Clinical Diagnostic Algorithm Research Articles

OPTIMIZATION OF ANTIBACTERIAL THERAPY FOR NONSPECIFIC VAGINITIS IN WOMEN OF REPRODUCTIVE AGE

Objective. To study the bacteriological composition and sensitivity of vaginal microflora and to optimize antibacterial therapy in women of reproductive age with aerobic vaginitis and bacterial vaginosis.
 Methods. 160 women (100%) were examined, which were divided into 2 clinical groups with subgroups: the main group - 94 (58,8 %) patients with nonspecific vaginitis, who received treatment according to developed clinical diagnostic algorithms and schemes. The comparison group included 66 (41,2 %) patients with nonspecific vaginitis, who received treatment according to known protocols. Methods: general clinical examination, gynecological examination, microscopic study (microscopy of vaginal smears according to the Amsel, Nugent and Donders criteria), bacteriological seeding and determination of the microflora’s sensitivity to antibacterial drugs on the automatic microbiological analyzer “VITEK 2” (France), statistical.
 Results. In women with AV the highest percentage of sensitivity of vaginal microflora was to moxifloxacin - 30,0 % and there were no resistant pathogens, in patients with BV – sensitivity to secnidazole was 86,3 %. After appropriate antibiotics were prescribed, a significant decrease was established in the main group of Escherichia coli (c2=7,23; P=0,008), Staphylococcus aureus (c2=3,87; P<0,049), Streptococcus agalactiae (c2=3,87; P<0,049) in AV, and a significant decrease of Gardnerella vaginalis (c2=28,20; P=0,001) і Atopobium vaginae (c2=3,87; P<0,049) in BV.
 Conclusion. Establishing the type of causative bacteria, its sensitivity to antibiotics and the appointment of rational antibacterial therapy are likely to improve clinical effectiveness in the near and long terms, reduce frequency of recurrence of nonspecific vaginitis.

Takotsubo cardiomyopathy. Literature review: clinical performance, diagnostic algorithm, treatment, prognosis. Part II

Up-to-date data on the problem of takotsubo cardiomyopathy, including data on the clinical manifestations, diagnostic algorithm and treatment approaches, as well as the prognosis of possible complications is presented in review.

Human Borna disease virus 1 encephalitis shows marked pro-inflammatory biomarker and tissue immunoactivation during the course of disease

ABSTRACT Human Borna disease virus 1 (BoDV-1) encephalitis is a severe emerging disease with a very high case-fatality rate. While the clinical disease, case definitions, diagnostic algorithms and neuropathology have been described, very little is known about the immunological processes of human BoDV-1 encephalitis. Here, we analyzed serum and cerebrospinal fluid (CSF) samples from 10 patients with fatal BoDV-1 encephalitis for changes of different cytokines, chemokines, growth factors and other biomarkers over time. From one of these individuals, also autoptic formalin-fixed brain tissue was analyzed for the expression of inflammatory biomarkers by mRNA levels and immunostaining; in a further patient, only formalin-fixed brain tissue was available and examined in addition. A marked and increasing immune activation from the initial phase to the last phase of acute BoDV-1 encephalitis is shown in serum and CSF, characterized by cytokine concentration changes (IFNγ, IL-5, IL-6, IL-9, IL-10, IL-12p40, IL-13, IL-18, TGF-β1) with a predominantly pro-inflammatory pattern over time. IFNγ production was demonstrated in endothelial cells, astrocytes and microglia, IL-6 in activated microglia, and TGF-β1 in endothelial cells, activated astrocytes and microglia. This was paralleled by an increase of chemokines (CCL-2, CCL-5, CXCL-10, IL-8) to attract immune cells to the site of infection, contributing to inflammation and tissue damage. Pathologically low growth factor levels (BDNF, β-NGF, PDGF) were seen. Changed levels of arginase and sTREM further fostered the pro-inflammatory state. This dysbalanced, pro-inflammatory state likely contributes importantly to the fatal outcome of human BoDV-1 encephalitis, and might be a key target for possible treatment attempts.

