Volume 8, Issue 4

Since its initial outbreak in late 2019, the COVID-19 pandemic has profoundly affected the global community. In addition to the negative health consequences of contracting COVID-19, the implementation of strict quarantine and lockdown measures has also disrupted social networks and devastated the global economy. As a result, there is rising concern that the pandemic has taken a toll on the mental health of the general population. To better understand its impact, an increasing number of studies examined the effects of the pandemic on mental health and psychosocial implications of enforced quarantine and lockdown. In this article, we aim to review and summarize the findings from a variety of studies that have explored the psychosociological effects of the pandemic and its impact on the mental well-being of the general population. We will also examine how various demographic groups, such as the elderly and youth, can be more susceptible or resilient to the pandemic’s mental health effects. We hope to provide a broader understanding of the underlying causes of mental health issues triggered by the pandemic and provide recommendations that may be employed to address mental health issues in the population over the long-term.

The COVID-19 pandemic will be remembered as one of the worst catastrophic events in human history. Unfortunately, no universally recognized effective therapeutic agents are currently available for the treatment of severe SARS-CoV-2 infection. In this context, the use of convalescent plasma from recovered COVID-19 patients has gained increasing interest thanks to the initially positive clinical reports. A number of mechanisms of action have been proposed for convalescent plasma, including direct neutralization and suppression of viremia, anti-inflammatory and immunomodulation effects and mitigation of the COVID-19-associated hypercoagulable state. These immune and non-immune mechanisms will be critically discussed in this narrative review.

Objectives Pyoderma gangrenosum (PG) is a chronic ulcerative neutrophilic dermatosis. It presents a diagnostic challenge due to the absence of disease-specific markers or histopathology, lack of universally accepted diagnostic criteria, and many mimicking diseases including necrotizing soft tissue infections (NSTI). PG cases often present first to specialties other than dermatology. We reviewed major educational resources in internal medicine, family medicine, and infectious disease for their coverage of PG. Content For each specialty, we reviewed five major textbooks, five prominent journals, and any commonly used online resources. Twelve of 15 textbooks mentioned PG, only three of which included a differential, with none including NSTI in the differential. Only two of 13 journals included review articles about PG, and none of these including NSTI in their differential. Interestingly, online resources tended to be the most complete; six of nine contained PG articles, nearly all including a differential and three listing NSTI within it. Summary We found an underrepresentation of PG among major textbooks and journals in clinical specialties, especially in differentiating PG from its mimickers. While online resources may help fill this gap in knowledge, texts and journals remain essential. Misdiagnosis and resultant mismanagement of PG can lead to disastrous outcomes. Outlook We recommend that PG be added to the differential diagnoses of chronic ulcers in educational resources. We also suggest the addition of identification and differentiation of PG to learning materials and lectures for providers in specialties who may encounter PG, NSTI, or similarly presenting diseases to address this gap.

While much diagnosis literature focuses on errors, our goal is to learn how to achieve diagnostic excellence. Before the explosion of cognitive psychology studies on errors, authors of fictional detectives understood the principles of arriving at the correct diagnosis (in their case the guilty party). Using quotes from many fictional detectives, we discuss a framework for diagnostic excellence. Understanding the implications of these quotes should help aspiring diagnosis experts on their path to excellence.

This is a first attempt to integrate the three pillars of infection management: the infection prevention and control (IPC), and surveillance (IPCS), antimicrobial stewardship (AMS), and rapid identification and management of sepsis (RIMS). The new ‘Sepsis-3’ definition extrapolates the diagnosis of sepsis from our previously slightly naïve concept of a stepwise evolving pattern. In doing so, however, we have placed the transition from infection toward sepsis in the domain of uncertainty and time-dependency. This now demands that clinical judgment be used in the risk stratification of patients with infection, and that pragmatic local solutions be used to prompt clinicians to evaluate formally for sepsis. We feel it is necessary to stimulate the development of a new generation of concepts and models aiming at embracing uncertainty. We see the opportunity for a heuristic approach focusing on the relevant clinical predictors at hand allowing to navigate the uncertainty of infection diagnosis under time constraints. The diverse and situated clinical approaches eventually emerging need to focus on the understanding of infection as the unbalanced interaction s of host, pathogen, and environment. In order extend such approach throughout the patient journey we propose a holistic early warning system underpinned by the risk-based categories of hazards and vulnerabilities iteratively fostered by the information gathered by the infection prevention control and surveillance, clinical microbiology, and clinical chemistry services.

