Covid-19 and Growth Hormone/Insulin-Like Growth Factor 1: Study in Critically and Non-Critically Ill Patients

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

A prospective study on endocrine function in patients with long-COVID symptoms

OBJECTIVE

To investigate hormonal status in patients with long-COVID and explore the interrelationship between hormone levels and long-COVID symptoms.

DESIGN

Prospective observational study.

PARTICIPANTS

Patients who visited our long-COVID outpatients' clinic due to long-COVID symptoms from February 2021 to December 2022.

MEASUREMENTS

Total triiodothyronine, free thyroxine, thyrotropin, thyroglobulin, anti-thyroperoxidase, and antithyroglobulin autoantibodies were measured for thyroid assessment. Other hormones measured were growth hormone, insulin-like growth factor 1 (IGF-1), adrenocorticotropic hormone (ACTH), serum cortisol, dehydroepiandrosterone sulfate (DHEA-S), total testosterone, plasma insulin, and C-peptide. Blood glucose and glycosylated hemoglobin were also measured. To assess adrenal reserve, an ACTH stimulation test was performed. The fatigue assessment scale (FAS) was used to evaluate fatigue severity.

RESULTS

Eighty-four adult patients were included. Overall, 40.5% of the patients had at least one endocrine disorder. These included prediabetes (21.4%), low DHEA-S (21.4%), subclinical hypothyroidism (3.6%), non-specific thyroid function abnormality (7.1%), thyroid autoimmunity (7.1%), low testosterone in males (6.6%), and low IGF-1 (3.6%). All patients had normal adrenal reserve. Long-COVID-19 symptoms were present in all patients and the most commonly reported symptom was fatigue (89.3%). The FAS score was higher than normal (≥ 22) in 42.8% of patients. There were no associations between patients' symptoms and hormone levels. Diabetic patients reported confusion (p = 0.020) and hair loss (p = 0.040) more often than non-diabetics.

CONCLUSIONS

The evaluation of endocrine function 3 months after a positive SARS-CoV2 test revealed only subclinical syndromes. The vast majority of patients reported mainly fatigue, among other symptoms, which were unrelated, however, to endocrine function.

Serum Insulin-like Growth Factor-Binding Protein-2 as a Prognostic Factor for COVID-19 Severity

Insulin-like growth factor-binding protein (IGFBP)-2 is a regulator of anabolic pathways, which become inactivated in severe illness. Here, we measured the serum IGFBP-2 levels of COVID-19 patients with moderate and severe disease as well as healthy controls to identify the associations of serum IGFBP-2 levels with disease severity. Patients with severe COVID-19 had higher serum IGFBP-2 levels than those with moderate disease and healthy controls, who had similar levels. Non-survivors of COVID-19 tended to have elevated serum IGFBP-2 levels compared to survivors. Increased serum IGFBP-2 levels were observed in patients requiring dialysis and vasopressor therapy. Serum IGFBP-2 was positively correlated with procalcitonin in both patient groups. Bacterial co-infection in severe COVID-19 patients did not influence serum IGFBP-2 levels. Patients with liver cirrhosis and obesity, showing increased and decreased serum IGFBP-2 levels, respectively, were excluded from the study. The present analysis showed that higher serum IGFBP-2 levels are associated with increased disease severity in COVID-19 patients. The similarity in serum IGFBP-2 levels between patients with moderate COVID-19 and healthy controls suggests that elevated IGFBP-2 is associated with critical illness rather than SARS-CoV-2 infection itself.

Is there a role for growth hormone replacement in adults to control acute and post-acute COVID-19?

