Critical Scenarios Research Articles

High-risk, Critical Decision-making under Time Pressure: Some Parallels and Learning from Split-second Choices Made in Extreme Adventure Sports

In a world beset with crises, everyone from professional manager down to the layman is keen to understand how to make quick decisions under emerging disruptive situations. This article, employing self-reflective analysis of critical incidents, describes the author’s personal experiences from the field of adventure sports categorised as high-risk, critical decisions, involving split-second choices—while sky-diving and flying—to trace the mental cognitive processes from a decision maker’s perspective. This is used to discuss and establish a practitioners’ operational framework for high-risk, critical decision scenarios, drawing upon established theories and frameworks from cognitive, social and psychological decision research.

A bioeconomic model for a multispecies small-scale fishery system

A fishery encompasses various interconnected systems, including ecological, socioeconomic, and governing systems. Managing fisheries requires the simultaneous consideration of all these systems, making it a challenging endeavor. To address these challenges, fisheries bioeconomic models have emerged as a crucial tool. They are particularly valuable in the context of small-scale fisheries, which are often complex, overlooked and poorly understood. Thus, this paper presents a dynamic multispecies and multigear bioeconomic model that can illuminate the ecological, economic, and social dimensions of small-scale fisheries under different management scenarios. The model was applied to a small-scale fisheries system in Southern Brazil that has as a notable feature a cooperative fishing behavior between dolphins and fishers. Three scenarios were explored: the base scenario (status quo), the optimal management scenario, and the constrained optimal management scenario. The model outputs demonstrated a clear tradeoff between labour effort, species conservation, and economic rent. Shifting from the base to an optimal management scenario would result in a labour employment reduction within the system but concurrently yield higher stock levels, economic rent, and wages. These results illustrate how our model can explore critical management scenarios across the multiple dimensions of fisheries systems. In essence, this research offers a novel contribution in the form of a bioeconomic model tailored for small-scale fisheries involving multiple species.

Climate Change Impacts for Multipurpose Reservoir Planning: Basnagoda Reservoir, Sri Lanka

Climate change via rainfall and temperature changes poses threats to water resources. Traditionally, these variations are rarely considered in irrigation infrastructure planning. Integrating climate impacts into early irrigation planning ensures resilience and sustainability.This study aims to assess the climate change impacts on Basnagoda reservoir using a reservoir operation study, system designing and sizing, water use strategies and making recommendations as mitigation and adaptation strategies.This study employed reservoir operation model recommended in the Irrigation guideline, Sri Lanka to assess four climatic scenarios derived from predicted temperature and rainfall changes. Sensitivity analysis included reservoir sizing for the most critical scenario. Mitigation and adaptation methodologies such as 1) Reservoir capacity enhancement 2) Seasonal shifting 3) Conveyance enhancement were analyzed. Reservoir operations currently meet 100% of domestic demand, irrigating total 950 ha annually (380 ha Maha, 570 ha Yala) with environmental flow. Design capacity fulfils 78% of domestic demand, with environmental flow for projected period. The maximum cultivable area at the design stage while providing 25% of design domestic demand is 544 ha in Maha and 680 ha in Yala season. With a 20% rainfall reduction posing the worst scenario, domestic water fulfilment reduced to 20% (Maha) and 19% (Yala). Optimal reservoir capacity enhancement is 15%, expanding cultivable area to 390 ha, while providing 25% of design domestic demand. Conveyance enhancement increases cultivable area from reservoir water by 15%. This study is unique for integrating climate change impacts into reservoir infrastructure planning and design stages.

Vulnerability-oriented risk identification framework for IoT risk assessment

The proliferation of Internet of Things (IoT) systems across diverse applications has led to a notable increase in connected smart devices. Nevertheless, this surge in connectivity has induced a broad spectrum of vulnerabilities and threats, jeopardizing the security and safety of IoT applications. Security risk assessment methods are commonly employed to analyze risks. However, traditional IT and existing IoT-tailored security assessment methods often fail to fully address key IoT aspects: complex assets intercommunication, dynamic system changes, assets’ potential as attack platforms, safety impacts of security breaches, and assets resource constraints. Such oversights lead to significant risks being overlooked in the IoT ecosystem. In this paper, we propose a novel vulnerability-oriented risk identification framework comprising a four-step process as a core element of IoT security risk assessment, applicable to any IoT system. Our process enhances both traditional and IoT-specific security risk assessment methods by providing tailored approaches that address their crucial oversights for comprehensive IoT risk assessment. We validate our process with a case study of an IoT smart healthcare system using a proposed expert-driven approach. The results confirm that our process effectively identifies critical attack scenarios originating from the lack of proper security measures, mobility, and intercommunication processes of IoT devices in the healthcare system. Furthermore, our analysis reveals potential attacks that exploit the IoT devices as platforms to target the backend and user domains. We demonstrate the feasibility of our process for identifying realistic risks by conducting simulations of two derived attack scenarios using the Contiki Cooja network simulator.

