Eye-tracking-based analysis of pharmacists' thought processes in the dispensing work: research related to the efficiency in dispensing based on right-brain thinking.

BACKGROUND: Pharmacists should be aware of their thought processes in dispensing work, including differences in the dispensing complexities owing to different drug positions in the left, center, and right areas. Dispensing errors associated with "same-name drugs (a pair of drugs with the same name but a different ingredient quantity)" are prevalent and often negatively affect patients. In this study, using five pairs of comparative models, the gaze movements of pharmacists in dispensing work were analyzed using an eye-tracking method to elucidate their thought processes. METHODS: We prepared verification slides and displayed them on a prescription monitor and three drug rack monitors. The dispensing information (drug name, drug usage, location display, and total amount) was displayed on a prescription monitor. A total of 180 drugs including five target drugs were displayed on the three drug rack monitors. Total gaze points in the prescription area, those in the drug rack area, total vertical movements between the two areas, and time required to dispense drugs were measured as the four classifications Gaze 1, Gaze 2, Passage, and Time, respectively. First, we defined the two types of location displays as "numeral combination" and "color/symbol combination." Next, we defined two pairs of models A1-A2 (numerals) and B1-B2 (color/symbol) to compare differences between the left and right areas. Moreover, three pairs of models C1-C2 (left), D1-D2 (center), and E1-E2 (right) were established to compare differences between "numeral combination" and "color/symbol combination." RESULTS: Significant differences in the complexities of dispensing work were observed in Gaze 2, Passage, and Time between the models A1-A2 (A1B2), and in Gaze 2 and Time between the models C1-C2, D1-D2, and E1-E2 (C1>C2, D1>D2, and E1>E2, respectively). CONCLUSIONS: Using the current dispensing rules, pharmacists are not good at dispensing drugs located in the right area. An effective measure for reducing the dispensing complexity is to introduce visual information in the prescription content; the utilization of the right brain facilitates reducing the complexity in the right dispensing area.

Cortical gyrification in women and men and the (missing) link to prenatal androgens.

Previous studies have reported sex differences in cortical gyrification. Since most cortical folding is principally defined in utero, sex chromosomes as well as gonadal hormones are likely to influence sex-specific aspects of local gyrification. Classic congenital adrenal hyperplasia (CAH) causes high levels of androgens during gestation in females, whereas levels in males are largely within the typical male range. Therefore, CAH provides an opportunity to study the possible effects of prenatal androgens on cortical gyrification. Here, we examined the vertex-wise absolute mean curvature-a common estimate for cortical gyrification-in individuals with CAH (33 women and 20 men) and pair-wise matched controls (33 women and 20 men). There was no significant main effect of CAH and no significant CAH-by-sex interaction. However, there was a significant main effect of sex in five cortical regions, where gyrification was increased in women compared to men. These regions were located on the lateral surface of the brain, specifically left middle frontal (rostral and caudal), right inferior frontal, left inferior parietal, and right occipital. There was no cortical region where gyrification was increased in men compared to women. Our findings do not only confirm prior reports of increased cortical gyrification in female brains but also suggest that cortical gyrification is not significantly affected by prenatal androgen exposure. Instead, cortical gyrification might be determined by sex chromosomes either directly or indirectly-the latter potentially by affecting the underlying architecture of the cortex or the size of the intracranial cavity, which is smaller in women.

Association between more complex special care needs and overweight status and adolescents' difficulty with dental caries.

OBJECTIVE: Little is known about dental caries experience in adolescents with overweight and complex special health care needs (SHCNs). METHODS: Adolescent data (10-17 years) from the 2016-2020 National Survey of Children's Health (n = 91,196) was analyzed. The sample was grouped into the following: more complex SHCN and overweight, more complex SHCN without overweight, less complex SHCN and overweight, less complex SHCN without overweight, no SHCN but with overweight, and neither SHCN nor overweight. A multivariable-adjusted logistic regression model was conducted. RESULTS: Adolescents with more complex SHCNs with (OR: 1.82, 95% CI: 1.44-2.30, p < 0.001) or without overweight (OR: 1.51, 95% CI: 1.30-1.76, p < 0.001) were at higher odds of experiencing dental caries compared to healthy adolescents. No significant associations were observed between adolescents with less complex or no SHCN regardless of the overweight status with healthy adolescents. CONCLUSIONS: Adolescents with more complex SHCNs, irrespective of overweight status, experienced a higher caries severity than adolescents with no SHCNs or overweight.

