Rejected

There is a lack of diagnostic tools that can objectively measure small fiber neuropathy (SFN) in patients with diabetes mellitus (DM). Recently, nociceptive nerve function was observed by nociceptive detection thresholds (NDTs) and brain evoked potentials (EPs) during intra-epidermal electrical stimulation (IES) targeting Aδ-fibers. In this proof of principle, we studied whether it is possible to measure NDTs combined with EPs in DM patients with and without neuropathic pain. Furthermore, we explored the sensitivity of NDTs and EPs for polyneuropathy in these patients. Five DM patients diagnosed with painful neuropathy (DMp), five DM patients without painful neuropathy (DM), and five healthy controls (HC) were analyzed. These preliminary results showed that we can accurately measure NDTs and EPs in patients with diabetes. Strikingly, increased NDTs were found in DM and DMp compared to HC, of which the DMp showed the largest NDTs. This suggests that NDTs during IES could be a powerful biomarker for monitoring peripheral dysfunctions. Current EEG data of patients did not show any significant differences. The population needs to be enlarged before we can investigate the sensitivity of these NDTs and EPs to diabetic polyneuropathy and associated changes in nociceptive processing in more detail.Clinical Relevance- This proof of principle in a small group of patients with diabetes mellitus potentially treats the observation of the loss of nociceptive function occurring with small fiber neuropathy. That helps the development of a diagnostic measure to monitor future (early-stage) nociceptive dysfunctions in a clinical environment.

Pelvic inflammatory disease (PID) and tubo-ovarian abscess (TOA) are serious diagnoses to consider in reproductive-age women presenting with abdominal or pelvic pain. Management can be medical or surgical depending on severity. This case report outlines the unique presentation of TOA in a 15-year-old female presenting with acute abdominal pain with a recent past surgical history of appendectomy. A discussion of the approach to similar presentations and the importance of maintaining a broad differential diagnosis follows.

Primary leptomeningeal lymphoma (PLML) is a rare disease, comprising less than 1% of all lymphomas. Clinical manifestations include headache, encephalopathy, ataxia, cranial nerve palsy, and myelitis. Diagnosis requires a combination of magnetic resonance images (MRI), cytology, flow cytometry of cerebrospinal fluid (CSF), and an extensive workup to rule out systemic lymphoma. We describe the case of a 49-year-old man who developed subacute onset headache, encephalopathy, and blindness. Whole-body examinations, including a bone marrow trephine biopsy, excluded systemic lymphoma. Brain MRI showed leptomeningeal enhancement. Cytology and flow cytometry of CSF found a clonal B-cell population making a diagnosis of PLML. He began treatment with rituximab and high-dose methotrexate (HD-MTX), with progressive clinical improvement. CSF analysis after two cycles and one intrathecal methotrexate dose was normal. Brain and spinal MRI images plus CSF analysis, along with an extensive workup to exclude systemic lymphoma, are necessary to diagnose PLM. Early treatment with HD-MTX alone or in combination with rituximab improves clinical outcomes.

Phantom Limb Pain (PLP) is a chronic condition frequent among individuals with acquired amputation. PLP has been often investigated with the use of functional MRI focusing on the changes that take place in the sensorimotor cortex after amputation. In the present study, we investigated whether a different type of data, namely electroencephalographic (EEG) recordings, can be used to study the condition. We acquired resting state EEG data from people with and without PLP and then used machine learning for a binary classification task that differentiates the two. Common Spatial Pattern (CSP) decomposition was used as the feature extraction method and two validation schemes were followed for the classification task. Six classifiers (LDA, Log, QDA, LinearSVC, SVC and RF) were optimized through grid search and their performance compared. Two validation approaches, namely all-subjects validation and leave-one-out cross-validation (LOOCV), resulted in high classification accuracy. Most notably, the 93.7% accuracy achieved with SVC in LOOCV holds promise for good diagnostic capabilities using EEG biomarkers. In conclusion, our findings indicate that EEG data is a promising target for future research aiming at elucidating the neural mechanisms underlying PLP and its diagnosis.

A major challenge associated with the Nuss procedure for pectus excavatum repair is postoperative pain control. Early Recovery Program (ERP) protocols for the Nuss procedure are becoming common, but there is a paucity of experience using liposomal bupivacaine (LB), a long-acting local anesthetic, for rib blocks in this setting. We investigated whether a protocol utilizing LB rib blocks decreased opioid use after the Nuss procedure while achieving equivalent pain control.

