Connected to the cloud at time of death: a case report.

BACKGROUND: Our case report provides the first clinical evaluation of autopsy practices for a patient death that occurs on the cloud. We question how autopsy practices may require adaptation for a death that presents via the 'Internet of Things', examining how existing guidelines capture data related to death which is no longer confined to the patient's body. CASE PRESENTATION: The patient was a British man in his 50s, who came to the attention of the medical team via an alert on the cloud-based platform that monitored his implanted cardioverter defibrillator (ICD). The patient had a background of congenital heart disease, with previous ventricular fibrillation cardiac arrest, for which the ICD had been implanted two years earlier. Retrospective analysis of the cloud data demonstrated a gradually decreasing nocturnal heart rate over the previous three months, falling to a final transmission of 24 beats per minute (bpm). In the patient post-mortem the ICD was treated as medical waste, structural tissue changes precluded the effective evaluation of device hardware, potential issues related to device software were not investigated and the cause of death was assigned to underlying heart failure. The documentation from the attending law enforcement officials did not consider possible digital causes of harm and relevant technology was not collected from the scene of death. CONCLUSION: Through this patient case we explore novel challenges associated with digital deaths including; (1) device hardware issues (difficult extraction processes, impact of pathological tissue changes), (2) software and data limitations (impact of negative body temperatures and mortuary radio-imaging on devices, lack of retrospective cloud data analysis), (3) guideline limitations (missing digital components in autopsy instruction and death certification), and (4) changes to clinical management (emotional impact of communicating deaths occurring over the internet to members of family). We consider the implications of our findings for public health services, the security and intelligence community, and patients and their families. In sharing this report we seek to raise awareness of digital medical cases, to draw attention to how the nature of dying is changing through technology, and to motivate the development of digitally appropriate clinical practice.

INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support.

Digital health solutions hold promise for enhancing healthcare delivery and patient outcomes, primarily driven by advancements such as machine learning, artificial intelligence, and data science, which enable the development of integrated care systems. Techniques for generating synthetic data from real datasets are highly advanced and continually evolving. This paper aims to present the INSAFEDARE project's ambition regarding medical devices' regulation and how real and synthetic data can be used to check if devices are safe and effective. The project will consist of three pillars: a) assurance of new state-of-the-art technologies and approaches (such as synthetic data), which will support the validation methods as part of regulatory decision-making; b) technical and scientific, focusing on data-based safety assurance, as well as discovery, integration and use of datasets, and use of machine learning approaches; and c) delivery to practice, through co-production involving relevant stakeholders, dissemination and sustainability of the project's outputs. Finally, INSAFEDARE will develop an open syllabus and training certification for health professionals focused on quality assurance.

Proposing an AI Passport as a Mitigating Action of Risk Associated to Artificial Intelligence in Healthcare.

The integration of Artificial Intelligence (AI) in healthcare signifies a substantial shift, offering benefits to patients and healthcare systems while also introducing new risks. The emphasis on patient safety and performance standards is pivotal, especially with the European Union's strides towards regulating AI through the AI Act. This act focuses on classifying AI systems based on risk levels, mandating stringent requirements for high-risk AI, enhancing transparency, and ensuring ethics in AI applications. The concept of an "AI passport" is introduced as a living document detailing the AI system's purpose, ethical declarations, training, evaluation, and potential biases. This passport aims to enhance transparency and safety in medical AI applications, serving as a comprehensive record for patients, clinicians, and stakeholders. The AI passport, structured in JSON format, encapsulates key information about the AI system as a mechanism for continuous performance evaluation and transparency. This initiative may represent a significant step towards mitigating the risks associated with AI in healthcare, emphasizing the importance of accountability, transparency, and patient safety in the development and application of AI technologies.

An Analysis of the Contaminants on Otoscopes of Otolaryngology Residents: An Observational Study.