Lactate Monitoring in Intensive Care: A Comprehensive Review of Its Utility and Interpretation.

Lactate monitoring is critical in managing critically ill patients in intensive care settings. Elevated lactate levels often signify underlying metabolic disturbances such as tissue hypoxia, anaerobic metabolism, or impaired lactate clearance, which are prevalent in conditions like sepsis, shock, and trauma. Understanding the physiological basis of lactate production and its significance in clinical practice is essential for interpreting its diagnostic and prognostic value. This comprehensive review aims to explore the utility of lactate monitoring across various critical care scenarios. It provides an overview of lactate's metabolic pathways, methods of measurement, and the clinical implications of interpreting lactate levels in different contexts. Additionally, the review discusses current evidence on lactate-guided therapeutic interventions and highlights challenges and limitations to their application. By synthesizing the existing literature and clinical insights, this review aims to enhance the understanding of the role of lactate monitoring in assessing disease severity, guiding treatment strategies, and predicting outcomes in critically ill patients. Ultimately, this review underscores the importance of integrating lactate monitoring into routine clinical practice to optimize patient care and improve clinical outcomes in intensive care settings.

Game-Theoretic Adversarial Interaction-Based Critical Scenario Generation for Autonomous Vehicles

Ensuring safety and efficiency in the rapidly advancing autonomous vehicle (AV) industry presents a significant engineering challenge. Comprehensive performance evaluations and critical scenario testing are essential for identifying situations that AVs cannot handle. Thus, generating critical scenarios is a key problem in AV testing system design. This paper proposes a game-theoretic adversarial interaction method to efficiently generate critical scenarios that challenge AV systems. Initial motion prediction for adversarial and surrounding vehicles is based on kinematic models and road constraints, establishing interaction action spaces to determine possible driving domains. A novel evaluation approach combines reachability sets with adversarial intensity to assess collision risks and adversarial strength for any state, used to solve behavior values for each interaction action state. Further, equilibrium action strategies for the vehicles are derived using Stackelberg game theory, yielding optimal actions considering adversarial interactions in the current traffic environment. Simulation results show that the adversarial scenarios generated by this method significantly increase incident rates by 158% to 1313% compared to natural driving scenarios, while ride comfort and driving efficiency decrease, and risk significantly increases. These findings provide critical insights for model improvement and demonstrate the proposed method’s suitability for assessing AV performance in dynamic traffic environments.

Automated or human: Which driver wins the race for the passengers’ trust? Examining passenger trust in human-driven and automated vehicles following a dangerous situation

Automated vehicles (AVs) provide numerous advantages over manually operated vehicles, but the extent of these benefits depends on whether we engage with AVs safely and efficiently. To achieve such interactions with AVs, an appropriate – or calibrated – level of trust in AVs especially during critical scenarios, is fundamental. The trust level also impacts individuals' decisions regarding the utilisation of AV technology. This study investigates trust calibration and factors that influence how trust develops in AVs compared to human drivers. Two groups of participants underwent a driving simulation, experiencing either a ride in a human-driven taxi or an AV, during which a dangerous situation occurred. Before, during and after the simulation, the passengers’ trust was measured.Pre-simulation trust was higher in the human driver than in the AV, but this difference disappeared after the simulation. Noticeably, during the simulation trust did not differ between the groups. Instead, the critical situation significantly influenced trust: following the dangerous incident, trust levels in both conditions dropped but recovered until the simulation ended. Additionally, self-esteem, which has been associated with trust in the past, was investigated. However, no significant relationship between self-esteem and trust was found in this study. Overall, the findings indicate that the dangerous situation prompted heightened caution among participants. A process of trust calibration was initiated in which the participants’ trust was highly susceptible to the driving style of the driver/AV. Moreover, the comparable evolution of trust in the human-driven vehicle and the AV, sheds light on the dynamics underlying attitudes towards AVs.

