Autosomal dominant polycystic kidney disease (ADPKD) is one of the leading causes of end-stage renal disease. In spite of the recent tremendous progress in the understanding of ADPKD pathogenesis, the molecular mechanisms of the disease remain incompletely understood. Considering emerging new targeted therapies for ADPKD, it has become crucial to disclose easily measurable and widely available biomarkers for identifying patients with future rapid disease progression. This review encompasses all the research with a shared goal of identifying promising serum or urine biomarkers for predicting ADPKD progression or response to therapy. The rate of the ADPKD progress varies significantly between patients. The phenotypic variability is only partly explained by the underlying genetic lesion diversity. Considering significant decline in kidney function in ADPKD is not usually evident until at least 50% of the parenchyma has been destroyed, conventional kidney function measures, such as glomerular filtration rate (GFR), are not suitable for monitoring disease progression in ADPKD, particularly in its early stages. Since polycystic kidney enlargement usually precedes the decline in GFR, height-adjusted total kidney volume (ht-TKV) has been accepted as an early biomarker for assessing disease severity in ADPKD patients. However, since measuring ht-TKV is time-consuming and observer-dependent, the identification of a sensitive and quickly measurable biomarker is of a great interest for everyday clinical practice. Throughout the last decade, due to development of proteomic and metabolomic techniques and the enlightenment of multiple molecular pathways involved in the ADPKD pathogenesis, a number of urine and serum protein biomarkers have been investigated in ADPKD patients, some of which seem worth of further exploring. These include copeptin, angiotensinogen, monocyte chemoattractant protein 1, kidney injury molecule-1 and urine-to-plasma urea ratio among many others. The aim of the current review is to provide an overview of all of the published evidence on potentially clinically valuable serum and urine biomarkers that could be used for predicting disease progression or response to therapy in patients with ADPKD. Hopefully, this review will encourage future longitudinal prospective clinical studies evaluating proposed biomarkers as prognostic tools to improve management and outcome of ADPKD patients in everyday clinical practice. Autosomal dominant polycystic kidney disease (ADPKD) is one of the leading causes of end-stage renal disease (ESRD) worldwide . This mo2) and metabolic syndrome have been recognized as additional modifiable risk factors for a rapid ADPKD progression  . HoweverAlthough MIC, ADPKD-OM and PROPKD are nowadays the most commonly used prognostic models in ADPKD clinical trials, all of these predictive scores remain limited by availability, high price and expertise mandatory for obtaining such parameters and therefore are not useful in everyday clinical practice , 31. FurFor these reasons, growing number of studies are investigating multiple serum and urinary molecules, particularly those involved in underlying pathophysiology, as alternative biomarkers for predicting fast disease progression in ADPKD patients. Herein, we highlight emerging urine and serum biomarkers that have been associated with a higher risk of rapid ADPKD progression.A comprehensive literature review was conducted using Medline and Scopus databases to discern published articles investigating the potential serum or urine biomarkers for predicting ADPKD progression, in accordance with the published guidelines for writing systematic reviews . We usedOne of the first clinical features in PKD patients that occurs prior to a kidney function decline is a decreased urine concentrating capacity , 115. To2) followed-up for 11 years. Serum copeptin level was inversely correlated with the renal function decline, even after adjusting for patients' age, gender, blood pressure and baseline eGFR values. Patients with a higher baseline copeptin (above the median of 2.7 pmol/L) started renal replacement therapy during follow-up. These findings confirmed the results of a previous cross-sectional study of 102 ADPKD patients in which copeptin was found to be associated positively with TKV and albuminuria and negatively with GFR and effective renal blood flow . Surprisingly, copeptin levels in donors did not change after donation, regardless of a significant GFR decline. Based on these findings the authors suggested that, in ADPKD, kidney damage and reduced urine concentrating capacity determine copeptin levels and that kidney function per se is not the leading determinant of the serum copeptin concentration. Therefore, changes in copeptin levels precede decline in GFR. These observations are limited by a lack of fluid and dietary intake standardization at the time of serum sample collection, as well as a lack of a control group with patients with a non-ADPKD CKD.To investigate whether increased copeptin serum levels emerge from a reduced kidney clearance or as a compensation for diminished concentrating capacity, Zittema et al.  comparedn = 53) and healthy controls (n = 53) was found   . TherefoBesides its correlation with disease severity and progression, higher copeptin levels have been associated with cardiovascular disease (CVD) manifestations  in ADPKD patients. A study including 202 early stage ADPKD patients  with a 3-year long follow-up, demonstrated that CVD develops even in ADPKD patients with preserved renal function and progresses faster than renal function decline (estimated by the eGFR decrease) . On top Gansevoort et al.  investigLacqueniti et al.  corroborThe use of copeptin as a biomarker has a few limitations. Copeptin levels are significantly higher in males compared to females, but are not strongly correlated with age , 132. InConclusively, analyzed studies uniformly suggest that copeptin could be a valuable early biomarker for identifying ADPKD patients with a greater risk of a rapid disease progression. Future studies on ADPKD patients with a standardized fluid and dietary intake should investigate whether assessment of serum or urine copeptin adds an extra value in predicting ADPKD progression over commonly used eGFR and TKV and whether copeptin could serve as a predictive biomarker for selecting ADPKD patients who will doubtlessly benefit from AVP-modifying therapies.Impaired urine concentrating capacity can be observed in patients with ADPKD even before kidney function starts to decline , 115. UnFurthermore, Zittema et al.  found ann = 203, 6 years follow-up) , another surrogate marker of the impaired maximal urine-concentrating capacity, emerged as an independent risk factor for a rapid GFR decline in a retrospective analysis of 139 ADPKD patients . The prellow-up) . Moreovellow-up)  assessedTaken all together, both urinary osmolality and U/P urea are reliable surrogate biomarkers for maximal urine-concentrating capacity and, based on the analyzed findings, seem to have a clinical utility as predictors of a rapid ADPKD progression. Since implementation of these potential prognostic biomarkers in everyday clinical practice is limited by the scarce evidence, additional studies are required for validating uOsm and U/P urea as predictors of a future kidney functiondecline and tolvaptan treatment efficacy in ADPKD patients.Hypertension occurs in ADPKD patients even earlier than in patients with essential hypertension and development of an early-onset hypertension is an important predictor of renal outcome in ADPKD –14, 139.n = 60) compared to sex, eGFR, blood pressure and RAAS inhibitor use matched non-ADPKD CKD patients (n = 57), while plasma levels of AGT and renin did not differ between the groups. Accordingly, higher urinary excretion levels of AGT and renin might be unique ADPKD features that are not simply a consequence of elevated plasma RAAS concentrations and renal function decline, but might be contributors to kidney damage. It must be noted that some of the included patients were on therapy with RAAS inhibitor and that there was a lack of age matching between ADPKD and non-ADPKD CKD patients. Lastly, even though significant, the strength of the associations detected in this study was modest, so additional studies in wider cohorts are warranted.Salih et al.  reportedPark et al.  found thn = 293) than in non-ADPKD CKD patients . Furthermore, the authors were the first to examine uAGT/Cr as a prognostic biomarker in ADPKD and found that, indeed, the uAGT/Cr ratio correlates positively with the risk of all-cause mortality and renal function decline in ADPKD patients, proposing its utility as a prognostic biomarker in ADPKD patients. However, this study did not include htTKV and PKD genotype as covariables. Moreover, since it takes a long time before ESRD or death occur in ADPKD (composite outcome in this study), it would be more convenient to analyze annual change in eGFR as a marker of renal function decline within a shorter (few years) follow-up duration.Kim et al.  confirmeThe same group of authors evaluated uAGT/Cr as a prognostic biomarker for renal function decline in addition to imaging classification in a subsequent prospective study on 207 ADPKD patients with different CKD stages followed-up for more than one year . PatientConsidering all the presented data, it is reasonable to conclude that uAGT is a valid early biomarker of ADPKD progression that reflects underlying pathophysiology. In addition to its individual prognostic value, combination of uAGT, imaging classification and/or genotype could be used to delicately define rapid ADPKD progressors. Nevertheless, additional studies validating utility of uAGT as a prognostic ADPKD biomarker are necessary before incorporating uAGT measurements in clinical settings.Fibroblast growth factor 23 (FGF23), a bone-derived phosphaturic hormone, has been recognized as a strong risk factor for ESRD, cardiovascular morbidity and mortality in CKD patients . Pavik eTo conclude, FGF23 is a potential prognostic biomarker for accelerated disease progression and early-onset undesirable clinical outcomes in ADPKD. Further studies are necessary to determine whether FGF23 improves prognostic value of commonly used prognostic models based on htTKV and PKD genotype as well as to elucidate whether the detected correlation between FGF23 and ADPKD outcome represents causal effect.Hayek et al.  investigSince the study reviewed above is, to our knowledge, so far the only published research on suPAR in ADPKD patients, additional studies are necessary for validating suPAR as a prognostic biomarker in ADPKD.Somatostatin (SST) inhibits cAMP production in kidney and, consequently, inhibits renal cyst cells proliferation , 144. He2 , serum bicarbonate is independently associated with kidney outcome . Namely, each mmol/l serum bicarbonate decline increased the risk of kidney function deterioration by 21% and was associated with further eGFR decline. Serum bicarbonate was not associated with changes in htTKV. Intriguingly, serum bicarbonate correlated with kidney outcome independently of urinary ammonium excretion (a biomarker of urinary acidification capacity) as well as of variables included in the most commonly used ADPKD prognostic models, MIC and PROPKD score. The authors proposed lower serum bicarbonate  as a predictor of poor kidney outcomes in ADPKD. Further studies with a longer follow-up are warranted to validate these