Evolution of Complexity of Palliative Care Needs and Patient Profiles According to the PALCOM Scale (Part Two): Pooled Analysis of the Cohorts for the Development and Validation of the PALCOM Scale in Advanced Cancer Patients.

INTRODUCTION: Identifying the complexity of palliative care needs is a key aspect of referral to specialized multidisciplinary early palliative care (EPC) teams. The PALCOM scale is an instrument consisting of five multidimensional assessment domains developed in 2018 and validated in 2023 to identify the level of complexity in patients with advanced cancer. (1) Objectives: The main objective of this study was to determine the degree of instability (likelihood of level change or death), health resource consumption and the survival of patients according to the level of palliative complexity assigned at the baseline visit during a 6-month follow-up. (2) Method: An observational, prospective, multicenter study was conducted using pooled data from the development and validation cohort of the PALCOM scale. The main outcome variables were as follows: (a) instability ratio (IR), defined as the probability of level change or death; (b) emergency department visits; (c) days of hospitalization; (d) hospital death; (e) survival. All the variables were analyzed monthly according to the level of complexity assigned at the baseline visit. (3) Results: A total of 607 patients with advanced cancer were enrolled. According to the PALCOM scale, 20% of patients were classified as low complexity, 50% as medium and 30% as high complexity. The overall IR was 45% in the low complexity group, 68% in the medium complexity group and 78% in the high complexity group (p < 0.001). No significant differences in mean monthly emergency department visits (0.2 visits/ patient/month) were observed between the different levels of complexity. The mean number of days spent in hospital per month was 1.5 in the low complexity group, 1.8 in the medium complexity group and 3.2 in the high complexity group (p < 0.001). The likelihood of in-hospital death was significantly higher in the high complexity group (29%) compared to the medium (16%) and low (8%) complexity groups (p < 0.001). Six-month survival was significantly lower in the high complexity group (24%) compared to the medium (37%) and low (57%) complexity groups (p < 0.001). CONCLUSION: According to the PALCOM scale, more complex cases are associated with greater instability and use of hospital resources and lower survival. The data also confirm that the PALCOM scale is a consistent and useful tool for describing complexity profiles, targeting referrals to the EPC and managing the intensity of shared care.

Predicting outcome after aneurysmal subarachnoid hemorrhage by exploitation of signal complexity: a prospective two-center cohort study.

BACKGROUND: Signal complexity (i.e. entropy) describes the level of order within a system. Low physiological signal complexity predicts unfavorable outcome in a variety of diseases and is assumed to reflect increased rigidity of the cardio/cerebrovascular system leading to (or reflecting) autoregulation failure. Aneurysmal subarachnoid hemorrhage (aSAH) is followed by a cascade of complex systemic and cerebral sequelae. In aSAH, the value of entropy has not been established yet. METHODS: aSAH patients from 2 prospective cohorts (Zurich-derivation cohort, Aachen-validation cohort) were included. Multiscale Entropy (MSE) was estimated for arterial blood pressure, intracranial pressure, heart rate, and their derivatives, and compared to dichotomized (1-4 vs. 5-8) or ordinal outcome (GOSE-extended Glasgow Outcome Scale) at 12 months using uni- and multivariable (adjusted for age, World Federation of Neurological Surgeons grade, modified Fisher (mFisher) grade, delayed cerebral infarction), and ordinal methods (proportional odds logistic regression/sliding dichotomy). The multivariable logistic regression models were validated internally using bootstrapping and externally by assessing the calibration and discrimination. RESULTS: A total of 330 (derivation: 241, validation: 89) aSAH patients were analyzed. Decreasing MSE was associated with a higher likelihood of unfavorable outcome independent of covariates and analysis method. The multivariable adjusted logistic regression models were well calibrated and only showed a slight decrease in discrimination when assessed in the validation cohort. The ordinal analysis revealed its effect to be linear. MSE remained valid when adjusting the outcome definition against the initial severity. CONCLUSIONS: MSE metrics and thereby complexity of physiological signals are independent, internally and externally valid predictors of 12-month outcome. Incorporating high-frequency physiological data as part of clinical outcome prediction may enable precise, individualized outcome prediction. The results of this study warrant further investigation into the cause of the resulting complexity as well as its association to important and potentially preventable complications including vasospasm and delayed cerebral ischemia.

