Tiny amphibious insects use tripod gait for seamless transition across land, water, and duckweed.

Insects exhibit remarkable adaptability in their locomotive strategies across diverse environments, a crucial trait for foraging, survival, and predator avoidance. Microvelia, tiny 2-3 mm insects that adeptly walk on water surfaces, exemplify this adaptability by using the alternating tripod gait in both aquatic and terrestrial terrains. These insects commonly inhabit low-flow ponds and streams cluttered with natural debris like leaves, twigs, and duckweed. Using high-speed imaging and pose-estimation software, we analyze Microvelia spp.'s movement across water, sandpaper (simulating land), and varying duckweed densities (10%, 25%, and 50% coverage). Our results reveal Microvelia maintain consistent joint angles and strides of their upper and hind legs across all duckweed coverages, mirroring those seen on sandpaper. Microvelia adjust the stride length of their middle legs based on the amount of duckweed present, decreasing with increased duckweed coverage and at 50% duckweed coverage, their middle legs' strides closely mimic their strides on sandpaper. Notably, Microvelia achieve speeds up to 56 body lengths per second on water, nearly double those observed on sandpaper and duckweed (both rough, frictional surfaces), highlighting their higher speeds on low friction surfaces such as the water's surface. This study highlights Microvelia's ecological adaptability, setting the stage for advancements in amphibious robotics that emulate their unique tripod gait for navigating complex terrains.

Predicting post-treatment symptom severity for adults receiving psychological therapy in routine care for generalised anxiety disorder: a machine learning approach.

Approximately half of generalised anxiety disorder (GAD) patients do not recover from first-line treatments, and no validated prediction models exist to inform individuals or clinicians of potential treatment benefits. This study aimed to develop and validate an accurate and explainable prediction model of post-treatment GAD symptom severity. Data from adults receiving treatment for GAD in eight Improving Access to Psychological Therapies (IAPT) services (n=15,859) were separated into training, validation and holdout datasets. Thirteen machine learning algorithms were compared using 10-fold cross-validation, against two simple clinically relevant comparison models. The best-performing model was tested on the holdout dataset and model-specific explainability measures identified the most important predictors. A Bayesian Additive Regression Trees model out-performed all comparison models (MSE=16.54 [95 % CI=15.58; 17.51]; MAE=3.19; R²=0.33, including a single predictor linear regression model: MSE=20.70 [95 % CI=19.58; 21.82]; MAE=3.94; R²=0.14). The five most important predictors were: PHQ-9 anhedonia, GAD-7 annoyance/irritability, restlessness and fear items, then the referral-assessment waiting time. The best-performing model accurately predicted post-treatment GAD symptom severity using only pre-treatment data, outperforming comparison models that approximated clinical judgement and remaining within the GAD-7 error of measurement and minimal clinically important differences. This model could inform treatment decision-making and provide desired information to clinicians and patients receiving treatment for GAD.

Dual-mobility tripod cup for revision hip arthroplasty: long-term (five to fourteen years) evaluation of a new generation cementless implant.

PURPOSE: The aims of this study were to evaluate the survivorships of a new generation cementless DMC with tripod additional fixation in revision total hip arthroplasty and complications at a minimum five year follow-up. METHODS: One hundred and fifteen revisions (THA) treated with tripod DMC performed between 2009 and 2015 were included in this retrospective study. Acetabular defects were classified as Paprosky 1 (n = 38, 33%), 2 (n = 75, 65%) or 3 (n = 2, 2%). Unipolar or bipolar revision was performed for the following indications: aseptic acetabular loosening (63%), infection (14%), aseptic bipolar loosening (11%), instability (4%), aseptic femoral loosening (3%), ALVAL (3%) and iliopsoas impingement (2%). Mean follow-up was 9.4 years ± two (range, 5 to 14). RESULTS: At the final follow-up, a single episode of dislocation occurred within three months after the procedure (0.8%) with no revision. Three cases of aseptic loosening were diagnosed (2.6%). Four infections (3.5%) required reoperation: three required a two stage bipolar revision; one was treated by DAIR procedure. At the latest follow-up, the survivorship of the acetabular cup for aseptic loosening was 98% [95% CI (91.2-99.4)] and for any reasons was 94.4% [95% CI (90.1%-98.9%)]; the mean HHS improved from 60 points (range, 18-94 points) to 83 points (range, 37-100 points) (p < .001). CONCLUSION: This study reports a low complication rate in favour of the use of a tripod DMC in revision THA with a satisfactory survivorship at a ten year follow-up.