results as well as to examine whether there is a causal relation between low serum bicarbonate and an accelerated kidney function decline.Blijdrop et al.  reportedSecreted frizzled-related protein 4 (sFRP4), an antagonist of the Wnt signaling pathway, is highly expressed in kidneys, blood, cyst fluid and urine of ADPKD patients . Zschied2 per year). These potentially important correlations must be verified in future large prospective clinical studies.As with patients with CKD of other causes, hyperuricemia seems to be involved in the development and progression of ADPKD . Higher The urine concentration of molecules which are highly expressed in the settings of kidney injury or ischemia may be predictive of further renal function deterioration. These include indicators of tubular injury, such as the kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL) or β 2-microglobulin (β2MG) , 149. LiMesschendorp et al. conducted two consecutive studies evaluating urinary biomarkers as predictors of ADPKD progression  , 86. The2), with a trend towards significant correlation in early ADPKD. Urinary KIM-1 levels correlated with baseline HtTKV, but did not associate with annual change in HtTKV, suggesting that elevated uKIM-1 levels are not entirely caused by tubular injury due to cyst expansion. Of notice, htTKV measures were available only for patients in an early ADPKD stage. Based on the findings of these two studies  compared to slow progressors in a cohort of 87 ADPKD patients. However, patients were in late stage of disease (eGFR 33 ± 20 ml/min/1.73 m2), making it possible that increased uNGAL levels were merely a consequence of a renal dysfunction. This hypothesis is further supported by the results of Boligano et al. , suggesting this novel marker as a candidate prognostic biomarker in ADPKD and supporting the proposed role of T cells in ADPKD pathogenesis. Li et al. (n = 16) showed increased expression of soluble forms of CD14. In this small group of ADPKD patients, baseline urinary CD14 levels (but not GFR) significantly correlated with a two-year rate of TKV change, indicating that urinary CD14 level could serve as a predictor of ADPKD outcome. Despite the strong correlations detected by flow cytometry analyses in these studies  than in healthy controls (n = 17) or patients with other renal diseases (n = 50). Moreover, in ADPKD patients, urinary Fetuin-A level significantly correlated with the CKD stage. Most importantly, in a cohort of early-stage ADPKD patients, urinary Fetuin-A concentrations significantly increased during 2 years of follow-up without a concomitant increase in eGFR, suggesting that the urinary level of Fetuin-A might be a more sensitive biomarker for detecting disease progression than eGFR. Limitations of this study include the lack of PKD genotyping and TKV assessment. Further studies should investigate the pathogenic mechanisms of increased Fetuin-A expression in ADPKD.Piazzon et al.  evaluaten = 11) compared to slow progressors (n = 11). Since all included patients had eGFR > 60 ml/min/1.73 m2, the authors suggested OPN is as an early biomarker of a rapid ADPKD progression. Interestingly, opposite to its decreased expression in ADPKD population, OPN expression in non-ADPKD CKD is increased  on top of that caused by ADPKD, unlike htTKV growth or PKD mutation which are specific for ADPKD. This might lead to a more individualized approach to ADPKD patients. Additional advantage of urinary biomarkers compared to TKV and PKD mutation is a rapid response to treatment allowing better therapeutic guidance. However, studies investigating whether baseline or treatment-induced short-term changes in urinary biomarkers correlate with long-term outcome are lacking.To summarize, among a large number of urinary molecules investigated in the studies reviewed above, urinary β2MG, MCP-1, KIM1 and VEGF have been discerned in most of the studies as the ones with the best predictive value for a rapid ADPKD progression –89. Stiln = 78) were found to have a significant shortening of telomere length (TL) and higher levels of RNA containing telomere repeat (TERRA) levels compared to healthy controls (n = 20). Moreover, 16 genetically unrelated patients with rapidly progressive ADPKD demonstrated higher levels of TERRA with shorter telomeres compared to slow progressors. Interestingly, genetically related individuals carrying the same PKD mutation differed in TL and TERRA levels, independently of gender and age. The reported intrafamilial variations emphasize a potential role of these epigenetic biomarkers in predicting the progression of ADPKD. Due to the intriguing correlations observed in this isolated study of TL and TERRA in a small cohort of ADPKD patients, further studies could be of a great significance for individualized approach and better management of ADPKD patients.Kocygit et al. are the first to explore the link between telomeric epigenome and ADPKD progression . ADPKD pSince conventional markers have numerous limitations, metabolic profiling holds a promise as biomarker for risk categorization of ADPKD patients. A small cross-sectional study by Gronwald et al.  demonstrFurthermore, Rowe et al.  identifiDekker et al.  singled 2/year) demonstrated an increase in the urinary myoinositol/citrate ratio whereas no significant change in the myoinositol/citrate ratio was found in slow progressors. The prognostic value of the urinary myoinositol/citrate ratio in predicting rapid disease progression was at least comparable to that of the conventional risk marker htTKV.In a subsequent study, Dekker et al.  validateBaliga et al.  performeKang et al.  performeIn summary, each of the reviewed metabolomic studies among ADPKD patients proposed different metabolites for predicting rapid ADPKD progression, and those are: urinary lactate/pyruvate ratio , urinary2 GFR decline over 8 years in patients younger than 24 years. The performance of this biomarker panel was comparable to that of htTKV and the combination of the biomarker panel with htTKV demonstrated the highest predictive value for ADPKD progression to ESRD.Proteomics, or the study of small peptides which compose a sample, has become a method widely applied in different fields of research. It comes as no surprise therefore that urinary proteomics have a promising potential for discovering novel biomarkers in ADPKD. Kistler et al.  were theβ-catenin and PDGF-signaling proteins in their urinary EVs at baseline, whereas those with a poor response to therapy had highly expressed angiogenesis pathway proteins.Recent progress in “omic” studies has facilitated the discovery of extracellular vesicles (EVs) as novel biomarkers allowing the detection of pathologic processes even earlier than conventional biomarkers . Indeed,Even though proteomic expression profiling might be superior to any other biochemical marker in predicting disease progression and response to therapy in ADPKD patients, incorporating urinary proteomics in everyday clinical practice has some challenges, including variations in the urine proteome based on multiple factors, such as age, sex, diet, and physiological state . FurtherTaken all together, the proteomic studies on ADPKD patients are only at the beginning. Despite the marked heterogeneity between the design and the results of the studies reviewed above, the observed correlations strongly advocate proteomic profiling as a promising tool for discerning patients with a future rapid ADPKD progression and for identifying those among rapid progressors who will doubtlessly benefit from treatment with tolvaptan. Further proteomic studies in ADPKD patients are indispensable for revealing reliable ADPKD prognostic biomarkers reflecting the underlying pathophysiological pathways. In addition, development of a human protein atlas, especially urinary exosomal protein expression atlas , will asAs with proteomics, microRNAs, small highly conserved non-coding RNA molecules with role in gene expression regulation, have also become an important subject of numerous basic and translational research, and ADPKD is no exception. Kocygit et al.  reportedMicroRNAs proposed as diagnostic and prognostic ADPKD biomarkers in these studies –114 requDespite tremendous effort to elucidate all aspects of ADPKD through extensive basic and translational research, there is still an unmet clinical requirement for biomarker(s) which could predict the rate of disease progression, either alone or in combination with the conventional prognostic markers in ADPKD patients. The recent entrance in the era of targeted therapies in ADPKD has emphasized the urgent need to identify reliable and widely accessible biomarkers for predicting ADPKD progress. Identification of such biomarker would allow optimal patient selection for an early introduction of therapy or inclusion in clinical trials.The studies incorporated in this review demonstrate the multifaceted character of the pursuit of identifying the most reliable prognostic marker for ADPKD. We focused on articles investigating markers that can simply be measured in patients' blood or urine samples since these are the most widely available tools. According to studies reviewed in the presented manuscript, the most promising ADPKD prognostic biomarkers are molecules involved in the disease pathogenesis: markers of tubular injury, inflammation, metabolism, the renin-angiotensin or the vasopressin system. However, multiple ADPKD pathogenic pathways and involved molecules are yet to be exposed. Although none of the proposed prognostic biomarkers has shown a prominent additional prognostic value beyond kidney volume- or genotype-based prognostic models, several studies provided evidence that incorporating certain serum or urine biomarker and Mayo classification or PROPKD score might be the most accurate risk prediction model for a rapid disease progression in patients with ADPKD. Among various molecules under investigation, the most promising ones for predicting ADPKD progression are copeptin, apelin, angiotensinogen, FGF23, suPAR, serum bicarbonate, sFRP4, KIM1, MCP1, β2MG, CD14, fetuin A, osteopontin, along with asymptomatic pyuria, urine osmolality and urine to plasma urea ratio. Despite numerous studies comparing these biochemical markers, to identify the finest for predicting ADPKD progression, many studies are still lacking. Moreover, in the “omics” era, multiple additional candidates are emerging as highly specific ADPKD prognostic biomarkers hopefully leading to individualized approach and personalized risk assessment and therapeutic decision-making in ADPKD patients.Even though ADPKD is increasingly diagnosed in pediatric age, studies investigating biomarkers of ADPKD progression in children are surprisingly scarce. Among the 73 studies thoroughly analyzed in this review, only 4 studies , 105 werIn conclusion, the available data are not sufficient to draw the final conclusions. Although the proposed molecules show promising results that warrant further investigation, scarce evidence limit their potential to displace traditional biomarkers in the near future. Additional studies with large cohorts and long follow-up are necessary to determine the superiority of proposed biomarkers to traditionally used ADPKD prognostic models. Hopefully, the emerging evidence from studies with large ADPKD cohorts will allow for some of the herein mentioned molecules to be used in everyday clinical practice for predicting ADPKD progression and therefore improving disease management.