Approach to a problem of the progressive muscular dystrophies in children: modern clinic-diagnostic algorithm

Objective — to study the features of clinical symptoms of progressive muscular dystrophies (PMD) in children and to improve their clinical diagnostic algorithm.
 Methods and subjects. Three groups of children were examined: 33 children with Duchenne PMD aged 2 to 16 years, 7 — with lumbosacral forms of muscular dystrophies aged 3 months to 16 years and 19 — with spinal muscular atrophy aged 3 months to 16 years. The duration of the disease ranged from 3 months to 12 years. Patients underwent clinical and neurological examination to determine the leading clinical syndromes. Motor functions were evaluated on unified scales. Based on the obtained data, the degree of loss of active movements and muscle strength was objectively determined. Assessment of motor dynamics was performed using the NSA (North Star Ambulatory Assessment Worksheet) scale, the 6‑minute gait test, and other functional tests. CHOP — INTEND and HINE2 scales were used in patients with type I spinal muscular atrophy, and Motor Function Measure (MFM), Hammersmith, RULM, etc. scales were used in children with type II and III. Blood biochemical analysis was also performed to determine the level of creatine phosphokinase and lactate dehydrogenase in the blood. Instrumental research methods were used (electroneuromyography, spinal radiography in two projections), in some cases — magnetic resonance imaging was applied. The last stage was molecular genetic diagnosis and verification of clinical diagnosis. After the final diagnosis, patients with Duchenne PMD were prescribed combination therapy (hormonal (corticosteroids) and physiotherapy) according to an international care protocol. Patients are being monitored.
 Results. Complete history taking, timely detection of the first symptoms of the disease and assessment of their dynamics, analysis of neurological symptoms are important for confirming the diagnosis of PMD. Given the similar clinical symptoms in the onset of various forms of PMD to confirm the diagnosis should follow a certain stage of research. Molecular genetic diagnostics should be performed only after evaluation of the results of general clinical, instrumental and laboratory examination of the child. Timely clarification of the clinical diagnosis of PMD, in particular Duchenne forms, helps to justify the appointment of glucocorticosteroids and disease‑modifying therapy.
 Conclusions. Treating a patient according to international standards will help stop the process of muscle atrophy with a timely diagnosis.

P005 Performance of giant cell arteritis pre-test probability score in a tertiary care setting

Abstract Background/Aims Giant cell arteritis (GCA) is a chronic, idiopathic, granulomatous vasculitis of medium and large arteries comprising overlapping phenotypes of cranial arteritis and extracranial GCA. Vascular complications are generally due to delay in diagnosis and initiation of effective treatment. Due to the imminent risk of visual loss and other ischaemic complications it is vital to secure the diagnosis and it is equally important to exclude the mimics as the treatment of GCA has it's own complications. The objective of this quality improvement project was to assess the performance of Southend GCA Pre-test Probability Score (GCA PS) in a cohort of patients who were referred urgently with suspected GCA to the Rheumatology Department of Addenbrooke’s Hospital. Methods We analysed the data of 50 new patients seen between Aug 2019 and Feb 2020. GCA PS were calculated based on the information from GPs (clinical and biochemical data). The likely hood of GCA was determined on review after 1 month, based on the clinical, biochemical, histopathological data and response to steroids. Results A total of 50 cases were included in the study. Thirty-eight (76%) of them were females while 12(24%) were males. The median age was 68.5. The median probability score was 12, it ranged between 0 to 24. Finally, 25 patients were diagnosed as likely to have GCA based on clinical, biochemical, histopathological findings and response to steroids. The lowest probability score among those who had a positive biopsy was 10. The p value for the likelihood of GCA when the probability score was 10 or higher was 0.0001 which was very significant. Conclusion GCA pre-test probability score is a very promising and utilitarian tool for risk stratification of patients with suspected GCA and prediction of the likelihood of GCA. It enables exclusion of GCA in cases with low probability score and to have a higher degree of scrutiny in those with intermediate and high probability scores. Clinical diagnostic algorithm based on the BSR guidelines could further be utilised for confirmation. Disclosure P. Kadamban: None. S. Pattapola: None. H. Alkoky: None. N. Jordan: None. B. Gupta: None.