The SARS-CoV-2 pandemic created a multitude of medical crossroads requiring real time adaptations of best practice covering preventative and interventional aspects of care. Among the many discoveries borne from efforts to address the myriad clinical presentations across multiple organ systems was a common impact on tissues with cells that express the ACE-2 receptor. The vast majority of acute infections began and often ended in the respiratory tract, but more recent evaluations have confirmed significant extrapulmonary manifestations including symptom clusters that extend beyond the acute phase of infection collectively referred to as "post-acute sequelae SARS-CoV-2 infection" (PASC) or more commonly as "long (-haul) COVID". Both acute SARS-CoV-2 infection and PASC are associated with gut microbiome dysbiosis and alterations in the gut-brain and HPA-axis in a subset of the infected. Mounting evidence suggests these extrapulmonary manifestations may ultimately lead to reduced growth hormone (GH) secretion as demonstrated following stimulation tests. Disrupted GH secretion could cause or exacerbate long lasting neuropsychological symptoms as seen in other similar manifesting conditions. Ongoing clinical research has shown promising improvement in PASC patients with fatigue and cognition complaints can be achieved via GH replacement therapy. GH stimulation testing should be considered in PASC workups and future research should delve deeper into the mechanistic effects of GH on acute COVID and PASC.

Evaluation of circulating insulin-like growth factor-1, heart-type fatty acid-binding protein, and endotrophin levels as prognostic markers of COVID-19 infection severity

BACKGROUND

Coronavirus Disease 2019 (COVID-19) is a worldwide pandemic challenge spreading enormously within a few months. COVID-19 is characterized by the over-activation of the immune system causing cytokine storm. Insulin-like growth factor-1 (IGF-1) pathway can regulate the immune response via interaction with various implicated cytokines. Heart-type fatty acid-binding protein (H-FABP) has been shown to promote inflammation. Given the fact that coronavirus infections induce cytokines secretion leading to inflammatory lung injury, it has been suggested that H-FABP levels are affected by COVID-19 severity. Moreover, endotrophin (ETP), the cleavage product of collagen VI, may be an indicator of an overactive repair process and fibrosis, considering that viral infection may predispose or exacerbate existing respiratory conditions, including pulmonary fibrosis. This study aims to assess the prognostic capacity of circulating IGF-1, HFABP, and ETP, levels for COVID-19 severity progression in Egyptian patients.

METHODS

The study cohort included 107 viral RNA-positive patients and an equivalent number of control individuals with no clinical signs of infection. Clinical assessments included profiling of CBC; serum iron; liver and kidney functions; inflammatory markers. Circulating levels of IGF-1; H-FABP, and ETP were estimated using the corresponding ELISA kits.

RESULTS

No statistical difference in the body mass index was detected between the healthy and control groups, while the mean age of infected patients was significantly higher (P = 0.0162) than the control. Patients generally showed elevated levels of inflammatory markers including CRP and ESR concomitant with elevated serum ferritin; D dimer and procalcitonin levels, besides the COVID-19 characteristic lymphopenia and hypoxemia were also frequent. Logistic regression analysis revealed that oxygen saturation; serum IGF-1, and H-FABP can significantly predict the infection progression (P < 0.001 each). Both serum IGF-1 and H-FABP as well as O₂ saturation showed remarkable prognostic potentials in terms of large AUC values, high sensitivity/specificity values, and wide confidence interval. The calculated threshold for severity prognosis was 25.5 ng/mL; 19.5 ng/mL, 94.5, % and for IGF-1, H-FABP, and O₂ saturation; respectively. The calculated thresholds of serum IGF-1; H-FABP, and O₂ saturation showed positive and negative value ranges of 79-91% and 72-97%; respectively, with 66-95%, 83-94% sensitivity, and specificity; respectively.

CONCLUSION

The calculated cut-off values of serum IGF-1 and H-FABP represent a promising non-invasive prognostic tool that would facilitate the risk stratification in COVID-19 patients, and control the morbidity/mortality associated with progressive infection.

A computational map of the human-SARS-CoV-2 protein-RNA interactome predicted at single-nucleotide resolution

RNA-binding proteins (RBPs) are critical host factors for viral infection, however, large scale experimental investigation of the binding landscape of human RBPs to viral RNAs is costly and further complicated due to sequence variation between viral strains. To fill this gap, we investigated the role of RBPs in the context of SARS-CoV-2 by constructing the first in silico map of human RBP-viral RNA interactions at nucleotide-resolution using two deep learning methods (pysster and DeepRiPe) trained on data from CLIP-seq experiments on more than 100 human RBPs. We evaluated conservation of RBP binding between six other human pathogenic coronaviruses and identified sites of conserved and differential binding in the UTRs of SARS-CoV-1, SARS-CoV-2 and MERS. We scored the impact of mutations from 11 variants of concern on protein-RNA interaction, identifying a set of gain- and loss-of-binding events, as well as predicted the regulatory impact of putative future mutations. Lastly, we linked RBPs to functional, OMICs and COVID-19 patient data from other studies, and identified MBNL1, FTO and FXR2 RBPs as potential clinical biomarkers. Our results contribute towards a deeper understanding of how viruses hijack host cellular pathways and open new avenues for therapeutic intervention.

