoring their levels in Emergency Room patients during the months preceding February 20th, 2020, might shade light on the prevalence of the disease in the pre-COVID-19 period. Methods: We retrospectively analyzed the AST and LDH levels from more than 30.000 patients admitted to the San Raffaele Hospital Emergency Room (ER) between September 2019 and May 2020 as well as between September 2018 and May 2019. The number of patients diagnosed with respiratory tract diseases were also analyzed. Results: Data showed that the ER averaged AST and LDH levels are highly sensitive to the presence of COVID-19 patients. During, the months preceding February 20th, 2020, AST and LDH levels, as well as the number of patients diagnosed with respiratory tract diseases were similar to their 2019 counterparts. Conclusions: No significant evidence showing that a large number of COVID-19 patients were admitted to the San Raffaele Hospital ER before February 20th, 2020, was found. Thus, the virus was likely circulating, within the Hospital catchment area, either in low amounts or through asymptomatic individuals. Because of the high LDH and AST levels’ variations induced by COVID-19, routine blood tests might be exploited as a surveillance indicator for a possible second wave

IGV short scale to assess implicit value of visualizations through explicit interaction

This paper reports the assessment of the infographics-value (IGV) short scale, designed to measure the value in the use of infographics. The scale was made to assess the implicit quality dimensions of infographics. These dimensions were experienced during the execution of tasks in a contextualized scenario. Users were asked to retrieve a piece of information by explicitly interacting with the infographics. After usage, they were asked to rate quality dimensions of infographics, namely, usefulness, intuitiveness, clarity, informativity, and beauty; the overall value perceived from interacting with infographics was also included in the survey. Each quality dimension was coded as a six-point rating scale item, with overall value included. The proposed IGV short scale model was validated with 650 people. Our analysis confirmed that all considered dimensions in our scale were independently significant and contributed to assessing the implicit value of infographics. The IGV short scale is a lightweight but exhaustive tool to rapidly assess the implicit value of an explicit interaction with infographics in daily tasks, where value in use is crucial to measuring the situated effectiveness of visual tools

A novel method for validating multi-classifiers. A case study for ICF-based health status classification

In this paper, we propose a novel method for the validation of a multi-classification model according to the intended use and aim of a device for health status classification and the clinical needs of the practitioners involved

A matter of words: NLP for quality evaluation of Wikipedia medical articles

Automatic quality evaluation of Web information is a task with many fields of applications and of great relevance, especially in critical domains like the medical one. We move from the intuition that the quality of content of medical Web documents is affected by features related with the specific domain. First, the usage of a specific vocabulary (Domain Informativeness); then, the adoption of specific codes (like those used in the infoboxes of Wikipedia articles) and the type of document (e.g., historical and technical ones). In this paper, we propose to leverage specific domain features to improve the results of the evaluation of Wikipedia medical articles. In particular, we evaluate the articles adopting an "actionable" model, whose features are related to the content of the articles, so that the model can also directly suggest strategies for improving a given article quality. We rely on Natural Language Processing (NLP) and dictionaries-based techniques in order to extract the bio-medical concepts in a text. We prove the effectiveness of our approach by classifying the medical articles of the Wikipedia Medicine Portal, which have been previously manually labeled by the Wiki Project team. The results of our experiments confirm that, by considering domain-oriented features, it is possible to obtain sensible improvements with respect to existing solutions, mainly for those articles that other approaches have less correctly classified. Other than being interesting by their own, the results call for further research in the area of domain specific features suitable for Web data quality assessment

La protesi di spalla negli esiti traumatici

Le fratture di omero prossimale esitano frequentemente in sequele che richiedono, nei casi gravi, un intervento di protesizzazione dell\u2019articolazione gleno-omerale. Lo scopo del nostro studio \ue8 analizzare i risultati clinici e funzionali dell\u2019utilizzo della protesi di spalla negli esiti traumatici. Abbiamo eseguito una revisione della letteratura dal 2005 al 2015 e abbiamo identificato 20 lavori che dimostrano come le protesi di spalla siano in grado di migliorare il dolore e la mobilit\ue0 nei pazienti con esiti di fratture dell\u2019omero prossimale ma con risultati inferiori rispetto a quelli ottenuti nel trattamento delle fratture in acuto o nell\u2019artrosi primaria. Nelle sequele di frattura infatti, l\u2019impianto di una protesi \ue8 spesso una procedura complessa con tassi di complicanze elevati. Se in passato erano tradizionalmente utilizzate le emiartroprotesi, recentemente le protesi totali anatomiche e inverse hanno mostrato risultati migliori anche nelle casiste con follow-up a medio-lungo termine.The treatment of fracture sequelae of proximal humerus is still a challenge. Shoulder arthroplasty improves pain and Range Of Motion (ROM) but the results are inferior to the outcomes currently obtained in primary osteoarthritis or acute trauma. Anatomical and reverse total shoulder prosthesis are becoming increasingly popular because of better results than hemiarthroplasty

