The diagnostic approach to hypopituitarism involves many disciplines. Clinical symptoms rarely are specific. Imaging techniques are helpful but cannot prove the specific functional defects. Therefore, the definitive diagnosis of pituitary insufficiency is largely based on laboratory tests. However, also laboratory methods come with inherent limitations, and it is essential for the clinician to know and recognize typical pitfalls. Most factors potentially impairing the quality of hormone measurements are introduced in the preanalytical phase, i.e. before the hormones are measured by the laboratory. For example, the timing of blood drawing with respect to circadian rhythm, stress, and medication can have an influence on hormone concentrations. During the actual analysis of the hormones, cross-reactions with molecules present in the sample presenting the same or similar epitopes than the intended analyte may affect immunoassays. Interference can also come from heterophilic or human anti-animal antibodies. Unexpected problems can also be due to popular nutritional supplements which interfere with the measurement procedures. An important example in this respect is the interference from biotin. It became only clinically visible when the use of this vitamin became popular among patients. The extreme serum concentrations reached when patients take it as a supplement can lead to incorrect measurements in immunoassays employing the biotin-streptavidin system. To some extent, hormone analyses using liquid chromatography mass spectrometry (LCMS) can overcome problems, although availability and cost-effectiveness of this method still imposes restrictions. In the post-analytical phase, appropriateness of reference intervals and cut-offs with respect to the specific analytical method used is of outmost importance. Furthermore, for interpretation, additional biological and pharmacological factors like BMI, age and concomitant diseases must be considered to avoid misinterpretation of the measured concentrations. It is important for the clinician and the laboratory to recognize when one or more laboratory values do not match the clinical picture. In an interdisciplinary approach, the search for the underlying cause should be initiated.

BACKGROUND: Although safety climate, teamwork, and other non-technical skills in operating rooms probably influence clinical outcomes, direct associations have not been shown, at least partially due to sample size considerations. We report data from a retrospective cohort of anesthesia evaluations that can simplify the design of prospective observational studies in this area. Associations between non-technical skills in anesthesia, specifically anesthesiologists\' quality of clinical supervision and nurse anesthetists\' work habits, and patient and operational factors were examined.
METHODS: Eight fiscal years of evaluations and surgical cases from one hospital were included. Clinical supervision by anesthesiologists was evaluated daily using a nine-item scale. Work habits of nurse anesthetists were evaluated daily using a six-item scale. The dependent variables for both groups of staff were binary, whether all items were given the maximum score or not. Associations were tested with patient and operational variables for the entire day.
RESULTS: There were 40,718 evaluations of faculty anesthesiologists by trainees, 53,772 evaluations of nurse anesthetists by anesthesiologists, and 296,449 cases that raters and ratees started together. Cohen\'s d values were small (≤0.10) for all independent variables, suggesting a lack of any clinically meaningful association between patient and operational factors and evaluations given the maximum scores. For supervision quality, the day\'s count of orthopedic cases was a significant predictor of scores (P = 0.0011). However, the resulting absolute marginal change in the percentage of supervision scores equal to the maximum was only 0.8% (99% confidence interval: 0.2% to 1.4%), i.e., too small to be of clinical or managerial importance. Neurosurgical cases may have been a significant predictor of work habits (P = 0.0054). However, the resulting marginal change in the percentage of work habits scores equal to the maximum, an increase of 0.8% (99% confidence interval: 0.1% to 1.6%), which was again too small to be important.
CONCLUSIONS: When evaluating the effect of assigning anesthesiologists and nurse anesthetists with different clinical performance quality on clinical outcomes, supervision quality and work habits scores may be included as independent variables without concern that their effects are confounded by association with the patient or case characteristics. Clinical supervision and work habits are measures of non-technical skills. Hence, these findings suggest that non-technical performance can be judged by observing the typical small sample size of cases. Then, associations can be tested with administrative data for a far greater number of patients because there is unlikely to be a confounding association between patient and case characteristics and the clinicians\' non-technical performance.

OBJECTIVE: It is essential for health researchers to have a systematic understanding of third-party variables that influence both the exposure and outcome under investigation, as shown by a directed acyclic graph (DAG). The traditional construction of DAGs through literature review and expert knowledge often needs to be more systematic and consistent, leading to potential biases. We try to introduce an automatic approach to building network linking variables of interest.
METHODS: Large-scale text mining from medical literature was utilized to construct a conceptual network based on the Semantic MEDLINE Database (SemMedDB). SemMedDB is a PubMed-scale repository of the \"concept-relation-concept\" triple format. Relations between concepts are categorized as Excitatory, Inhibitory, or General.
RESULTS: To facilitate the use of large-scale triple sets in SemMedDB, we have developed a computable biomedical knowledge (CBK) system (https://cbk.bjmu.edu.cn/), a website that enables direct retrieval of related publications and their corresponding triples without the necessity of writing SQL statements. Three case studies were elaborated to demonstrate the applications of the CBK system.
CONCLUSIONS: The CBK system is openly available and user-friendly for rapidly capturing a set of influencing factors for a phenotype and building candidate DAGs between exposure-outcome variables. It could be a valuable tool to reduce the exploration time in considering relationships between variables, and constructing a DAG. A reliable and standardized DAG could significantly improve the design and interpretation of observational health research.