IntroductionHypertension (HTN) is a chronic condition that serves as a major risk factor for cardiovascular diseases, leading to increased mortality and morbidity. It is a frequent modifiable illness affecting global health, resulting in catastrophic fatalities and morbidity.AimThis study aims to investigate blood parameter profiles and their clinical implications in hypertensive patients at the Prince Faisal bin Khalid Cardiac Center in Abha, Saudi Arabia.MethodsUtilizing retrospective data from 121 patients at the Prince Faisal bin Khalid Cardiac Center in Abha, Saudi Arabia. The hematological parameter examined were hemoglobin (HB), platelets, hematocrit (HCT), calcium, phosphorus, sodium, potassium, urea, creatinine, and uric acid. The SPSS version 28 software was used for data analysis.ResultsSignificant correlations between various hematological parameters were found in the results, pointing to potential connections between kidney function, the production of blood cells, and electrolyte balance in hypertensive patients. The results align with earlier studies carried out in the area and offer insightful information for clinicians and researchers interested in managing HTN and its complications.ConclusionThe study emphasized the significance of considering hypertensive patients' age, gender, and lifestyle when interpreting their blood parameter profiles. The findings imply that a thorough comprehension of these blood parameter values and their potential effects on HTN is necessary for effectively managing HTN in this population. This study on the blood parameter profiles in hypertensive patients in Saudi Arabia provides the relationships between various hematological parameter and their clinical implications. These findings should be considered when creating targeted interventions and strategies to address the specific requirements and difficulties of managing HTN and its associated complications in this population. More research is required to comprehend the underlying reasons for the observed variations in hematological parameter profiles and their effects on the management of HTN. Hypertension (HTN) is a frequent controllable condition that affects the worldwide population's health and causes morbidity and mortality. A total of 19.60 million hypertensive heart disease cases were documented in 2019 compared to 7.82 million in 1990, corresponding to an estimated annual percentage change of 0.17 . The burThis is a retrospective study conducted at Prince Faisal Bin Khalid Cardiac Center located in Abha, Saudi Arabia, approximately 1.2 km from the central part of Abha. The Prince Faisal Bin Khalid Cardiac Center is a renowned medical facility that specializes in providing advanced cardiac care and treatment to patients with various heart-related conditions.Inclusion criteriaThis study encompassed all eligible hypertensive patients attending Prince Faisal Bin Khalid Cardiac Center between 2021 and 2022, aged 20 years or above, who agreed to participate in the study. Exclusion criteriaWe excluded patients aged below 20 years and above 70 years, individuals on lipid-lowering medications, those with thyroid disease, and those with pre-eclampsia/eclampsia. Additionally, patients with hematologic derangements and hypertensive patients with co-morbid diabetes mellitus were precluded from the study to mitigate potential confounding factors.In this study, we investigated the correlation between HTN and various laboratory parameters, including lipid profiles such as serum total cholesterol (TC), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C). We also examined hematologic parameters such as hemoglobin, hematocrit, RBC count, platelet count, and RBC indices. Other considered laboratory parameters included calcium, phosphorus, sodium, potassium, urea, creatinine, and uric acid. Beyond these laboratory variables, we incorporated sociodemographic factors, anthropometric measurements, and clinical characteristics to evaluate their potential impact on HTN.Operational definitionsDyslipidemia refers to abnormally elevated levels of lipids and/or lipoproteins in the blood, indicating a defect in lipoprotein metabolism. It can manifest as increased cholesterol (below 200 mg/d), increased triglycerides (TG) (below 150 mg/dL), increased low-density lipoprotein cholesterol (LDL) (below 100 mg/dL), and decreased high-density lipoprotein cholesterol (HDL) (above 60 mg/dL).Controlled blood pressure refers to blood pressure that is effectively managed by antihypertensive medications  and non-pharmacological treatments. In this case, systolic blood pressure (SBP) is maintained below 140 mmHg, and diastolic blood pressure (DBP) is maintained below 90 mmHg.Uncontrolled or poorly controlled blood pressure indicates blood pressure that remains elevated despite the prescribed antihypertensive drugs. In this case, SBP equals or exceeds 140 mmHg, and/or DBP is 90 mmHg or higher.Anthropometric measurements are various aspects of the human body and its parts, providing quantitative indices of their variability. These indicators include height, weight, BMI, waist circumference (WC), and waist-to-hip ratio (WHR).Statistical analysesThe SPSS version 28.0 software was employed for all statistical analyses. A significance level of p-value <0.05 was considered to indicate statistical significance. The statistical analysis included calculating descriptive statistics for age, weight, and height, stratified by gender, to explore gender differences in these variables. Additionally, for hematological parameters such as hematocrit (HCT), platelets, hemoglobin, calcium, phosphorus, sodium, potassium, urea, creatinine, and uric acid levels, mean, median, SD, and the minimum and maximum values were computed. Furthermore, a Pearson's correlation matrix was constructed to assess the relationships between these hematological parameters and demographic variables. Additionally, to compare these variables in terms of gender, an independent samples t-test was utilized. The results of these analyses are detailed in the Results section of this study.Ethical considerationThe study obtained ethical approval from King Khalid University's local Institutional Review Board (IRB) committee, ensuring adherence to ethical guidelines. To safeguard confidentiality and data protection, all participant information was securely stored in a password-protected cloud. We strictly followed the Helsinki guidelines and ensured the anonymity of the data collection process.Descriptive statistics for age, weight, and height of patients with HTN have been stratified by gender. For age, the mean and standard deviation are 58.65 and 13.06 for males, respectively, and 68.09 and 15.72 for females. In terms of weight, males have a mean of 77.91 with a standard deviation of 14.01, while females have a mean of 73.19 and a standard deviation of 23.63. Regarding height, the mean for males is 162.98 with a standard deviation of 8.52, whereas, for females, the mean is 154.74 with a standard deviation of 6.81. These statistics underscore the gender differences in these three variables, offering valuable insights for researchers and clinicians exploring gender-related health disparities , platelets, HCT, calcium, phosphorus, sodium, potassium, urea, creatinine, and uric acid. The results provided each parameter's mean, median, SD, minimum, and maximum values.According to the results, the median hemoglobin value is 14.56, with an SD of 2.27, a minimum of 8.36, and a maximum of 18.73. The mean hemoglobin value is 14.50. Similarly, the median platelets value is 250.00, with an SD of 132.76, a minimum value of 14.50, and a maximum value of 905.80. The mean platelets value is 280.99. Additionally, the median hematocrit value is 44.06, with an SD of 18.39, a minimum of 13.28, and a maximum of 215.70. The mean hematocrit value is 45.59.Additionally, for calcium, the median value is 4.82, the mean is 5.07, the standard deviation (SD) is 1.26, and the range is 2.07-12.39. For phosphide, the median is 3.36, the mean is 3.27, and the SD is 0.88, with values ranging from 0.50 to 5.97. For sodium, the median is 136.00, the mean is 134.54, the SD is 12.99, and the range is 2.41-158.00.Further, for potassium, the median value is 4.17, the mean is 4.13, the SD is 0.48, and the range is 2.29 to 5.16. For urea, the median is 37.10, the mean is 43.88, and the SD is 27.76, with values between 9.82 and 163.95. For creatinine, the median is 1.05, the mean is 1.12, and the SD is 0.41, with the lowest value being 0.44 and the highest 3.10. For uric acid, the median is 6.16, the mean is 6.29, and the SD is 2.00, ranging from 2.75 to 13.82  and creatinine , as shown in the matrix. HCT and calcium also had a highly significant positive correlation . The correlations between HB and uric acid, HCT and uric acid, and HCT and platelets were all significantly negative , as were the correlations between HCT and platelets . Additionally, there were highly significant negative correlations between calcium and HB  and calcium and platelets . Additionally, there was a significant positive correlation between potassium and phosphate  as well as between phosphate and calcium . Finally, all the variables, except for sodium, showed statistically significant positive correlations with urea  = 2.144, p =0.034). Males had higher mean creatinine levels than females, which was also a significant difference (t(119) = 2.228, p =0.008).The results show that there may be gender differences in some hematological parameters but not in others and strong correlations between some variables that should be considered in future analyses  = 2.144, p =0.034). This outcome is in line with earlier research that discovered gender differences in HB levels in several populations, including Saudi Arabia ,18. DiffBased on the findings of this study, there are notable differences in height, weight, and age between the genders among HTN patients in the Saudi Arabian region. To properly discuss and interpret these results, it's essential to reference earlier research. To start, the average age of male patients with HTN is 58.65 years (SD = 13.06), while female patients average 68.09 years (SD = 15.72). Previous research conducted in Saudi Arabia suggests that women are more likely than men to develop HTN later in life ,21. MoreStrengths and limitationsDespite offering insightful data, this study has some drawbacks. The sample size might not be sufficient to extrapolate the results to Saudi Arabia's entire population. Additionally, because the study is cross-sectional, it is difficult to prove that one variable causes another. Additionally, the study does not take into account possible confounding variables, such as comorbidities or medication use, which might affect the relationships that were found.This study provides valuable insights into the blood parameters of hypertensive patients in Saudi Arabia, offering information on their overall health status and potential risk factors for HTN. The research highlights the importance of considering age, gender, and lifestyle choices when managing HTN and underscores the significance of electrolyte balance and kidney function markers. The findings align with earlier studies and emphasize the need for further research to fully comprehend the underlying factors influencing these blood parameters' variations and correlations. Clinicians and researchers should consider these results when designing interventions for efficient HTN management and associated complications. Future research should focus on understanding the relationships between blood parameters, gender differences, and HTN onset in Saudi Arabia. Large-scale longitudinal studies are recommended to gain deeper insights while also exploring the impact of confounding factors like comorbidities, medications, and lifestyle choices.