Testing urine for Bence Jones Protein (BJP) had been a time old procedure used for screening and monitoring of monoclonal disorders since its description. However, has poor sensitivity and despite advances in diagnostic methods of monoclonal disorders it is being continued to be requested in individuals for evaluation of myeloma or plasma cell disorders. Effective utilization and minimizing untimely or unnecessary investigations is important in the evaluation and management of any medical condition. Though, we are hard-wired during our education with some “trigger” or “peculiar” words that make us jump to actions too quickly, without comprehending the actual problem. Supporting evidence is presented to avoid reflexive use of multiple tests and utilize tests that improve utilization, reduce waste, and uphold the Choosing Wisely principles in providing optimal care to the patients.

Objectives Despite inter-individual variations in their diagnostic efficiency, dogs have been trained to investigate many human pathologies, especially cancer, diabetes, migraine, seizures and even infectious diseases. To this end, we performed a critical review and pooled analysis of current scientific literature on the performance of dogs trained for identifying severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive human specimens. Methods We carried out an electronic search in PubMed, Scopus and Web of Science with the keywords “dog(s)” AND “sniffer” OR “scent” OR “smell” AND “SARS-CoV-2” OR “severe acute respiratory syndrome coronavirus 2” OR “coronavirus disease 2019” OR “COVID-19” within all fields, without date or language restrictions, to identify studies describing dogs’ performance for identifying SARS-CoV-2 infected material. Results Three studies could be finally included in pooled analysis, totaling 17 dogs (47% females), aged between 0.5 and 12 years. The pooled diagnostic sensitivity was 0.88 (95% CI, 0.84–0.91; I 2 , 85.3%), the diagnostic specificity 0.99 (95% CI, 0.99–0.99; I 2 , 97.4%), whilst the area under the summary receiver operating characteristic curve (SROC) was 0.979 (standard error, 0.003). Conclusions The notable performance observed in this pooled analysis would persuade us to suggest that adequately trained dogs could represent an intriguing and sustainable resource for purposes of rapid SARS-CoV-2 mass screening.

Objectives Obtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, and time of day. Methods For patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients’ COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: (1) body temperature alone; (2) body temperature and pretest probability; (3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3. Results Data from 117 patients were included. The models’ AUCs were: (1) 0.69 (2) 0.72, and (3) 0.76, respectively. The absolute difference in AUC was 0.029 (95% CI −0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95% CI −0.021 to 0.097, p=0.10) between model 3 and 2. Conclusions By incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.

Objectives Electronic alert systems to identify potential sepsis in children presenting to the emergency department (ED) often either alert too frequently or fail to detect earlier stages of decompensation where timely treatment might prevent serious outcomes. Methods We created a predictive tool that continuously monitors our hospital’s electronic health record during ED visits. The tool incorporates new standards for normal/abnormal vital signs based on data from ∼1.2 million children at 169 hospitals. Eighty-two gold standard (GS) sepsis cases arising within 48 h were identified through retrospective chart review of cases sampled from 35,586 ED visits during 2012 and 2014–2015. An additional 1,027 cases with high severity of illness (SOI) based on 3 M’s All Patient Refined – Diagnosis-Related Groups (APR-DRG) were identified from these and 26,026 additional visits during 2017. An iterative process assigned weights to main factors and interactions significantly associated with GS cases, creating an overall “score” that maximized the sensitivity for GS cases and positive predictive value for high SOI outcomes. Results Tool implementation began August 2017; subsequent improvements resulted in 77% sensitivity for identifying GS sepsis within 48 h, 22.5% positive predictive value for major/extreme SOI outcomes, and 2% overall firing rate of ED patients. The incidence of high-severity outcomes increased rapidly with tool score. Admitted alert positive patients were hospitalized nearly twice as long as alert negative patients. Conclusions Our ED-based electronic tool combines high sensitivity in predicting GS sepsis, high predictive value for physiologic decompensation, and a low firing rate. The tool can help optimize critical treatments for these high-risk children.