Clinical diagnostic algorithm in defining tuberculous unilateral pleural effusion in high tuberculosis burden areas short of diagnostic tools.

BackgroundEmpirical treatment was introduced when pathological or microbiological results of tuberculosis (TB) were not available. This report was designed to evaluate an algorithm based on empirical treatment in defining tuberculous pleural effusion (TPE) in high burden areas but short of diagnostic tools.MethodsIn this retrospective study, a total of 924 eligible patients were enrolled and 203 (22.0%) were primarily diagnosed as TPE by our diagnostic algorithm based on effusion characteristics [adenosine deaminase (ADA) and exudate] and immunoassays [purified protein derivative (PPD), M. tuberculosis antibody (TB-Ab) and interferon-gamma release assay (IGRA)]. All diagnosed cases received World Health Organization (WHO) standard anti-TB treatment and 187 of them had at least one year of follow-up. The final diagnosis and prognosis of these patients were traced and recorded.ResultsA total of 177 (94.65%) cases benefited from standard treatment, 5 (2.67%) failed due to early termination or drug resistance, and 5 (2.67%) were finally confirmed as misdiagnosis. Regarding diagnostic efficacy, 72 (30.13%) patients received four TB tests, and the combination of the four tests could increase the diagnosis of TPE. Besides, receiving operating characteristics curve (ROC) analysis revealed that our algorithm was the best method to differentiate TPE from malignant pleural effusion (MPE) with higher sensitivity and specificity than other serum markers.ConclusionsThis clinical diagnostic algorithm was an efficient and available method for the diagnosis of TPE. This diagnostic algorithm should be implemented in regions with high TB prevalence but short of diagnostic tools.

The Role of Nuclear Medicine Imaging with 18F-FDG PET/CT, Combined 111In-WBC/99mTc-Nanocoll, and 99mTc-HDP SPECT/CT in the Evaluation of Patients with Chronic Problems after TKA or THA in a Prospective Study.

Background: The aim of this prospective study was to assess the diagnostic value of nuclear imaging with 18F-FDG PET/CT (FDG PET/CT), combined 111In-WBC/99mTc-Nanocoll, and 99mTc-HDP SPECT/CT (dual-isotope WBC/bone marrow scan) for patients with chronic problems related to knee or hip prostheses (TKA or THA) scheduled by a structured multidisciplinary algorithm. Materials and Methods: Fifty-five patients underwent imaging with 99mTc–HDP SPECT/CT (bone scan), dual-isotope WBC/bone marrow scan, and FDG PET/CT. The final diagnosis of prosthetic joint infection (PJI) and/or loosening was based on the intraoperative findings and microbiological culture results and the clinical follow-up. Results: The diagnostic performance of dual-isotope WBC/bone marrow SPECT/CT for PJI showed a sensitivity of 100% (CI 0.74–1.00), a specificity of 97% (CI 0.82–1.00), and an accuracy of 98% (CI 0.88–1.00); for PET/CT, the sensitivity, specificity, and accuracy were 100% (CI 0.74–1.00), 71% (CI 0.56–0.90), and 79% (CI 0.68–0.93), respectively. Conclusions: In a standardized prospectively scheduled patient group, the results showed highly specific performance of combined dual-isotope WBC/bone marrow SPECT/CT in confirming chronic PJI. FDG PET/CT has an appropriate accuracy, but the utility of its use in the clinical diagnostic algorithm of suspected PJI needs further evidence.