To report the effects of a tunica vagina flap on testicular compartment syndrome. This single-arm clinical trial was conducted from September 2020 to October 2021. Consecutive patients with suspected testicular torsion within 24 hours of pain onset were included. Patients with past testicular torsion, bilateral torsion, or previous atrophy were excluded. The tunica vaginalis was opened, and the intratesticular pressure was measured before testicular retrieval from the scrotum and detorsion (P1), after detorsion (P2), and after transverse incision (P3). A tunica vaginalis flap was performed and a new intratesticular pressure was recorded (P4). The contralateral testicular pressure was recorded before fixation (Pc). The minimum follow-up period was 6 months. Fifteen patients were recruited from September 2020 to October 2021. Nine patients completed the follow-up. The median age (range) was 15 years (9-19). The mean P1, P2, P3, P4, and Pc (range) were 43, 60, 23, 20, and 14mmHg, respectively. The atrophy rate was 66.3% and the viability was 88.9%. No major complications were observed. The modified tunica vaginalis flap in acute testicular torsion decreased intratesticular pressure. Furthermore, normal testicular pressure can improve testicular preservation. It can also decrease testicular pressure to normal levels and preserve the testicular parenchyma. Testicular torsion causes orchiectomy in more than 80% of the cases after 24 hours of pain onset.Testicular detorsion only (P1-P2) showed a small difference in intratesticular pressure (median 4mmHg).Testicular incision (P2-P3) only demonstrated a major pressure decrease .The final pressure after TVR was similar to the non-twisted testicle pressure .Testicular salvage (88.9%) and atrophy (66.3%) rates were slightly higher than the previous literature reports, perhaps the initial learning curve of this novel technique. Time and degree of torsion are the main predictors of testicular death. Scrotal exploration is recommended within 4-6 hours of pain onset to maximize the testicular salvage rate. After 24 hours, the testicular death rate is >90%.Testicular torsion is an emergency situation, and the time to treatment affects the testicular salvage rate in the first 24 hours after pain onset. It occurs in one in every 4,000 men within 25 years.Compartment syndromes associated with testicular torsion have been debated over the past few decades. Its exact mechanism of action remains unclear. However, torsion causes an abrupt reduction of the venous blood efflux from the testis leading to intratesticular swelling and damage to the parenchyma and micro-circulation. These harmful substances have deleterious effects on the structure and function of cells. Under physiological conditions, antioxidative enzymes can modulate the synthesis of ROS to protect organs and cells against oxidative stress. In ischemic injury, an imbalance between the antioxidant system and produced ROS reduces the activity and content of antioxidative enzymes, thereby increasing the levels of ROS.,8Regarding oxidative stress, leucocytes contribute to the production of reactive oxygen species (ROS).During surgical exploration, the testis is considered unsalvable if the ischemic or necrotic aspects do not improve after detorsion and heating. In these cases, orchiectomy and contralateral orchiopexy are the standard treatments.To validate the tunica vaginalis flap (TVF) technique in humans and prove compartment syndrome in testicular torsion, Kutikov et al. reported the TVF.To evaluate the safety, feasibility, and intratesticular pressure effect of the tunica vaginalis flap modification technique and to report our preliminary outcomes.After counseling and consent, patients with suspected unilateral testicular torsion within 24 hours were included in this study. The underage patients’ parents or legal guardians were counseled and they agreed. The exclusion criteria were bilateral torsion, previous torsion, contralateral atrophy, and complete restoration of testicular morphology after detorsion.Centro Universitário FMABC .This was a prospective, single-arm, unicentric clinical trial. The study was approved by the ethics committee of All IPMs were performed concurrently under anesthesia. No longer than 10 seconds was required per measurement. An electronic vital sign monitor from the operating room was adapted to measure ITP since there is no authorized device for proper use in Brazil. The same invasive technique was used to measure arterial pressure. A venous punction 20-G catheter was used to puncture the testes after injection of 0.3mL of saline solution. Standard arterial pressure tubing was placed and connected to a puncture catheter. The mean pressure (mmHg) was recorded. Intratesticular pressure measurement were recorded at four moments: before and after detorsion, after albuginea incision, and after TVF. Non-twisted testicle was punctured at the same location as the fixation stitch . . Testis detorsion and heat were applied. A contralateral orchiopexy was performed. The second IPM was recorded (P2). Wide transverse incision (WTI) was performed. This step was a modification of the original description by Kutikov et al.  to prese  and 2C.  . The detTo decrease the ITP and promote wide flap coverage, the vascular pedicle must be preserved from the vaginal flap . The ratAll patients were discharged with a standard orientation. Scrotal suspension was recommended for 14 days. First-generation cephalosporins were prescribed for 7 days postoperatively. If any sign of wound infection was observed, the medication was postponed or changed to quinolone for additional 7 days.Intrahospital, 7 days post hospital discharge, and 2 and 6 months postoperative complications were recorded during routine medical presentation. Doppler ultrasonography and flowmetry were performed 2 months postoperatively. Atrophy was measured using a physical examination (orchidometer) and an ultrasound report.The primary outcome was the effect of TVF on testicular pressure.-11 this outcome was dichotomized into any atrophy or none. Viability was defined as a normal testicular blood flow on Doppler ultrasonography.The secondary outcomes were the safety, feasibility, and reproducibility of the modified TVF technique. To define testicular atrophy and salvage rates, atrophy was considered if the affected testicle contained <50% of the volume of the non-twisted testicle. Following previous reports,Fifteen consecutive patients were recruited from September 2020 to October 2021. Three patients were excluded from the surgical procedure because of complete morphological recovery of the testicle, and bilateral orchidopexy was performed. Two patients who had no testicular torsion were excluded from the study. Eleven patients were eligible for the TVF therapy. Nine patients completed the 6 months follow up and were considered for statistical analysis. The median age (range) was 15 years (9-19). The right side was affected in 70% of the patients. The mean degree of torsion (range) was 180 (180-360).The mean P1, P2, P3, P4, and Pc were 43, 60, 23, 20, and 14mmHg (range), respectively. The surgical pressure step differences are presented in No major complications were observed. No testicular abscesses, hematomas, or wound infections were observed. Only one case of wound dehiscence that resolved after 2 months was reported.Prolonged or even short ischemia causes tissue damage and necrosis, which can produce high levels of oxidative stress in the testes, especially during the reperfusion period. Testicular torsion/detorsion increases lipid peroxidation and decreases antioxidant enzyme levels. Increased levels of peroxidase enzyme injury after testicular reperfusion can induce molecular damage to the DNA.To validate the TVF technique in humans and prove the compartment syndrome in testicular torsion, Kutikov et al. reported TVF in three cases. All treated 4-7 hours after the onset of pain. Testes without aspect improvement after detorsion and heating and those with active parenchymal bleeding after a wide anterior longitudinal albuginea incision were candidates for TVF. Intratesticular pressure was measured in only one patient and decreased from 34mmHg before detorsion to 5mmhg after TVF correction. Atrophy was reported in one case and Doppler flowmetry was positive in two cases. advocates a wide longitudinal incision on the anti-epididymal side. However, considering that the albuginea vessels run transversally, our technique was modified to make a wide transverse incision in the avascular equatorial area of the testis to preserve the albuginea vessels.The initial technique, described in 2018In this series, all cases experienced a decrease in ITP before and after TVF. To investigate the impact of the detorsion maneuver only (P1-P2), we measured the pressure before (P1) and after detorsion and heating (P2). Most patients exhibited a slight decrease in ITP, with a median value of 4mmHg. Interestingly, detorsion did not lower the ITP in many cases. A major decrease occurred after the albuginea incision (P2-P3) with a median value of 45mmHg. The most important outcome was approximately the same pressure after TVF and the contralateral testicle, with a median range of 1mmHg. Based on our results, we concluded that TVF may achieve normal testicular pressure, which may improve testicular reperfusion. The puncture of non-twisted testicles appears to be safe. Once the Pc puncture point was planned to be in the same place as the fixation stitch, no minor or major complications regarding twisted or non-twisted organs were recorded in this study. In 2018, Chu et al. performed a retrospective analysis; the results were similar to those reported by Figueroa et al. The study showed testicular salvage and atrophy rates <24 hours and >24 hours from pain onset of 95% TVF and 67% versus 67% TVF and 83%, respectively. Both authors reported no major complications.In 2012, Figueroa et al. reported a retrospective analysis, where the TVF was compared between orchidopexy and orchiectomy groups. They applied TVF in selected cases within 96 hours of pain onset. The ITP was not assessed in this study. The testicular salvage rate in the TVF group was 54.6% (p=0.19), being successful within a median of 31.2 hours of pain onset. This report revealed a longer treatment time with preservation of nearly 50% of the