Causal Inference of Central Nervous System-Regulated Hormones in COVID-19: A Bidirectional Two-Sample Mendelian Randomization Study

We assessed the causal association of three COVID-19 phenotypes with insulin-like growth factor 1, estrogen, testosterone, dehydroepiandrosterone (DHEA), thyroid-stimulating hormone, thyrotropin-releasing hormone, luteinizing hormone (LH), and follicle-stimulating hormone. We used bidirectional two-sample univariate and multivariable Mendelian randomization (MR) analyses to evaluate the direction, specificity, and causality of the association between CNS-regulated hormones and COVID-19 phenotypes. Genetic instruments for CNS-regulated hormones were selected from the largest publicly available genome-wide association studies of the European population. Summary-level data on COVID-19 severity, hospitalization, and susceptibility were obtained from the COVID-19 host genetic initiative. DHEA was associated with increased risks of very severe respiratory syndrome (odds ratio [OR] = 4.21, 95% confidence interval [CI]: 1.41-12.59), consistent with multivariate MR results (OR = 3.72, 95% CI: 1.20-11.51), and hospitalization (OR = 2.31, 95% CI: 1.13-4.72) in univariate MR. LH was associated with very severe respiratory syndrome (OR = 0.83; 95% CI: 0.71-0.96) in univariate MR. Estrogen was negatively associated with very severe respiratory syndrome (OR = 0.09, 95% CI: 0.02-0.51), hospitalization (OR = 0.25, 95% CI: 0.08-0.78), and susceptibility (OR = 0.50, 95% CI: 0.28-0.89) in multivariate MR. We found strong evidence for the causal relationship of DHEA, LH, and estrogen with COVID-19 phenotypes.

Obesity-Associated Hepatic Steatosis, Somatotropic Axis Impairment, and Ferritin Levels Are Strong Predictors of COVID-19 Severity

The full spectrum of SARS-CoV-2-infected patients has not yet been defined. This study aimed to evaluate which parameters derived from CT, inflammatory, and hormonal markers could explain the clinical variability of COVID-19. We performed a retrospective study including SARS-CoV-2-infected patients hospitalized from March 2020 to May 2021 at the Umberto I Polyclinic of Rome. Patients were divided into four groups according to the degree of respiratory failure. Routine laboratory examinations, BMI, liver steatosis indices, liver CT attenuation, ferritin, and IGF-1 serum levels were assessed and correlated with severity. Analysis of variance between groups showed that patients with worse prognoses had higher BMI and ferritin levels, but lower liver density, albumin, GH, and IGF-1. ROC analysis confirmed the prognostic accuracy of IGF-1 in discriminating between patients who experienced death/severe respiratory failure and those who did not (AUC 0.688, CI: 0.587 to 0.789, p < 0.001). A multivariate analysis considering the degrees of severity of the disease as the dependent variable and ferritin, liver density, and the standard deviation score of IGF-1 as regressors showed that all three parameters were significant predictors. Ferritin, IGF-1, and liver steatosis account for the increased risk of poor prognosis in COVID-19 patients with obesity.