Metabolomics is an emerging and powerful bioanalytical method supporting clinical investigations. Serum and plasma are commonly used without rational prioritization. Serum is collected after blood coagulation, a complex biochemical process involving active platelet metabolism. This may affect the metabolome and increase the variance, as platelet counts and function may vary substantially in individuals. A multiomics approach systematically investigating the suitability of serum and plasma for clinical studies demonstrated that metabolites correlated well (n = 461, R2 = 0.991), whereas lipid mediators (n = 83, R2 = 0.906) and proteins (n = 322, R2 = 0.860) differed substantially between specimen. Independently, analysis of platelet releasates identified most biomolecules significantly enriched in serum compared to plasma. A prospective, randomized, controlled parallel group metabolomics trial with acetylsalicylic acid administered for 7 days demonstrated that the apparent drug effects significantly differ depending on the analyzed specimen. Only serum analyses of healthy individuals suggested a significant downregulation of TXB2 and 12-HETE, which were specifically formed during coagulation in vitro. Plasma analyses reliably identified acetylsalicylic acid effects on metabolites and lipids occurring in vivo such as an increase in serotonin, 15-deoxy-PGJ2 and sphingosine-1-phosphate and a decrease in polyunsaturated fatty acids. The present data suggest that plasma should be preferred above serum for clinical metabolomics studies as the serum metabolome may be substantially confounded by platelets.

Observational studies have determined numerous correlations between sequence-based gut microbiota data and human mental traits. However, these associations are often inconsistent across studies. This inconsistency is one of the reasons that mechanistic validation studies of the observed correlations are lagging, making it difficult to establish causal associations. The absence of consistent study findings may partially be due to the lack of clear guidelines for identifying confounders of relations between complex microbial communities and mental conditions. Gut microbial complexity also impedes deciphering microbiota-host relations by using a single analytical approach. The aim of the current review is to help solve these problems by providing methodological recommendations for future human microbiota-gut-brain axis research on the selection of confounders, the use of integrative biostatistical methods, and the steps needed to translate correlative findings into causal conclusions.

Bevezetés: A túlsúlyos vagy elhízott átlagpopuláció jelentős hányada választja a ketogén diéták egyes típusait testsúlycsökkentés céljából. E népszerű divatdiéta tudományos és laikus irodalma is igen széles körű. Számos, az evidenciapiramis csúcsán álló, ezért hiteles forrásnak tartott metaanalízis vizsgálta a ketogén diéták egészségre gyakorolt hatásait. Sok közülük jótékony hatásokról számol be mind az antropometriai, mind a vérparaméreket tekintve, elhízott és 2-es típusú cukorbeteg páciensek esetében is. Ám számos zavaró tényező módosíthatja e kedvező eredményeket, melyeket a metaanalízisek többsége figyelmen kívül hagy. Célkitűzés: Irodalmi áttekintő közleményünk célja, hogy ezekre a módszertani nehézségekre és a belőlük adódó értelmezési kihívásokra felhívja a szakemberek és azok figyelmét, akik szintén rendszeres olvasói, érdeklődői a táplálkozástudománynak. Módszer: A PubMed adatbázisban történt 2023 szeptemberében az olyan metaanalízisek keresése, amelyek nem az epilepszia kezeléséről, valamint nem a különböző rosszindulatú daganatos megbetegedésekben szenvedő páciensek ketogén diétájáról szóltak. A kereséskor használt kulcsszó a „ketogenic diet” volt, kizárólag a metaanalízis címében. Eredmények: Az áttekintő közleményünkbe bevont 18 metaanalízis számos zavaró tényezőt figyelmen kívül hagyott, mint például a kalória- és szénhidrátbeviteli különbségeket a ketogén diétás és a kontrollcsoportok között, az elfogyasztott zsírsavtípusok és a vérzsírparaméterek kapcsolatát, valamint a táplálkozási ketosis meglétét a ketogén diétát követő csoportokban. Következtetés: A ketogén diétákról szóló széles körű, sokszor pozitív eredményeket közlő irodalmi háttér ellenére e diéta ajánlása mindaddig nem javasolt, amíg jól tervezett, hosszú távú klinikai kutatások és az azokat elemző metaanalízisek nem jelennek meg, nagyobb figyelmet fordítva e zavaró tényezőkre. Orv Hetil. 2024; 165(7): 260–264.

