Risk prediction of encephalitis in hand, foot and mouth disease: a nomogram model based on platelet indices for resource-limited settings

Abstract

Objective

This study aimed to assess differences in peripheral blood platelet indices including platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and the platelet-to-lymphocyte ratio (PLR) between children with hand, foot and mouth disease (HFMD) complicated by encephalitis and those with uncomplicated HFMD. A further objective was to develop a robust predictive model for HFMD complicated by encephalitis, specifically designed for resource-limited clinical settings.

Methods

This retrospective study enrolled children with HFMD who were hospitalized at the Children’s Hospital of Soochow University between January 2015 and December 2020. The participants were categorized into two groups: an encephalitis group (HFMD complicated by encephalitis) and a control group (those with uncomplicated HFMD). The baseline data, clinical features and platelet indices of the children in the two groups were then compared. Binary logistic regression analysis was used to identify the risk factors for HFMD complicated by encephalitis, and a nomogram prediction model for HFMD complicated by encephalitis was developed based on these risk factors.

Results

The risk factors in children with HFMD complicated by encephalitis included fever for more than 3 days, listlessness, headache, limb myoclonus, positive neck resistance and/or pathological signs, and certain PLT, PDW, and PLR values. These risk factors were used to construct a simple and practical nomogram prediction model for HFMD complicated by encephalitis, which demonstrated strong predictive performance with an area under the curve (AUC) of 0.902, along with satisfactory calibration and stability upon validation.

Conclusion

The nomogram prediction model of platelet indices (PLT, PDW and PLR) combined with clinical risk factors demonstrated a robust predictive capacity for HFMD complicated by encephalitis.

Clinical trial number

Not applicable.

Introduction

Hand, foot and mouth disease is an acute exanthematous infectious disease caused by an enterovirus and is most common in children under 5 years of age. Although predominantly self-limiting, the disease can lead to central nervous system infections and is associated with high morbidity and mortality if not promptly identified and treated. Current understanding suggests a multifaceted etiology for HFMD encephalitis, involving virus-host interactions, particularly the inflammatory “cascade” effect induced by viral infection. However, the exact pathogenesis remains incompletely elucidated [1]. Although the immune-related functions of platelets remain an area of ongoing research, platelet indices such as PLT, PDW, MPV, and PLR are widely used in the assessment of infectious diseases. Routine blood tests are among the most commonly performed laboratory tests. This study had a two-fold objective: first, to identify objective predictive indices within routine blood investigations for HFMD complicated by encephalitis; and second, to construct and validate a practical nomogram prediction model for resource-limited settings.

Research objectives and methods

Research subjects

This study enrolled children with HFMD who were hospitalized at the Affiliated Children’s Hospital of Soochow University between January 2015 and December 2020. The clinical study was conducted in accordance with the fundamental principles of the Declaration of Helsinki and was reviewed and approved by the hospital’s Medical Ethics Committee (Approval No. 2022CS148). The parents or guardians of the children who participated in the study provided informed consent.

Inclusion and exclusion criteria

The inclusion criteria for HFMD and the diagnostic criteria for HFMD complicated by encephalitis are both based on the 2010 edition of the hand, foot and mouth disease diagnosis and treatment guidelines (Ministry of Health of the People’s Republic of China). The diagnostic criteria for HFMD include a history of direct or indirect contact with HFMD, fever and typical maculopapular rash, papules, and herpes on the hands, feet, and mouth. All patients were tested for enterovirus (universal) nucleic acid in throat and/or anal swab samples, and only positive patients were included.

The diagnostic criteria for hand, foot and mouth disease complicated by encephalitis are as follows: (1) a clear diagnosis of hand, foot and mouth disease; (2) manifestations of possible neurological involvement, such as limb myoclonus, headache, vomiting, listlessness, neck resistance and/or positive pathological signs; and (3) lumbar puncture showing increased intracranial pressure, accompanied by an increase in white blood cells in the cerebrospinal fluid and other manifestations of viral encephalitis.