Severe acute respiratory syndrome coronavirus 2 may cause liver injury via Na+/H+ exchanger

The liver has many significant functions, such as detoxification, the urea cycle, gluconeogenesis, and protein synthesis. Systemic diseases, hypoxia, infections, drugs, and toxins can easily affect the liver, which is extremely sensitive to injury. Systemic infection of severe acute respiratory syndrome coronavirus 2 can cause liver damage. The primary regulator of intracellular pH in the liver is the Na⁺/H⁺ exchanger (NHE). Physiologically, NHE protects hepatocytes from apoptosis by making the intracellular pH alkaline. Severe acute respiratory syndrome coronavirus 2 increases local angiotensin II levels by binding to angiotensin-converting enzyme 2. In severe cases of coronavirus disease 2019, high angi-otensin II levels may cause NHE overstimulation and lipid accumulation in the liver. NHE overstimulation can lead to hepatocyte death. NHE overstimulation may trigger a cytokine storm by increasing proinflammatory cytokines in the liver. Since the release of proinflammatory cytokines such as interleukin-6 increases with NHE activation, the virus may indirectly cause an increase in fibrinogen and D-dimer levels. NHE overstimulation may cause thrombotic events and systemic damage by increasing fibrinogen levels and cytokine release. Also, NHE overstimulation causes an increase in the urea cycle while inhibiting vitamin D synthesis and gluconeogenesis in the liver. Increasing NHE3 activity leads to Na⁺ loading, which impairs the containment and fluidity of bile acid. NHE overstimulation can change the gut microbiota composition by disrupting the structure and fluidity of bile acid, thus triggering systemic damage. Unlike other tissues, tumor necrosis factor-alpha and angiotensin II decrease NHE3 activity in the intestine. Thus, increased luminal Na⁺ leads to diarrhea and cytokine release. Severe acute respiratory syndrome coronavirus 2-induced local and systemic damage can be improved by preventing virus-induced NHE overstimulation in the liver.

Genetically predicted high IGF-1 levels showed protective effects on COVID-19 susceptibility and hospitalization: a Mendelian randomisation study with data from 60 studies across 25 countries

Background

Epidemiological studies observed gender differences in COVID-19 outcomes, however, whether sex hormone plays a causal in COVID-19 risk remains unclear. This study aimed to examine associations of sex hormone, sex hormones-binding globulin (SHBG), insulin-like growth factor-1 (IGF-1), and COVID-19 risk.

Methods

Two-sample Mendelian randomization (TSMR) study was performed to explore the causal associations between testosterone, estrogen, SHBG, IGF-1, and the risk of COVID-19 (susceptibility, hospitalization, and severity) using genome-wide association study (GWAS) summary level data from the COVID-19 Host Genetics Initiative (N=1,348,701). Random-effects inverse variance weighted (IVW) MR approach was used as the primary MR method and the weighted median, MR-Egger, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test were conducted as sensitivity analyses.

Results

Higher genetically predicted IGF-1 levels have nominally significant association with reduced risk of COVID-19 susceptibility and hospitalization. For one standard deviation increase in genetically predicted IGF-1 levels, the odds ratio was 0.77 (95% confidence interval [CI], 0.61-0.97, p=0.027) for COVID-19 susceptibility, 0.62 (95% CI: 0.25-0.51, p=0.018) for COVID-19 hospitalization, and 0.85 (95% CI: 0.52-1.38, p=0.513) for COVID-19 severity. There was no evidence that testosterone, estrogen, and SHBG are associated with the risk of COVID-19 susceptibility, hospitalization, and severity in either overall or sex-stratified TSMR analysis.

Conclusions

Our study indicated that genetically predicted high IGF-1 levels were associated with decrease the risk of COVID-19 susceptibility and hospitalization, but these associations did not survive the Bonferroni correction of multiple testing. Further studies are needed to validate the findings and explore whether IGF-1 could be a potential intervention target to reduce COVID-19 risk.

Funding

We acknowledge support from NSFC (LR22H260001), CRUK (C31250/A22804), SHLF (Hjärt-Lungfonden, 20210351), VR (Vetenskapsrådet, 2019-00977), and SCI (Cancerfonden).