Objectives The aim of this study was to identify delays in early pre-sepsis diagnosis in emergency departments (ED) using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach. Methods SPADE methodology was employed using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (KPMAS). Study cohort included KPMAS members ≥18 years with ≥1 sepsis hospitalization 1/1/2013–12/31/2018. A look-back analysis identified treat-and-release ED visits in the month prior to sepsis hospitalizations. Top 20 diagnoses associated with these ED visits were identified; two diagnosis categories were distinguished as being linked to downstream sepsis hospitalizations. Observed-to-expected (O:E) and temporal analyses were performed to validate the symptom selection; results were contrasted to a comparison group. Demographics of patients that did and did not experience sepsis misdiagnosis were compared. Results There were 3,468 sepsis hospitalizations during the study period and 766 treat-and-release ED visits in the month prior to hospitalization. Patients discharged from the ED with fluid and electrolyte disorders (FED) and altered mental status (AMS) were most likely to have downstream sepsis hospitalizations (O:E ratios of 2.66 and 2.82, respectively). Temporal analyses revealed that these symptoms were overrepresented and temporally clustered close to the hospitalization date. Approximately 2% of sepsis hospitalizations were associated with prior FED or AMS ED visits. Conclusions Treat-and-release ED encounters for FED and AMS may represent harbingers for downstream sepsis hospitalizations. The SPADE approach can be used to develop performance measures that identify pre-sepsis.

Objectives Delays in sepsis diagnosis can increase morbidity and mortality. Previously, we performed a Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) “look-back” analysis to identify symptoms at risk for delayed sepsis diagnosis. We found treat-and-release emergency department (ED) encounters for fluid and electrolyte disorders (FED) and altered mental status (AMS) were associated with downstream sepsis hospitalizations. In this “look-forward” analysis, we measure the potential misdiagnosis-related harm rate for sepsis among patients with these symptoms. Methods Retrospective cohort study using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (2013–2018). Patients ≥18 years with ≥1 treat-and-release ED encounter for FED or AMS were included. Observed greater than expected sepsis hospitalizations within 30 days of ED treat-and-release encounters were considered potential misdiagnosis-related harms. Temporal analyses were employed to differentiate case and comparison (superficial injury/contusion ED encounters) cohorts. Results There were 4,549 treat-and-release ED encounters for FED or AMS, 26 associated with a sepsis hospitalization in the next 30 days. The observed (0.57%) minus expected (0.13%) harm rate was 0.44% (absolute) and 4.5-fold increased over expected (relative). There was a spike in sepsis hospitalizations in the week following FED/AMS ED visits. There were fewer sepsis hospitalizations and no spike in admissions in the week following superficial injury/contusion ED visits. Potentially misdiagnosed patients were older and more medically complex. Conclusions Potential misdiagnosis-related harms from sepsis are infrequent but measurable using SPADE. This look-forward analysis validated our previous look-back study, demonstrating the SPADE approach can be used to study infectious disease syndromes.

