Phenotype-specific therapeutic efficacy of ilofotase alfa in patients with sepsis-associated acute kidney injury

BACKGROUND

There is no effective treatment for sepsis-associated acute kidney injury (SA-AKI). Ilofotase alfa (human recombinant alkaline phosphatase) has been shown to exert reno-protective properties, although it remains unclear which patients might be most likely to benefit. We aimed to identify a clinical phenotype associated with ilofotase alfa's therapeutic efficacy.

METHODS

Data from 570 out of 650 patients enrolled in the REVIVAL trial were used in a stepwise machine learning approach. First, clinical variables with increasing or decreasing risk ratios for ilofotase alfa treatment across quartiles for the main secondary endpoint, Major Adverse Kidney Events up to day 90 (MAKE90), were selected. Second, linear regression analysis was used to determine the therapeutic effect size. Finally, the top-15 variables were used in different clustering analyses with consensus assessment.

RESULTS

The optimal clustering model comprised two phenotypes. Phenotype 1 displayed relatively lower disease severity scores, and less pronounced renal and pulmonary dysfunction. Phenotype 2 exhibited higher severity scores and creatinine, with lower eGFR and bicarbonate levels. Compared with placebo treatment, ilofotase alfa significantly reduced MAKE90 events for phenotype 2 patients (54% vs. 68%, p = 0.013), but not for phenotype 1 patients (49% vs. 46%, p = 0.54).

CONCLUSION

We identified a clinical phenotype comprising severely ill patients with underlying kidney disease who benefitted most from ilofotase alfa treatment. This yields insight into the therapeutic potential of this novel treatment in more homogeneous patient groups and could guide patient selection in future trials, showing promise for personalized medicine in SA-AKI and other complex conditions.

[Management of cardiomyopathies : New ESC guidelines 2023]

The group of cardiomyopathies has received increasing attention over the last few years after some of the causes were identified and they could be characterized more exactly using modern imaging methods. New definitions and classification schemes were regularly provided by national and international cardiac societies. The new guidelines of the European Society of Cardiology (ESC) from 2023 on the management of cardiomyopathies are the first guidelines that comprehensively address all cardiomyopathies in one document. As these are new guidelines most of the recommendations are also new. An exception is the section on hypertrophic cardiomyopathy (HCM), which provides a targeted update of the 2014 ESC guidelines on the diagnosis and treatment of HCM. The main aim of the guidelines is to provide clear guidance for the diagnosis of cardiomyopathies, to highlight general assessment and management problems and to point out the relevant scientific evidence for the recommendations to the readership. Due to the magnitude detailed descriptions and recommendations cannot be provided for each individual cardiomyopathy phenotype; however, reference is made to the relevant literature.

Latent Class Analysis Identifies Distinctive Behavioral Subtypes in Children with Fragile X Syndrome

Fragile X syndrome (FXS) is characterized by variable neurobehavioral abnormalities, which leads to difficulties in developing and evaluating treatments and in determining accurate prognosis. We employed a pediatric cross-sectional sample (1,072 males, 338 females) from FORWARD, a clinic-based natural history study, to identify behavioral subtypes by latent class analysis. Input included co-occurring behavioral conditions, sleep and sensory problems, autistic behavior scales (SCQ, SRS-2), and the Aberrant Behavior Checklist revised for FXS (ABCFX). A 5-class solution yielded the most clinically meaningful, pharmacotherapy independent behavioral groups with distinctive SCQ, SRS-2, and ABCFX profiles, and adequate non-overlap (≥ 71%): "Mild" (31%), "Moderate without Social Impairment" (32%), "Moderate with Social Impairment" (7%), "Moderate with Disruptive Behavior" (20%), and "Severe" (9%). Our findings support FXS subtyping, for improving clinical management and therapeutic development.