Streptococcal Pharyngitis and Rheumatic Fever

Streptococcus pyogenes (Group A Streptococcus) causes a variety of diseases, from benign self-limiting infections of the skin or throat to lethal infections of soft tissue accompanied by multi-organ failure. GAS is one of significant species among Gram-positive pathogens which is responsible for several suppurative infections and non-suppurative sequelae. They also cause pharyngitis, streptococcal toxic shock syndrome (STSS), necrotizing fasciitis and other diseases. Currently, global burden of RF / RHD is undervalued. In 2010, RF and RHD were estimated as 15.6 million cases and deaths around 200,000 annually. Laboratory diagnosis includes cultural techniques, serology, PYR test, Bacitracin susceptibility test and antibiotic resistance testing helps in differentiating the Streptococcus pyogenes from other groups of Streptococci. Most of the Acute Rheumatic Fever cases gets missed or does not present in the initial stage rather it has been developed into advanced Rheumatic Heart Disease condition. Modified Jones criteria in 2015 will be helpful especially to the low risk population as it is challenging because of limited access to primary health care, diagnosis of streptococcal disease. In addition to this revised criteria, diagnosis still relies on clinical diagnostic algorithm. Vaccines based on M protein and T antigens are continuing to evolve with different results. Ongoing vaccine development is still challenging for the GAS research community, it will make a positive and lasting impact on the peoples globally.

Characteristics of patients presenting with acute myocardial injury with non-obstructive coronary arteries in Sfax, Tunisia

In approximately 4–10% of patients with acute myocardial infarction, coronary angiography does not reveal an obstructive coronary stenosis. This is known as myocardial infarction with non-obstructive coronary arteries (MINOCA). Therefore, mechanisms are not unequivocal and there are a variety of aetiologies grouping ischemic and non-ischemic causes, for this reason the generic term for MINOCA should be replaced with acute myocardial injury with non-obstructive coronary arteries (aMINOCA). Prospective study including all patients presenting aMINOCA, between 2019 and 2020. Other imaging tests such as echocardiography and CMR were used to better support the aetiological diagnosis. Among 1032 consecutive patients admitted for acute myocardial infarction, aMINOCA was identified in 31 (4%) patients and clinical presentation was more often STEMI than NSTEMI (52% vs. 48%). Median age was 47.3 years, male predominance (81%). Two patients presented with cardiogenic shock. Tobacco use was the most noted risk factor (67.7%). According to a clinical diagnostic algorithm using 2D STE and CMR imaging, diagnostic accuracy was 90% to identify causes of aMINOCA (38.7% myocarditis, 32.3% MI, and 19.4% Takotsubo cardiomyopathy). Peak troponin levels were significantly higher in the MI group (21.5 ± 29.24 vs. 10 ± 21.4, P = 0.035). However, CRP was significantly higher in myocarditis group (36 ± 45 vs. 4.7 ± 4, P = 0.007). There was no difference between MI and myocarditis groups in clinical presentation with or without ST elevation, in the mean left ventricular ejection fraction and in the LV Global longitudinal systolic strain. At follow-up, one death was noted in Takotsubo group. Non-obstructive coronary myocardial injury is a rare clinical entity that affects a particularly young population, with a predominance of men in our country. Clinical diagnosis algorithm with echocardiography and CMR imaging established a diagnosis in almost 9 of 10 cases.

A machine learning–based clinical decision support algorithm for reducing unnecessary coronary angiograms