Endocrine Aspects of ICU-Hospitalized COVID-19 Patients

The unprecedented scale of the current SARS-CoV-2/COVID-19 pandemic has led to an extensive—yet fragmented—assessment of its endocrine repercussions; in many reports, the endocrine aspects of COVID-19 are lumped together in intensive care unit (ICU) patients and non-ICU patients. In this brief review, we aimed to present endocrine alterations in ICU-hospitalized patients with COVID-19. There are tangible endocrine disturbances that may provide fertile ground for COVID-19, such as preexisting diabetes. Other endocrine disturbances accompany the disease and more particularly its severe forms. Up to the time of writing, no isolated robust endocrine/hormonal biomarkers for the prognosis of COVID-19 have been presented. Among those which may be easily available are admission glycemia, thyroid hormones, and maybe (OH)₂₅-vitamin D3. Their overlap among patients with severe and less severe forms of COVID-19 may be considerable, so their levels may be indicative only. We have shown that insulin-like growth factor 1 may have prognostic value, but this is not a routine measurement. Possibly, as our current knowledge is expanding, the inclusion of selected routine endocrine/hormonal measurements into artificial intelligence/machine learning models may provide further information.

Endocrine and metabolic complications of COVID-19: lessons learned and future prospects

Coronavirus disease 2019 (COVID-19) is well known for its respiratory complications; however, it can also cause extrapulmonary manifestations, including cardiovascular, thrombotic, renal, gastrointestinal, neurologic, and endocrinological symptoms. Endocrinological complications of COVID-19 are rare but can considerably impact the outcome of the patients. Moreover, preexisting endocrinologic disorders can affect the severity of COVID-19. Thyroid, pancreas, adrenal, neuroendocrine, gonadal, and parathyroid glands are the main endocrinologic organs that can be targeted by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Endocrinological complications of COVID-19 are rare but can significantly deteriorate the patients' prognosis. Understanding the interaction between COVID-19 and the endocrine system can provide a potential treatment option to improve the outcome of COVID-19. In this article, we aim to review the short-term and long-term organ-based endocrinological complications of COVID-19, the pathophysiology, the influence of each complication on COVID-19 prognosis, and potential therapeutic interventions based on current published data. Moreover, current clinical trials of potential endocrinological interventions to develop therapeutic strategies for COVID-19 have been discussed.

Effects of growth hormone/estrogen/androgen on COVID-19-type proinflammatory responses in normal human lung epithelial BEAS-2B cells

Background

COVID-19 is a disease caused by SARS-CoV-2, which can cause mild to serious infections in humans. We aimed to explore the effect of growth hormone (GH)/estrogen/androgen in normal human lung epithelial BEAS-2B cells on COVID-19-type proinflammatory responses.

Methods

A BEAS-2B COVID-19-like proinflammatory cell model was constructed. After that, the cells were treated with GH, 17β-estradiol (E2), and testosterone (Tes) for 24 h. CCK-8 assays were utilized to evaluate cell viability. The mRNA expression of ACE2, AGTR1, TMRRSS2, and ISG15 and the protein expression of ACE2, AGTR1, TMRRSS2, and ISG15 were measured by qRT‒PCR and Western blotting, respectively. ELISAs were performed to determine IL-6, MCP-1, MDA and SOD expression. Flow cytometry was used to measure ROS levels. Finally, MAPK/NF-κB pathway-related factor expression was evaluated.

Results

The COVID-19-type proinflammatory model was successfully constructed, and 1000 ng/mL RBD treatment for 24 h was selected as the condition for the model group for subsequent experiments. After RBD treatment, cell viability decreased, the mRNA expression of ACE2, AGTR1, TMRRSS2, and ISG15 and the protein expression of ACE2, AGTR1, TMRRSS2, and ISG15 increased, IL-6, MCP-1, MDA and ROS levels increased, and MDA levels decreased. The mRNA levels of MAPK14 and RELA increased, but the protein levels did not change significantly. In addition, phospho-MAPK14 and phospho-RELA protein levels were also increased. Among the tested molecules, E2 had the most pronounced effect, followed by GH, while Tes showed the opposite effect.

Conclusion

GH/E2 alleviated inflammation in a COVID-19-type proinflammatory model, but Tes showed the opposite effect.