Development and internal validation of a prediction model for patients with hematologic diseases of fall risk: a cohort study.

BACKGROUND: To develop and internally validate a prediction model for identifying patients with hematologic diseases of fall risk. RESEARCH DESIGN AND METHODS: This is a prospective cohort study from a prospective collection of data for 6 months. We recruited 412 patients with hematologic diseases in medical institutions and home environment of China. The outcome of the prediction model was fall or not. These variables were filtered via univariable logistic analysis, LASSO, and multivariable logistic analysis. We adopt an internal validation method of K-fold cross validation. The area under the ROC curve and the H-L test were used to evaluate the discrimination and calibration of the model. RESULTS: Five influencing factors were identified multivariable logistic regression analysis. The established model equation is as follows: the H-L goodness-of-fit test of the model p > 0.05. The area under the ROC curve of train is 0.957 (95% CI: 0.936 ~ 0.978), and the area under the ROC curve of test is 0.962 (95% CI: 0.884 ~ 1), so the model calibration and discriminant validity are good. CONCLUSION: Our equation has good sensitivity and specificity in predicting the fall risk of patients with hematologic diseases, and has certain positive significance for clinical assessment of their fall risk. TRIAL REGISTRATION NUMBER: ChiCTR2200063940.

New labor curves of dilation and station to improve the accuracy of predicting labor progress.

BACKGROUND: The diagnosis of failure to progress, the most common indication for intrapartum cesarean delivery, is based on the assessment of cervical dilation and station over time. Labor curves serve as references for expected changes in dilation and fetal descent. The labor curves of Friedman, Zhang et al, and others are based on time alone and derived from mothers with spontaneous labor onset. However, labor induction is now common, and clinicians also consider other factors when assessing labor progress. Labor curves that consider the use of labor induction and other factors that influence labor progress have the potential to be more accurate and closer to clinical decision-making. OBJECTIVE: This study aimed to compare the prediction errors of labor curves based on a single factor (time) or multiple clinically relevant factors using two modeling methods: mixed-effects regression, a standard statistical method, and Gaussian processes, a machine learning method. STUDY DESIGN: This was a longitudinal cohort study of changes in dilation and station based on data from 8022 births in nulliparous women with a live, singleton, vertex-presenting fetus ≥35 weeks of gestation with a vaginal delivery. New labor curves of dilation and station were generated with 10-fold cross-validation. External validation was performed using a geographically independent group. Model variables included time from the first examination in the 20 hours before delivery; dilation, effacement, and station recorded at the previous examination; cumulative contraction counts; and use of epidural anesthesia and labor induction. To assess model accuracy, differences between each model's predicted value and its corresponding observed value were calculated. These prediction errors were summarized using mean absolute error and root mean squared error statistics. RESULTS: Dilation curves based on multiple parameters were more accurate than those derived from time alone. The mean absolute error of the multifactor methods was better (lower) than those of the single-factor methods (0.826 cm [95% confidence interval, 0.820-0.832] for the multifactor machine learning and 0.893 cm [95% confidence interval, 0.885-0.901] for the multifactor mixed-effects method and 2.122 cm [95% confidence interval, 2.108-2.136] for the single-factor methods; P<.0001 for both comparisons). The root mean squared errors of the multifactor methods were also better (lower) than those of the single-factor methods (1.126 cm [95% confidence interval, 1.118-1.133] for the machine learning [P<.0001] and 1.172 cm [95% confidence interval, 1.164-1.181] for the mixed-effects methods and 2.504 cm [95% confidence interval, 2.487-2.521] for the single-factor [P<.0001 for both comparisons]). The multifactor machine learning dilation models showed small but statistically significant improvements in accuracy compared to the mixed-effects regression models (P<.0001). The multifactor machine learning method produced a curve of descent with a mean absolute error of 0.512 cm (95% confidence interval, 0.509-0.515) and a root mean squared error of 0.660 cm (95% confidence interval, 0.655-0.666). External validation using independent data produced similar findings. CONCLUSION: Cervical dilation models based on multiple clinically relevant parameters showed improved (lower) prediction errors compared to models based on time alone. The mean prediction errors were reduced by more than 50%. A more accurate assessment of departure from expected dilation and station may help clinicians optimize intrapartum management.