BackgroundConventional clinical risk scores and diagnostic algorithms are proving to be suboptimal in the prediction of obstructive coronary artery disease, contributing to the low diagnostic yield of invasive angiography. Machine learning could help better predict which patients would benefit from invasive angiography vs other noninvasive diagnostic modalities.ObjectiveTo reduce patient risk and cost to the healthcare system by improving the diagnostic yield of invasive coronary angiography through optimized outpatient selection.MethodsRetrospective analysis of 12 years of referral data from a provincial cardiac registry, including all patients referred for invasive angiography of more than 1.4 million individuals in Ontario, Canada. Stable outpatients undergoing coronary angiography during the study period were included in the analysis. The training set (80% random sample, n = 23,750) was used to develop 8 prediction models in Python using grid-search cross-validation. The test set (20% random sample, n = 5938), evaluated the discrimination performance of each model.ResultsThe machine-learning model achieved a substantially better performance (area under the receiver operating characteristics curve: 0.81) than existing models for predicting obstructive coronary artery disease in patients referred for invasive angiography. It significantly outperformed both the reference model and current clinical practice with a net reclassification index of 27.8% (95% confidence interval [CI]: [24.9%–30.8%], P value <.01) and 44.7% (95% CI: [42.4%–47.0%], P value <.01), respectively.ConclusionThis prediction model, when coupled with a point-of-care, online decision support tool to be used by referring physicians, could improve the diagnostic yield of invasive coronary angiography in stable, elective outpatients, thus improving patient safety and reducing healthcare costs.

Mycophenolate Mofetil and Clostridium difficile-associated Colitis

Aim.A clinical observation of colitis conditioned by mycophenolate mofetil intake and concomitant Clostridium difficile-associated disease.Key points.Mycophenolate mofetil (MMF) is an active immunosuppressant with side effects affecting gastrointestinal tract (GIT). A 37-yo male patient with type 1 diabetes mellitus was admitted at a gastroenterology unit with clinical signs of diarrhoea with haematochezia. A history of diabetic nephropathy and related-donor pre-dialysis kidney transplantation in 2012, since when MMF intake was 2000 mg daily. Catarrhal ulcerative colitis in colonoscopy, C. difficile toxins in pathogen stool panel. Ulcerative, ischaemic colitises and the graft-versus-host disease were ruled out in examination. A positive clinical and endoscopic trend was observed upon MMF withdrawn and start of vancomycin.Conclusion.The case presented illustrates the clinical picture and diagnostic algorithm in MMF-associated colitis. The case-distinctive is association with C. difficile infection.

Interpretability of a Deep Learning Based Approach for the Classification of Skin Lesions into Main Anatomic Body Sites.

Simple SummaryThe detection of skin moles driven by current deep learning based approaches yields impressive results in the classification of malignant melanoma. It has been observed that the specific criteria for in situ and early invasive melanoma highly depend on the anatomic site of the body. To address this problem, we propose a deep learning architecture based framework to classify skin lesions into the three most important anatomic sites, including the face, trunk and extremities, and acral lesions. In this study, we take advantage of pretrained networks,we perform in depth analysis on database, architecture, and result regarding the effectiveness of the proposed framework. Experiments confirm the ability of the developed algorithms to classify skin lesions into the most important anatomical sites with 91.45% overall accuracy for the EfficientNetB0 architecture, which is a state-of-the-art result in this domain.Over the past few decades, different clinical diagnostic algorithms have been proposed to diagnose malignant melanoma in its early stages. Furthermore, the detection of skin moles driven by current deep learning based approaches yields impressive results in the classification of malignant melanoma. However, in all these approaches, the researchers do not take into account the origin of the skin lesion. It has been observed that the specific criteria for in situ and early invasive melanoma highly depend on the anatomic site of the body. To address this problem, we propose a deep learning architecture based framework to classify skin lesions into the three most important anatomic sites, including the face, trunk and extremities, and acral lesions. In this study, we take advantage of pretrained networks, including VGG19, ResNet50, Xception, DenseNet121, and EfficientNetB0, to calculate the features with an adjusted and densely connected classifier. Furthermore, we perform in depth analysis on database, architecture, and result regarding the effectiveness of the proposed framework. Experiments confirm the ability of the developed algorithms to classify skin lesions into the most important anatomical sites with 91.45% overall accuracy for the EfficientNetB0 architecture, which is a state-of-the-art result in this domain.

