The aim of this paper is to build a case for the utility of conceptualizing ADHD, not as a unitary disorder that contains several subtypes, but rather as a marker of impairment in attention and/or impulsivity that can be used to identify one of several disorders belonging to a spectrum. The literature will be reviewed to provide an overview of what is known about ADHD in terms of heterogeneity in symptomatology, neuropsychology, neurobiology, as well as comorbidity with other diseases and treatment options. The data from these areas of research will be critically analyzed to support the construct of a spectrum of disorders that can capture the great variability that exists between individuals with ADHD and can discriminate between separate disorders that manifest similar symptoms. The symptoms associated with ADHD can be viewed as dimensional markers that point to a spectrum of related disorders that have as part of their characteristics impairments of attention and impulsivity. The spectrum can accommodate symmetrically and asymmetrically comorbid psychiatric disorders associated with ADHD as well as the wide heterogeneity known to be a part of the ADHD disorder. Individuals presenting with impairments associated with ADHD should be treated as having a positive marker for a spectrum disorder that has as part of its characteristics impairments of attention and/or impulsivity. The identification of impairment in attention and/or impulsivity should be a starting point for further testing rather than being an endpoint of diagnosis that results in pharmacological treatment that may or may not be the optimal therapy. Rather than continuing to attribute a large amount of heterogeneity in symptom presentation as well as a high degree of symmetric and asymmetric comorbidity to a single disorder, clinical evaluation should turn to the diagnosis of the type of attentional deficit and/or impulsivity an individual has in order to colocate the individual's disorder on a spectrum that captures the heterogeneity in symptomatology, the symmetrical and asymmetrical comorbidity, as well as subthreshold presentation and other variants often worked into the disorder of ADHD. The spectrum model can accommodate not only the psychophysiological profiles of patients, but is also consistent with what is known about the functional heterogeneity of the prefrontal cortex as well as the construct that cognitive processes are supported by overlapping and collaborative networks.

BackgroundThe duodenum and the left renal vein occupy the vascular angle made by the superior mesenteric artery and the aorta. When the angle becomes too acute, compression of either structure can occur. Each type of compression is associated with specific clinical symptoms that constitute a rare disorder. If clinical symptoms are mild, conservative treatment is implemented. However, surgery is often the only solution that can improve quality of life and/or avoid life-threatening complications. This report describes a case of a patient with both types of aortomesenteric compression that required two separate surgeries to alleviate all symptoms.Case presentationA 20-year-old white woman presented to the Emergency Room complaining of sudden onset severe left flank and lower left quadrant abdominal pain, nausea, and vomiting. A clinical work-up revealed elevated white blood cells and hematuria. She was discharged with a diagnosis of urinary tract infection. Symptoms continued to worsen over the subsequent 2 months. Repeated and extensive clinical work-ups failed to suggest evidence of serious pathology. Ultimately, an endoscopy revealed obstruction of her duodenum, and barium swallow identified compression by the superior mesenteric artery, leading to the diagnosis of superior mesenteric artery syndrome. She underwent a Roux-en-Y duodenojejunostomy. Six weeks later she continued to have severe left-sided pain and intermittent hematuria. Venography revealed compression of the left renal vein, extensive pelvic varices, and significant engorgement of her left ovarian vein. A diagnosis of nutcracker syndrome was made and a left renal vein transposition was performed. Significant improvement was seen after 8 weeks.ConclusionsThe disorders associated with aortomesenteric compression can lead to serious symptoms and sometimes death. Diagnosis is challenging not only because of the lack of awareness of these rare disorders, but also because they are associated with symptoms that are similar to those seen in less serious diseases. Guidance for health care professionals with respect to relevant radiological and clinical markers needs to be reconsidered in order to clarify the etiology of the diseases and create better diagnostic protocols.

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Aims The objective of this study is to establish a predictive model using transparent machine learning (ML) to identify any drivers that characterize therapeutic inertia. Methods Data in the form of both descriptive and dynamic variables collected from electronic records of 1.5 million patients seen at clinics within the Italian Association of Medical Diabetologists between 2005–2019 were analyzed using logic learning machine (LLM), a “clear box” ML technique. Data were subjected to a first stage of modeling to allow ML to automatically select the most relevant factors related to inertia, and then four further modeling steps individuated key variables that discriminated the presence or absence of inertia. Results The LLM model revealed a key role for average glycated hemoglobin (HbA1c) threshold values correlated with the presence or absence of insulin therapeutic inertia with an accuracy of 0.79. The model indicated that a patient's dynamic rather than static glycemic profile has a greater effect on therapeutic inertia. Specifically, the difference in HbA1c between two consecutive visits, what we call the HbA1c gap, plays a crucial role. Namely, insulin therapeutic inertia is correlated with an HbA1c gap of <6.6 mmol/mol (0.6%), but not with an HbA1c gap of >11 mmol/mol (1.0%). Conclusions The results reveal, for the first time, the interrelationship between a patient's glycemic trend defined by sequential HbA1c measurements and timely or delayed initiation of insulin therapy. The results further demonstrate that LLM can provide insight in support of evidence‐based medicine using real world data.