De Novo Dissecting the Three-Dimensional Facial Morphology of 2379 Han Chinese Individuals

Phenotypic diversity, especially that of facial morphology, has not been fully investigated in the Han Chinese, which is the largest ethnic group in the world. In this study, we systematically analyzed a total of 14,838 facial traits representing 15 categories with both a large-scale three-dimensional (3D) manual landmarking database and computer-aided facial segmented phenotyping in 2379 Han Chinese individuals. Our results illustrate that homogeneous and heterogeneous facial morphological traits exist among Han Chinese populations across the three geographical regions: Zhengzhou, Taizhou, and Nanning. We identified 1560 shared features from extracted phenotypes, which characterized well the basic facial morphology of the Han Chinese. In particular, heterogeneous phenotypes showing population structures corresponded to geographical subpopulations. The greatest facial variation among these geographical populations was the angle of glabella, left subalare, and right cheilion (p = 3.4 × 10-161). Interestingly, we found that Han Chinese populations could be classified into northern Han, central Han, and southern Han at the phenotypic level, and the facial morphological variation pattern of central Han Chinese was between the typical differentiation of northern and southern Han Chinese. This result was highly consistent with the results revealed by the genetic data. These findings provide new insights into the analysis of multidimensional phenotypes as well as a valuable resource for further facial phenotype-genotype association studies in Han Chinese and East Asian populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00109-x.

Exploring different models of pain phenotypes and their association with pain worsening in people with early knee osteoarthritis: The MOST cohort study

OBJECTIVE

To determine i) pain phenotypes (PP) in people with early-stage knee osteoarthritis (EKOA); ii) the longitudinal association between the phenotypes and pain worsening at two years.

DESIGN

We studied participants with EKOA from the Multicenter Osteoarthritis Study defined as pain intensity ≤3/10, Kellgren and Lawrence grade ≤2, intermittent pain none to sometimes, and no constant pain. Two models of PP were explored. Model A included pressure pain thresholds, temporal summation, conditioned pain modulation, pain catastrophizing, sleep quality, depression, and widespread pain (WSP). In Model B, gait characteristics, quadriceps strength, comorbidities, and magnetic resonance imaging features were added to Model A. Latent Class Analysis was used to create phenotypes, and logistic regression was used to determine their association with pain worsening.

RESULTS

750 individuals (60% females), mean age [standard deviation (SD)]: 60.3 (9.4) were included in Model A and 333 individuals (60% females), mean age (SD): 59.4 (8.1) in Model B. 3-class and 4-class solutions were chosen for Model A and Model B. In Model A, the most "severe" phenotype was dominated by psychosocial factors, WSP, and measures of nervous system sensitization. Similarly in Model B, the Model A phenotype plus gait variables, quadriceps strength, and comorbidities were dominant. Surprisingly, none of the phenotypes in either model had a significant relationship with pain worsening.

CONCLUSION

Phenotypes based upon various factors thought to be important for the pain experience were identified in those with EKOA but were not significantly related to pain worsening. These phenotypes require validation with clinically relevant endpoints.

Comorbid Inducible Urticaria Is Linked to Non-Autoimmune Chronic Spontaneous Urticaria: CURE Insights

BACKGROUND

Patients with chronic spontaneous urticaria (CSU) can have comorbid inducible urticaria (CIndU). How comorbid CIndU affects patients and their CSU is largely unclear.

OBJECTIVE

To compare patients with CSU with and without comorbid CIndUs for differences in demographic features, clinical characteristics, and laboratory markers.

METHODS

We analyzed 708 patients with CSU of our Urticaria Center of Reference and Excellence enrolled in CURE, the chronic urticaria registry. CURE data collected until October 2022 were used to compare patients with and without comorbid CIndU for their demographic characteristics, disease onset, activity, impact, and control, as well as concomitant allergic and autoimmune diseases and laboratory parameters associated with autoimmune CSU.

RESULTS

Of 708 patients with CSU, 247 (35%) had comorbid CIndU. Compared with patients with standalone CSU, patients with CSU with comorbid CIndU were significantly younger, had earlier disease onset, longer disease duration, higher impact on quality of life, and a higher rate of concomitant allergic diseases. Moreover, patients with CSU with comorbid CIndU less often had features linked to autoimmune CSU such as angioedema, concomitant autoimmune diseases, eosinopenia, low levels of total IgE, and low total IgE combined with elevated anti-thyroid peroxidase IgG.

CONCLUSIONS

Autoimmune CSU may be less common in patients with comorbid CIndU than without, and comorbid CIndU may point to autoallergic CSU.

Increasing Age at the Time of Diagnosis and Evolving Phenotypes of Eosinophilic Esophagitis Over 20 Years

BACKGROUND

The presentation of eosinophilic esophagitis (EoE) is heterogeneous, but trends over time are not known.

AIM

To determine whether clinical and endoscopic phenotypes at EoE diagnosis have changed over the past 2 decades.