testicular candidates for orchiectomy. They included the retail technique reported by Figueroa et al. which showed the highest atrophy rate. Despite the lack of well-designed studies with longer and proper follow-up periods, there is an apparent overall lower atrophy rate. There is no strong evidence for testicular viability in the literature.However, a recent meta-analysis of orchidopexy techniques demonstrated an ipsilateral atrophy rate in only three studies, ranging from 9.1% to 47.5%.versus 5 versus 9 hours groups. The best recovery was observed in the 9 hours group.A clinical trial using TVF in a rat model demonstrated a reduction in ROS levels. Oxidative stress was assessed using malondialdehyde levels in the 1 In this clinical trial, prospective evaluation revealed a high atrophy rate of 66.6%, with a similar testicular salvage rate of 88.9%. Despite documented decompression, this high rate may be associated with the initial learning curve and lack of initial standardization of pressure measurement and surgical technique. This pilot project standardized TVF in a university hospital.Initially, our university hospital had only one experienced surgeon with expertise in this approach. The first cases were documented for educational purposes by all the department surgeons. This initial learning curve might have affected our outcomes negatively. Second, owing to the lack of approved medical tools to properly measure the ITP, we adapted a surgical monitor and an invasive pressure tool. Similar to the initial surgical learning curve, pressure measurements might have affected the initial pressure outcomes. Therefore, to minimize this bias, the differences between the pressures of each patient were used. It is not possible to define normal human testicular pressure using this measurement tool. Third, only a few patients were included in the statistical analysis. Regarding the public health system of our city and interhospital transportation needs, few patients reached a urologist within 24 hours of pain onset.versus orchiopexy alone may elucidate the real benefit of this technique in orchiectomy candidates.To address these initial difficulties, we aim to conduct a multicenter randomized controlled trial in the near future. Perhaps a prospective randomized trial comparing the flap group The modified tunica vaginalis flap seems to decrease intratesticular pressure in acute testicular torsion. Normal testicular pressure can be used to improve testicular preservation. It can decrease testicular pressure to normal levels and preserve the testicular parenchyma. Further studies are required to validate these results.


Overlapping eligibility to different biologics for severe asthma is still challenging, especially when addressing the same target. We aimed to characterize severe eosinophilic asthma patients according to their maintained or reduced response to mepolizumab over time and to explore baseline variables significantly associated with the occurrence of switching to benralizumab. We performed a multicentre retrospective observational study evaluating OCS reduction, exacerbation rate, lung function, exhaled nitric oxide levels (FeNO), Asthma control test (ACT), and blood eosinophil concentrations at baseline and before and after switching occurrence among 43 female and 25 male patients with severe asthma aged 23 to 84 years. Younger age, higher OCS daily dose and lower blood eosinophils at baseline were associated with a significantly higher risk (odds) for switching occurrence. All the patients showed an optimal response to mepolizumab, up to six months. The need for switching, according to the above-mentioned criterion, occurred for 30 out of 68 patients after a median time of 21 months (Q1–Q3: 12–24) from mepolizumab initiation. At the follow-up time-point after the switch , all the outcomes substantially improved and no cases of poor clinical response to benralizumab were detected. Although the small sample size and the retrospective design represent major limitations, to our knowledge, our study provides the first real-word focus on clinical variables potentially predicting a better response to anti IL-5r in patients fully eligible for both mepolizumab and benralizumab and suggests that in late non responder patients to mepolizumab, more robustly targeting the IL-5 axis may be effective. Overlapping eligibility to different biologics for severe asthma is still challenging, especially when addressing the same target. Such is the case of mepolizumab and benralizumab, targeting IL5 and IL5 receptor, respectively . MepolizIn fact, the prescription requirements established by the regulatory agencies are extremely similar, not supporting the identification of the best responder to each drug ,3. AvailWe aimed to characterize severe asthma patients according to their maintained or reduced response to mepolizumab over time and to explore baseline variables significantly associated with the occurrence of switching to benralizumab.n = 68). Severe asthma diagnosis was established according to the ERS/ATS guidelines [We performed a retrospective observational study involving five Referral Centres for severe asthma across Italy . All consenting patients affected by severe eosinophilic asthma and prescribed with mepolizumab during the period January–December 2015 were enrolled  with 95% CI. Associations were also estimated after adjustment for OCS dose at baseline as a proxy indicator of disease severity.Changes over time of lung function, exhaled nitric oxide levels (FeNO), Asthma control test (ACT) and blood eosinophil concentrations were also assessed. This secondary analysis was restricted to the subsample of patients with available information, which were 38 and 15 in the non-switch and the switch group, respectively. The 15 patients excluded were not lost to follow up, but the full set of clinical data could not be provided by all the collaborating centres for the time-points after month 6. Baseline and six months follow-up data for both subgroups were analysed. Two further time-points were considered for patients subsequently addressed to switching: the benralizumab-related baseline and the last available follow-up visit. Comparisons of outcomes between time-points were conducted using the Wilcoxon matched-pairs signed-rank test (with the 6-month visit as reference). Missing data were deleted listwise. Statistical analyses were done using STATA release 17.0 .We included 43 female and 25 male patients with severe asthma aged 23 to 84 years. p = 0.054), blood eosinophils , and OCS dose  (n. of subjects in the model = 57).Younger age, higher OCS daily dose and lower blood eosinophils at baseline were associated with a significantly higher risk (odds) for switching in univariate analysis. The results were very similar when adjusting for OCS dose at baseline , a proxyp < 0.001) and the switch subgroups . A significant reduction was also observed in the exacerbation rate in both the non-switch  and the switch subgroups .All the patients showed an optimal response to mepolizumab according to all the evaluated clinical variables , up to sThe need for switching, according to the above-mentioned criterion, occurred for 30 patients after a median time of 21 months (Q1–Q3: 12–24) from mepolizumab initiation. At the time of switching, a significant worsening of most the outcomes was detected in comparison to the 6 months assessment . At the Little real-life evidence focused on the clinical profile of responders to benralizumab after ineffective mepolizumab treatment. A large study described benralizumab efficacy in patients not responding to mepolizumab or reslizumab, without any subgroup-focused analysis, thus not excluding the potential confounding effect related to the weight-adjusted reslizumab dose . In anotThe proportion of late non-responders to mepolizumab we have described in our report seems not to be in line with other studies on the long-term efficacy of the same drug ,9. COLUMREALITI-A is a prospective single arm observational cohort study aiming to collect real-world data on asthma patients undergoing mepolizumab treatment. The initial analysis  on 368 sIn fact, in our study, the timing of poor response onset suggests that in a subset of patients initially well controlled by mepolizumab a change in the immunological background occurred. According to the low levels of blood eosinophils even at the switch time-point the development of anti-drug antibodies is unlikely. The known heterogeneity of inflammatory phenotype, which is intra-individually dynamic over time in asthma patients, may account for the “late non-response” . Under tWhat mentioned above may account for the different clinical response following the inhibition of IL-5 or the interaction with all the cells expressing its receptor, besides eosinophils, and substantially contributing to the T2 high inflammation.On clinical grounds, a higher OCS use has been described by Bleecker et al. as a predictor of better clinical response to benralizumab, independently of baseline blood eosinophilia, in the pooled-data analysis from the SIROCCO and CALIMA benralizumab trials . OCS useThe small sample size and the retrospective design represent major limitations. Further studies with larger sample sizes and prospective design are needed to confirm our findings and to reinforce their external validity and applicability to other populations.However, to our knowledge, our study provides the first real-word focus on clinical variables potentially predicting a better response to anti IL-5r in patients fully eligible for both mepolizumab and benralizumab.Taken together, our data suggest that in patients eligible to monoclonal antibodies interfering with Il-5 driven cascade, younger age, higher OCS daily dose and lower blood eosinophils at baseline were associated with a significantly higher risk for switching from mepolizumab to benralizumab, somehow predicting a better response to anti IL-5r. Furthermore, according to our observations, in late non-responder patients to mepolizumab, more robustly targeting the IL-5 axis may be effective.Overlapping eligibility and monoclonal antibody switching deserves larger investigations, also by exploring data from the national and international severe asthma registries, and consensus recommendations due to its major clinical and pharmaco-economical relevance.