Transparent layer constancy improves with increased naturalness of the scene.

The extent to which hue, saturation, and transmittance of thin light-transmitting layers are perceived as constant when the illumination changes (transparent layer constancy, TLC) has previously been investigated with simple stimuli in asymmetric matching tasks. In this task, a target filter is presented under one illumination and a second filter is matched under a second illumination. Although two different illuminations are applied in the stimulus generation, there is no guarantee that the stimulus will be interpreted appropriately by the visual system. In previous work, we found a higher degree of TLC when both illuminations were presented alternately than when they were presented simultaneously, which could be explained, for example, by an increased plausibility of an illumination change. In this work, we test whether TLC can also be increased in simultaneous presentation when the filter's belonging to a particular illumination context is made more likely by additional cues. To this end, we presented filters in differently lit areas of complex, naturalistically rendered 3D scenes containing different types of cues to the prevailing illumination, such as scene geometry, object shading, and cast shadows. We found higher degrees of TLC in such complex scenes than in colorimetrically similar simple 2D color mosaics, which is consistent with the results of similar studies in the area of color constancy. To test which of the illumination cues available in the scenes are actually used, the different types of cues were successively removed from the naturalistically rendered complex scene. A total of eight levels of scene complexity were examined. As expected, TLC decreased the more cues were removed. Object shading and illumination gradients due to shadow cast were both found to have a positive effect on TLC. A second filter had a small positive effect on TLC when added in strongly reduced scenes, but not in the complex scenes that already provide many cues about the illumination context of the filter.

Chronic pain as an emergent property of a complex system and the potential roles of psychedelic therapies.

Despite research advances and urgent calls by national and global health organizations, clinical outcomes for millions of people suffering with chronic pain remain poor. We suggest bringing the lens of complexity science to this problem, conceptualizing chronic pain as an emergent property of a complex biopsychosocial system. We frame pain-related physiology, neuroscience, developmental psychology, learning, and epigenetics as components and mini-systems that interact together and with changing socioenvironmental conditions, as an overarching complex system that gives rise to the emergent phenomenon of chronic pain. We postulate that the behavior of complex systems may help to explain persistence of chronic pain despite current treatments. From this perspective, chronic pain may benefit from therapies that can be both disruptive and adaptive at higher orders within the complex system. We explore psychedelic-assisted therapies and how these may overlap with and complement mindfulness-based approaches to this end. Both mindfulness and psychedelic therapies have been shown to have transdiagnostic value, due in part to disruptive effects on rigid cognitive, emotional, and behavioral patterns as well their ability to promote neuroplasticity. Psychedelic therapies may hold unique promise for the management of chronic pain.

Introduction.

Atopic dermatitis (AD) is a chronic relapsing condition that is characterized by itching and redness of the skin. Our modern usage of atopic dermatitis dates back to 1933, when Wise and Sulzberger first coined the term to signify the disease's close association with other respiratory atopy, such as bronchial asthma and allergic rhinitis. A recent systematic review of 69 cross-sectional and cohort studies has confirmed that AD is now a worldwide phenomenon with lifetime AD prevalences of well over 20% in many affluent country settings. Although there is no obvious consistent overall global trend in the prevalence of AD, studies have shown that climate, urbanization, lifestyle, and socioeconomic class influence the prevalence of atopic dermatitis. Despite the pervasiveness of the disease, an understanding of atopic dermatitis has been hampered by a number of factors. Data suggests that extrinsic environmental factors work in concert with intrinsic immune mechanism and genetic factors to drive disease progression. With such a complex etiology, management of atopic dermatitis currently at best achieves symptomatic control rather than cure. This approach poses a significant burden on healthcare resources, as well as patients' quality of life. Current management methods of AD often involve a combination of non-pharmacologic modalities and prescription medications. Though they can be effective when employed, there are significant barriers to treatment for patients including time, costs, and medication side effects. Our aim, throughout this text, is to explore the complexities of AD, providing the healthcare provider with tips and tricks to improve patient care and satisfaction and the most current trends and treatment approaches on the horizon.

Objective measurement of movement variability using wearable sensors predicts ASD outcomes in infants at high likelihood for ASD and ADHD.