METHODS

In this retrospective cohort study, adults and children with newly diagnosed EoE were phenotyped as follows: (1) inflammatory vs fibrostenotic vs mixed on endoscopy; (2) atopic vs non-atopic; (3) age at symptom onset; (4) age at diagnosis; (5) presence of autoimmune or connective tissue disease; and (6) responsive to steroids. The prevalence of different phenotypes was categorized by 5-year intervals. Multivariate analysis was performed to assess for changes in patient features over time.

RESULTS

Of 1187 EoE patients, age at diagnosis increased over time (from 22.0 years in 2002-2006 to 31.8 years in 2017-2021; p < 0.001) as did the frequency of dysphagia (67% to 92%; p < 0.001). Endoscopic phenotypes were increasingly mixed (26% vs 68%; p < 0.001) and an increasing proportion of patients had later onset of EoE. However, there were no significant trends for concomitant autoimmune/connective tissue disease or steroid responder phenotypes. On multivariate analysis, after accounting for age, dysphagia, and food impaction, the increase in the mixed endoscopic phenotype persisted (aOR 1.51 per each 5-year interval, 95% CI 1.31-1.73).

CONCLUSION

EoE phenotypes have changed over the past two decades, with increasing age at diagnosis and age at symptom onset. The mixed endoscopic phenotype also increased, even after controlling for age and symptomatology. Whether this reflects changes in provider recognition or disease pathophysiology is yet to be elucidated.

Integrating single-cell transcriptomics with cellular phenotypes: cell morphology, Ca2+ imaging and electrophysiology

I review recent technological advancements in coupling single-cell transcriptomics with cellular phenotypes including morphology, calcium signaling, and electrophysiology. Single-cell RNA sequencing (scRNAseq) has revolutionized cell type classifications by capturing the transcriptional diversity of cells. A new wave of methods to integrate scRNAseq and biophysical measurements is facilitating the linkage of transcriptomic data to cellular function, which provides physiological insight into cellular states. I briefly discuss critical factors of these phenotypical characterizations such as timescales, information content, and analytical tools. Dedicated sections focus on the integration with cell morphology, calcium imaging, and electrophysiology (patch-seq), emphasizing their complementary roles. I discuss their application in elucidating cellular states, refining cell type classifications, and uncovering functional differences in cell subtypes. To illustrate the practical applications and benefits of these methods, I highlight their use in tissues with excitable cell-types such as the brain, pancreatic islets, and the retina. The potential of combining functional phenotyping with spatial transcriptomics for a detailed mapping of cell phenotypes in situ is explored. Finally, I discuss open questions and future perspectives, emphasizing the need for a shift towards broader accessibility through increased throughput.

Incidence of Different Characters of Neuropathic Pain in Cancer Patients Coming to Tertiary Care Centre in North India Over A Period of 1 Year - An Observational Study

Objectives

Pain is classified as nociceptive, neuropathic, or nociplastic. Neuropathic pain presents as variable phenotypes (characters) based on specific aetiology and pathophysiology. This study aimed to find out among cancer patients the incidence of different phenotypes of neuropathic pain and form specific phenotypic clusters based on the underlying neurophysiology and association of sensory profile with various organ systems - A prospective observational study.

Materials and methods

The Institutional Ethical Committee clearance (IEC code: 2020-49-MD-EXP-15) https://ctri.nic.in/Clinicaltrials/showallp.php?mid1=44886&EncHid=88651.15716&userName=CTRI/2020/09/027964 approval was obtained. After written and informed consent, patients of age group 18-80 years, registering in the pain and palliative outpatient department or radiotherapy department with complaints of pain and not taking any anti-neuropathic pain medications, were enrolled. They were assessed using Leeds assessment of neuropathic symptoms and signs (LANSS) pain score, and a score of >12 was eligible for assessment of neuropathic pain phenotypes.

Results

Out of 210 cancer patients complaining of pain, a neuropathic component with LANSS >12 was found in 73 (34.76%). The most predominant phenotypes, allodynia> tingling> pricking = burning, were found in 72.60%, 56.16%, and 43.84% of patients, respectively. Phenotypes were clustered into Nodes 1 and 2 based on clinically significant separation of phenotypes. Node 1 had neuropathic pain of spontaneous origin found predominantly in gastrointestinal tract (GIT) and genitourinary tract (GUT) cancers. Node 2 had stimulus-evoked negative and positive characters which occurred in head and neck, thoracic, and spinal metastatic cancers.