Risk analysis of petroleum storage tank based on uncertain data incorporated into mapped Bow-tie to Bayesian network

The petroleum industry has an important impact on the environment, which is why risk analysis for a petroleum storage tank is required in the process industry. However, conducting an exhaustive study is frequently complicated due to the incomplete data based on historical system information, feedback, or test results. The main goal of this study is to develop an innovative framework that integrates the Bow-tie method with MIMAH (Methodology for the Identification of Major Accident Hazards). This approach specifically aims to identify the most critical accident scenario and comprehensively list all realistic causes (basic events) associated with petroleum storage tanks. Acquiring historical data on basic events poses challenges due to the lack, insufficiency, and imprecision of failure data. To address this obstacle and predict the system’s evolution, a combination of established methods for handling uncertainty and multi-criteria decision-making has been proposed. This combination incorporates a modified Fuzzy Analytical Hierarchy Process with Chang’s Extent Analysis Method (FAHP-EAM), fuzzy set theory, and expert elicitation, contributing to an extensive approach for managing uncertainty and making informed decisions in the absence of comprehensive historical data. Furthermore, the Bow-tie model is converted into a dynamic Bayesian network to improve risk analysis by integrating probabilistic reasoning and capturing the dynamic interactions among multiple risk factors. This integrated approach is validated on real scenarios. The utilization of dynamic Bayesian networks further facilitates the suggestion of scenarios to assess the contribution of basic events to the critical event and evaluate the resulting environmental impacts. Finally, the prediction of threat zones for various hazardous effects, such as toxicity, thermal radiation, and overpressure linked to chemical releases following the occurrence of the critical event, is carried out. The risk analysis outcomes from this study offer valuable data for assessment, enabling managers to improve the quality of risk management and formulate effective risk mitigation strategies.

The implementation of a collision warning system in Formula racing

Advanced Emergency Braking (AEB) is used to reduce rear-end collisions in critical traffic scenarios. The racing environment contributes critical cases. In Formula races, critical collisions occur during cornering. Drivers may not concentrate on the boundary regions at high speeds. For this reason, an AEB system may support the drivers in such cases. On the other hand, this system is not permitted to be implemented in racing cars. Therefore, an AEB system may be implemented into the environment of the track by using several Long-Range Radars (LRR) at critical points. The originality of this study is the approach in the implementation of an AEB system into the racing environment as a collision warning system. The effectiveness of the implementation of the AEB system into the racing environment depends on the reaction time of the racing drivers. A fuzzy logic controller was proposed to control Time to Collision (TTC) during cornering according to the track geometry. The controller design was established in MATLAB/Simulink interface with the simulations in the IPG/CarMaker environment. According to the simulation results, the approach in the implementation of the AEB system prevented a pile-up.

Method for selecting emergency material reserve bases in chemical industry parks under typhoon scenarios

Rationally selecting emergency material reserve bases (EMSBs) for chemical industry parks is crucial to ensure timely emergency responses during major accidents. To identify practical site selection schemes for EMSBs under typhoon scenarios, a prioritization/sorting site selection model considering typhoon disasters for EMSBs is developed. Firstly, an improved k-means clustering algorithm is employed to cluster typhoon paths and classify them into several critical typhoon scenarios, which are used to assess the risk of typhoon disasters affecting chemical industrial parks in specific areas. Then, according to the region's functional characteristics of EMSBs, candidate areas with emergency capabilities are identified through kernel density analysis, and safe candidate areas are further determined based on the identified typhoon scenarios. Finally, the safe candidate areas are ranked based on emergency path distances, and the preferred site selection areas are ultimately obtained through administrative planning analysis of the top-ranked areas. Furthermore, a case study is conducted based on data from Zhejiang Province, verifying the effectiveness of the decision-making method.

Educational perspectives in cardiothoracic anesthesia in the United States using a survey of educators and learners.