The exclusion criteria were as follows: (1) concurrent infections of other systems (respiratory, digestive, or urinary); (2) underlying conditions that could affect platelet indices, such as tumors or chronic immune thrombocytopenic purpura; and (3) autoimmune diseases.

Initiation of case data collection

After the children were admitted to the hospital and diagnosed by a physician at or above the attending level in the Department of Infectious Diseases, the clinical data and initial blood test results, including the PLT, MPV, and PDW, were collected in a timely manner within three days of disease onset. The PLR was then calculated according to the following formula:

Statistical analyses

SPSS 23.0 software was used to perform the statistical analyses. The count data are expressed as the number of cases and percentages, and the chi-square test was applied. The measurement data were tested for normality, and compliance with a normal distribution was expressed as the mean ± standard deviation (X ± S) after application of the t test. Failure to meet a normal distribution was described by the median and quartiles [M (P25, P75)], and the Mann‒Whitney U test was used to perform comparative analyses. 2. Statistical comparisons of clinical features and platelet indices between the encephalitis group and the control group were performed. Variables that showed significant differences in the univariate analysis were incorporated into a binary logistic regression model, with adjustments for age and gender, to identify risk factors for HFMD complicated with encephalitis. 3. A predictive model for HFMD complicated by encephalitis was developed by risk factors using the ‘rms’ package in R software (version 4.2.2). The calibration ability of the nomogram predictive model was assessed using the Hosmer‒Lemeshow goodness-of-fit test, and the stability of the model was evaluated by plotting a calibration curve after 1000 internal validations by bootstrapping. Statistical significance was set at P < 0.05.

Results

Analysis of baseline data and clinical features of children with HFMD complicated by encephalitis

This study included 1,959 children with HFMD who were hospitalized between January 2015 and December 2020. Among these, 505 children with encephalitis were included in the encephalitis group, and 1,454 children with uncomplicated HFMD were included in the control group. No significant differences were observed in baseline date (age, gender, and weight) between children in the encephalitis and control groups (Table 1). Based on established guidelines and relevant literature [2–4], a univariate analysis was performed for the following clinical indicators: temperature ≥ 39 °C, fever > 3 days, listlessness, headache (infants with unappeasable crying with head shaking/patting), vomiting, limb myoclonus, convulsions, positive neurological examinations (neck resistance and/or positive pathological signs), tachypnea, tachycardia and hypertension. The results indicated that the incidence of fever > 3 days, listlessness, headache, limb myoclonus, positive neurological examinations and hypertension was significantly higher in the encephalitis group than in the control group (P < 0.05, Table 2).

Table 1.

Comparison of baseline data between the encephalitis and control groups

Group	n	Age (n/%)				Male/Female	Weight (kg)
		0–<1 years	≥1–<3 years	≥ 3–<6 years	≥ 6 years
Control group	1454	168 (11.55)	850 (58.46)	396 (27.24)	40 (2.75)	953/501	12.89 ± 3.98
Encephalitis group	505	59 (11.68)	285 (56.46)	140 (27.72)	21 (4.16)	312/193	12.65 ± 2.86
χ 2 /t		2.687				2.318	1.309
P		0.018				0.442	0.191

Table 2.