Conclusion

Careful patient assessment reveals the incidence of neuropathic pain in 34.76%; allodynia and tingling astable the most prominent phenotypes. Broadly, sensory characters were clustered into spontaneous and stimulus-evoked sensations with GIT and GUT cancers presenting with Node 1 symptoms.

Phylogenetic Survival Analysis

Going back in time through a phylogenetic tree makes it possible to evaluate ancestral genomes and assess their potential to acquire key polymorphisms of interest over evolutionary time. Knowledge of this kind may allow for the emergence of key traits to be predicted and pre-empted from currently circulating strains in the future. Here, we present a novel genome-wide survival analysis and use the emergence of drug resistance in Mycobacterium tuberculosis as an example to demonstrate the potential and utility of the technique.

Obstructive sleep apnea diagnosis and beyond using portable monitors

Obstructive sleep apnea (OSA) is a chronic sleep and breathing disorder with significant health complications, including cardiovascular disease and neurocognitive impairments. To ensure timely treatment, there is a need for a portable, accurate and rapid method of diagnosing OSA. This review examines the use of various physiological signals used in the detection of respiratory events and evaluates their effectiveness in portable monitors (PM) relative to gold standard polysomnography. The primary objective is to explore the relationship between these physiological parameters and OSA, their application in calculating the apnea hypopnea index (AHI), the standard metric for OSA diagnosis, and the derivation of non-AHI metrics that offer additional diagnostic value. It is found that increasing the number of parameters in PMs does not necessarily improve OSA detection. Several factors can cause performance variations among different PMs, even if they extract similar signals. The review also highlights the potential of PMs to be used beyond OSA diagnosis. These devices possess parameters that can be utilized to obtain endotypic and other non-AHI metrics, enabling improved characterization of the disorder and personalized treatment strategies. Advancements in PM technology, coupled with thorough evaluation and validation of these devices, have the potential to revolutionize OSA diagnosis, personalized treatment, and ultimately improve health outcomes for patients with OSA. By identifying the key factors influencing performance and exploring the application of PMs beyond OSA diagnosis, this review aims to contribute to the ongoing development and utilization of portable, efficient, and effective diagnostic tools for OSA.

Chronic endometritis incidence in infertile women with and without polycystic ovary syndrome: a propensity score matched study

BACKGROUND

Polycystic ovary syndrome (PCOS) is known to be associated with chronic low-grade inflammation and endometrial dysfunction. Chronic endometritis (CE) is a type of local inflammation that can contribute to endometrial dysfunction in infertile women. Some clinicians recommend screening for CE in women at high risk, such as those with endometrial polyps. However, it is still uncertain whether there is a relationship between PCOS and CE, as well as whether women with PCOS require enhanced screening for CE. This study was to assess the incidence of CE among infertile women with PCOS by hysteroscopy combined with histopathology CD138 immunohistochemical staining of endometrium.

METHODS

A total of 205 patients in the PCOS group and 4021 patients in the non-PCOS group from July 2017 to August 2022 were included in this retrospective study. After nearest-neighbor 1:4 propensity score matching (PSM), 189 PCOS patients were matched with 697 non-PCOS patients. Basic information was recorded. The CE incidence was compared. The risk factors affecting CE incidence were also analyzed.

RESULTS

No significantly higher CE incidence in infertile women with PCOS were found either in total analysis or after PSM (P = 0.969; P = 0.697; respectively). Similar results were discovered in the subgroup of Body Mass Index (BMI) (P = 0.301; P = 0.671; P = 0.427; respectively) as well as the four PCOS phenotypes (P = 0.157). Intriguingly, the incidence of CE increased as BMI increased in the PCOS group, even though no significant differences were found (P = 0.263). Multivariate logistic regression showed that age, infertility duration, infertility type, PCOS, and obesity were not the independent risk factors affecting CE incidence.

CONCLUSION

The incidence of CE in PCOS patients did not significantly increase compared to non-PCOS patients. Similarly, no significant differences in the incidence of CE were observed among different PCOS phenotypes. The current evidence does not substantiate the need for widespread CE screening among PCOS women, potentially mitigating the undue financial and emotional strain associated with such screenings.