Cardiothoracic anesthesiology training presents learners with unique challenges, procedural skills, and the management of high-intensity critical scenarios. An effective relationship between educator and learner can serve as the backbone for effective learning, which is crucial for the development of budding anesthesiologists. Strengthening this educational alliance between teachers and trainees involves understanding the educational values educators and learners find most important to their learning experiences. This study aimed to identify the key educational values related to cardiothoracic anesthesia for both learners and educators. By identifying these values in separate cohorts (learners and educators), the importance of various educational values can be examined and compared between the trainees and teachers. Two separate surveys (one for learners and one for teachers) were adapted from the Pratt and Collins Teaching Perspectives Inventory to establish the importance of various educational values related to cardiothoracic anesthesia. Surveys were sent to 165 Accreditation Council for Graduate Medical Education-accredited anesthesiology residency training programs in the United States to trainees (residents and cardiothoracic anesthesiology fellows) and educators (board-certified cardiothoracic anesthesiologists). Analysis of survey results from 19 educators and 57 learners revealed no statistical differences across the two groups, except Q15: "Let trainee perform critical technical steps" (P value = 0.02). While learners and educators in cardiothoracic anesthesia hold similar values regarding cardiac anesthesia education, they differ in the degree to which critical technical steps should be performed by learners.

A Framework for Selecting and Assessing Wearable Sensors Deployed in Safety Critical Scenarios.

Wearable sensors for psychophysiological monitoring are becoming increasingly mainstream in safety critical contexts. They offer a novel solution to capturing sub-optimal states and can help identify when workers in safety critical environments are suffering from states such as fatigue and stress. However, sensors can differ widely in their application, design, usability, and measurement and there is a lack of guidance on what should be prioritized or considered when selecting a sensor. The paper aims to highlight which concepts are important when creating or selecting a device regarding the optimization of both measurement and usability. Additionally, the paper discusses how design choices can enhance both the usability and measurement capabilities of wearable sensors. The hopes are that this paper will provide researchers and practitioners in human factors and related fields with a framework to help guide them in building and selecting wearable sensors that are well suited for deployment in safety critical contexts.

Design and construct of an assessment tool for the handover of critical patient the in urgent care and emergency setting

ObjectivesTo design and construct an assessment tool for the handover of critical patients in the urgent care and emergency setting. Research methodologyThis metric and descriptive study comprised two phases in accordance with the Clinical practice guidelines for A Reporting Tool for Adapted Guidelines in Health Care: The RIGHT-Ad@pt Checklist. In the first phase, the identification and selection of items related to the handover of critical patients were performed by consensus of a group of experts. The second phase consisted of two stages. In the first stage, the items were selected by applying the e-Delphi technique across two assessment rounds and in the second stage, the items were subjected a pilot test in a real critical patient handover scenario. Professionals from different disciplines and work areas (hospital and prehospital) caring for critically ill patients in the urgency and emergency setting participated in each of the phases. ResultsA total of 58 critical patient care, and urgent and emergency care professionals participated in the design and construction of the assessment tool. The initial list consisted of 14 categories and 57 items, which were reduced to 28 items grouped into five categories after the intervention of the participants. The content validity index (CVI) of the instrument was 0.966. ConclusionsThis study describes an assessment tool developed in Spanish-language designed to assess the handover of critical patients in the urgent care and emergency setting. This tool has a high CVI, and is the only currently available tool that consider all of the dimensions and characteristics of the handover process. Implications for clinical practiceThe assessment tool developed in this study could enable critical care professionals in their clinical practice to work in a systematic way, universalizing the handover of critically ill patients in the urgent care and emergency setting through scientifically proven guidelines.

Possible criticality scenario and its mechanism of the Windscale Works criticality accident in 1970 analyzed by computational fluid dynamics and Monte Carlo neutron transport

The Windscale Works criticality accident in 1970 resulted from mixing an aqueous solution with an organic solvent with different plutonium concentrations and densities. Although this accident has been studied using improved computer capabilities in recent years, a precise criticality scenario has not yet been identified. This study aims to clarify a possible criticality scenario of the accident—the time variation of reactivity and its mechanism. The accident was simulated by combining the multiphase computational fluid dynamics solver of OpenFOAM and the delta-tracking-based Monte Carlo neutron transport code Serpent2. Consequently, the periodic uneven arrangement of fluids might have caused oscillations in neutron leakage and absorption, resulting in periodic wavy reactivity changes. Furthermore, the emulsion, which was thought to be the primary cause, might not be the dominant mechanism for reactivity change, although it contributed to the criticality of the accident.

Applications of Fog Computing in Healthcare.