Correlates with Vaccine Protective Capacity and COVID-19 Disease Symptoms Identified by Serum Proteomics in Vaccinated Individuals

In the last two years, the coronavirus disease 19 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a scientific and social challenge worldwide. Vaccines have been the most effective intervention for reducing virus transmission and disease severity. However, genetic virus variants are still circulating among vaccinated individuals with different disease symptomatology. Understanding the protective- or disease-associated mechanisms in vaccinated individuals is relevant to advances in vaccine development and implementation. To address this objective, serum-protein profiles were characterized by quantitative proteomics and data-analysis algorithms in four cohorts of uninfected and SARS-CoV-2-infected vaccinated individuals with asymptomatic, non-severe, and severe disease symptomatology. The results show that immunoglobulins were the most overrepresented proteins in infected cohorts when compared to PCR-negative individuals. The immunoglobulin profile varied between different infected cohorts and correlated with protective- or disease-associated capacity. Overrepresented immunoglobulins in PCR-positive individuals correlated with protective response against SARS-CoV-2, other viruses, and thrombosis in asymptomatic cases. In non-severe cases, correlates of protection against SARS-CoV-2 and HBV together with risk of myasthenia gravis and allergy and autoantibodies were observed. Patients with severe symptoms presented risk for allergy, chronic idiopathic thrombocytopenic purpura, and autoantibodies. The analysis of underrepresented immunoglobulins in PCR-positive compared to PCR-negative individuals identified vaccine-induced protective epitopes in various coronavirus proteins, including the spike receptor-binding domain RBD. Non-immunoglobulin proteins were associated with COVID-19 symptoms and biological processes. These results evidence host-associated differences in response to vaccination and the possibility of improving vaccine efficacy against SARS-CoV-2.

Immunomodulatory mechanisms of abatacept: A therapeutic strategy for COVID-19

Coronavirus disease 2019 (COVID-19) caused by coronavirus-2 (SARS-CoV-2) infection has rapidly spread throughout the world and become a major threat to human beings. Cytokine storm is a major cause of death in severe patients. Abatacept can suppress cytokines used as antirheumatic drugs in clinical applications. This study analyzed the molecular mechanisms of abatacept treatment for COVID-19. Differentially expressed genes (DEGs) were identified by analyzing expression profiling of abatacept treatment for rheumatoid arthritis (RA) patients and SARS-CoV-2 infection patients. We found that 59 DEGs were upregulated in COVID-19 patients and downregulated following abatacept treatment. Gene set enrichment analysis (GSEA) and Gene Ontology (GO) analysis showed that immune and inflammatory responses were potential regulatory mechanisms. Moreover, we verified 8 targeting genes and identified 15 potential drug candidates for the treatment of COVID-19. Our study illustrated that abatacept could be a promising property for preventing severe COVID-19, and we predicted alternative potential drugs for the treatment of SARS-CoV-2 infection.

Development of a Novel Algorithm to Identify People with High Likelihood of Adult Growth Hormone Deficiency in a US Healthcare Claims Database

OBJECTIVE

Adult growth hormone deficiency (AGHD) is an underdiagnosed disease associated with increased morbidity and mortality. Identifying people who may benefit from growth hormone (GH) therapy can be challenging, as many AGHD symptoms resemble those of aging. We developed an algorithm to potentially help providers stratify people by their likelihood of having AGHD.

DESIGN

The algorithm was developed with, and applied to, data in the anonymized Truven Health MarketScan® claims database. Patients. A total of 135 million adults in the US aged ≥18 years with ≥6 months of data in the Truven database. Measurements. Proportion of people with high, moderate, or low likelihood of having AGHD, and differences in demographic and clinical characteristics among these groups.

RESULTS

Overall, 0.5%, 6.0%, and 93.6% of people were categorized into groups with high, moderate, or low likelihood of having AGHD, respectively. The proportions of females were 59.3%, 71.6%, and 50.4%, respectively. People in the high- and moderate-likelihood groups tended to be older than those in the low-likelihood group, with 58.3%, 49.0%, and 37.6% aged >50 years, respectively. Only 2.2% of people in the high-likelihood group received GH therapy as adults. The high-likelihood group had a higher incidence of comorbidities than the low-likelihood group, notably malignant neoplastic disease (standardized difference -0.42), malignant breast tumor (-0.27), hyperlipidemia (-0.26), hypertensive disorder (-0.25), osteoarthritis (-0.23), and heart disease (-0.22).

CONCLUSIONS

This algorithm may represent a cost-effective approach to improve AGHD detection rates by identifying appropriate patients for further diagnostic testing and potential GH replacement treatment.