The study was conducted to learn if the otoscope, a noncritical medical device, used by ENT residents harbor pathogenic organism. This study was conducted in a medical teaching hospital in India. Total of 38 otoscopes of ENT residents were examined after taking samples using sterile cotton swabs from otoscope speculum and otoscope head and both bacterial and fungal culture were studied. The study showed that 11 otoscope heads (28.94%) and 11 otoscope speculums (28.94%) out of the 38 otoscopes studied showed bacterial growth. Most commonly isolated bacteria were skin commensals followed by Klebsiella species. Fungal growth was seen in 3 out of 38 otoscope Speculums (7.89%). All 3 fungi isolated during the study belonged to Aspergillus species. Training residents regarding hygiene of medical equipments is necessary. Residents must be periodically assessed regarding their practice in handling medical equipments. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-024-04695-8.

Round Robin Study for evaluation KeraSkin™ as an in vitro skin irritation test for medical device extracts in Korea.

With the growing importance of alternative test methods that implement the 3Rs principles (Reduction, Refinement and Replacement) and the global importance of biological safety assessment data for medical devices is increasing. We have developed and optimized the 'KeraSkin™ Skin Irritation Test (KeraSkin™ SIT) for medical device' for regulatory application in biological evaluation according to ISO 10993-23. We conducted a round robin study to optimize and evaluate the performance of KeraSkin™ SIT for medical devices using KeraSkin™ Reconstructed Human Epidermis (RhE), which is developed and manufactured in Korea. This round robin study was performed to assess the transferability, reproducibility (within and between laboratories) and predictive capacity in 1 lead laboratory and 3 participating laboratories based on OECD Guidance Document 34. The predictive capacity, the results showed 83.3 % of sensitivity, 100 % of specificity and 91.6 % of accuracy. In conclusion, the results demonstrate that 'KeraSkin™ SIT for medical device' provides a robust test method for detecting irritant activity of medical device extracts and can be utilized for identifying low levels of potent irritants in medical device extracts. Therefore, it fulfills the requirements to be included as a 'me-too' test method to EpiDerm™ and SkinEthic™ skin irritation test in ISO 10993-23.

Accuracy study of Angiotensin 1-7 composite index test to predict pulmonary fibrosis and guide treatment.

BACKGROUND: Pulmonary fibrosis can develop after acute respiratory distress syndrome (ARDS). The hypothesis is we are able to measure phenotypes that lie at the origin of ARDS severity and fibrosis development. The aim is an accuracy study of prognostic circulating biomarkers. METHODS: A longitudinal study followed COVID-related ARDS patients with medical imaging, pulmonary function tests and biomarker analysis, generating 444 laboratory data. Comparison to controls used non-parametrical statistics; p < 0·05 was considered significant. Cut-offs were obtained through receiver operating curve. Contingency tables revealed predictive values. Odds ratio was calculated through logistic regression. RESULTS: Angiotensin 1-7 beneath 138 pg/mL defined Angiotensin imbalance phenotype. Hyper-inflammatory phenotype showed a composite index test above 34, based on high Angiotensin 1-7, C-Reactive Protein, Ferritin and Transforming Growth Factor-ß. Analytical study showed conformity to predefined goals. Clinical performance gave a positive predictive value of 95 % (95 % confidence interval, 82 %-99 %), and a negative predictive value of 100 % (95 % confidence interval, 65 %-100 %). Those severe ARDS phenotypes represented 34 (Odds 95 % confidence interval, 3-355) times higher risk for pulmonary fibrosis development (p < 0·001). CONCLUSIONS: Angiotensin 1-7 composite index is an early and objective predictor of ARDS evolving to pulmonary fibrosis. It may guide therapeutic decisions in targeted phenotypes.

Early access programs for medical devices in France: Overview of recent reforms and outcomes (2015-2022).

The medical technology sector is characterised by a constant influx of innovations with the potential to revolutionise patient care. In France, there are several pathways for medical devices to enter the market, from diagnosis-related group tariffs to reimbursement lists. However, traditional regulatory pathways can delay market access for innovative technologies. In response, France has established Early Access Programs to expedite patient access to medical devices. This paper looks at three of these Early Access Programs for medical devices. Innovation Funding, introduced in its final version in 2015, provides temporary coverage for innovative devices and facilitates data collection for informed funding decisions. Transitional Coverage (PECT), established in 2021, targets CE-marked devices for rare or serious conditions. Transitional coverage for digital health applications (PECAN), introduced in 2022, covers digital medical devices, either therapeutic or for patient monitoring. Innovation funding has been granted to 16 technologies out of 35 applications (46%) since 2015. 6 technologies out of 11 (64%) applications benefit from PECT. PECAN, in its first year, has granted a telemonitoring solution with a favourable opinion. The French experience could provide valuable lessons for the development of a harmonised European framework to ensure that innovative medical technologies benefit those who need them, while maintaining high safety standards.