Validation of community health worker identification of maternal puerperal sepsis using a clinical diagnostic algorithm in Bangladesh and Pakistan.

BackgroundPuerperal sepsis (PP sepsis) is a leading cause of maternal mortality globally. The majority of maternal sepsis cases and deaths occur at home and remain undiagnosed and under-reported. In this paper, we present findings from a nested case-control study in Bangladesh and Pakistan which sought to assess the validity of community health worker (CHW) identification of PP sepsis using a clinical diagnostic algorithm with physician assessment and classification used as the gold standard.MethodsUp to 300 postpartum women were enrolled in each of the 3 sites 1) Sylhet, Bangladesh (n = 278), 2) Karachi, Pakistan (n = 278) and 3) Matiari, Pakistan (n = 300). Index cases were women with suspected PP Sepsis as diagnosed by CHWs clinical assessment of one or more of the following signs and symptoms: temperature (recorded fever ≥38.1°C, reported history of fever, lower abdominal or pelvic pain, and abnormal or foul-smelling discharge. Each case was matched with 3 control women who were diagnosed by CHWs to have no infection. Cases and controls were assessed by trained physicians using the same algorithm implemented by the CHWs. Using physician assessment as the gold standard, Kappa statistics for reliability and diagnostic validity (sensitivity and specificity) are presented with 95% CI. Sensitivity and specificity were adjusted for verification bias.ResultsThe adjusted sensitivity and specificity of CHW identification of PP sepsis across all sites was 82% (Karachi: 78%, Matiari: 78%, Sylhet: 95%) and 90% (Karachi: 95%, Matiari: 85%, Sylhet: 90%) respectively. CHW-Physician agreement was highest for moderate and high fever (range across sites: K = 0.84-0.97) and lowest for lower abdominal pain (K = 0.30-0.34). The clinical signs and symptoms for other conditions were reported infrequently, however, the CHW-physician agreement was high for all symptoms except severe headache/ blurred vision (K = 0.13-0.38) and reported “lower abdominal pain without fever” (K = 0.39-0.57).ConclusionIn all sites, CHWs with limited training were able to identify signs and symptoms and to classify cases of PP sepsis with high validity. Integrating postpartum infection screening into existing community-based platforms and post-natal visits is a promising strategy to monitor women for PP sepsis - improving delivery of cohesive maternal and child health care in low resource settings.

Acute Coronary Syndrome (ACS) in Preclinical Emergency Medicine

Acute coronary syndrome (ACS) is a common diagnosis in preclinical emergency medicine. The term summarizes the acute manifestations of coronary artery disease. It ranges from unstable angina pectoris via cardiogenic shock to sudden cardiac death. The leading key symptom is chest pain. With this trigger symptom, a clinical diagnostic algorithm is initiated, acting quickly on the suspected diagnosis of acute myocardial infarction. Due to the potentially life-threatening course, rapid diagnosis and initiation of therapeutic measures is crucial. Pre-clinical antithrombotic medication and therapy for accompanying symptoms are paramount. As part of the initial assessment, important differential diagnoses should be considered and, within the first 10 minutes after medical contact, an ECG diagnosis should differentiate between ACS with and without ST segment elevations. If ACS is diagnosed, acetylsalicylic acid should be given to inhibit platelet aggregation. The benefits outweigh the very low risk of unnecessary administration. Patients with ACS should be taken to hospital immediately for coronary interventions (PCI). In the case of an ACS with ST segment elevations, reperfusion therapy should be carried out within 120 minutes. In the case of an ACS without ST segment elevations, the time limit (2 - 72 h) until reperfusion is based on the risk stratification. In the majority of cases, the coronary stenosis causing the infarction can be treated with PCI. However, invasive diagnostics show no significant stenosis in a significant proportion of patients with myocardial infarction (prevalence 1 - 14%). This is known as "myocardial infarction with non-obstructive coronary arteries" (MINOCA) and further differential diagnosis should be initiated in these patients.