The role of the complement system in schizophrenia (Sz) is inconclusive due to heterogeneity of the disease and study designs. Here, we assessed the levels of complement activation products and functionality of the classical pathway in acutely ill unmedicated Sz patients at baseline and after 6 weeks of treatment versus matched controls. The study included analyses of the terminal complement complex (sTCC) and C5a in plasma from 96 patients and 96 controls by enzyme-linked immunosorbent assay. Sub-group analysis of serum was conducted for measurement of C4 component and activity of the classical pathway (28 and 24 cases per cohort, respectively). We found no differences in levels of C5a, C4 and classical pathway function in patients versus controls. Plasma sTCC was significantly higher in patients [486 (392-659) ng/mL, n = 96] compared to controls [389 (304-612) ng/mL, n = 96] (p = 0.027, δ = 0.185), but not associated with clinical symptom ratings or treatment. The differences in sTCC between Sz and controls were confirmed using an Aligned Rank Transformation model considering the covariates age and sex (p = 0.040). Additional analysis showed that sTCC was significantly associated with C-reactive protein (CRP; p = 0.006). These findings suggest that sTCC plays a role in Sz as a trait marker of non-specific chronic immune activation, as previously described for CRP. Future longitudinal analyses with more sampling time points from early recognition centres for psychoses may be helpful to better understand the temporal dynamics of innate immune system changes during psychosis development.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.

Non-destructive assessments are required for the quality control of tissue-engineered constructs and the optimization of the tissue culture process. Near-infrared (NIR) spectroscopy coupled with machine learning (ML) provides a promising approach for such assessment. However, due to its nonspecific nature, each spectrum incorporates information on both neotissue and non-neotissue constituents of the construct; the effect of these constituents on the NIR-based assessments of tissue-engineered constructs has been overlooked in previous studies. This study investigates the effect of scaffolds, growth factors, and buffers on NIR-based assessments of tissue-engineered constructs. To determine if these non-neotissue constituents have a measurable effect on the NIR spectra of the constructs that can introduce bias in their assessment, nine ML algorithms were evaluated in classifying the NIR spectra of engineered cartilage according to the scaffold used to prepare the constructs, the growth factors added to the culture media, and the buffers used for storing the constructs. The effect of controlling for these constituents was also evaluated using controlled and uncontrolled NIR-based ML models for predicting tissue maturity as an example of neotissue-related properties of interest. Samples used in this study were prepared using norbornene-modified hyaluronic acid scaffolds with or without the conjugation of an N-cadherin mimetic peptide. Selected samples were supplemented with transforming growth factor-beta1 or bone morphogenetic protein-9 growth factor. Some samples were frozen in cell lysis buffer, while the remaining samples were frozen in PBS until required for NIR analysis. The ML models for classifying the spectra of the constructs according to the four constituents exhibited high to fair performances, with F1 scores ranging from 0.9 to 0.52. Moreover, controlling for the four constituents significantly improved the performance of the models for predicting tissue maturity, with improvement in F1 scores ranging from 0.09 to 0.77. In conclusion, non-neotissue constituents have measurable effects on the NIR spectra of tissue-engineered constructs that can be detected by ML algorithms and introduce bias in the assessment of the constructs by NIR spectroscopy. Therefore, controlling for these constituents is necessary for reliable NIR-based assessments of tissue-engineered constructs.

Although frozen section pathology (FSP) is commonly performed during surgery for glioma-suspicious lesions, confounders of accuracy are largely unknown. FSP and final diagnosis were compared in 398 surgeries for glioma-suspicious lesions. Diagnostic accuracy, risk factors for diagnostic shift from neoplastic to non-neoplastic tissue and vice versa according to the final diagnosis, and the impact on intraoperative and postoperative decision-making were analyzed. Diagnostic shift occurred in 70 cases (18%), and sensitivity, specificity, and the positive (PPV) and negative (NPV) predictive value of FSP were 82.5%, 77.8%, 99.4%, and 9.3%, respectively. No correlations between shift and patients\' age and sex, sample fluorescence or volume, tumor location, correct information on the pathology form, final high- or low-grade histology, or molecular alterations were found (p > .05, each). Shift was more common after irradiation (25% vs 15%; p = .025) or chemotherapy (26% vs 15%; p = .022) than in treatment naïve cases and correlated with the type of surgery (p = .002). FSP altered intraoperative decision-making in 25 cases (6%). Postoperative shift led to repeated surgery in 12 patients (3%). In 45 cases, in which FSP and final diagnosis based on the same tissue, shift occurred in only 5 patients (11%), and sensitivity, specificity, PPV, and NPV for FSP were 77.4%, 78.6%, 88.9%, and 61.1%, respectively. No correlations between diagnostic shift and any of the analyzed variables were found (p > .05, each). Although accuracy of FSP during glioma surgery is sufficient, moderate NPV should be considered during intraoperative decision-making. While confounders are sparse, accuracy might be increased by repeated sampling. Diagnostic shift rarely alters postoperative treatment strategy.