Early motor delays and differences are common among children with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Yet, little work has shown whether there are early atypical motor signs that differentiate these groups. Quantitative measures of movement variability hold promise for improving the identification of subtle and specific differences in motor function among infants and toddlers at high likelihood for ASD and ADHD. To this end, we created a novel quantitative measure of movement variability (movement curvature) and conducted a preliminary investigation as to whether this measure improves outcome predictions. We used a wearable triaxial accelerometer to evaluate continuous motion-based activity in infants at high and low likelihood for ASD and ADHD at 12, 18, 24, and 36 months of age. At 36 months, participants were categorized into three outcome groups: ASD (n = 19), ADHD concerns (n = 17), and a comparison group (n = 82). We examined group differences in movement curvature and whether movement curvature is predictive of a later ASD or ADHD concerns classification. We found that movement curvature was significantly lower in infants with later ASD diagnosis at 18, 24, and 36 months of age compared to infants with either ADHD concerns or those in the comparison group. Movement curvature was also a significant predictor of ASD at 18, 24, and 36 months (AUC 0.66-0.71; p = 0.005-0.039) and when adjusting for high ASD likelihood at 18 and 24 months (AUC 0.90, p = 0.05-0.019). These results indicate that lower movement curvature may be a feature of early motor differences in infants with later ASD diagnosis as early as 18 months of age.

"This patient is not appropriate": Perspectives of physiotherapy students and clinical educators on exposing students to patients with complex needs during clinical practice placements.

BACKGROUND: Clinical practice placements play an important role in preparing students for challenging areas of clinical practice. Little is known about student learning needs for working with patients with complex needs during clinical practice placements, and clinical educator decision-making that underpins this exposure. PURPOSE: To explore the perspectives of physiotherapy students and clinical educators on exposing students to working with and learning from patients with complex needs during clinical practice placements across Queensland and New South Wales, Australia. METHODS: Six semi-structured focus groups with pre-registration physiotherapy students undertaking clinical practice placements (n = 19) and semi-structured one-on-one interviews with clinical educators (n = 20). Data were analyzed using reflexive thematic analysis. RESULTS: Four overarching themes were generated following analysis: 1) Complexity is challenging; 2) Tension between student exposure and patient care; 3) Variance in expectations; and 4) Readiness for complexity. CONCLUSION: Physiotherapy students and clinical educators recognize the challenges and importance of exposure to patients with complex needs. Student learning experiences are influenced by clinical educator decision-making, which is often unclear, leading to varying opportunities. This study highlights the need for enhanced support from clinical educators to prepare students for working with patients with complex needs.

Analyzing the Iatrogenic Triad: Discovering Strategies for Preventing Harm in the Elderly.

Objectives: The iatrogenic triad is a significant global health problem in the elderly population. This study aimed to evaluate the iatrogenic triad in the elderly and identify potential preventive measures to mitigate its occurrence. Materials and Methods: A preliminary observational study was conducted on 150 ambulatory elderly patients to assess potentially inappropriate medications (PIMs), polypharmacy, and drug interactions. The AGS Beers Criteria 2019, Polypharmacy, Medication Complexity Regimen Index (MRCI), and Micromedex (a drug information software) were used to assess the harmful triad. Before and after data collection, we observed, identified, and unfolded potential strategies to avoid the harmful triad in the elderly population. Results: MRCI is 30.49 ± 13.77, suggesting a moderate level of complexity in the drug regimens of elderly patients. Among the PIMs identified by the AGS Beer criteria for 2019, glimepiride (45) and diclofenac (23) were found to be the most frequently prescribed. Moderate-level drug-drug interactions were identified between aspirin and metoprolol (20), metoprolol and metformin (13), and aspirin and enalapril (11). All drug-ethanol and drug-food interactions were rapid and often unknown to patients. Furthermore, the study found that MRCI and polypharmacy were significantly associated with the number of PIMs and drug interactions (p < 0.01). Based on data collection, this study identified three possible ways to prevent the iatrogenic triad in elderly patients: interaction, collaboration, and continuing education. Conclusion: In conclusion, this study sheds light on medication regimen complexity, PIMs, and drug interactions in elderly patients. The study also highlights three possible ways to prevent the iatrogenic triad: interaction, collaboration, and continuing education. By implementing these strategies, healthcare providers can help prevent harm and improve the quality of care for elderly patients.

Economic complexity, greenfield investments, and energy innovation: policy implications for sustainable development goals in newly industrialised economies.