Wearable cuffless photoplethysmographic blood pressure monitors have garnered widespread attention in recent years; however, the long-term performance values of these devices are questionable. Most cuffless blood pressure monitors require initial baseline calibration and regular recalibrations with a cuffed blood pressure monitor to ensure accurate blood pressure estimation, and their estimation accuracy may vary over time if left uncalibrated. Therefore, this study assessed the accuracy and long-term performance of an upper-arm, cuffless photoplethysmographic blood pressure monitor according to the ISO 81060-2 standard. This device was based on a nonlinear machine-learning model architecture with a fine-tuning optimized method. The blood pressure measurement protocol followed a validation procedure according to the standard, with an additional four weekly blood pressure measurements over a 1-month period, to assess the long-term performance values of the upper-arm, cuffless photoplethysmographic blood pressure monitor. The results showed that the photoplethysmographic signals obtained from the upper arm had better qualities when compared with those measured from the wrist. When compared with the cuffed blood pressure monitor, the means ± standard deviations of the difference in BP at week 1 (baseline) were −1.36 ± 7.24 and −2.11 ± 5.71 mmHg for systolic and diastolic blood pressure, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg and met the second criterion of a systolic blood pressure ≤ 6.89 mmHg and a diastolic blood pressure ≤ 6.84 mmHg. The differences in the uncalibrated blood pressure values between the test and reference blood pressure monitors measured from week 2 to week 5 remained stable and met both criteria 1 and 2 of the ISO 81060-2 standard. The upper-arm, cuffless photoplethysmographic blood pressure monitor in this study generated high-quality photoplethysmographic signals with satisfactory accuracy at both initial calibration and 1-month follow-ups. This device could be a convenient and practical tool to continuously measure blood pressure over long periods of time. Hypertension is a major risk factor for various cardiovascular diseases ,2,3. It Advances in mobile technology have resulted in the widespread use of health-related wearables and smartphone apps. Wearable cuffless BPMs, such as the Aktiia bracelet, Samsung Galaxy Watch, and Biobeat chest/wrist monitor, as well as smartphone-based BP-measuring apps such as the Riva digital app, AlwaysBP, and Opti BP, have gained popularity in recent years ,14,15,16The cuffless PPG-type BPM estimates BP by measuring the finger, wrist, and upper arm. Finger PPG signals are more reliable estimators of changes in BP and are therefore better suited for continuous monitoring because they are less affected by movement and positioning than wrist or arm PPG signals. In addition, finger PPG signals may be more accurate in certain populations, such as elderly people or those with peripheral artery disease because the finger arteries may be more responsive to changes in BP . HoweverThe exponential Gaussian process regression (expGPR) has proven to be the most suitable machine-learning (ML) model for PPG physiological data . The uppA BPM must be regularly and clinically validated according to a standard protocol before it can be used for diagnostics . AlthougThe purpose of this study was to validate the accuracy of a newly developed upper-arm, cuffless PPG BPM according to the Association for the Advancement of Medical Instrumentation (AAMI)/European Society of Hypertension (ESH)/International Organization for Standardization (ISO) 81060-2 universal standard . In addiThe institutional review board (IRB) of Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation (IRB No. IRB111-206-B), approved the study. Informed consent was obtained from all participants, to whom the study protocol was fully explained. In total, 34 participants (aged 20 years and above) were recruited, and 30 of the 34 eligible participants were divided into predefined BP ranges on the basis of their reference BP . The refWe designed a wearable device as a cuffless BPM, called the WatchBP O3 wearable , which could be worn on the upper arm and measure BP; its performance was evaluated during a 5-week BP calibration period. The WatchBP O3 wearable used a low-power embedded architecture with an ARM Cortex-M4 microcontroller  as its computing core. The processor had a maximum operating frequency of 64 MHz with 512 KB cache memory and 64 KB random access memory, and it supported the Bluetooth low-energy (BLE) communication protocol. The top of the device included a power switch button and a light-emitting diode (LED) operation indicator light A.On the other side closest to the skin (the bottom of the device), there were three green light-emitting diode (LED) elements  and a photodiode (PD) phototransistor . The optical sensing module under this configuration was arranged in a T shape B. The PDIn this study, the reflected PPG signal was acquired from PD, receiving the green LED light reflected from the blood and tissue and detecting the difference in the intensity of the reflected light absorbed by the blood and tissue, which could be used to estimate BP on the basis of a machine-learning algorithm. The periodic fluctuation of PPG amplitude reflected the changes in blood volume of cutaneous microvascular bed during heart-beating cycle. The PPG signal consisted of (1) a DC signal that detected optical signal reflected by tissues, bones, and muscles, as well as the average blood volume in arteries and veins, and (2) an AC signal indicating the change in blood volume between the systolic and diastolic periods of the heart-beating cycle. A PPG signal that reflects the characteristics of blood flow was obtained by extracting the AC signal. The cuffless BPM is positioned on the inner arm, near the brachial pulse, approximately 2 cm medial from the biceps tendon in the antecubital fossa and 2–3 cm above it A 36] Th Th36] ThOur team previously pretrained the expGPR model using a BP database of PPG signals measured at the wrist . HoweverThere were very little or no public data available on upper-arm PPG signals, and the BP waveform characteristics of upper-arm PPG signals were highly correlated with those of wrist PPG signals. Therefore, we directly extracted 10 PPG waveform characteristics per 15-s interval from the previous study, which included the following: waveform parameters and time-related parameters such as the systolic area over total area, diastolic area over total area, systolic area over pulse amplitude, diastolic area over pulse amplitude, maximal amplitude over time as maximal slope, systolic time, diastolic time, and mean peak-to-peak interval. The pretrained model parameters were used as the initial parameter values for the pretrained model. We then re-trained the model using the new upper-arm PPG database collected in this study, where we adjusted the kernel parameters to optimize the pretrained model. The kernel adjustment parameters were the kernel scale and the signal standard deviation. We first fixed the initial values of these two parameters to the values calculated when only wrist PPG signals were added to the training data. The calculation method is as follows:μ represents the mean value of predictor data, as in Equation (3):The kernel scale is defined as that through which the software searched among real values in the range Through this formula, we fixed the kernel scale and the signal standard deviation of the pretrained model to 11.9 and 9.6, respectively. This reduced the size of the training data feature matrix from 54.2 KB , to calibrate BP measurements and improve their accuracy. The calibration mode required the WatchBP O3 wearable, WatchBP O3, and smartphone to be placed within the range of BLE transmission. The calibration mode of the WatchBP O3 and WatchBP O3 wearable was activated through the BP App, and BP was measured using the WatchBP O3. After the measurement was complete, the data were automatically transmitted to the WatchBP O3 wearable to calibrate the model. Such autocalibration could reduce the likelihood of manually inputting incorrect data and hence increase the precision of subsequent BP estimations. The BP App was a cuffless BPM based on mobile health  applications and a specific wearable device to prevent and manage chronic diseases. The BP App display provided the following information: SBP and DBP, pulse rate, posture, date, and battery status. The BP App had two modes: default and calibration. The former reported a single BP measurement, whereas the latter indicated a BP value used for device calibration . It was The study consisted of two parts: the main analysis validated the accuracy and assessed long-term performances of the upper-arm, cuffless PPG BPM, whereas the secondary analysis evaluated the qualities of PPG signals obtained from the upper-arm and wrist-type PPG BPMs.First, the study protocol followed the ISO 81060-2 standard, with an additional four BP measurements, over a 1-month period to assess the long-term performance values of the cuffless BPM  . Three wThe reference measurement for this study was recorded using the WatchBP O3 sphygmomanometer with a digital screen and the cuffs provided by the device. The reference sphygmomanometer was calibrated by using the same WatchBP O3 prior to the study. BP was measured in this study by using the same-arm sequential method, according to the AAMI/ESH/ISO 81060-2 protocol . The meaTo compare the quality of the PPG signals obtained from the upper-arm and wrist-type BPMs, the BP values of all 30 participants at week 1 were measured by using the upper-arm, cuffless PPG BPM and the wrist-type PPG BPM [Fair—systolic and diastolic peaks cannot be easily distinguished from noise.Good—the systolic peak is clearly detectable, but the diastolic peak is not.Excellent—systolic and diastolic peaks are both clearly detectable.To assess PPG signal quality, 120 PPG pulses measured by both upper-arm and wrist-type BPMs from each subject were randomly selected and assigned to one of the three quality levels by three raters, defined as follows :Fair—syst-test was used to compare the differences in the PPG signals obtained from the upper-arm and wrist-type device in each of the three quality levels. All analyses were performed using SPSS 20.0 .A paired For primary analysis, each of the three BP readings  taken from the upper-arm, cuffless PPG BPM was compared with those taken from the reference BP , generating 90 pairs of measurements per week.Two international guidelines, the ISO 81060-2 standard and the British Hypertension Society (BHS) guideline, were used to evaluate the accuracy and long-term performance values of the upper-arm, cuffless PPG BPM. The mean and standard deviation (SD) of the difference between the readings from the test and reference device were calculated to determine whether the results met the passing criteria of the ISO 81060-2 standard:(1) Criterion 1—the mean ± SD of the SBP and DBP ≤5 ± ≤8.0 mmHg.