From bytes to bedside: a systematic review on the use and readiness of artificial intelligence in the neonatal and pediatric intensive care unit.

PURPOSE: Despite its promise to enhance patient outcomes and support clinical decision making, clinical use of artificial intelligence (AI) models at the bedside remains limited. Translation of advancements in AI research into tangible clinical benefits is necessary to improve neonatal and pediatric care for critically ill patients. This systematic review seeks to assess the maturity of AI models in neonatal and pediatric intensive care unit (NICU and PICU) treatment, and their risk of bias and objectives. METHODS: We conducted a systematic search in Medline ALL, Embase, Web of Science Core Collection, Cochrane Central Register of Controlled Trials, and Google Scholar. Studies using AI models during NICU or PICU stay were eligible for inclusion. Study design, objective, dataset size, level of validation, risk of bias, and technological readiness of the models were extracted. RESULTS: Out of the 1257 identified studies 262 were included. The majority of studies was conducted in the NICU (66%) and most had a high risk of bias (77%). An insufficient sample size was the main cause for this high risk of bias. No studies were identified that integrated an AI model in routine clinical practice and the majority of the studies remained in the prototyping and model development phase. CONCLUSION: The majority of AI models remain within the testing and prototyping phase and have a high risk of bias. Bridging the gap between designing and clinical implementation of AI models is needed to warrant safe and trustworthy AI models. Specific guidelines and approaches can help improve clinical outcome with usage of AI.

Solar insolation in springtime influences age of onset of bipolar I disorder.

OBJECTIVE: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. METHOD: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. RESULTS: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). CONCLUSION: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.

Inflammatory, cardio-metabolic and diabetic profiling of chronic schizophrenia.

BACKGROUND: There is a growing interest in low-grade inflammatory and metabolic alterations in patients with chronic schizophrenia (SCH). METHODS: Inflammatory (tumor-necrosis factor-α [TNF-α], interferon-γ [IFN-γ], interleukins [IL-1α, IL-1ß, IL-2, IL-4, IL-6, IL-8, IL-10], monocyte chemo-attractant protein-1 [MCP-1]) and growth factors (vascular endothelial growth factor [VEGF], epidermal growth factor [EGF]) were measured in blood serum samples of 105 SCH patients and 148 control subjects (CS). Simultaneously the clinical biomarkers (C-reactive protein [CRP], triglycerides [TG], low-density lipoprotein [LDL-c] and high-density lipoprotein [HDL-c] cholesterol, glycated hemoglobin [HbA1c]) were measured, and body mass index (BMI) was calculated for patients. RESULTS: Several cyto-/chemokines (IFN-γ, MCP-1, IL-2, IL-6, IL-8 and IL-10) were significantly (P<0.0000001) elevated in SCH patients compared to CS. Odds ratios, obtained from logistic regression analyses, were significantly elevated for IL-2, IL-6, IL-10, INF-γ, and decreased for TNF-α in SCH group. Among the patients, higher IL-2, IL-6, INF-γ and lower MCP-1 levels as well as male gender were together significant (P<0.000001) predictors of higher HbA1c levels, and TG/HDL-c parameter was associated with ratios of INF-γ/IL-10 (P=0.004), and INF-γ/IL-4 (P=0.049), HbA1c (P=0.005), INF-γ (P=0.009), as well as LDL-c (P=0.02) levels. CONCLUSIONS: IL-2, IL-6, IL-10 and IFN-γ were the most significant SCH-related markers among the measured cytokines in our patient group. Furthermore, significant associations between pro-/anti-inflammatory imbalance and HbA1c as well as cardio-metabolic risk marker (TG/HDL-c) were observed, indicating higher risks of diabetes and cardiovascular diseases among SCH patients.