Association of insulin resistance with polycystic ovary syndrome phenotypes and patients' characteristics: a cross-sectional study in Iran

BACKGROUND

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women. This disorder affects 6-15% of women of childbearing age worldwide. It is diagnosed with hyperandrogenism, polycystic ovaries, and chronic anovulation with insulin resistance. This study aimed to assess the prevalence of insulin resistance (IR) in 4 phenotypes of PCOS, and its relationship with demographic, clinical, and paraclinical individual characteristics in a sample of Iranian PCOS patients.

METHODS

This particular cross-sectional investigation involved 160 female participants, aged between 18 and 45 years, who were receiving care at gynecology clinics in Urmia, northwestern Iran. All the participants had been diagnosed with PCOS and were categorized into one of four phenotypes. All the participants underwent clinical evaluations, paraclinical assessments, and ultrasound scans. IR was defined as HOMA-IR > 2.5. The statistical significance level was 0.05.

RESULTS

Among the 160 participants, the prevalences of the 4 phenotypes were: A: 83 (51.9%), B: 37 (23.1%), C: 21 (13.1%), and D: 19 (11.9%). IR was detected in 119 participants (74.4%); its rate was significantly different between the 4 phenotypes (p-value: 0.008) as A: 62 (74.7%), B: 34 (91.9%), C: 12 (57.1%), D: 11 (57.9%). Linear and logistic regression analyses were performed to control confounding factors. In linear regression, PCOS phenotype, classic phenotype (A&B), economic status, and Hb levels were significantly related to HOMA-IR; in logistic regression Hb levels, exercise, economic status, and PCOS phenotypes were significantly associated with insulin resistance.

CONCLUSIONS

The most prevalent PCOS phenotype in this study was A. PCOS phenotypes were significantly related to insulin resistance and HOMA-IR, with the highest levels of insulin resistance and HOMA-IR observed in phenotype B. Determining the phenotype of PCOS may be helpful for better management of PCOS and its associated complications. However, further investigations are recommended in this regard.

Acute heart failure: mechanisms and pre-clinical models-a Scientific Statement of the ESC Working Group on Myocardial Function

While chronic heart failure (CHF) treatment has considerably improved patient prognosis and survival, the therapeutic management of acute heart failure (AHF) has remained virtually unchanged in the last decades. This is partly due to the scarcity of pre-clinical models for the pathophysiological assessment and, consequently, the limited knowledge of molecular mechanisms involved in the different AHF phenotypes. This scientific statement outlines the different trajectories from acute to CHF originating from the interaction between aetiology, genetic and environmental factors, and comorbidities. Furthermore, we discuss the potential molecular targets capable of unveiling new therapeutic perspectives to improve the outcome of the acute phase and counteracting the evolution towards CHF.

Is metabolic-healthy obesity associated with risk of dementia? An age-stratified analysis of the Whitehall II cohort study

BACKGROUND

Metabolically healthy obesity is hypothesized to be a benign condition but whether this is the case for dementia remains debated. We examined the role of age at assessment of metabolic-obesity phenotypes in associations with incident dementia.

METHODS

Obesity (body mass index ≥ 30 kg/m2) and poor metabolic health (≥ 2 of elevated serum triglycerides, low HDL-C, elevated blood pressure, and elevated serum fasting glucose) were used to define four metabolic-obesity phenotypes (metabolically healthy (MHNO) and unhealthy non-obesity (MUNO), metabolically healthy (MHO) and unhealthy obesity (MUO)) at < 60, 60 to < 70, and ≥ 70 years using 6 waves of data from the Whitehall II study and their associations with incident dementia was examined using Cox regression.

RESULTS

Analyses with exposures measured < 60, 60 to < 70, and ≥ 70 years involved 410 (5.8%), 379 (5.6%), and 262 (7.4%) incident dementia cases over a median follow-up of 20.8, 10.3, and 4.2 years respectively. In analyses of individual components, obesity before 60 years (HR 1.41, 95% CI: [1.08, 1.85]) but not at older ages was associated with dementia; unhealthy metabolic status when present < 60 years (HR 1.33, 95% CI: [1.08, 1.62]) and 60 to < 70 years (HR 1.32, 95% CI: [1.07, 1.62]) was associated with dementia. Compared to the metabolically healthy non-obesity group, the risk of dementia was higher in those with metabolically healthy obesity before 60 years (1.69; 95% CI: [1.16, 2.45]); this was not the case when metabolic-obesity phenotype was present at 60 to < 70 years or ≥ 70 years. Analyses at older ages were on smaller numbers due to death and drop-out but inverse probability weighting to account for missing data yielded similar results.