(2) Criterion 2—the SD ≤6.89 mmHg and ≤6.84 mmHg, respectively, for SBP and DBP .The standard accuracy criteria of the BHS were defined as follows for the cumulative percentage in 5, 10, and 15 mmHg, with four grades: Grade A , Grade B , Grade C , and Grade D (worse than Grade C). A Pearson correlation analysis and a Bland–Altman analysis were used to assess agreement between the test and reference devices. In addition, the BP values of subjects with Fitzpatrick skin type II and type III were compared by using the Wilcoxon rank sum test to further examine the impact of skin phototype on BP measurements.In total, 34 subjects were recruited for this study. Four subjects were excluded from the analysis, of whom one had a history of atrial fibrillation, and the other three failed to complete the follow-up sessions. This resulted in 30 subjects  and 90 pairs of valid BP readings per week. The average upper-arm circumference was 27.2 ± 2.8 cm, with a range of 22.0–31.0 cm, covering the full range of the standard M–L cuffs used. The participants’ demographics are shown in The characteristics of the PPG signals and their quality levels measured by the upper-arm and wrist-type BPMs from the same subject are shown in p = 0.029, * p < 0.05). Those categorized as good were not significantly different (p = 0.2).r = 0.802 and 0.822, respectively; both *** p < 0.001)  were −1.36 ± 7.24 and −2.11 ± 5.71 mmHg for SBP and DBP, respectively, which met the first criterion of ≤5 ± ≤8.0 mmHg . The mea< 0.001) .In this study, the accuracy and precision of an upper-arm-designed, cuffless PPG BPM based on a nonlinear expGPR ML model architecture with a fine-tuning optimized method was evaluated by comparing its performance values to those of a reference cuffed BP device. The PPG signals obtained from the upper-arm, cuffless PPG BPM showed distinguishable systolic and diastolic peaks. The differences between the SBPs and the DBPs measured by the upper-arm, cuffless PPG BPM and the reference BPM at baseline and weekly follow-ups over 1 month satisfied the first criterion of ≤5 ± ≤8.0 mmHg and the second criterion of SBP ≤ 6.89 mmHg and DBP ≤ 6.84 mmHg described by the ISO 81060-2 standard .Hypertension is a chronic condition that requires the proper management of BP. Many cuffless BPs have been recently developed for consumer use ,34,35,41Cuffless BPMs offer detailed insights into BP management to both patients and healthcare providers. Users can easily store their BP data and provide the data to their healthcare providers for informed treatment plans. Using cuffless BPMs to self-monitor BP may also promote healthy lifestyle changes such as daily BP measurements to control hypertension . HoweverGiven these limitations, ISO is creating a new standard specific to cuffless BPMs ,53. ReseIn this study, the differences between the uncalibrated BP values obtained from the upper-arm, cuffless PPG BPM and those obtained from the cuffed BPM from 4 weeks of follow-ups all satisfied both criteria of the ISO 81060-2 standard . These rIn this study, we designed a new device, an upper-arm, cuffless PPG BPM, called the WatchBP O3 wearable, to measure BP. The proposed prediction model was based on a nonlinear expGPR ML model with a fine-tuning optimization method, which enhanced model training and reduced the size of the model. A fully automated calibration system from the same manufacturer was also integrated to increase the precision of the calibration model and user convenience. The upper-arm, cuffless PPG BPM used in this study measured BP from the upper arm, a body part that was less affected by motion artifacts than the wrist, and more comfortable compared with wearing a device on the fingers. Additionally, compared with the PPG signals obtained from the wrist, the PPG waveforms obtained from the upper arm showed higher-quality, distinguishable systolic and diastolic peaks such as those measured by standard invasive BPMs. The accuracy and the precision of an upper-arm, cuffless PPG BPM were evaluated by comparing its performance with that of a reference cuffed BPM according to the ISO 81060-2 standard. The initial calibrated BP and the follow-up uncalibrated BP measured weekly over a 1-month period by the upper-arm, cuffless PPG BPM met the requirement criteria specified by the ISO 81060-2 standard, which required a BP ≤ 5 ± ≤ 8.0 mmHg as well as an SBP ≤ 6.89 mmHg and a DBP ≤ 6.84 mmHg. Most PPG BPMs require an initial calibration using a traditional cuffed BPM that inconveniently must be regularly recalibrated to ensure accuracy. Therefore, we assessed changes in uncalibrated BP values of our PPG BPM over different time periods, which could help manufacturers determine proper calibration intervals. Overall, the cuffless PPG BPM with the upper-arm design evaluated here provided high-quality PPG signals and an efficient prediction model within an embedded system; its satisfactory accuracy and its precision over a 1-month period render it a convenient and practical alternative for long-term BP monitoring.There were limitations to this study. First, the number of subjects recruited in this study did not meet the requirements of the standard (ISO 81060-2), so it should not be considered a clinical validation study for the cuffless BPM. Another limitation was that the skin tone of the subjects was in the lighter skin range (Fitzpatrick types II and III), and thus, caution should be exercised when generalizing the current results to a population with darker skin tones. Lastly, the population in the current study was generally healthy. Further studies should be conducted on a variety of patient populations to test the clinical feasibility of the upper-arm cuffless PPG BPM.


No official clinical reference values have been established for MostGraph, which measures total respiratory resistance and reactance using the forced oscillation technique, complicating result interpretation. This study aimed to establish a reference range for MostGraph measurements and examine its usefulness in discriminating participants with asthma from controls (participants without any respiratory diseases). The study also aimed to investigate the effectiveness of deep learning in discriminating between the two aforementioned groups. To establish reference ranges, the MostGraph measurements of healthy controls (n = 215) were power-transformed to distribute the data more normally. After inverse transformation, the mean ± standard deviation × 2 of the transformed values were used to establish the reference ranges. The number of measured items outside the reference ranges was evaluated to discriminate patients with asthma (n = 941) from controls. Additionally, MostGraph measurements were evaluated using deep learning. Although reference ranges were established, patients with asthma could not be discriminated from controls. However, with deep learning, we could discriminate between the two groups with 78% accuracy. Therefore, deep learning, which considers multiple measurements as a whole, was more effective in interpreting MostGraph measurement results than use of reference ranges, which considers each result individually. As it does not require breathing effort, it may be applicable for patients who cannot follow instructions or patients with low lung function. FOT can measure different indices to those of spirometry and is thus expected to have new applications in respiratory diseases. An increasing number of reports of the usefulness of FOT in the evaluation and management of obstructive pulmonary diseases are being published5. MostGraph, the FOT device in accordance with the “Oscillometry Technical Standards”1, was developed in Japan. However, official reference ranges for MostGraph measurement results have not been established. One study in which an attempt was made to determine the MostGraph parameter reference values6 had a few limitations, such as that the age of the enrolled participants was > 46 years and participants with pulmonary diseases were not excluded. Thus, more than 14% of the study participants showed abnormal spirometry6. Furthermore, participants with abnormal chest radiographs were likely included. Consequently, standardized reference values still need to be determined.Forced oscillation technique (FOT) is a non-invasive method for measurement of respiratory resistance and reactance at various frequencies (commonly 4–50 Hz)In the present study, we first aimed to establish reference ranges for MostGraph measurements in healthy Japanese adults and to examine whether the established reference ranges are useful in differentiating between healthy controls and patients with asthma. Second, we aimed to investigate whether deep learning can discriminate between healthy controls and patients with asthma. Third, to support researchers conducting similar research, the Python programs used to define and train deep learning models, as well as simple HTML, CSS, and JavaScript programs on the web, will be made available to contribute to the medical field.7. Although some patients with asthma have normal lung function, they may also exhibit abnormal FOT findings owing to airway remodeling, a structural change in the lungs8. For an objective diagnosis of asthma, either variable expiratory airflow limitation or airway hyperresponsiveness needs to be demonstrated7. Methods for demonstrating variable expiratory airflow limitations include the following: (i) a positive bronchodilator responsiveness (reversibility) test (the patient should have expiratory airflow limitation at the time of presentation); (ii) excessive variation in lung function between visits ; and (iii) excessive variability in peak flow 7. Airway hyper-responsiveness tests are rarely performed in Japan because they require an hour-long test with a doctor in attendance. Some asthma patients show increased Fractional exhaled Nitric Oxide (FeNO) levels; however, some people with allergic predispositions also show increased FeNO levels, even if they do not have asthma. CVA is a type of asthma in which the only symptom is cough, and it is especially difficult to diagnose objectively. Other respiratory diseases usually show abnormal chest radiography, spirometry, hematologic, or sputum findings, leading to a diagnosis. Physicians usually make a comprehensive CVA diagnosis and provide diagnostic treatment to alleviate the patient's suffering as soon as possible. As a non-specialist respiratory physician cannot always make an immediate CVA diagnosis in an outpatient setting, MostGraph measurements may be beneficial. We hypothesized that an increase in the odds ratio for the diagnosis of asthma/CVA using MostGraph measurements would be clinically beneficial.We chose patients with asthma and cough variant asthma (CVA) as the patient group with respiratory diseases, because asthma is sometimes difficult to diagnose objectively in a clinical setting. Patients with asthma present with coughing, wheezing, or dyspnea often show expiratory airflow limitation on pulmonary function tests, which may vary in intensityDeep