Objectives Diagnostic errors are pervasive in medicine and most often caused by clinical reasoning failures. Clinical presentations characterized by nonspecific symptoms with broad differential diagnoses (e.g., dizziness) are especially prone to such errors. Methods We hypothesized that novice clinicians could achieve proficiency diagnosing dizziness by training with virtual patients (VPs). This was a prospective, quasi-experimental, pretest-posttest study (2019) at a single academic medical center. Internal medicine interns (intervention group) were compared to second/third year residents (control group). A case library of VPs with dizziness was developed from a clinical trial (AVERT-NCT02483429). The approach (VIPER – Virtual Interactive Practice to build Expertise using Real cases) consisted of brief lectures combined with 9 h of supervised deliberate practice. Residents were provided dizziness-related reading and teaching modules. Both groups completed pretests and posttests. Results For interns (n=22) vs. residents (n=18), pretest median diagnostic accuracy did not differ (33% [IQR 18–46] vs. 31% [IQR 13–50], p=0.61) between groups, while posttest accuracy did (50% [IQR 42–67] vs. 20% [IQR 17–33], p=0.001). Pretest median appropriate imaging did not differ (33% [IQR 17–38] vs. 31% [IQR 13–38], p=0.89) between groups, while posttest appropriateness did (65% [IQR 52–74] vs. 25% [IQR 17–36], p<0.001). Conclusions Just 9 h of deliberate practice increased diagnostic skills (both accuracy and testing appropriateness) of medicine interns evaluating real-world dizziness ‘ in silico ’ more than ∼1.7 years of residency training. Applying condensed educational experiences such as VIPER across a broad range of common presentations could significantly enhance diagnostic education and translate to improved patient care.

Objectives Diagnostic Management Teams (DMTs) are one strategy for reducing diagnostic errors. This study examined errors in serology test selection after a positive antinuclear antibody (ANA) test in patients with suspected systemic autoimmune rheumatic disorder (SARD). Methods This retrospective study included 246 patient cases reviewed by our ANA DMT from March to August 2019. The DMT evaluated the appropriateness of tests beyond ANA screening tests (overutilization, underutilization, or both) based on American College of Rheumatology recommendations and classified cases into diagnostic error or no error groups. Errors were quantified, and patient and provider characteristics associated with diagnostic errors were assessed. Results Among 246 cases, 60.6% had at least one diagnostic error in test selection. The number of sub-serology tests ordered was 2.4 times higher in the diagnostic error group than in the no error group. The likelihood of at least one diagnostic error was higher in males and African American/Black patients, although the differences were not statistically significant. Providers from general internal medicine, primary care, and non-rheumatology specialties were approximately two times more likely to make diagnostic errors than rheumatology specialists. Conclusions Diagnostic errors in test selection after a positive ANA for patients with suspected SARD were common, although there were fewer errors when ordered by rheumatology specialists. These findings support the need to develop strategies to reduce diagnostic errors in test selection for autoimmunity evaluation and suggest that implementation of a DMT can be useful for providing guidance to clinicians to reduce overutilization and underutilization of laboratory tests.

Objectives Renal anomalies are the most common fetal abnormalities that occur during prenatal development, and are typically detected by observing hydronephrosis on fetal ultrasound imaging. Follow-up with post-natal ultrasound is important to detect clinically-important obstruction, because many of the pre-natal abnormalities resolve spontaneously. This study aimed to evaluate the postnatal hydronephrosis follow-up rate, and reasons for non follow-up in affected neonates. Methods In this cross-sectional study all neonates born during a period of one year at Ayatollah Mousavi Hospital with hydronephrosis on fetal ultrasound imaging were recruited. All mothers were also given face-to-face information about fetal hydronephrosis and its postnatal outcomes, and follow-up with at least a postnatal ultrasound was recommended from the fourth day of their neonates’ birth until the end of the fourth week. The neonates were subsequently observed for one month to determine the postnatal ultrasound follow-up rate and to reflect on diagnostic test results, reasons for failure to follow-up, as well as causes of hydronephrosis. Results In this study, 71 cases (1.2%) out of 5,952 neonates had fetal hydronephrosis on prenatal ultrasound images. The postnatal ultrasound imaging showed kidney involvement in 18 neonates (25%), particularly in the left kidney (61.1%). Seven neonates had no follow-up at one month (10%). No significant relationship was found between lack of follow-up and the neonates’ place of residence (p=0.42), maternal education (p=0.90), number of siblings (p=0.33), or gender (p=0.64). Conclusions Postnatal ultrasound follow-up rate in these neonates with a history of fetal hydronephrosis was incomplete even though parents had been provided with education and advice at their birth time. Accordingly, it is recommended to perform postnatal ultrasound once neonates are discharged from hospitals.