The crucial role of environmental assessment quality has been recognised by environmental and sustainable development goals in addressing climate change challenges. By focusing on the key identifier of environmental assessment, progress can be made towards overcoming climate change issues effectively. The current study considers environmental commitments under COP28 to study the role of economic complexity, greenfield investments, and energy innovation in environmental degradation in newly industrialised economies from 1995 to 2021. We employ novel panel estimations from CS-ARDL, CS-DL, AMG, and CCEMG to confirm that economic growth and greenfield investments degrade environmental quality. On the other hand, energy innovation and urbanisation improve environmental sustainability. Lastly, we confirm the EKC hypothesis for economic complexity as well. Given the reported empirical findings, the study suggests policymakers must focus on economic complexity to transform industrial sectors' economic potential. Furthermore, foreign investment projects must be linked with environmental goals to increase renewable energy capacity.

Unleashing sustainability in uncertain times: Can we leverage economic complexity, uncertainty, and remittances to combat environmental degradation?

Rapid economic growth and human activities have seriously damaged the environment and hindered the achievement of Sustainable Development Goals (SDGs). Hence, this study aims to explore the impact of economic complexity, uncertainty, and remittance on environmental degradation in 134 countries from 2000 to 2022. In addition, it examines whether uncertainty moderates the relationship between remittance and environmental degradation. Two proxies (ecological footprint and CO2) were used to measure environmental degradation. The analysis was conducted using a cross-sectional dependency test, second-generation unit root test, and panel quantile regression. The results revealed that economic complexity significantly and positively impacted environmental degradation, while uncertainty and remittance significantly and negatively impacted environmental degradation. Furthermore, uncertainty weakened the negative relationship between remittance and environmental degradation. Accordingly, this paper discusses various recommendations and policy implications regarding economic complexity, uncertainty, remittance, and environmental degradation.

A Method to Redesign and Simplify Schedules of Assessment and Quantify the Impacts. Applications to Merck Protocols.

The growing complexity of biopharmaceutical sponsored trials has adverse impacts on increased burdens on participants, clinical sites, and sponsors, including greater difficulty recruiting and retaining participants, difficulty engaging sites to participate in trials, excessive cost of trials, and increased cycle times. The schedule of assessments (SoAs) is the origin of and blueprint for complexity that is often generated by copying and pasting from previous SoAs. We developed an approach, termed Lean Design, for redesigning the assessments in SoAs that generate data, the 'Data SoA.' It starts with a simple "ground zero" SoA. Any addition is challenged using several principles of trial design. We employed a system, the Faro Trial Designer Tool, to quantify the impacts of changes in an SoA to provide real-time feedback to the team and sponsor. We applied the approach in workshops with teams for six clinical trials in various stages of design and implementation. The approach resulted in recommendation for substantial potential savings in participant and site staff time, costs, and complexity of the trials. Application of this approach to very early stages of protocol design has the potential to reduce the complexity of biopharmaceutical sponsored trials and its consequences.

Molnupiravir increases SARS-CoV-2 genome diversity and complexity: A case-control cohort study.

Molnupiravir, an oral direct-acting antiviral effective in vitro against SARS-CoV-2, has been largely employed during the COVID-19 pandemic, since December 2021. After marketing and widespread usage, a progressive increase in SARS-CoV-2 lineages characterized by a higher transition/transversion ratio, a characteristic signature of molnupiravir action, appeared in the Global Initiative on Sharing All Influenza Data (GISAID) and International Nucleotide Sequence Database Collaboration (INSDC) databases. Here, we assessed the drug effects by SARS-CoV-2 whole-genome sequencing on 38 molnupiravir-treated persistently positive COVID-19 outpatients tested before and after treatment. Seventeen tixagevimab/cilgavimab-treated outpatients served as controls. Mutational analyses confirmed that SARS-CoV-2 exhibits an increased transition/transversion ratio seven days after initiation of molnupiravir. Moreover we observed an increased G->A ratio compared to controls, which was not related to apolipoprotein B mRNAediting enzyme, catalytic polypeptide-like (APOBEC) activity. In addition, we demonstrated for the first time an increased diversity and complexity of the viral quasispecies.

Natural language syntax complies with the free-energy principle.