[Monitoring System of Medical Device Adverse Events in the US and Application of MAUDE Database in Medical Device Registration].

In order to achieve precise risk control of medical devices, it is necessary to establish a scientific evaluation system throughout the entire life cycle of medical devices that focuses on risk identification and risk control. This study summarizes the medical device adverse event monitoring system of the US on regulatory agencies and regulatory law, adverse events reporting forms and time limits, adverse event database, adverse event report analysis and evaluation, as well as adverse event feedback and control. Furthermore, some examples are provided to illustrate the application of the MAUDE database in risk analysis, physical and mechanical performance research, and clinical evaluation of medical device registration and application materials.

Incidence of medical device-related pressure injuries: a meta-analysis.

BACKGROUND: Medical device-related pressure injures (MDRPIs) are common in critically ill patients and associated with negative clinical outcomes and elevated healthcare expenses. We aim to estimate worldwide incidence of MDRPI and explore associated factors through systemic review and meta-analysis. METHODS: The PubMed, Web of Science, Cochrane Library, and Ovid EMBASE databases were systematically queried to identify relevant studies published from Jan 1, 2010 up until June 30, 2024. Studies were included if they provided data on the incidence or prevalence of MDRPI. Random-effect models were utilized to calculate the overall or domain-specific aggregated estimates of MDRPI. A meta-regression analysis was additionally performed to investigate the heterogeneity among studies. RESULTS: We included 28 observational studies on 117,624 patients in the meta-analysis. The overall incidence of MDRPI was 19.3% (95% confidence interval (CI) 13.5-25.2%). The incidence of MDRPI in Europe, North America, Asia, South America, and Oceania was 17.3% (95% CI 12.7-21.9%), 3.6% (95% CI 0.0-8.5%), 21.9% (95% CI 14.3-29.6%), 48.3% (95% CI 20.8-75.7%), and 13.0% (95% CI 5.0-21.1%), respectively (p < 0.01). Multivariate meta-regressions revealed South America and special inpatient (critically ill patient, etc.) were independently associated with higher MDRPI incidence. CONCLUSIONS: Nearly, 20% of the patients in ICU suffered from MDRPI. The incidence of MDRPI in underdeveloped regions is particularly concerning, highlighting the importance of focusing on measures to prevent it, in order to reduce the medical burden and enhance the quality of life for affected patients.

Assessment by finite element analysis modelling of tissue strains associated with the use of two different nasogastric tube securement devices.

OBJECTIVES: Nasogastric tube use can lead to pressure injury. Some nasogastric tube securement devices (NG-SD) include hard plastic components. In the current study, we assessed the differences in strain profiles for two NG-SD, one with hard segments and one without hard segments, using finite element analysis (FEA) to measure strain and deformation occurring at the nasogastric tube-tissue interface. METHODS: FEA in silico models of devices were based on device mechanical test data and clinically relevant placements. Peak strain values were determined by modelling different scenarios using Abaqus software whereby the tubing is moved during wear. RESULTS: The modelling showed peak strains ranging from 52% to 434% for the two NG-SD depending on the tubing placement and device type. Peak strain was always higher for the hard plastic device. Tissue strain energy was a minimum of 133.8 mJ for the NG-SD with no hard parts and a maximum of 311.6 mJ for the NG-SD with hard parts. CONCLUSIONS: This study provided evidence through in silico modelling that NG-SD without hard components may impart less strain and stress to tissues which may provide an option for tube securement that is less likely to cause medical device-related pressure injury.

Correction for partial volume averaging in the quantification of radiopaque nanomaterial-embedded resorbable polymers.