Pediatric Paroxysmal Exercise-Induced Neurological Symptoms: Clinical Spectrum and Diagnostic Algorithm.

Paroxysmal exercise-induced neurological symptoms (PENS) encompass a wide spectrum of clinical phenomena commonly presenting during childhood and characteristically elicited by physical exercise. Interestingly, few shared pathogenetic mechanisms have been identified beyond the well-known entity of paroxysmal exercise-induced dyskinesia, PENS could be part of more complex phenotypes including neuromuscular, neurodegenerative, and neurometabolic disease, epilepsies, and psychogenetic disorders. The wide and partially overlapping phenotypes and the genetic heterogeneity make the differential diagnosis frequently difficult and delayed; however, since some of these disorders may be treatable, a prompt diagnosis is mandatory. Therefore, an accurate characterization of these symptoms is pivotal for orienting more targeted biochemical, radiological, neurophysiological, and genetic investigations and finally treatment. In this article, we review the clinical, genetic, pathophysiologic, and therapeutic landscape of paroxysmal exercise induced neurological symptoms, focusing on phenomenology and differential diagnosis.

A comparison of diagnostic algorithms and clinical parameters to diagnose ventilator-associated pneumonia: a prospective observational study

BackgroundSuspicion and clinical criteria continue to serve as the foundation for ventilator-associated pneumonia (VAP) diagnosis, however the criteria used to diagnose VAP vary widely. Data from head-to-head comparisons of clinical diagnostic algorithms is lacking, thus a prospective observational study was performed to determine the performance characteristics of the Johanson criteria, Clinical Pulmonary Infection Score (CPIS), and Centers for Disease Control and Prevention’s National Healthcare Safety Network (CDC/NHSN) criteria as compared to Hospital in Europe Link for Infection Control through Surveillance (HELICS) reference standard.MethodsA prospective observational cohort study was performed in three mixed medical-surgical ICUs from one academic medical center from 1 October 2016 to 30 April 2018. VAP diagnostic criteria were applied to each patient including CDC/NHSN, CPIS, HELICS and Johanson criteria. Tracheal aspirate cultures (TAC) and serum procalcitonin values were obtained for each patient.ResultsEighty-five patients were enrolled (VAP 45, controls 40). Using HELICS as the reference standard, the sensitivity and specificity for each of the assessed diagnostic algorithms were: CDC/NHSN (Sensitivity 54.2%; Specificity 100%), CPIS (Sensitivity 68.75%; Specificity 95.23%), Johanson (Sensitivity 67.69%; Specificity 95%). The positive TAC rate was 81.2%. The sensitivity for positive TAC with the serum procalcitonin level > 0.5 ng/ml was 51.8%.ConclusionVAP remains a considerable source of morbidity and mortality in modern intensive care units. The optimal diagnostic method remains unclear. Using HELICS criteria as the reference standard, CPIS had the greatest comparative diagnostic accuracy, whereas the sensitivity of the CDC/NHSN was only marginally better than a positive TAC plus serum procalcitonin > 0.5 ng/ml. Algorithm accuracy was improved by adding serum procalcitonin > 0.5 ng/ml, but not positive quantitative TAC.Trial Registration: Not indicated for this study type.

Use of Pulmonary Computed Tomography for Evaluating Suspected Stroke-Associated Pneumonia