Natural language syntax yields an unbounded array of hierarchically structured expressions. We claim that these are used in the service of active inference in accord with the free-energy principle (FEP). While conceptual advances alongside modelling and simulation work have attempted to connect speech segmentation and linguistic communication with the FEP, we extend this program to the underlying computations responsible for generating syntactic objects. We argue that recently proposed principles of economy in language design-such as "minimal search" criteria from theoretical syntax-adhere to the FEP. This affords a greater degree of explanatory power to the FEP-with respect to higher language functions-and offers linguistics a grounding in first principles with respect to computability. While we mostly focus on building new principled conceptual relations between syntax and the FEP, we also show through a sample of preliminary examples how both tree-geometric depth and a Kolmogorov complexity estimate (recruiting a Lempel-Ziv compression algorithm) can be used to accurately predict legal operations on syntactic workspaces, directly in line with formulations of variational free energy minimization. This is used to motivate a general principle of language design that we term Turing-Chomsky Compression (TCC). We use TCC to align concerns of linguists with the normative account of self-organization furnished by the FEP, by marshalling evidence from theoretical linguistics and psycholinguistics to ground core principles of efficient syntactic computation within active inference.

Unraveling the Complexity of REM Microstates: Insights from Nonlinear EEG Analysis.

While rapid eye movement (REM) sleep is conventionally treated as a unified state, it comprises two distinct microstates: phasic and tonic REM. Recent research emphasizes the importance of understanding the interplay between these microstates, hypothesizing their role in transient shifts between sensory detachment and external awareness. Previous studies primarily employed linear metrics to probe cognitive states, such as oscillatory power, while in this study, we adopt Lempel-Ziv Complexity (LZC), to examine the nonlinear features of electroencephalographic (EEG) data from the REM microstates and to gain complementary insights into neural dynamics during REM sleep. Our findings demonstrate a noteworthy reduction in LZC during phasic REM compared to tonic REM states, signifying diminished EEG complexity in the former. Additionally, we noted a negative correlation between decreased LZC and delta band power, along with a positive correlation with alpha band power. This study highlights the potential of nonlinear EEG metrics, particularly LZC, in elucidating the distinct features of REM microstates. Overall, this research contributes to advancing our understanding of the complex dynamics within REM sleep and opens new avenues for exploring its implications in both clinical and non-clinical contexts.

Unraveling the unknown: Adaptive spatial planning to enhance climate resilience for the endangered Swamp Grass-babbler (Laticilla cinerascens) with habitat connectivity and complexity approach.

The endangered and poorly known Swamp Grass-babbler, Laticilla cinerascens (Passeriformes: Pellorneidae), confronts critical threats and vulnerability due to its specific habitat requirements and restricted populations in the northeastern region of the Indian Subcontinent. This study investigates the distribution of the species, habitat quality, geometry and shape complexity of connectivity among the protected areas (PAs), and responses to climate change in Northeast India under different climate change pathways by utilizing ensemble distribution models, and ecological metrics. From the total distribution extent (1,42,000 km2), approximately 9366 km2 (6.59 %) is identified as the suitable habitat for this threatened species. Historically centered around Dibru Saikhowa National Park (DSNP), the species faced a drastic decline due to anthropogenic activities and alteration in land use and lover cover. The study also reveals a significant decline in suitable habitat for L. cinerascens in future climate scenarios, with alarming reductions under SSP126 (>10 % in the timeframe 2041-2060 and > 30 % from 2061 to 2080), SSP245 (>90 % in both time periods), and SSP585 (>90 % in both timeframes) from the present scenario. At present, DSNP has the most suitable habitat within the distribution range but is projected to decline (>90 %) under more severe climate change scenarios, as observed in other PAs. Landscape fragmentation analysis indicates a shift in habitat geometry, highlighting the intricate impact of climate change. It predicts a substantial 343 % increase (in the SSP126) in small habitat patches in the future. Connectivity analysis among PAs shows a significant shift, with a decline exceeding 20 %. The analysis of shape complexity and connectivity geometry reveals a significant increase of over 220 % in the fragmentation of connectivity among PAs between 2061 and 2080 under the SSP585 climate change scenario compared to the present conditions. The study underscores the urgent need for conservation actions, emphasizing the complex interplay of climate change, habitat suitability, and fragmentation. Prioritizing PAs with suitable habitats and assessing their connectivity is crucial. Adaptive management strategies are essential to address ongoing environmental changes and safeguard biodiversity. Future research in critical areas is needed to establish long-term monitoring programs to lead/extend effective conservation strategies.