Fog computing is a decentralized computing infrastructure that processes data at or near its source, reducing latency and bandwidth usage. This technology is gaining traction in healthcare due to its potential to enhance real-time data processing and decision-making capabilities in critical medical scenarios. A systematic review of existing literature on fog computing in healthcare was conducted. The review included searches in major databases such as PubMed, IEEE Xplore, Scopus, and Google Scholar. The search terms used were "fog computing in healthcare," "real-time diagnostics and fog computing," "continuous patient monitoring fog computing," "predictive analytics fog computing," "interoperability in fog computing healthcare," "scalability issues fog computing healthcare," and "security challenges fog computing healthcare." Articles published between 2010 and 2023 were considered. Inclusion criteria encompassed peer-reviewed articles, conference papers, and review articles focusing on the applications of fog computing in healthcare. Exclusion criteria were articles not available in English, those not related to healthcare applications, and those lacking empirical data. Data extraction focused on the applications of fog computing in real-time diagnostics, continuous monitoring, predictive analytics, and the identified challenges of interoperability, scalability, and security. Fog computing significantly enhances diagnostic capabilities by facilitating real-time data analysis, crucial for urgent diagnostics such as stroke detection, by processing data closer to its source. It also improves monitoring during surgeries by enabling real-time processing of vital signs and physiological parameters, thereby enhancing patient safety. In chronic disease management, continuous data collection and analysis through wearable devices allow for proactive disease management and timely adjustments to treatment plans. Additionally, fog computing supports telemedicine by enabling real-time communication between remote specialists and patients, thereby improving access to specialist care in underserved regions. Fog computing offers transformative potential in healthcare, improving diagnostic precision, patient monitoring, and personalized treatment. Addressing the challenges of interoperability, scalability, and security will be crucial for fully realizing the benefits of fog computing in healthcare, leading to a more connected and efficient healthcare environment.

Impact of the COVID-19 Pandemic on Pharmacist Interventions: A Retrospective Study with Inpatients in a University Hospital.

Despite growing interest in understanding the challenges faced by multidisciplinary health teams during the COVID-19 pandemic, there is a lack of studies specifically focusing on changes in pharmacist interventions and drug-related problems. To analyze and compare the interventions performed by pharmacists during comprehensive medication management in the adult intensive care unit and general internal medicine ward of the University Hospital of the University of São Paulo, Brazil, for defined periods before the onset of the COVID-19 pandemic and during the pandemic itself. All pharmacist interventions performed in relation to inpatient prescriptions from March to December 2019 (before the pandemic) and from March to December 2021 (during the pandemic) were collected and tabulated. These interventions were then classified according to the Pharmaceutical Care Network Europe (PCNE) system, version 9.1, and categorized based on first-level codes of the Anatomical Therapeutic Chemical classification system. The analysis revealed substantial changes in the patterns of pharmacist interventions and the therapeutic classes of drugs for COVID-19-positive and COVID-19-negative patients during the pandemic relative to patients in the pre-pandemic period. Among COVID-19-positive patients, interventions were predominantly related to enhancing patient safety (PCNE code P2), drug selection (C1), dose selection (C3), prescribing and dispensing processes (C5), the drug-use process (C6), and patient transfers between different levels of care (C8). The drug-related problems addressed by pharmacist interventions primarily involved COVID-19-positive patients in the pandemic period and were related to systemic hormonal preparations (excluding sex hormones and insulins), anti-infective agents for systemic use, nervous system and drugs for the blood and blood-forming organs. The results of this study highlight the adaptability and competence of pharmacists in responding to critical scenarios such as the COVID-19 pandemic. These scenarios are characterized by new work dynamics, the hiring of additional professionals, an increase in the number of beds, the rapid evolution of evidence-based information, and drug shortages that necessitate the use of alternative medications. Pharmacists play a crucial role in ensuring patient safety during these difficult times.

Improving Neonatal Resuscitation Knowledge in Advanced Providers Through Simulation: A Quality Improvement Project.