CONCLUSIONS

Individuals with metabolically healthy obesity before age 60 had a higher risk of incident dementia over a 27-year follow-up; the excess risk dissipates when metabolic health and obesity are measured after 70 years.

Application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) to frontal lobe epilepsy using multicenter data

RATIONALE

The International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) was recently introduced as a consensus-based, empirically-driven taxonomy of cognitive disorders in epilepsy and has been effectively applied to patients with temporal lobe epilepsy (TLE). The purpose of this study was to apply the IC-CoDE to patients with frontal lobe epilepsy (FLE) using national multicenter data.

METHODS

Neuropsychological data of 455 patients with FLE aged 16 years or older were available across four US-based sites. First, we examined test-specific impairment rates across sites using two impairment thresholds (1.0 and 1.5 standard deviations below the normative mean). Following the proposed IC-CoDE guidelines, patterns of domain impairment were determined based on commonly used tests within five cognitive domains (language, memory, executive functioning, attention/processing speed, and visuospatial ability) to construct phenotypes. Impairment rates and distributions across phenotypes were then compared with those found in patients with TLE for which the IC-CoDE classification was initially validated.

RESULTS

The highest rates of impairment were found among tests of naming, verbal fluency, speeded sequencing and set-shifting, and complex figure copy. The following IC-CoDE phenotype distributions were observed using the two different threshold cutoffs: 23-40% cognitively intact, 24-29% single domain impairment, 13-20% bi-domain impairment, and 18-33% generalized impairment. Language was the most common single domain impairment (68% for both thresholds) followed by attention and processing speed (15-18%). Overall, patients with FLE reported higher rates of cognitive impairment compared with patients with TLE.

CONCLUSIONS

These results demonstrate the applicability of the IC-CoDE to epilepsy syndromes outside of TLE. Findings indicated generally stable and reproducible phenotypes across multiple epilepsy centers in the U.S. with diverse sample characteristics and varied neuropsychological test batteries. Findings also highlight opportunities for further refinement of the IC-CoDE guidelines as the application expands.

Structural phenotypes of knee osteoarthritis: potential clinical and research relevance

A joint contains many different tissues that can exhibit pathological changes, providing many potential targets for treatment. Researchers are increasingly suggesting that osteoarthritis (OA) comprises several phenotypes or subpopulations. Consequently, a treatment for OA that targets only one pathophysiologic abnormality is unlikely to be similarly efficacious in preventing or delaying the progression of all the different phenotypes of structural OA. Five structural phenotypes have been proposed, namely the inflammatory, meniscus-cartilage, subchondral bone, and atrophic and hypertrophic phenotypes. The inflammatory phenotype is characterized by marked synovitis and/or joint effusion, while the meniscus-cartilage phenotype exhibits severe meniscal and cartilage damage. Large bone marrow lesions characterize the subchondral bone phenotype. The hypertrophic and atrophic OA phenotype are defined based on the presence large osteophytes or absence of any osteophytes, respectively, in the presence of concomitant cartilage damage. Limitations of the concept of structural phenotyping are that they are not mutually exclusive and that more than one phenotype may be present. It must be acknowledged that a wide range of views exist on how best to operationalize the concept of structural OA phenotypes and that the concept of structural phenotypic characterization is still in its infancy. Structural phenotypic stratification, however, may result in more targeted trial populations with successful outcomes and practitioners need to be aware of the heterogeneity of the disease to personalize their treatment recommendations for an individual patient. Radiologists should be able to define a joint at risk for progression based on the predominant phenotype present at different disease stages.

Asthma in the era of COVID-19

Since its global invasion in 2019, COVID-19 has affected several aspects of patients' lives and posed a significant impact on the health care system. Several patient populations were identified to be at high risk of contracting SARS-CoV-2 infection and/or developing severe COVID-19-related sequelae. Conversely, anyone who has contracted SARS-CoV-2 is at risk to experience symptoms and signs consistent with post-COVID manifestations. Patients with asthma were initially thought to be at increased risk and severity for SARS-CoV-2 infection. However, accumulating evidence demonstrates that asthma endotypes/phenotypes and comorbidities influence the risk stratification in this population. Furthermore, initial concerns about the potentially increased risk of poor outcomes with asthma treatments such as inhaled corticosteroids and biologics have not been substantiated. In this review, we provide an update on COVID-19 and asthma, including risk of susceptibility, clinical manifestations and course in this population as well as discuss recommendations for management.

