A new model to deliver scheduled outpatient care

Here we describe an integrated model for scheduled care (the ‘cluster clinic’). Following a pilot in April 2018, cluster clinics were established across Aberdeen City from April 2019 but not the area surrounding Aberdeen (ie, Aberdeenshire). There were 2360 referrals in 2017/2018 (pre-cluster clinic), and 2615 in 2019/2020 (post-Aberdeen City cluster clinics). The proportions of referrals from City practices seen pre-cluster and post-cluster were 72% and 56%, respectively, and from Shire practices the corresponding proportions were 70% and 65%. The cluster clinic received positive feedback from parents and referring clinicians and was not associated with increased ‘missed diagnoses’ compared with business as usual clinic. The cluster clinic model is a realistic and effective method to deliver integrated scheduled care for children.

What Every Internist-Endocrinologist Should Know about Rare Genetic Syndromes in Order to Prevent Needless Diagnostics, Missed Diagnoses and Medical Complications: Five Years of ‘Internal Medicine for Rare Genetic Syndromes’

Patients with complex rare genetic syndromes (CRGS) have combined medical problems affecting multiple organ systems. Pediatric multidisciplinary (MD) care has improved life expectancy, however, transfer to internal medicine is hindered by the lack of adequate MD care for adults. We have launched an MD outpatient clinic providing syndrome-specific care for adults with CRGS, which, to our knowledge, is the first one worldwide in the field of internal medicine. Between 2015 and 2020, we have treated 720 adults with over 60 syndromes. Eighty-nine percent of the syndromes were associated with endocrine problems. We describe case series of missed diagnoses and patients who had undergone extensive diagnostic testing for symptoms that could actually be explained by their syndrome. Based on our experiences and review of the literature, we provide an algorithm for the clinical approach of health problems in CRGS adults. We conclude that missed diagnoses and needless invasive tests seem common in CRGS adults. Due to the increased life expectancy, an increasing number of patients with CRGS will transfer to adult endocrinology. Internist-endocrinologists (in training) should be aware of their special needs and medical pitfalls of CRGS will help prevent the burden of unnecessary diagnostics and under- and overtreatment.

Anion gap physiology and faults of the correction formula

Disclaimer In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Purpose The anion gap is a calculated fundamental laboratory parameter used to identify and monitor acid-base disturbances. A recently popularized correction formula transforms the resulting integer to compensate for hypoalbuminemia and improve diagnostic yield. Clinical pharmacists should be aware of the underlying biochemistry, interpretation, and limitations of this formula to discern drug- and disease-related etiologies. Summary The anion gap is utilized in most care settings, ranging from outpatient monitoring to inpatient intensive care units. Supported by decades of experience, the original anion gap derives its value from its simplicity. Applying the anion gap in metabolic acidosis can help narrow differential diagnosis and detect concomitant acid-base disorders. To account for hypoalbuminemia and potential missed diagnoses, a correction formula was developed to improve sensitivity. Yet, the law of electroneutrality ensures that hypoalbuminemia is already accounted for in the original anion gap, and the proposed correction formula was derived from samples unrepresentative of human physiology. Evidence from clinical trials shows no benefit from applying the correction formula. Conclusion There is no advantage to correcting the anion gap, and such correction may increase the risk of misinterpretation or error. Clinicians should understand these limitations when diagnosing or trending acid-base disturbances.

Red urine and a red herring – diagnosing rare diseases in the light of the COVID-19 pandemic

Background The COVID-19 pandemic has occupied the time and resources of health care professionals for more than 1 year. The risk of missed diagnoses has been discussed in the medical literature, mainly for common diseases such as cancer and cardiovascular events. However, rare diseases also need appropriate attention in times of a pandemic. Case Report We report a 34-year-old woman with fever, pinprick sensation in her chest and thoracic spine, and dizziness after receiving the first dose of ChAdOx1 nCoV-19 vaccination. The patient’s condition worsened with abdominal pain, red urine, and hyponatremia, needing intensive care admission. Syndrome of inappropriate antidiuretic hormone secretion (SIADH) was diagnosed. Vaccine-induced thrombocytopenia and thrombosis were ruled out. Acute hepatic porphyria was finally diagnosed, and the patient recovered completely after treatment with hemin. Conclusion Currently, the focus of physicians is on COVID-19 and associated medical problems, such as vaccine side effects. However, it is important to be vigilant for other uncommon medical emergencies in medically exceptional situations that may shift our perception.

