Derivation and Validation of a Mortality Risk Score for Severe Hand, Foot and Mouth Disease in China

Establishment of Asia-Pacific Network for Enterovirus Surveillance

Enteroviruses (EV), the major pathogens of hand, foot, and mouth disease (HFMD) and herpangina, affect millions of children each year. Most human enteroviruses cause self-limited infections except polioviruses, enterovirus A71 (EV-A71), enterovirus D68 (EV-D68), and several echoviruses (Echo) and coxsackieviruses (CV). Especially, EV-A71 has repeatedly caused large-scale outbreaks in the Asia-Pacific region since 1997. Some Asian countries have experienced cyclical outbreaks of severe EV-A71 infections and initiated development of EV-A71 vaccines. Five EV-A71 vaccine candidates have been clinically evaluated and three of them were approved for marketing in China. However, none of the China-approved products seek marketing approval in other countries. This situation supports a role for collaboration among Asian countries to facilitate clinical trials and licensure of EV-A71 vaccines. Additionally, enterovirus D68 outbreaks have been reported in the US and Taiwan currently and caused severe complications and deaths. Hence, an Asia-Pacific Network for Enterovirus Surveillance (APNES) has been established to estimate disease burden, understand virus evolution, and facilitate vaccine development through harmonizing laboratory diagnosis and data collection. Founded in 2017, the APNES is comprised of internationally recognized experts in the field of enterovirus in Asian countries working to raise awareness of this potentially fatal and debilitating disease. This article demonstrated the summaries of the first expert meeting, 2017 International Workshop on Enterovirus Surveillance and Vaccine Development, held by APNES in Taipei, Taiwan, March 2017.

A Simple Scoring System for Quick, Accurate, and Reliable Early Diagnosis of Hand, Foot, and Mouth Disease

BACKGROUND To construct an accurate, reliable, and simple scoring system of improving HFMD diagnosis. MATERIAL AND METHODS Based on the following 3 steps, a simple scoring diagnostic system was built: (1) we selected basic markers (age and sex), markers recommended in HFMD diagnosis guidelines, and significant biomarkers among severity groups found in a large dataset; (2) we used positive constituent ratio for determining scores of each marker; and (3) we applied receiving operating curve in an external dataset to determine the optimal cut-off score. RESULTS The selected markers were sex, age, fever, skin rashes, nervous system disorder, respiratory system disorder, digestive system disorder and cardiopulmonary complications, C-reactive-protein, White Blood Cell, Creatinine Kinase, Creatinine Kinase Isoenzyme, Gamma-Glutamyl Transpeptidase, Albumin, Globulin, Albumin/Globulin Ratio, Natrium, Chloride, Calcium, and Glucose. A simple scoring system with 3.9684 as the lower cut-off was constructed. The AUC was 0.918 (95% CI: 0.874-0.963, P<0.01). The sensitivity, specificity, and Youden Index, which were based on the validation dataset of 200 subjects (80 cases, 120 non-cases with skin rashes or fever), were 0.95, 0.90, and 0.85, respectively. CONCLUSIONS This simple scoring system is an effective method to diagnose HFMD.

Chinese guidelines for the diagnosis and treatment of hand, foot and mouth disease (2018 edition)

BACKGROUND

Hand, foot, and mouth disease (HFMD) is a common infectious disease in childhood caused by an enterovirus (EV), and which is principally seen in children under 5 years of age. To promote diagnostic awareness and effective treatments, to further standardize and strengthen the clinical management and to reduce the mortality of HFMD, the guidelines for diagnosis and treatment have been developed.

METHODS

National Health Commission of China assembled an expert committee for a revision of the guidelines. The committee included 33 members who are specialized in diagnosis and treatment of HFMD.

RESULTS

Early recognition of severe cases is utmost important in diagnosis and treatment of patients with HFMD. The key to diagnosis and treatment of severe cases lies in the timely and accurate recognition of stages 2 and 3 of HFMD, in order to stop progression to stage 4. Clinicians should particularly pay attention to those EV-A71 cases in children aged less than 3 years, and those with disease duration less than 3 days. The following indicators should alert the clinician of possible deterioration and impending critical disease: (1) persistent hyperthermia; (2) involvement of nervous system; (3) worsening respiratory rate and rhythm; (4) circulatory dysfunction; (5) elevated peripheral WBC count; (6) elevated blood glucose and (7) elevated blood lactic acid. For treatment, most mild cases can be treated as outpatients. Patients should be isolated to avoid cross-infection. Intense treatment modalities should be given for those severe cases.

CONCLUSION

The guidelines can provide systematic guidance on the diagnosis and management of HFMD.

Developing a Machine Learning System for Identification of Severe Hand, Foot, and Mouth Disease from Electronic Medical Record Data

Children of severe hand, foot, and mouth disease (HFMD) often present with same clinical features as those of mild HFMD during the early stage, yet later deteriorate rapidly with a fulminant disease course. Our goal was to: (1) develop a machine learning system to automatically identify cases with high risk of severe HFMD at the time of admission; (2) compare the effectiveness of the new system with the existing risk scoring system. Data on 2,532 HFMD children admitted between March 2012 and July 2015, were collected retrospectively from a medical center in China. By applying a holdout strategy and a 10-fold cross validation method, we developed four models with the random forest algorithm using different variable sets. The prediction system HFMD-RF based on the model of 16 variables from both the structured and unstructured data, achieved 0.824 sensitivity, 0.931 specificity, 0.916 accuracy, and 0.916 area under the curve in the independent test set. Most remarkably, HFMD-RF offers significant gains with respect to the commonly used pediatric critical illness score in clinical practice. As all the selected risk factors can be easily obtained, HFMD-RF might prove to be useful for reductions in mortality and complications of severe HFMD.