Analysis of sputum microbial flora in chronic obstructive pulmonary disease patients with different phenotypes during acute exacerbations

BACKGROUND

Increasing studies have shown that the imbalance of the respiratory microbial flora is related to the occurrence of COPD, the severity and frequency of exacerbations and mortality.However, it remains unclear how the sputum microbial flora differs during exacerbations in COPD patients manifesting emphysema phenotype, chronic bronchitis with emphysema phenotype and asthma-COPD overlap phenotype.

METHODS

Sputum samples were obtained from 29 COPD patients experiencing acute exacerbations who had not received antibiotics or systemic corticosteroids within the past four weeks.Patients were divided into three groups;emphysema phenotype(E);chronic bronchitis with emphysema phenotype(B+E) and asthma-COPD overlap phenotype(ACO).We utilized metagenomic Next Generation Sequencing (mNGS) technology to analyze the sputum microbial flora in COPD patients with different phenotypes during exacerbations.

RESULTS

There was no significant difference in alpha diversity and beta diversity among three groups.The microbial flora composition was similar in all three groups during exacerbations except for a significant increase in Streptococcus mitis in ACO.Through network analysis,we found Candidatus Saccharibacteria oral taxon TM7x and Fusobacterium necrophorum were the core nodes of the co-occurrence network in ACO and E respectively.They were positively correlated with some species and play a synergistic role.In B+E,Haemophilus pittmaniae and Klebsiella pneumoniae had a synergistic effect.Besides,some species among the three groups play a synergistic or antagonistic role.Through Spearman analysis,we found the relative abundance of Streptococcus mitis was negatively correlated with the number of hospitalizations in the past year(r = -0.410,P = 0.027).We also observed that the relative abundance of Prevotella and Prevotella melaninogenica was negatively correlated with age(r = -0.534,P = 0.003;r = -0.567,P = 0.001),while the relative abundance of Streptococcus oralis and Actinomyces odontolyticus was positively correlated with age(r = 0.570,P = 0.001;r = 0.480,P = 0.008).In addition,the relative abundance of Prevotella melaninogenica was negatively correlated with peripheral blood neutrophil ratio and neutrophil to lymphocyte ratio(r = -0.479,P = 0.009;r = -0.555,P = 0.002),while the relative abundance of Streptococcus sanguinis was positively correlated with peripheral blood neutrophil ratio and neutrophil to lymphocyte ratio (r = 0.450,P = 0.014;r = 0.501,P = 0.006).There was also a significant positive correlation between Oribacterium and blood eosinophil counts(r = 0.491,P = 0.007).

CONCLUSION

Overall,we analyzed the sputum microbiota of COPD patients with different phenotypes and its relationship with clinical indicators, and explored the relationships between microbiota and inflammation in COPD.We hope to alter the prognosis of patients by inhibiting specific bacterial taxa related to inflammation and using guide individualized treatment in the future research.

The role of endotoxin in septic shock

Septic shock can be caused by a variety of mechanisms including direct effects of bacterial toxins such as endotoxin. Annually, approximately 5-7 million patients worldwide develop sepsis with very high endotoxin activity in the blood and more than half die. The term endotoxic septic shock has been used for these patients but it is important to emphasize that endotoxin may be a factor in all forms of septic shock including non-bacterial etiologies like COVID-19 since translocation of bacterial products is a common feature of septic shock. A pattern of organ failure including hepatic dysfunction, acute kidney injury and various forms of endothelial dysfunction ranging from disseminated intravascular coagulation to thrombotic microangiopathy characterize endotoxic septic shock. However, while characteristic, the clinical phenotype is not unique to patients with high endotoxin, and the diagnosis relies on the measurement of endotoxin activity in addition to clinical assessment. Therapies for endotoxic septic shock are limited with immune modulating therapies under investigation and extracorporeal blood purification still controversial in many parts of the world.

Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit

BACKGROUND

Sepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output.

SUMMARY

Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI.

KEY MESSAGES

Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.

Clinical and radiographic characterization of three-dimensional gait profiles of patients with knee osteoarthritis

BACKGROUND

Previous authors have utilized gait kinematics to categorize knee osteoarthritis patients into four distinct profiles: (1) flexed knee; (2) externally rotated knee; (3) stiff knee; and (4) knee varus thrust and rotational rigidity. However, the relationship between these gait profiles and patients' characteristics remains poorly understood. Thus, this study aimed to investigate whether differences in clinical and radiographic characteristics were associated with these four gait profiles.