Resorbable inferior vena cava (IVC) filters require embedded contrast for image-guided placement and integrity monitoring. We calculated correction factors to account for partial volume averaging of thin nanoparticle (NP)-embedded materials, accounting for object and slice thicknesses, background signal, and nanoparticle concentration. We used phantoms containing polycaprolactone disks embedded with bismuth (Bi) or ytterbium (Yb): 0.4- to 1.2-mm-thick disks of 20 mg ml-1NPs (thickness phantom), 0.4-mm-thick disks of 0-20 mg ml-1NPs in 2 mg ml-1iodine (concentration phantom), and 20 mg ml-1NPs in 0.4-mm-thick disks in 0-10 mg ml-1iodine (background phantom). Phantoms were scanned on a dual-source CT with 80, 90, 100, and 150 kVp with tin filtration and reconstructed at 1.0- to 1.5-mm slice thickness with a 0.1-mm interval. Following scanning, disks were processed for inductively coupled plasma optical emission spectrometry (ICP-OES) to determine NP concentration. Mean and maximum CT numbers (HU) of all disks were measured over a 0.5-cm2area for each kVp. HU was converted to concentration using previously measured calibrations. Concentration measurements were corrected for partial volume averaging by subtracting residual slice background and extrapolating disk thickness to both nominal and measured slice sensitivity profiles (SSP, mm). Slice thickness to agreement (STTA, mm) was calculated by replacing the CT-derived concentrations with ICP-OES measurements and solving for thickness. Slice thickness correction factors improved agreement with ICP-OES for all measured data. Yb corrections resulted in lower STTA than Bi corrections in the concentration phantom (1.01 versus 1.31 STTA/SSP, where 1.0 is perfect agreement), phantoms with varying thickness (1.30 versus 1.87 STTA/SSP), and similar ratio in phantoms with varying background iodine concentration (1.34 versus 1.35 STTA/SSP). All measured concentrations correlated strongly with ICP-OES and all corrections for partial volume averaging increased agreement with ICP-OES concentration, demonstrating potential for monitoring the integrity of thin IVC resorbable filters with CT.

Regulatory landscape, risks, and solutions for refurbished medical devices: a comparative analysis in the US, EU, Malaysia, and Ghana.

INTRODUCTION: Refurbished medical devices are previously owned equipment that undergo a process of restoration to ensure they meet quality standards and function effectively. The utilization of refurbished medical devices, coupled with the integration of software, poses intricate challenges in terms of regulatory compliance, risk management, and patient safety. AREAS COVERED: This article explores the regulatory frameworks governing refurbished medical devices in the United States (US), the European Union (EU), Malaysia, and Ghana. Included information from a range of primary and secondary sources. Additionally, it aims to identify and analyze the risks associated with refurbished medical devices, with a specific focus on the implications of software integration, and recommend practical solutions for mitigating these risks. EXPERT OPINION: The landscape of refurbished medical devices presents challenges in terms of regulatory compliance, risk management, and patient safety. Addressing these challenges requires careful consideration and strategies to ensure that refurbished devices meet stringent quality standards. By focusing on these areas, policymakers and healthcare professionals can enhance the safe utilization of refurbished medical devices, thereby improving access to quality healthcare, particularly in underserved regions.

Lessons on the use of real-world data in medical device research: findings from the National Evaluation System for Health Technology Test-Cases.

Aim: Although the US FDA encourages manufacturers of medical devices to submit real-world evidence (RWE) to support regulatory decisions, the ability of real-world data (RWD) to generate evidence suitable for decision making remains unclear. The 2017 Medical Device User Fee Amendments (MDUFA IV), authorized the National Evaluation System for health Technology Coordinating Center (NESTcc) to conduct pilot projects, or 'Test-Cases', to assess whether current RWD captures the information needed to answer research questions proposed by industry stakeholders. We synthesized key lessons about the challenges conducting research with RWD and the strategies used by research teams to enhance their ability to generate evidence from RWD based on 18 Test-Cases conducted between 2020 and 2022. Materials & methods: We reviewed study protocols and reports from each Test-Case team and conducted 49 semi-structured interviews with representatives of participating organizations. Interview transcripts were coded and thematically analyzed. Results: Challenges that stakeholders encountered in working with RWD included the lack of unique device identifiers, capturing key data elements and their appropriate meaning in structured data, limited reliability of diagnosis and procedure codes in structured data, extracting information from unstructured electronic health record (EHR) data, limited capture of long-term study end points, missing data and data sharing. Successful strategies included using manufacturer and supply chain data, leveraging clinical registries and registry reporting processes to collect and aggregate data, querying standardized EHR data, implementing natural language processing algorithms and using multidisciplinary research teams. Conclusion: The Test-Cases identified numerous challenges working with RWD but also opportunities to address these challenges and improve researchers' ability to use RWD to generate evidence on medical devices.