learning is a machine-learning method mimicking human neurons and neural networks. A neuron in the human brain receives signals from many other neurons via dendrites and dendritic branches and transmits to other neurons via axons. The artificial neuron receives signals from artificial neurons in the previous layer and transmits to artificial neurons in the next layer. Specifically, it is a mechanism in which the neuron output signals in the previous layer are weighted by applying coefficients, summing them, adding bias, and outputting them after passing through the activation function. Deep learning refers to multilayer neural networks, typically more than three layers. The loss is the difference between the final output from the deep learning network and the desired output, which is called the “ground truth” or “teaching data.” The learning process, called “backpropagation,” is repeated by changing the weighting coefficients and bias so that the error is close to zero. Theoretically, the multivariate analysis is equivalent to a one-layer neural network, except that its coefficients are calculated theoretically. Deep learning allows for more complex analysis by multiple layering. The performance and accuracy of deep learning was widely recognized at the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) and speech recognition challenges in 2012. Thereafter, deep learning started to be widely used. The advantage of deep learning lies in its future expandability; one can aim for better outputs by changing the network configuration. As only a small number of people appear to be educated in this field of study, we made the source code public for other researchers to use in their own fields.This study was approved by the Medical Research Institute of the Tokyo Medical and Dental University  and was conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all participants.Healthy participants over 16 years of age were recruited between September 2013 and May 2022 in the following three ways: (i) from among those attending a medical checkup at the Medical Check-up Center of Yokohama City Minato Red Cross Hospital. Healthy participants with normal chest radiographic findings in the previous annual medical checkup before the study entry were chosen. (ii) Healthy medical staff of the Medical Check-up Center of Yokohama City Minato Red Cross Hospital, with no respiratory diseases and normal chest radiographic findings during the annual medical checkup, were recruited. (iii) Healthy staff or students of Tokyo Medical and Dental University (TMDU), with no respiratory diseases and normal chest radiographic findings during the annual medical checkup, were additionally recruited.The following were included in the study: (i) current smokers, ex-smokers, non-smokers, and participants with allergic rhinitis, if they showed no respiratory abnormalities; (ii) participants with diseases not related to the respiratory system, such as hypertension, hyperlipidemia, gout, or diabetes mellitus; (iii) participants with a medical history of childhood asthma, if they did not have demonstrable symptoms and were not taking any medications.Healthy controls underwent FeNO, MostGraph, and spirometry measurements, in that order, to ensure that the previous measurements did not affect the subsequent ones. As FeNO is easily influenced by physical stimulation of airway epithelial cells during other testing modalities, it was performed first. Spirometry was performed last as participants were required to breathe deeply, which could cause bronchial constriction.10) or abnormal spirometry /predicted FVC of < 80% or forced expiratory volume in 1 s (FEV1)/FVC of < 70%) results were excluded. Participants with pulmonary complications and those who could not undergo a thorough examination were also excluded. MostGraph measurements were performed thrice in accordance with the “Oscillometry Technical Standards”1 using pulse wave pressure, which is the general measurement method. Participants were familiar with this measurement method because they had been measured previously using white noise pressure, thrice. The best result of three measurements stimulated by the pulse wave pressure was adopted for subsequent analysis. The measurement results are greatly affected by factors such as breathing volume, body position, and tongue position1. As the measurements were repeated, the participants tended to become less nervous and relaxed, leading to better results. Therefore, the best result was chosen.Those with elevated FeNO  × 2 were set for reference ranges of the transformed data. The inverse_transform13 method was used to obtain reference ranges for the measured values. Calculations and presentations were performed using the Python programs available at https://github.com/sumi-yuki/mostgraph/blob/main/YeoJohnson-male.py and https://github.com/sumi-yuki/mostgraph/blob/main/YeoJohnson-female.py.Males and females were analyzed separately. We obtained 24 MostGraph measurements for the average, inhaled, exhaled, and delta  values of R5 (resistance at 5 Hz), R20 (resistance at 20 Hz), R5-R20, X5 (reactance at 5 Hz), Fres (resonant frequency), and ALX (reactance area). A power transform was used to distribute the data more normally. We applied the Yeo–Johnson transformation17. They had had no previous treatments for asthma and underwent MostGraph measurement via pulse wave pressure. The following were included in the study: (i) current smokers, ex-smokers, and non-smokers; (ii) participants with diseases not related to the respiratory system, such as hypertension, hyperlipidemia, gout, and diabetes mellitus. The patients were excluded if they had severe diseases like cancer, comorbid lung diseases, or infectious diseases including common cold or bronchitis. All data were collected at the initial presentation, before treatments were administered.Patients with asthma/CVA more than 16 years old were recruited retrospectively, from September 2013 to June 2021, in the following three ways: (i) from amongst those visiting the Allergy Center of Yokohama City Minato Red Cross Hospital; (ii) from amongst those visiting the Ikebukuro Otani Clinic; and (iii) from amongst those visiting the Shibata Ekimae Hiratanaika Clinic. For the inclusion, they were the first visit patients who were given final diagnosis of asthma based on the Japanese guidelines for adult asthmahttps://github.com/sumi-yuki/mostgraph/blob/main/YeoJohnson-male-linearregression.py and https://github.com/sumi-yuki/mostgraph/blob/main/YeoJohnson-female-linearregression.py.Heat maps showing items outside the reference ranges for each participant were drawn for an overview. The number of measured items outside the reference range was used to distinguish between healthy controls and patients with asthma/CVA. Receiver operating characteristic (ROC) curves were drawn to determine cutoff values (the number outside the MostGraph reference ranges). Calculations and presentations were performed using Python, available at To distinguish between healthy controls and patients with asthma/CVA, we applied deep learning to the MostGraph measurement results. To evaluate the models, we applied an iterated k-fold validation with shuffling. Briefly, 10 controls and 10 patients were randomly selected as test data Fig. a. BecausMostGraph measurement reports consisted of the total, inhaled, exhaled, and delta values for R5, R20, R5-R20, X5, Fres, and ALX. The total value was the average of the inhaled and exhaled values, and the delta value was the difference between the inhaled and exhaled values. Considering multicollinearity, it should be possible to express with only 10 inhaled and exhaled data points for R5, R20, X5, Fres, and ALX. Therefore, we examined both the models. We also examined models in which age was added to the study items.https://github.com/sumi-yuki/mostgraph/blob/main/deeplearning-mostgraph.py.In addition, we compared three other models: male only, female only, and both male and female, adding sex as input data. The source code can be obtained from 11, and the following metrics were assessed: sensitivity, specificity, accuracy and F1 score at the cutoff point defined by the maximum Youden's index, and AUC (area under the ROC curve) .Written informed consent was obtained from all participants.Of the recruited participants in the healthy control group, 215  were ultimately included in our study (Table 12) was applied to make the data more normally distributed  were included in our study Table . The ageHeat maps of the MostGraph measurement results based on the reference range are shown in Fig. The diagnostic accuracies of the deep learning model are listed in Table https://sumi-yuki.github.io/mostgraph/index.html and https://plaza.umin.ac.jp/~pulm/mostgraph/index.html.Based on these results, we adopted a single model for both males and females and input only the measurement results calculated during exhalation and inhalation for each item. We have published the MostGraph measurement results classifier on Next, under identical conditions, we compared the diagnostic accuracy of diagnosis by deep learning and diagnosis based on the presence of one or more items outside the reference range Table . The resThe five-layer deep learning model had a lower loss than the single-layer neural network models .The inability to see how deep learning systems make their decisions is known as the black box problem. Unwanted results output by deep learning systems can be difficult to fix and can cause ethical problems. We do not think that black box pattern recognition is a disadvantage in this case. It can be compared to visual inspection of a patient. The results of the visual inspection are used simply for reference, just as the deep learning diagnosis in this case. When examining a patient, it is important to visually observe the patient and to assess their condition as good, bad, or in pain. A clinician can instinctively determine a patient's general condition from their facial expressions by recognizing overall patterns without considering any theoretical basis for such judgement. Examination of individual areas of the face, such as the eyes and mouth, provides important findings but that differ from information about general health conditions assessed via visual inspection. A patient's condition can also be inferred from the way they speak. In these cases, the overall pattern is evaluated rather than individual pitch, tempo, intonation, etc. We believe that an approach that recognizes the overall pattern without considering the theoretical basis for the meaning of individual measurements can add value.The main limitation of this study is that the numbers of healthy participants were relatively small. However, even if the number of participants increases, the reference ranges will likely not be narrowed, and the conclusion that the reference ranges are not clinically useful may not change.In conclusion, pattern recognition using deep learning is an effective method for evaluation of MostGraph measurement results.Supplementary Information.