Notes on Healing After a Missed Diagnosis.

In this narrative medicine essay, a family physician maintains her patient's trust despite missing what could have been a catastrophic diagnosis because she apologized for her oversight.

[What have we missed because of COVID-19? Missed diagnoses and delayed follow-ups. SESPAS Report 2022]. / ¿Qué hemos dejado de atender por la COVID-19? Diagnósticos perdidos y seguimientos demorados. Informe SESPAS 2022.

The COVID-19 pandemic and the associated public health emergency have affected patients and health services in non-COVID-19 pathologies. Several studies have shown its dissociation from health services, with a decrease in emergency department visits, in hospital admissions for non-COVID-19 pathologies, as well as in the reported weekly incidence of acute illnesses and new diagnoses in primary care. In parallel, the pandemic has had direct and indirect effects on people with chronic diseases; the difficulties in accessing health services, the interruption of care, the saturation of the system itself and its reorientation towards non-face-to-face formats has reduced the capacity to prevent or control chronic diseases. All this has also had an impact on the different areas of people's lives, creating new social and economic difficulties, or aggravating those that existed before the pandemic. All these circumstances have changed with each epidemic wave. We present a review of the most relevant studies that have been analyzing this problem and incorporate as a case study the results of a retrospective observational study carried out in Primary Care in the Madrid Health Service, which provides health coverage to a population of more than 6 million people, and whose objective was to analyze the loss of new diagnoses in the most prevalent pathologies such as common mental health problems, cardiovascular and cerebrovascular diseases, type 2 diabetes, chronic obstructive pulmonary disease, and breast and colon tumors, in the first and second waves. Annual incidence rates with their confidence interval were calculated for each pathology and the monthly frequency of new codes recorded between 1/01/2020 and 12/31/2020 was compared with the monthly mean of observed counts for the same months between 2016 and 2019. The annual incidence rate for all processes studied decreased in 2020 except for anxiety disorders. Regarding the recovery of lost diagnoses, heart failure is the only diagnosis showing an above-average recovery after the first wave. To return to pre-pandemic levels of diagnosis and follow-up of non-COVID-19 pathology, the healthcare system must reorganize and contemplate specific actions for the groups at highest risk.

Missing Diagnoses during the COVID-19 Pandemic: A Year in Review.

The COVID-19 pandemic has had major impacts on population health not only through COVID-positive cases, but also via the disruption of healthcare services, which in turn has impacted the diagnosis and treatment of all other diseases during this time. We study changes in all new registered diagnoses in ICD-10 groups during 2020 with respect to a 2019 baseline. We compare new diagnoses in 2019 and 2020 based on administrative records of the public primary health system in Central Catalonia, Spain, which cover over 400,000 patients and 3 million patient visits. We study the ratio of new diagnoses between 2019 and 2020 and find an average decline of 31.1% in new diagnoses, with substantial drops in April (61.1%), May (55.6%), and November (52%). Neoplasms experience the largest decline (49.7%), with heterogeneity in the magnitudes of the declines across different types of cancer diagnoses. While we find evidence of temporal variation in new diagnoses, reductions in diagnoses early in the year are not recouped by the year end. The observed decline in new diagnoses across all diagnosis groups suggest a large number of untreated and undetected cases across conditions. Our findings provide a year-end summary of the impact of the pandemic on healthcare activities and can help guide health authorities to design evidence-based plans to target under-diagnosed conditions in 2021.

Bare necessities? The utility of full skin examination in the COVID-19 era.

Full skin examination (FSE) may improve the detection of malignant melanoma (MM). The objective of this study was to assess the safety of targeted lesion examination (TLE) compared with FSE in our Pigmented Lesion Clinic (PLC). Patients attending the PLC were randomized in a 2 : 1 ratio to FSE (intervention) or TLE (standard care). Demographic details and risk factors were documented, and the time taken to perform FSE and TLE was noted. Of 763 participants, 520 were assigned to FSE and 243 were assigned to TLE. On average, FSE took 4.02 min and TLE took 30 s to perform. Of the 520 participants assigned to FSE, 37 (7.1%) had incidental findings, of whom 12 patients (2.3%) had additional lesions biopsied. No additional melanomas were detected that would have been missed by use of the standard protocol. This study suggests that in low-risk patients referred to a PLC with a lesion of concern, the possibility of missing incidental cutaneous malignancies using lesion-directed examination is low.