Advanced neonatal resuscitation events are high-risk, low-volume critical situations. Healthcare systems have placed emphasis on improving resuscitation skills for advanced providers based on evidence showing that it can directly impact patient outcomes. Neonatal resuscitation program (NRP) renewal is only required every 2 years. This gap and low usage of skills can result in lack of competency and expertise leading to an increased risk of poor patient outcomes. This project aimed to provide simulation education based on NRP curriculum for a large group of advanced providers at multiple level II, III, and IV neonatal intensive care units (NICUs) and to improve confidence and knowledge in advanced resuscitation. A high-fidelity mannequin was used to simulate a reproducible, critical scenario that spanned the entire NRP algorithm. NRP knowledge and the effectiveness of simulation on confidence and knowledge in neonatal resuscitation were measured. The average knowledge score from the pretest to the posttest improved by 7%. Based on the simulation evaluation tool-modified (SET-M), debriefing was the most effective in improving confidence and knowledge. The neonatal nurse practitioners (NNPs) with the most years of clinical experience had the largest improvement in knowledge. With the most experienced NNPs providing majority of coverage in the Level II NICUs, a correlation may be drawn that the effect of simulations on NRP knowledge has a greater impact on these groups due to the low exposure of advanced resuscitation events at these sites. Debriefing stood out as the most critical component of simulation.

Hydropower Enhancing the Future of Variable Renewable Energy Integration: A Regional Analysis of Capacity Availability in Brazil

As the share of variable renewables in the power system generation mix increases, meeting capacity requirements becomes challenging. In this context, hydropower reservoirs can play a vital role in integrating renewable energy due to their storage potential, contributing to meeting power supply criteria. However, given that reservoirs serve multiple purposes, various constraints can limit their capacity potential. This article introduces an analytical methodology that is designed to evaluate the maximum available power of hydro plants in critical scenarios. By applying concepts related to hydropower production calculations for the peak power demand and metrics evaluating the compliance with supply criteria, this study distinguishes itself from region-specific investigations. It conducts a generalized analysis of power availability across all regions of Brazil, with a focus on identifying the reasons for the most significant power losses and their specific locations. The results of this analysis demonstrate the feasibility of enhancing the available power of reservoirs, effectively addressing demand fluctuations, and sustainably improving energy security. This is particularly crucial in countries that are heavily reliant on renewables, including hydropower, for a huge portion of their electricity. The findings underscore the feasibility of increasing the penetration of variable renewable generation by optimizing the operation of existing hydropower plants. This optimization not only enhances energy security but also contributes to a more resilient and sustainable future, benefiting policy makers, energy planners, and stakeholders in the field of hydropower with reservoirs.

VExUS: The Holy Grail or Achilles Heel of fluid management?

Excessive use of intravenous fluids is becoming less favored in most critical case scenarios due to increased identification of adverse effects associated with fluid overload. Venous Excess Ultrasound (VExUS) is a recent point of care ultrasound (POCUS) tool in critical care. It has a promising utility to identify end point of resuscitation, onset of fluid congestion and to facilitate initiation of de-resuscitation. Whether or not significant association or causation exists between congestion as identified by VExUS and clinically relevant outcomes is yet to be observed as newer evidences surface and establish the place of VExUS in clinical practice. This narrative review aims to describe the current need to have a tool to accurately identify fluid overload, give a brief description of the physiology behind along with techniques of performing VExUS. We have also summarized the available evidences so far for and against VExUS and the limitations of this technique.

A novel PEG-mediated approach to entrap hemoglobin (Hb) within ZIF-8 nanoparticles: Balancing crystalline structure, Hb content and functionality

Hemoglobin (Hb)-based oxygen carriers are investigated as a potential alternative or supplement to regular blood transfusions, particularly in critical and life-threatening scenarios. These include situations like severe trauma in remote areas, battlefield conditions, instances where blood transfusion is not feasible due to compatibility concerns, or when patients decline transfusions based on religious beliefs.This study introduces a novel method utilizing poly(ethylene glycol) (PEG) to entrap Hb within ZIF-8 nanoparticles (i.e., Hb@ZIF-8 NPs). Through meticulous screening, we achieved Hb@ZIF-8 NPs with a record-high Hb concentration of 34 mg mL−1. These NPs, sized at 168 nm, displayed exceptional properties: a remarkable 95 % oxyhemoglobin content, excellent encapsulation efficiency of 85 %, and resistance to Hb oxidation into methemoglobin (metHb). The addition of PEG emerged as a crucial factor amplifying Hb entrapment within ZIF-8, especially at higher Hb concentrations, reaching an unprecedented 34 mg mL−1. Importantly, PEG exhibited a protective effect, preventing metHb conversion in Hb@ZIF-8 NPs at elevated Hb concentrations.