An inflammatory process involving the pancreas, known as pancreatitis, can be categorized as either acute or chronic and may present in one of many ways. The clinical manifestations of acute pancreatitis are generally limited to epigastric or right upper quadrant pain, while manifestations of chronic pancreatitis are broader and may include abdominal pain in tandem with signs and symptoms of pancreatic endocrine and exocrine insufficiency. An understanding of the initial insult, proper classification, and prognosis are all factors that are of paramount importance as it pertains to managing patients who are afflicted with this disease. Our review delves into the depths of pancreatitis by exploring the embryology and anatomy of the pancreas, the pathophysiology and etiology of acute and chronic pancreatitis, and the medical and surgical management of acute and chronic pancreatitis.

Diagnosis and stratification of chronic pain patients is difficult due to a lack of sensitive biomarkers for altered nociceptive and pain processing. Recent developments enabled to preferentially stimulate epidermal nerve fibers and simultaneously quantify the psychophysical detection probability and neurophysiological EEG responses. In this work, we study whether using one or a combination of both outcome measures could aid in the observation of altered nociceptive processing in chronic pain. A set of features was extracted from data from a total of 66 measurements on 16 failed back surgery syndrome patients and 17 healthy controls. We assessed how well each feature discriminates both groups. Subsequently, we used a random forest classifier to study whether psychophysical features, EEG features or a combination can improve the classification accuracy. It was found that a classification accuracy of 0.77 can be achieved with psychophysical features, while a classification accuracy of 0.65 was achieved using only EEG features.Clinical Relevance-This study shows which combined features of nociceptive detection behavior and evoked EEG responses are most sensitive and specific to altered nociception in failed back surgery syndrome.

Psoriasis is an immune-mediated inflammatory skin disease that causes significant physical and psychological burden to the patient. While there is currently no curative treatment, recent breakthroughs involving stem cell therapy, in particular, adipose tissue-derived from mesenchymal stem cells (AD-MSCs), have been promising. This single-arm study evaluated the feasibility, safety, and efficacy of AD-MSC infusions for the treatment of moderate to severe psoriasis.

The coronavirus disease 2019 (COVID-19) may have multisystem organ involvement. Thrombotic events are well-recognized complications of COVID-19. Such complications may include the pulmonary, renal, and other organs vasculature. The risk of coagulopathy is usually related to the severity of COVID-19 pneumonia. Few cases suggested that the coagulopathy risk may persist for some period after the recovery from COVID-19. We report the case of a middle-aged man with severe COVID-19 pneumonia that required seven days of endotracheal intubation and mechanical ventilation who presented with headache and left-sided weakness that occurred three days after his discharge. A computed tomography scan was performed to rule out intracranial hemorrhage before initiating the thrombolytic therapy. The scan demonstrated hemorrhage in the right temporal lobe with surrounding vasogenic edema along with density in the right transverse sinus. Subsequently, computed tomography venography was performed and demonstrated the filling defect representing right sigmoid venous sinus thrombosis. The patient received conservative measures in the form of intravenous hydration, anticoagulation, analgesics, and anticonvulsants. During the hospital stay, the patient had improvement in his symptom and mild neurological deficit persisted. The case highlighted that risk of thrombotic complications in COVID-19 pneumonia may persist for some period after the recovery from the disease. Hence, thromboprophylaxis may be indicated in selected patients with a risk of thrombotic events after their recovery from severe COVID-19.

The lack of an integral characterization of chronic neuropathic pain (NP) has led to pharmacotherapy mismanagement and has hindered advances in clinical trials. In this study, we attempted to identify chronic NP by fusing psychometric (based on the Brief Inventory of Pain – BIP), and both linear and non-linear electroencephalographic (EEG) features. For this purpose, 35 chronic NP patients were recruited voluntarily. All the volunteers answered the BIP; and additionally, 22 EEG channels positioned in accordance with the 10/20 international system were registered for 10 minutes at resting state: 5 minutes with eyes open and 5 minutes with eyes closed. EEG Signals were sampled at 250 Hz within a bandwidth between 0.1 and 100 Hz. As linear features, absolute band power was obtained per clinical frequency band: delta (0.1~4 Hz), theta (4~8 Hz), alpha (8~12 Hz), beta (12~30 Hz) and gamma (30~100 Hz); considering five regions: prefrontal, frontal, central, parietal and occipital. As non-linear features, approximate entropy was calculated per channel and per clinical frequency band with addition of the broadband (0.1~100 Hz). Resulting feature vectors were grouped in line with the BIP outcome. Three groups were considered: low, moderate, and high pain. Finally, BIP-EEG patterns were classified in those three classes, achieving 96% accuracy. This result improves a previous work of a SVM classifier that used exclusively linear EEG features and showed an accuracy between 87% and 90% per class to predict central NP after spinal cord injury.