Using the Novel Mortality-Prevalence Ratio to Evaluate Potentially Undocumented SARS-CoV-2 Infection: Correlational Study.

BACKGROUND: The high prevalence of COVID-19 has resulted in 200,000 deaths as of early 2020. The corresponding mortality rate among different countries and times varies. OBJECTIVE: This study aims to investigate the relationship between the mortality rate and prevalence of COVID-19 within a country. METHODS: We collected data from the Johns Hopkins Coronavirus Resource Center. These data included the daily cumulative death count, recovered count, and confirmed count for each country. This study focused on a total of 36 countries with over 10,000 confirmed COVID-19 cases. Mortality was the main outcome and dependent variable, and it was computed by dividing the number of COVID-19 deaths by the number of confirmed cases. RESULTS: The results of our global panel regression analysis showed that there was a highly significant correlation between prevalence and mortality (ρ=0.8304; P<.001). We found that every increment of 1 confirmed COVID-19 case per 1000 individuals led to a 1.29268% increase in mortality, after controlling for country-specific baseline mortality and time-fixed effects. Over 70% of excess mortality could be attributed to prevalence, and the heterogeneity among countries' mortality-prevalence ratio was significant (P<.001). Further, our results showed that China had an abnormally high and significant mortality-prevalence ratio compared to other countries (P<.001). This unusual deviation in the mortality-prevalence ratio disappeared with the removal of the data that was collected from China after February 17, 2020. It is worth noting that the prevalence of a disease relies on accurate diagnoses and comprehensive surveillance, which can be difficult to achieve due to practical or political concerns. CONCLUSIONS: The association between COVID-19 mortality and prevalence was observed and quantified as the mortality-prevalence ratio. Our results highlight the importance of constraining disease transmission to decrease mortality rates. The comparison of mortality-prevalence ratios between countries can be a powerful method for detecting, or even quantifying, the proportion of individuals with undocumented SARS-CoV-2 infection.

Clinical Characteristics and Short-Term Outcomes of Acute Kidney Injury Missed Diagnosis in Older Patients with Severe COVID-19 in Intensive Care Unit.

OBJECTIVES: Patients with severe or critical COVID-19 are at higher risk for developing acute kidney injury (AKI). However, whether AKI is diagnosed in all the patients and the correlation between the outcomes of COVID-19 are not well understood. PATIENTS AND METHODS: This cohort study was conducted from February 4, 2020 to April 16, 2020 in Wuhan, China. All consecutive inpatients with laboratory-confirmed COVID-19 were included in this study. AKI was defined according to the KDIGO 2012 criteria. The outcomes of patients with and without AKI and whether AKI was or was not recognized were compared. RESULTS: A total of 107 elderly patients were included in the final analysis. The median age was 70 (64-78) years, and 69 (64.5%) were men. Overall, 48 of 107 patients (44.9%) developed AKI during hospitalization. Meanwhile, 22 (45.8%) cases with AKI was not recognized (missed diagnosis) in this cohort. The Kaplan-Meier curves showed that survival was better in the non-AKI group than in the AKI group (log-rank, all P < 0.001); in the subgroups of the patients with AKI, the hospital survival rate decreased when AKI was not recognized. The survival of patients with recognized AKI was better than that of patients with unrecognized AKI (log-rank, all P < 0.001). According to the multivariate regression analysis, the independent risk factors for in-hospital mortality were AKI (recognized AKI vs non-AKI: HR = 2.413; 95% CI = 1.092-5.333; P = 0.030 and unrecognized AKI vs non-AKI: HR = 4.590; 95% CI = 2.070-10.175; P <0.001), C-reactive protein level (HR = 1.004; 95% CI = 1.000-1.008; P = 0.030), lactate level (HR = 1.236; 95% CI = 1.098-1.391; P < 0.001), and disease classification (critical vs severe: HR = 0.019; 95% CI = 1.347-26.396; P = 5.963). CONCLUSIONS: AKI is not an uncommon complication in elderly patients with COVID-19 who admitted to ICU. Extremely high rates of underdiagnosis and undertreatment of AKI have resulted in an elevated in-hospital mortality rate. Kidney protection is an important issue that cannot be ignored, and intensive care kidney specialists should take responsibility for leading the battle against AKI.

[Prediction of severe outcomes of patients with COVID-19].