ObjectivesAccurate and timely diagnosis of pneumonia complicating stroke remains challenging and the diagnostic accuracy of chest X-ray (CXR) in the setting of stroke-associated pneumonia (SAP) is uncertain. The overall objective of this study was to evaluate the use of pulmonary computed tomography (CT) in diagnosis of suspected SAP. Materials and MethodsPatients with acute ischemic stroke (IS) or intracerebral hemorrhage (ICH) were recruited within 24h of clinically suspected SAP and underwent non-contrast pulmonary CT within 48h of antibiotic initiation. CXR and pulmonary CT were reported by two radiologists. Pulmonary CT was used as the reference standard for final diagnosis of SAP. Sensitivity, specificity, positive and negative predictive values (PPV and NPV), and diagnostic odds ratio (OR) for CXR were calculated. Results40 patients (36 IS, 4 ICH) with a median age of 78y (range 44y-90y) and a median National Institute of Health Stroke Scale score of 13 (range 3-31) were included. All patients had at least one CXR and 35/40 patients (88%) underwent pulmonary CT. Changes consistent with pneumonia were present in 15/40 CXRs (38%) and 12/35 pulmonary CTs (34%). 9/35 pulmonary CTs (26%) were reported normal. CXR had a sensitivity of 58.3%, specificity of 73.9%, PPV of 53.8 %, NPV of 77.2 %, diagnostic OR of 3.7 (95% CI 0.7 - 22) and an accuracy of 68.5% (95% CI 50.7% -83.1%). DiscussionCXR has limited diagnostic accuracy in SAP. The majority of patients started on antibiotics had no evidence of pneumonia on pulmonary CT with potential implications for antibiotic stewardship. ConclusionsPulmonary CT could be applied as a reference standard for evaluation of clinical and biomarker diagnostic SAP algorithms in multi-center studies.

Update on cerebrotendinous xanthomatosis.

Cerebrotendinous xanthomatosis (CTX) is a rare genetic lipid storage disorder with highly pleomorphic clinical phenotype. Complications of this disease can be devastating and may include severe cognitive impairment and dementia in later stages. Disease progression can be prevented or stabilized by bile acid replacement therapy, although a subset of patients with advanced disease continue to deteriorate despite therapy. Delayed diagnosis of CTX continues to impede effective treatment. A clinical diagnostic algorithm for CTX was developed that can decrease the age of diagnosis of CTX. The strategy of screening children with bilateral juvenile cataracts for CTX also improved diagnosis, as this group had a 500-fold higher-rate of CTX than the general population. Improved diagnosis of CTX is critical, as patients treated early in the course of the disease have significantly better outcomes compared with those treated later. More sensitive and specific biochemical testing for CTX has been developed that is potentially more informative than blood cholestanol to assess treatment efficacy and medication compliance in CTX. Because we are recognizing more severe presentations of CTX in infants and children, and delayed diagnosis and treatment worsens the prognosis, CTX is an excellent candidate disorder for newborn screening using recently reported methods for newborn dried bloodspot analysis.

Modern methods for evaluating the process of the wound process

The article presents the data of a comprehensive assessment of the course of the wound process using modern methods. The effectiveness of additional physical methods of sanitation in local treatment has been proved.&#x0D; It was found that the proposed diagnostic algorithm made it possible to identify the features of the wound process, as well as the features and patterns of pathomorphological changes. The proposed clinical diagnostic algorithm can be used to assess the effectiveness of various means of local wound treatment, including physical methods of influencing the wound process (2 figs, bibliography: 11 refs).

Interstitial pneumonitis in the COVID-19 era: a difficult differential diagnosis in patients with lung cancer.

In this coronavirus 2019 (COVID-19) era, when pneumonitis occurs in patients with lung cancer receiving immune checkpoint inhibitors (ICIs), a major challenge is to make a rapid and correct differential diagnosis among drug-induced pulmonary toxicity, tumour progression, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced pneumonitis. While waiting for polymerase chain reaction (PCR) testing results, an accurate evaluation of the symptoms and serologic features can help us make a first diagnostic hypothesis and quickly start correct treatment. Physicians need a collaborative effort to develop and share a common database reporting clinical (anosmia, dysgeusia), serologic, and radiologic data in ICI-treated patients with lung cancer developing interstitial disease to create an evidence-based clinical diagnostic algorithm. This tool will continue to be helpful when we emerge from the pandemic crisis into a world in which COVID-19 may not have been eradicated to better select the target population requiring the most resource-consuming PCR tests.