Objectives The differential diagnosis between acute bacterial meningitis (BM) and viral meningitis (VM) is crucial for treatment and prognosis. Cerebrospinal fluid (CSF) lactate (LA) is considered a good biomarker for differentiating BM from VM. The objective of this study was to compare the clinical performance of amperometry, which is not validated for measurement of LA in CSF samples, with a validated method (enzymatic ultra violet), for their ability to discriminate between acute BM and VM. Methods It was a retrospective, descriptive comparative study, 320 CSF reports were included; LA was quantified in CSF using either Dimension AR machine (Dade Behring) or amperometry (RAPID Point 500, Siemens). All samples with bacteria (n=54) or virus (n=139) identified, compared with a control with normal CSF (n=127). Results CSF LA levels were comparable for amperometry or enzymatic methods on each group studied, in a wide range of LA levels; it was capable to distinguish BM from VM independent of the method used to quantify. Conclusions The findings support the use of the amperometric method in measuring LA concentrations in CSF in a wide range of values. Amperometry is a less expensive method, validated for blood, easily available in small laboratories including in limited resources countries.

Objectives Errors in clinical reasoning are a major factor for delayed or flawed diagnoses and put patient safety at risk. The diagnostic process is highly dependent on dynamic team factors, local hospital organization structure and culture, and cognitive factors. In everyday decision-making, physicians engage that challenge partly by relying on heuristics – subconscious mental short-cuts that are based on intuition and experience. Without structural corrective mechanisms, clinical judgement under time pressure creates space for harms resulting from systems and cognitive errors. Based on a case-example, we outline different pitfalls and provide strategies aimed at reducing diagnostic errors in health care. Case presentation A 67-year-old male patient was referred to the neurology department by his primary-care physician with the diagnosis of exacerbation of known myasthenia gravis. He reported shortness of breath and generalized weakness, but no other symptoms. Diagnosis of respiratory distress due to a myasthenic crisis was made and immunosuppressive therapy and pyridostigmine were given and plasmapheresis was performed without clinical improvement. Two weeks into the hospital stay, the patient’s dyspnea worsened. A CT scan revealed extensive segmental and subsegmental pulmonary emboli. Conclusions Faulty data gathering and flawed data synthesis are major drivers of diagnostic errors. While there is limited evidence for individual debiasing strategies, improving team factors and structural conditions can have substantial impact on the extent of diagnostic errors. Healthcare organizations should provide the structural supports to address errors and promote a constructive culture of patient safety.

Objectives The COVID-19 pandemic has introduced strains in the diagnostic process through uncertainty in diagnosis, changes to usual clinical processes, and introduction of a unique social context of altered health care delivery and fear of the medical environment. These challenges created a context ripe for diagnostic error involving both systems and cognitive factors. Case presentation We present a series of three pediatric cases presenting to care during the early phases of the COVID-19 pandemic that highlight the heightened potential for diagnostic errors in the pandemic context with particular focus on the interplay of systems and cognitive factors leading to delayed and missed diagnoses. These cases illustrate the particular power of availability bias, diagnostic momentum, and premature closure in the diagnostic process. Conclusions Through integrated commentary and a fishbone analysis of the cognitive and systems factors at play, these three cases emphasize the specific influence of the COVID-19 pandemic on pediatric patients.