Predictive factors for relapse in triple-negative breast cancer patients without pathological complete response after neoadjuvant chemotherapy

IntroductionTriple-negative breast cancer (TNBC) patients who do not obtain pathological complete response (pCR) after neoadjuvant chemotherapy (NACT) present higher rate of relapse and worse overall survival. Risk factors for relapse in this subset of patients are poorly characterized. This study aimed to identify the predictive factors for relapse in TNBC patients without pCR after NACT. MethodsWomen with TNBC treated with NACT from January 2008 to May 2020 at the Modena Cancer Center were included in the analysis. In patients without pCR, univariate and multivariable Cox analyses were used to determine factors predictive of relapse. ResultsWe identified 142 patients with a median follow-up of 55 months. After NACT, 62 patients obtained pCR (43.9%). Young age at diagnosis (<50 years) and high Ki-67 (20%) were signi!cantly associated with pCR. Lack of pCR after NACT resulted in worse 5-year event-free survival (EFS) and overall survival (OS). Factors independently predicting EFS in patients without pCR were the presence of multifocal disease [hazard ratio (HR), 3.77; 95% CI, 1.45-9.61; p=0.005] and residual cancer burden (RCB) III (HR, 3.04; 95% CI, 1.09-9.9; p=0.04). Neither germline BRCA status nor HER2-low expression were associated with relapse. DiscussionThese data can be used to stratify patients and potentially guide treatment decision-making, identifying appropriate candidates for treatment intensi!cation especially in neo-/adjuvant setting

Development, evaluation, and validation of machine learning models for COVID-19 detection based on routine blood tests

The rRT-PCR test, the current gold standard for the detection of coronavirus disease (COVID-19), presents with known shortcomings, such as long turnaround time, potential shortage of reagents, false-negative rates around 15-20%, and expensive equipment. The hematochemical values of routine blood exams could represent a faster and less expensive alternative. Three different training data set of hematochemical values from 1,624 patients (52% COVID-19 positive), admitted at San Raphael Hospital (OSR) from February to May 2020, were used for developing machine learning (ML) models: the complete OSR dataset (72 features: complete blood count (CBC), biochemical, coagulation, hemogasanalysis and CO-Oxymetry values, age, sex and specific symptoms at triage) and two sub-datasets (COVID-specific and CBC dataset, 32 and 21 features respectively). 58 cases (50% COVID-19 positive) from another hospital, and 54 negative patients collected in 2018 at OSR, were used for internal-external and external validation. We developed five ML models: for the complete OSR dataset, the area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.83 to 0.90; for the COVID-specific dataset from 0.83 to 0.87; and for the CBC dataset from 0.74 to 0.86. The validations also achieved good results: respectively, AUC from 0.75 to 0.78; and specificity from 0.92 to 0.96. ML can be applied to blood tests as both an adjunct and alternative method to rRT-PCR for the fast and cost-effective identification of COVID-19-positive patients. This is especially useful in developing countries, or in countries facing an increase in contagions

Revision reverse shoulder arthroplasty in failed shoulder arthroplasties for rotator cuff deficiency

PURPOSE: the aim of this systematic literature review is to report clinical outcomes of reverse shoulder arthroplasty (RSA) used as a revision surgery following failure of the primary implant due to rotator cuff insufficiency. METHODS: a systematic review was performed using the following key words: revision, shoulder, rotator cuff deficiency, outcome assessment, treatment outcome, complications. Studies eligible for inclusion in the review were clinical trials investigating patients in whom a primary shoulder arthroplasty implant with an incompetent rotator cuff was replaced with a reverse shoulder prosthesis. RESULTS: nine articles were identified and further reviewed. The results refer to a total of 226 shoulders that were treated with RSA as revision surgery. The patients in the studies had a mean age ranging from 64 to 72 years and the longest follow-up was 3.8 years. Improvements in function and reduction of pain were shown by many studies, but the mean Constant score ranged from 44.2 to 56. High complication rates (of up to 62%) were recorded, and a mean reoperation rate of 27.5%. CONCLUSIONS: RSA as revision surgery for patients with rotator cuff deficiency is a valid option, and often the only solution available, but it should be limited to elderly patients with poor function and severe pain. LEVEL OF EVIDENCE: level IV, systematic review of level I-IV studies