Prediction model protocols indicate better adherence to recommended guidelines for study conduct and reporting.

BACKGROUND AND OBJECTIVE: Protocols are invaluable documents for any research study, especially for prediction model studies. However, the mere existence of a protocol is insufficient if key details are omitted. We reviewed the reporting content and details of the proposed design and methods reported in published protocols for prediction model research. METHODS: We searched MEDLINE, Embase, and the Web of Science Core Collection for protocols for studies developing or validating a diagnostic or prognostic model using any modeling approach in any clinical area. We screened protocols published between Jan 1, 2022 and June 30, 2022. We used the abstract, introduction, methods, and discussion sections of The Transparent Reporting of a multivariable prediction model of Individual Prognosis Or Diagnosis (TRIPOD) statement to inform data extraction. RESULTS: We identified 30 protocols, of which 28 were describing plans for model development and six for model validation. All protocols were open access, including a preprint. 15 protocols reported prospectively collecting data. 21 protocols planned to use clustered data, of which one-third planned methods to account for it. A planned sample size was reported for 93% development and 67% validation analyses. 16 protocols reported details of study registration, but all protocols reported a statement on ethics approval. Plans for data sharing were reported in 13 protocols. CONCLUSION: Protocols for prediction model studies are uncommon, and few are made publicly available. Those that are available were reasonably well-reported and often described their methods following current prediction model research recommendations, likely leading to better reporting and methods in the actual study.

Catalytic Oxidation of Methanol to Formaldehyde Catalyzed by Iron Complex with N3S3-type Tripodal Ligand.

A Fe3+ complex with N3S3-type tripod ligand, 1, reacts with O2 in CH3OH to generate formaldehyde, which has been studied structurally, spectroscopically, and electrochemically. Complex 1 crystallizes as an octahedral structure with crystallographic C3 symmetry around the metal, with Fe-N=2.2917(17) Å and Fe-S=2.3574(6) Å. UV-vis spectrum of 1 in CH3OH under Ar shows an intense band at 572 nm (ϵ 4,100 M-1cm-1), which shifts to 590 nm (ϵ 2,860 M-1cm-1) by the addition of O2, and a new peak appeared at 781 nm (ϵ 790 M-1cm-1). Such a spectral change is not observed in CH2Cl2. Cyclic voltammogram (CV) of 1 in CH2Cl2 under Ar gives reversible redox waves assigned to Fe2+/Fe3+ and Fe3+/Fe4+ couples at -1.60 V (ΔE=69 mV) and -0.53 V (ΔE=71 mV) vs Fc/Fc+, respectively. In contrast, in CH3OH, the reversible redox waves, albeit accompanied by a positive shift of the Fe2+/Fe3+ couple, are observed at -1.20 V (ΔE=85 mV) and -0.53 V (ΔE=64 mV) vs Fc/Fc+ under Ar. Interestingly, a catalytic current was observed for the CV of 1 in CH3OH in the presence of CH3ONa under Ar, when the sweep rate was slowed down.

Increased endorsement of TRIPOD and other reporting guidelines by high impact factor journals: survey of instructions to authors.

OBJECTIVES: To assess the endorsement of reporting guidelines by high impact factor journals over the period 2017-2022, with a specific focus on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. STUDY DESIGN AND SETTING: We searched the online 'instructions to authors' of high impact factor medical journals in February 2017 and in January 2022 for any reference to reporting guidelines and TRIPOD in particular. RESULTS: In 2017, 205 out of 337 (61%) journals mentioned any reporting guideline in their instructions to authors and in 2022 this increased to 245 (73%) journals. A reference to TRIPOD was provided by 27 (8%) journals in 2017 and 67 (20%) in 2022. Of those journals mentioning TRIPOD in 2022, 22% provided a link to the TRIPOD website and 60% linked to TRIPOD information on the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network website. Twenty-five percent of the journals required adherence to TRIPOD. CONCLUSION: About three-quarters of high-impact medical journals endorse the use of reporting guidelines and 20% endorse TRIPOD. Transparent reporting is important in enhancing the usefulness of health research and endorsement by journals plays a critical role in this.