Objective: To establish a new model for the prediction of severe outcomes of COVID-19 patients and provide more comprehensive, accurate and timely indicators for the early identification of severe COVID-19 patients. Methods: Based on the patients' admission detection indicators, mild or severe status of COVID-19, and dynamic changes in admission indicators (the differences between indicators of two measurements) and other input variables, XGBoost method was applied to establish a prediction model to evaluate the risk of severe outcomes of the COVID-19 patients after admission. Follow up was done for the selected patients from admission to discharge, and their outcomes were observed to evaluate the predicted results of this model. Results: In the training set of 100 COVID-19 patients, six predictors with higher scores were screened and a prediction model was established. The high-risk range of the predictor variables was calculated as: blood oxygen saturation <94%, peripheral white blood cells count >8.0×10(9), change in systolic blood pressure <-2.5 mmHg, heart rate >90 beats/min, multiple small patchy shadows, age >30 years, and change in heart rate <12.5 beats/min. The prediction sensitivity of the model based on the training set was 61.7%, and the missed diagnosis rate was 38.3%. The prediction sensitivity of the model based on the test set was 75.0%, and the missed diagnosis rate was 25.0%. Conclusions: Compared with the traditional prediction (i.e. using indicators from the first test at admission and the critical admission conditions to assess whether patients are in mild or severe status), the new model's prediction additionally takes into account of the baseline physiological indicators and dynamic changes of COVID-19 patients, so it can predict the risk of severe outcomes in COVID-19 patients more comprehensively and accurately to reduce the missed diagnosis of severe COVID-19.

Testing for gestational diabetes during the COVID-19 pandemic. An evaluation of proposed protocols for the United Kingdom, Canada and Australia.

AIMS: We assessed how altered diagnostic processes and criteria for gestational diabetes mellitus (GDM) recommended by the United Kingdom (UK), Canada and Australia for use during the COVID-19 pandemic would affect both GDM frequency and related adverse outcomes. METHODS: Secondary analysis of 5974 HAPO study women with singleton pregnancies who underwent 75 g OGTTs and HbA1c assays between 24 and 32 weeks' gestation and who received no treatment for GDM. RESULTS: All post COVID-19 modified pathways reduced GDM frequency - UK (81%), Canada (82%) and Australia (25%). Canadian women whose GDM would remain undetected post COVID-19 (missed GDMs) displayed similar rates of pregnancy complications to those with post COVID-19 GDM. Using UK modifications, the missed GDM group were at slightly lower risk whilst the women missed using the Australian modifications were at substantially lower risk. CONCLUSIONS: The modifications in GDM diagnosis proposed for the UK, Canada and Australia result in differing reductions of GDM frequency. Each has both potential benefits in terms of reduction in potential exposure to COVID-19 and costs in terms of missed opportunities to influence pregnancy and postpartum outcomes. These factors should be considered when deciding which protocol is most appropriate for a particular context.

[Comparison of the clinical characteristics between RNA positive and negative patients clinically diagnosed with coronavirus disease 2019].

Objective: To raise awareness about 2019 novel coronavirus pneumonia (NCP) and reduce missed diagnosis rate and misdiagnosis rate by comparing the clinical characteristics between RNA positive and negative patients clinically diagnosed with NCP. Methods: From January 2020 to February 2020, 54 patients who were newly diagnosed with NCP in Wuhan Fourth Hospital were included in this study. RT-PCR method was used to measure the level of 2019-nCov RNA in pharyngeal swab samples of these patients. The patients were divided into RNA positive and negative group, and the differences of clinical, laboratory, and radiological characteristics were compared. Results: There were 31 RNA of 2019-nCov positive cases, and 23 negative cases. Common clinical symptoms of two groups were fever (80.64% vs. 86.96%) , chills (61.29% vs. 52.17%) , cough (80.64% vs. 95.65%) , fatigue (61.30% vs. 56.52%) , chest distress (77.42% vs.73.91%) . Some other symptoms were headache, myalgia, dyspnea, diarrhea, nausea and vomiting. The laboratory and radiological characteristics of two groups mainly were lymphopenia, increased erythrocyte sedimentation rate, increased C-reactive protein, increased lactate dehydrogenase, decreased oxygenation index, normal white blood cell count and bilateral chest CT involvement. There was no statistically significant difference in other clinical characteristics except for dyspnea between two groups. Conclusions: RNA positive and negative NCP patients shared similar clinical symptoms, while RNA positive NCP patients tended to have dyspnea. Therefore, we should improve the understanding of NCP to prevent missed diagnosis and misdiagnosis; In addition, more rapid and accurate NCP diagnostic approaches should be further developed.