Contactless and Calibration-Free Blood Pressure and Pulse Rate Monitor for Screening and Monitoring of Hypertension: Cross-Sectional Validation Study.

BACKGROUND: The key to reducing the immense morbidity and mortality burdens of cardiovascular diseases is to help people keep their blood pressure (BP) at safe levels. This requires that more people with hypertension be identified, diagnosed, and given tools to lower their BP. BP monitors are critical to hypertension diagnosis and management. However, there are characteristics of conventional BP monitors (oscillometric cuff sphygmomanometers) that hinder rapid and effective hypertension diagnosis and management. Calibration-free, software-only BP monitors that operate on ubiquitous mobile devices can enable on-demand BP monitoring, overcoming the hardware barriers of conventional BP monitors. OBJECTIVE: This study aims to investigate the accuracy of a contactless BP monitor software app for classifying the full range of clinically relevant BPs as hypertensive or nonhypertensive and to evaluate its accuracy for measuring the pulse rate (PR) and BP of people with BPs relevant to stage-1 hypertension. METHODS: The software app, known commercially as Lifelight, was investigated following the data collection and data analysis methodology outlined in International Organization for Standardization (ISO) 81060-2:2018/AMD 1:2020 "Non-invasive Sphygmomanometers-Part 2: Clinical investigation of automated measurement type." This validation study was conducted by the independent laboratory Element Materials Technology Boulder (formerly Clinimark). The study generated data from 85 people aged 18-85 years with a wide-ranging distribution of BPs specified in ISO 81060-2:2018/AMD 1:2020. At least 20% were required to have Fitzpatrick scale skin tones of 5 or 6 (ie, dark skin tones). The accuracy of the app's BP measurements was assessed by comparing its BP measurements with measurements made by dual-observer manual auscultation using the same-arm sequential method specified in ISO 81060-2:2018/AMD 1:2020. The accuracy of the app's PR measurements was assessed by comparing its measurements with concurrent electroencephalography-derived heart rate values. RESULTS: The app measured PR with an accuracy root-mean-square of 1.3 beats per minute and mean absolute error of 1.1 (SD 0.8) beats per minute. The sensitivity and specificity with which it determined that BPs exceeded the in-clinic systolic threshold for hypertension diagnosis were 70.1% and 71.7%, respectively. These rates are consistent with those reported for conventional BP monitors in a literature review by The National Institute for Health and Care Excellence. The app's mean error for measuring BP in the range of normotension and stage-1 hypertension (ie, 65/85, 76% of participants) was 6.5 (SD 12.9) mm Hg for systolic BP and 0.4 (SD 10.6) mm Hg for diastolic BP. Mean absolute error was 11.3 (SD 10.0) mm Hg and 8.6 (SD 6.8) mm Hg, respectively. CONCLUSIONS: A calibration-free, software-only medical device was independently tested against ISO 81060-2:2018/AMD 1:2020. The safety and performance demonstrated in this study suggest that this technique could be a potential solution for rapid and scalable screening and management of hypertension.

Robotics in interventional endoscopy-evolution and the way forward.

The integration of robotics into gastrointestinal (GI) endoscopy represents a transformative advancement and bears the potential to bridge the gap between traditional limitations by offering unprecedented precision and control in diagnostic and therapeutic procedures. This review explores the historical progression, current applications and future potential of robotic platforms in GI endoscopy. Originally designed for surgical applications, robotic systems have expanded their reach into endoscopy, potentially enhancing procedural accuracy and reducing ergonomic strain on practitioners. Natural Orifice Transluminal Endoscopic Surgery (NOTES) emerged as a promising technique, leveraging natural orifices to perform minimally invasive surgeries. Despite its initial potential, several factors, including limitations of the available instrumentations and lack of reliable closure techniques, hindered its widespread adoption and progress. Conventional endoscopic tools often fall short in terms of triangulation, traction and degrees of freedom, necessitating the adoption of robotic interventions. Over recent decades, robotic endoscopy has significantly evolved, focusing on both diagnostic and complex therapeutic procedures such as endoscopic sub-mucosal dissection (ESD) and endoscopic full-thickness resection (EFTR). Various robotic platforms demonstrate enhanced safety and efficiency in GI procedures. As the field progresses, the emphasis on clinical validation, advanced training and the exploration of new applications remains crucial. Continuous innovation in robotic technology and endoscopic techniques promises to overcome existing limitations, further revolutionizing the management of GI diseases and improving patient outcomes.