Glycans as Potential Diagnostic Markers of Traumatic Brain Injury

The diagnosis of mild traumatic brain injury (TBI) is challenging in the acute setting because the symptoms are nonspecific and often transient, or they develop with a delay. In these cases, the criteria for acute head imaging are frequently not fulfilled. This may lead to missed diagnoses in emergency care. There is a need for developing a rapid diagnostic test to verify the presence of TBI using body fluids. Blood, urine, and saliva samples from 11 adult patients (mean age 64 years, SD 24 years) with acute and clinically diagnosed TBI, and 12 healthy volunteers were collected at Turku University Hospital during a period of 5 months. The injuries necessitated hospitalization for at least one day. The TBIs were classified mild in nine cases and severe in two cases. The mean period between the trauma and the time for obtaining the samples was 27 h, SD 11 h. The samples were analyzed in an ISO-certified laboratory for the number of lectin-bound glycan molecules indicating destruction of nerve tissue. The screening was performed on several possible glycans for binding, and the measurement by degree of fluorescence. In the analysis, the group of patients with TBI was compared with healthy volunteers. The results showed a significant decrease (p < 0.05, Wilcoxon rank–sum two-sided test) in the level of two glycans in plasma, but no significant increase for any glycan; in saliva, one glycan showed a significant increase in the TBI group; in urine, three glycans were significantly different between the groups (one showed an increase, whereas two showed a decrease). The results support the idea of conducting more research on how diagnostic glycans could be detected in body fluids after TBI. As a proof-of-concept, significant changes in the concentration of five glycans were found in plasma, saliva, and urine between TBI patients and healthy controls. This may enable the development of a rapid body fluid-based point-of-care test to identify patients with TBI after a head injury.

Cause of Death in Patients in Radiation Oncology

BackgroundThe accurate attribution of death in oncologic patients is a difficult task. The patient’s death is often attributed to his or her underlying cancer and therefore judged as cancer-related. We hypothesized that even though our patient’s cancers were either advanced or metastatic, not all patients had died simply because of their cancer.MethodsA total of 105 patients were included in this retrospective analysis. Patient data were collected from digital and paper-based records. Cause of death was assessed from death certificate and compared to the medical autopsy reports. Discrepancies between premortem and postmortem diagnoses were classified as class I and II discrepancies.ResultsOf 105 patients included, autopsy consent was obtained in 56 cases (53%). Among them, 32 of 56 were palliatively sedated, and 42/56 patients died cancer-related as confirmed by autopsy. The most common cause of death by autopsy report was multiorgan failure followed by a combination of tumor and infection, predominantly lung cancer with pneumonia. Here, 21/56 cases (37%) showed major missed diagnoses: seven cases showed class I, 10 class II, and both discrepancies. The most commonly missed diagnoses in both categories were infections, again mainly pneumonia.ConclusionsCancer was the leading cause of death in our study population. A quarter of the patients, however, did not die due to their advanced or metastatic cancers but of potentially curable causes. We therefore conclude that it is important to consider competing causes of death when treating palliative cancer patients. In a palliative setting, the treatment of a potentially curable complication should be discussed with the patients and their families in a shared decision-making process. From our experience, many patients will decline treatment or even further diagnostics when given the option of best supportive care.

Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment

Background Limited evidence is available on the clinical impact of artificial intelligence (AI) in radiology. Early health technology assessment (HTA) is a methodology to assess the potential value of an innovation at an early stage. We use early HTA to evaluate the potential value of AI software in radiology. As a use-case, we evaluate the cost-effectiveness of AI software aiding the detection of intracranial large vessel occlusions (LVO) in stroke in comparison to standard care. We used a Markov based model from a societal perspective of the United Kingdom predominantly using stroke registry data complemented with pooled outcome data from large, randomized trials. Different scenarios were explored by varying missed diagnoses of LVOs, AI costs and AI performance. Other input parameters were varied to demonstrate model robustness. Results were reported in expected incremental costs (IC) and effects (IE) expressed in quality adjusted life years (QALYs). Results Applying the base case assumptions (6% missed diagnoses of LVOs by clinicians, $40 per AI analysis, 50% reduction of missed LVOs by AI), resulted in cost-savings and incremental QALYs over the projected lifetime (IC: − $156, − 0.23%; IE: + 0.01 QALYs, + 0.07%) per suspected ischemic stroke patient. For each yearly cohort of patients in the UK this translates to a total cost saving of $11 million. Conclusions AI tools for LVO detection in emergency care have the potential to improve healthcare outcomes and save costs. We demonstrate how early HTA may be applied for the evaluation of clinically applied AI software for radiology.

Clinical Evaluation of a Metagenomics-Based Assay for Pneumonia Management

Clinical value of metagenomic next-generation sequencing (mNGS) in pneumonia management is still controversial. A prospective study was conducted to evaluate the clinical impact of PneumoSeq in 57 immunocompetent (ICO) and 75 immunocompromised (ICH) pneumonia patients. The value of PneumoSeq for both etiological and clinical impact investigation in pneumonia was assessed. Among the 276 potential pathogens detected with PneumoSeq in our cohort, 251 (90.9%) were cross-validated. Clinical diagnoses of the causative pathogens were obtained for 97 patients, 90.7% of which were supported by PneumoSeq. Compared to conventional testing, PneumoSeq suggested potentially missed diagnoses in 16.7% of cases (22/132), involving 48 additional pathogenic microorganisms. In 58 (43.9%) cases, PneumoSeq data led to antimicrobial treatment de-escalation (n = 12 in ICO, n = 18 in ICH) and targeted treatment initiation (n = 7 in ICO, n = 21 in ICH). The PneumoSeq assay benefited the diagnosis and clinical management of both ICH and ICO pneumonia patients in real-world settings.