Around the EQUATOR with Clin-STAR: Prediction modeling opportunities and challenges in aging research.

The 2015 Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement was published to improve reporting transparency for prediction modeling studies. The objective of this review is to highlight methodologic challenges that aging-focused researchers will encounter when designing and reporting studies involving prediction models for older adults and provide guidance for addressing these challenges. In following the 22-item TRIPOD checklist, researchers must consider the representativeness of cohorts used (e.g., whether older adults with frailty, cognitive impairment, and social isolation were included), strategies for incorporating common geriatric predictors (e.g., age, comorbidities, functional status, and frailty), methods for handling missing data and competing risk of death, and assessment of model performance heterogeneity across important subgroups (e.g., age, sex, race, and ethnicity). We provide guidance to help aging-focused researchers develop, validate, and report models that can inform and improve patient care, which we label "TRIPOD-65."

Clinical efficacy analysis of percutaneous "tripod" combined with radiofrequency ablation and bone cement filling in the treatment of periacetabular metastases.

BACKGROUND: To investigate the clinical efficacy of a percutaneous "tripod" combined with radiofrequency ablation and bone cement filling surgery in treating acetabular bone metastases. METHODS: We retrospectively analyzed 11 patients who underwent percutaneous "tripod" combined with radiofrequency ablation and bone cement filling for acetabular bone metastases at a tertiary care hospital from February 2021 to December 2022. RESULTS: 11 cases with 13 hips underwent this procedure, including two female patients who underwent both sides, and the rest were unilateral. All cases were followed up for 3-24 months, with a mean of 12 months and a median follow-up time of 11 months. Two of the 11 patients died by the final follow-up, and nine survived. One died 7 months after surgery, and one died 8 months after surgery; the survival of the deceased patients was 7.5 months (range: 7-8 months), with a median survival time of 7.5 months. All 11 patients completed the surgery successfully, and the average unilateral operation time was 167.4 min (148-193). The amelioration of postoperative pain, concomitant with improved quality of life, was observed significantly, ultimately resulting in a prolonged and sustained effect. CONCLUSIONS: The combination of percutaneous "tripod", radiofrequency ablation, and bone cement filling can effectively relieve pain without delaying the patient's systemic anti-tumor therapy and is a minimally invasive, safe, and effective procedure for the treatment of periacetabular metastases.

Highly Selective Turn-on Fluorescence Sensor for Cd2+ Ions by Tripodal Organic Ligand.

Organic fluorescence sensor for selectively detecting and quantifying toxic heavy metal ions has received significant interest due to their environmental hazards. Herein, we have designed and synthesized a simple tripodal Schiff base ligand (1) based on hydroxy-naphthaldehyde and tris(2-aminoethyl)amine (TREN) and demonstrated highly selective turn-on fluorescence sensing of Cd2+ ions. The free ligand did not show any fluorescence in DMF. In contrast, Cd2+ (10- 4 M) addition exhibited a strong enhancement of fluorescence at 450 nm. Interestingly, other metal ions including Zn2+, which exhibit similar chemistry, did not show any turn-on fluorescence. The concentration-dependent studies of 1 with Cd2+ showed the detection limit of 6.78 × 10- 8 M. NMR spectra of 1 with Cd2+ and computational studies were performed to understand the mechanism of sense.

Surgical robot-assisted tripod percutaneous reconstruction technique combined with bone cement filling technique for the treatment of acetabular metastasis.