Testing Usability of a Medical Device Using Virtual Reality.

Before commercialization of a medical device, it is important to evaluate its usability. Traditional methods such as user testing to evaluate usability of medical device encountered difficulties to put participants in simulation conditions that are sufficiently realistic to be representative of real life. Virtual reality can be used to immerse participants in a high-fidelity simulation at a lower cost, but is not widely used today. This feasibility study aims to compare the results obtained between user tests in a real simulated environment and in a virtual reality environment, with feedback on the advantages and disadvantages of both conditions.

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms.

Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is polysomnography (PSG). A major challenge associated with this method is all the cables needed to connect the recording devices, making the examination more intrusive and usually requiring a clinical environment. This can have potential consequences on the test results and their accuracy. One simple way to assess the state of the central nervous system (CNS), a well-known indicator of sleep disorder, could be the use of a portable medical device. With this in mind, we implemented a simple model using both the RR interval (RRI) and its second derivative to accurately predict the awake and napping states of a subject using a feature classification model. For training and validation, we used a database providing measurements from nine healthy young adults (six men and three women), in which heart rate variability (HRV) associated with light-on, light-off, sleep onset and sleep offset events. Results show that using a 30 min RRI time series window suffices for this lightweight model to accurately predict whether the patient was awake or napping.

Effective manual cleaning as the first step of reprocessing glass probes of a medical device for non-invasive physical plasma therapy.

Background: For reusable devices and device components, effective reprocessing is essential to prevent nosocomial infections. Aim: The objective of the study was to evaluate manual cleaning as the first step of reprocessing reusable glass probes of a device for generation of non-invasive physical plasma, in accordance with regulations. Methods: Two glass probes of the device were contaminated with human blood. For manual cleaning, both probes were cleaned with instrument cleaning agent and instrument brushes. Cleaning efficacy was evaluated by total protein measurement in the rinsing solution. Results: After manual cleaning of the two test glass probes, no protein from the test contamination with human blood could be detected. Neither the different design of the two probes nor the use of a hard or a soft instrument brush demonstrated any difference. Conclusion: Our data suggest that manual cleaning of glass probes achieves complete removal of organic contaminants. This should enable safe applications in clinical practice.

Optimization-Based Stable Balancing Weights Versus Propensity Score Weighting for Samples With High Covariate Imbalance.

PURPOSE: To compare the performance (covariate balance, effective sample size [ESS]) of stable balancing weights (SBW) versus propensity score weighting (PSW). Two applied cases were used to compare performance: (Case 1) extreme imbalance in baseline covariates between groups and (Case 2) substantial discrepancy in sample size between groups. METHODS: Using the Premier Healthcare Database, we selected patients who (Case 1) underwent a surgical procedure with one of two different bipolar forceps between January 2000 and June 2020, or (Case 2) a neurological procedure using one of two different nonabsorbable surgical sutures between January 2000 and March 2020. Average treatment effects on the treated (ATT) weights were generated based on selected covariates. SBW was implemented using two techniques: (1) "grid search" to find weights of minimum variance at the lowest target absolute standardized mean difference (SMD); (2) finding weights of minimum variance at prespecified SMD tolerance. PSW and SBW methods were compared on postweighting SMDs, the number of imbalanced covariates, and ESS of the ATT-weighted control group. RESULTS: In both studies, improved covariate balance was achieved with both SBW techniques. All methods suffered from postweighting ESS that was lower than the unweighted control group's original sample size; however, SBW methods achieved higher ESS for the control groups. Sensitivity analyses using SBW to apply variable-specific SMD thresholds increased ESS, outperforming PSW. CONCLUSIONS: In this applied example, the optimization-based SBW method provided ample flexibility with respect to prespecification of covariate balance goals and resulted in better postweighting covariate balance and larger ESS as compared with PSW.