METHODS

This cross-sectional study used available data from a previous biomechanical study. Data on the four gait profiles were collected from 42 patients with advanced knee osteoarthritis. Three-dimensional kinematics of the knee was recorded during gait using an optoelectronic system. Subjects were evaluated for knee strength, range of motion, tibial slope, femorotibial angle, radiographic severity, anthropometric measurements, and patient-reported outcomes. Multiple comparisons were made using Dunn's test. The level of significance was set at 5%, and the effect size was calculated.

FINDINGS

Body mass index (BMI) was the only variable associated with a specific gait profile: profile 4 (P = 0.01; effect size = P1 × P4: -0.62; P2 × P4: -0.41; P3 × P4: -0.40).

INTERPRETATION

Our findings suggest that most clinical and radiographic characteristics commonly measured in clinical practice did not differ significantly among knee osteoarthritis patients with the four different gait profiles. The only exception was a higher BMI noted in those with gait profile 4; however, it remains unclear whether it can cause varus thrust or rotation rigidity. The incorporation of three-dimensional motion analysis to identify gait profiles provided clinical insights beyond the limitations of traditional clinical assessments.

Pregnancy outcomes in the different phenotypes of gestational diabetes mellitus based on the oral glucose tolerance test. A systematic review and meta-analysis

AIMS

To assess the prevalence variation in pregnancy outcomes of the different phenotypes of gestational diabetes mellitus (GDM).

MATERIALS

Cohort, cross sectional and case control studies grouping together pregnant women with GDM, based on the results of oral glucose tolerance test(OGTT) and reporting pregnancy outcomes in each group, were included. The primary outcomes were (i)large for gestational age and ii)hypertensive disorders of pregnancy (HDP). The secondary outcomes included (i)insulin treatment, ii)admission to neonatal intensive care unit, iii)preterm birth, iv)small for gestational age and v)caesarean section. The pooled proportions of the outcomes of interest were calculated for each phenotype.

RESULTS

8 studies (n = 20.928 women with GDM) were included. The pooled prevalence of LGA, HDP and insulin treatment were 20 %, 8 % and 24 % respectively in women with abnormal fasting plasma glucose,10 %, 6 % and 9 % respectively in women with abnormal post-load plasma glucose and 14 %,14 % and 30 % in women with abnormal combined plasma glucose.

CONCLUSIONS

Pregnant women with abnormal fasting plasma glucose, present with the highest prevalence of LGA, while those with abnormal combined plasma glucose, present with the highest prevalence of HDP. Pregnant women with abnormal post-load plasma glucose present with the lowest need for insulin treatment.

Thyroid Peroxidase Antibodies in Infertile Women with Polycystic Ovary Syndrome

To compare the rate of positive thyroid peroxidase antibodies (TPO Ab) between women with different polycystic ovary syndrome (PCOS) phenotypes and women without PCOS. This is a retrospective cohort study. Women with PCOS at My Duc Hospital between June 1, 2020, and March 27, 2021, were matched with non-PCOS women by age. TPO Ab (cut-off: 34 IU/mL) and thyroid-stimulating hormone (TSH) levels were measured as markers of Hashimoto thyroiditis and thyroid function, respectively. One thousand eight hundred eight infertile women were included, 904 with PCOS (mean age 29.0 ± 3.58 years) and 904 without PCOS (29.1 ± 3.4 years; controls). Women with PCOS had a higher body mass index (22.8 ± 3.84 vs. 19.9 ± 2.23 kg/m2, p < 0.001), but most were not overweight/obese. Rates of positive TPO Ab in women with versus without PCOS were 8.2% and 8.4%, respectively (p = 0.932). Rates of positive TPO Ab in patients with PCOS phenotype A, B, C, or D were not statistically different (7.5%, 2.9%, 20.0%, and 7.8%, respectively). Median TSH concentrations were similar in the PCOS and control groups (1.84 mIU/L vs. 1.78 mIU/L, respectively; p = 0.194). Based on a linear regression model, there was no correlation between either BMI or the estradiol to progesterone ratio and TPO Ab status. In a large population of infertile women with PCOS who were mostly lean patients, rates of positive TPO Ab across all four PCOS phenotypes did not differ significantly from those in women without PCOS. These findings did not support the hypothesis that PCOS is a risk factor for Hashimoto thyroiditis.