Background: Acetabular metastasis is a type of metastatic bone cancer, and it mainly metastasizes from cancers such as lung cancer, breast cancer, and renal carcinoma. Acetabular metastasis often causes severe pain, pathological fractures, and hypercalcemia which may seriously affect the quality of life of acetabular metastasis patients. Due to the characteristics of acetabular metastasis, there is no most suitable treatment to address it. Therefore, our study aimed to investigate a novel treatment technique to relieve these symptoms. Methods: Our study explored a novel technique to reconstruct the stability of the acetabular structure. A surgical robot was used for accurate positioning and larger-bore cannulated screws were accurately inserted under the robot's guidance. Then, the lesion was curetted and bone cement was injected through a screw channel to further strengthen the structure and kill tumor cells. Results: A total of five acetabular metastasis patients received this novel treatment technique. The data relating to surgery were collected and analyzed. The results found that this novel technique can significantly reduce operation time, intraoperative bleeding, visual analogue score scores, Eastern Cooperative Oncology Group scores, and postoperative complications (e.g., infection, implant loosening, hip dislocation) after treatment. Follow-up time ranged from 3 months to 6 months, and the most recent follow-up results showed that all patients survived and no acetabular metastasis progressed in any of the patients after surgery. Conclusion: Surgical robot-assisted tripod percutaneous reconstruction combined with the bone cement filling technique may be a novel and suitable treatment in acetabular metastasis patients. Our study may provide new insights into the treatment of acetabular metastasis.

The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications.

BACKGROUND: To investigate the reporting of prognostic prediction model studies in obstetric care through a cross-sectional survey design. METHODS: PubMed was searched to identify prognostic prediction model studies in obstetric care published from January 2011 to December 2020. The quality of reporting was assessed by the TRIPOD checklist. The overall adherence by study and the adherence by item were calculated separately, and linear regression analysis was conducted to explore the association between overall adherence and prespecified study characteristics. RESULTS: A total of 121 studies were included, while no study completely adhered to the TRIPOD. The results showed that the overall adherence was poor (median 46.4%), and no significant improvement was observed after the release of the TRIPOD (43.9 to 46.7%). Studies including both model development and external validation had higher reporting quality versus those including model development only (68.1% vs. 44.8%). Among the 37 items required by the TRIPOD, 10 items were reported adequately with an adherence rate over of 80%, and the remaining 27 items had an adherence rate ranging from 2.5 to 79.3%. In addition, 11 items had a report rate lower than 25.0% and even covered key methodological aspects, including blinding assessment of predictors (2.5%), methods for model-building procedures (4.5%) and predictor handling (13.5%), how to use the model (13.5%), and presentation of model performance (14.4%). CONCLUSIONS: In a 10-year span, prognostic prediction studies in obstetric care continued to be poorly reported and did not improve even after the release of the TRIPOD checklist. Substantial efforts are warranted to improve the reporting of obstetric prognostic prediction models, particularly those that adhere to the TRIPOD checklist are highly desirable.

External validation of a prediction model for timely implementation of innovations in radiotherapy.

BACKGROUND AND PURPOSE: The aim of this study was to externally validate a model that predicts timely innovation implementation, which can support radiotherapy professionals to be more successful in innovation implementation. MATERIALS AND METHODS: A multivariate prediction model was built based on the TRIPOD (Transparent Reporting of a multivariate prediction model for Individual Prognosis Or Diagnosis) criteria for a type 4 study (1). The previously built internally validated model had an AUC of 0.82, and was now validated using a completely new multicentre dataset. Innovation projects that took place between 2017-2019 were included in this study. Semi-structured interviews were performed to retrieve the prognostic variables of the previously built model. Projects were categorized according to the size of the project; the success of the project and thepresence of pre-defined success factors were analysed. RESULTS: Of the 80 included innovation projects (32.5% technological, 35% organisational and 32.5% treatment innovations), 55% were successfully implemented within the planned timeframe. Comparing the outcome predictions with the observed outcomes of all innovations resulted in an AUC of the external validation of the prediction model of 0.72 (0.60-0.84, 95% CI). Factors related to successful implementation included in the model are sufficient and competent employees, desirability and feasibility, clear goals and processes and the complexity of a project. CONCLUSION: For the first time, a prediction model focusing on the timely implementation of innovations has been successfully built and externally validated. This model can now be widely used to enable more successful innovation in radiotherapy.

Minimal reporting improvement after peer review in reports of COVID-19 prediction models: systematic review.

OBJECTIVES: To assess improvement in the completeness of reporting coronavirus (COVID-19) prediction models after the peer review process. STUDY DESIGN AND SETTING: Studies included in a living systematic review of COVID-19 prediction models, with both preprint and peer-reviewed published versions available, were assessed. The primary outcome was the change in percentage adherence to the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) reporting guidelines between pre-print and published manuscripts. RESULTS: Nineteen studies were identified including seven (37%) model development studies, two external validations of existing models (11%), and 10 (53%) papers reporting on both development and external validation of the same model. Median percentage adherence among preprint versions was 33% (min-max: 10 to 68%). The percentage adherence of TRIPOD components increased from preprint to publication in 11/19 studies (58%), with adherence unchanged in the remaining eight studies. The median change in adherence was just 3 percentage points (pp, min-max: 0-14 pp) across all studies. No association was observed between the change in percentage adherence and preprint score, journal impact factor, or time between journal submission and acceptance. CONCLUSIONS: The preprint reporting quality of COVID-19 prediction modeling studies is poor and did not improve much after peer review, suggesting peer review had a trivial effect on the completeness of reporting during the pandemic.

Tetrelanes versus Tetrylenes as Precursors to Transition Metal Complexes Featuring Tridentate PEP Tetryl Ligands (E=Si, Ge, Sn).

Two synthetic approaches have until now been used to synthesize transition metal complexes having a tridentate (pincer or tripod) PEP tetryl (E=Si, Ge, Sn) ligand. These approaches differ in the metal-free precursor, tetrelane or tetrylene, that gives rise to the corresponding PEP tetryl ligand. Tetrelanes (PSiP silanes, PGeP germanes and PSnP stannanes and simple phosphane-free stannanes) have led to tetryl ligands by oxidatively adding an E-X bond (X=H, C or halogen in most cases) to the metal atom of a low-valent transition metal complex, whereas tetrylenes (PGeP germylenes and PSnP stannylenes) have led to tetryl ligands upon insertion of their E atom into an M-X bond (X=Cl in most cases) of the metal precursor or through a derivatization of the E atom after the tetrylene fragment is coordinated to the metal. For each synthetic approach, all the currently known types of PEP tetryl ligand frameworks that have been found in transition metal complexes are presented and discussed in this review.

Biomechanical comparison of different internal fixation devices for transversely unstable Mason type II radial head fractures.

Background: The integrity of the radial head is critical to maintaining elbow joint stability. For radial head fractures requiring surgical treatment, headless compression cannulated screw fixation is a less invasive scheme that has fewer complications. The aim of this study was to compare the mechanical stability of different fixation devices, including headless compression cannulated screws and mini-T-plates, for the fixation of transversely unstable radial head fractures. Methods: Forty identical synthetic radius bones were used to construct transverse unstable radial head fracture models. Parallel, cross, and tripod headless compression cannulated screw fixation and mini-T plate fixation were applied. The structural stiffness of each group was compared by static shear loading. Afterward, cyclic loading was performed in each of the three directions of the radial head, and the shear stability of each group was compared by calculating the maximum radial head displacement at the end of the cycle. Findings: The mini-T plate group had the lowest structural stiffness (51.8 ± 7.7 N/mm) and the highest relative displacement of the radial head after cyclic loading (p < 0.05). The tripod headless compression cannulated screw group had the highest structural stiffness among all screw groups (p < 0.05). However, there was no significant difference in the relative displacement of the radial head between the screw groups after cyclic loading in different directions (p > 0.05). Interpretation: In conclusion, the biomechanical stability of the mini-T plate for fixation of transverse unstable radial head fractures is lower than that of headless compression cannulated screws. Tripod fixation provides more stable fixation than parallel and cross fixation with headless compression cannulated screws for the treatment of transversely unstable radial head fractures.

Concerns surrounding application of artificial intelligence in hip and knee arthroplasty : a review of literature and recommendations for meaningful adoption.

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular ("AI/machine learning"), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.Cite this article: Bone Joint J 2022;104-B(12):1292-1303.