Comparison of clinical features between the encephalitis and control groups (n/%)

Items	Control group (n = 1454)	Encephalitis group (n = 505)	χ2	P
T ≥ 39 °C	794(54.61)	253(50.10)	3.063	0.080
Fever>3d	647(44.50)	357(70.69)	102.942	<0.01
Listlessness	200(13.76)	306(60.59)	429.326	<0.01
Headache	135(9.28)	162(32.08)	151.413	<0.01
Vomiting	313(21.53)	122(24.16)	1.503	0.220
Limb myoclonus	483(33.22)	337(66.73)	172.983	<0.01
Convulsion	35(2.41)	10(1.98)	0.304	0.581
Positive examinations	36(2.48)	154(30.50)	335.983	<0.01
Tachypnea	175(12.06)	69(13.66)	0.957	0.328
Tachycardia	298(20.50)	117(23.17)	1.616	0.204
Hypertension	58(3.99)	29(5.54)	4.550	0.033

Comparison of platelet indices in children with HFMD complicated by encephalitis and those in the control group

A comparative analysis of initial routine blood test indices, including white blood cell count (WBC), C-reactive protein (CRP), PLT, MPV, and PDW, was conducted between the two groups. The results showed that the WBC was significantly higher in the control group than in the encephalitis group. In contrast, the PLT and PDW values were significantly elevated in the encephalitis group compared to the control group (P < 0.05). Furthermore, PLR was calculated for both groups, revealing significantly higher values in the encephalitis group than in the control group (P < 0.05, Table 3).

Table 3.

Comparison of routine blood indices between the encephalitis and control groups

Items	Control group (n = 1454)	Encephalitis group (n = 505)	Z/t	P
WBC (109/L)	10.32 (8.10, 13.33)	9.94 (8.02, 12.49)a	2.031	0.042
CRP (mg/L)	8.46 (1.99, 22.61)	9.82 (2.27, 29.85)	1.800	0.072
PLT (109/L)	286.12 ± 77.86	311.36 ± 71.23 b	11.316	<0.01
MPV (fL)	9.60 (8.80, 10.30)	9.50 (8.70, 10.30)	0.889	0.374
PDW (%)	12.00 (10.30, 15.40)	15.10 (10.85, 15.60)b	5.706	<0.01
PLR	65.34 (47.65, 93.44)	88.09 (64.44, 127.80)b	10.831	<0.01

Note: “a” indicates that the parameters in the encephalitis group were significantly lower than those in the control group, and “b” indicates that the parameters in the encephalitis group were significantly higher than those in the control group (P < 0.05)

Logistic regression analysis of risk factors for HFMD complicated by encephalitis patients

Fever > 3 days, listlessness, headache, limb myoclonus, positive neurological examinations, hypertension, PLT, PDW, and PLR were included as independent variables, with the presence of encephalitis as the dependent variable in a binary logistic regression model. The analysis was adjusted for age and sex. The results indicated that all these factors, except hypertension, were identified as risk factors for hand, foot, and mouth disease complicated by encephalitis (P < 0.05, Table 4).

Table 4.

Binary logistic regression analysis of the clinical features and platelet indices

Variant	β	SE	Wald	P	OR (95%CI)
Fever > 3d	0.783	0.147	28.484	<0.01	2.189 (1.642–2.918)
Listlessness	2.224	0.153	212.331	<0.01	9.242 (6.853–12.465)
Headache	1.274	0.181	49.608	<0.01	3.576 (2.508–5.098)
Myoclonus	1.623	0.149	118.142	<0.01	5.069 (3.783–6.792)
Positive examinations	2.73	0.245	124.524	<0.01	15.423 (9.539–24.938)
Hypertension	0.410	0.315	1.696	0.193	1.507(0.813–2.792)
PLT (109/L)	0.005	0.001	23.543	<0.01	1.005(1.003–1.006)
PDW (%)	0.131	0.028	22.381	<0.01	1.140(1.080–1.203)
PLR	0.008	0.001	38.490	<0.01	1.008(1.005–1.010)

Note: Age and gender were corrected

Construction of a nomogram prediction model for HFMD complicated by encephalitis

The risk factors identified through the aforementioned binary logistic regression model were incorsporated into the prediction model. Using the“rms”package in R software (version 4.2.2), a nomogram was developed to visualize the model. Each risk factor was assigned a score on a point scale, and the total score obtained by summing individual scores was used to estimate the probability of encephalitis in children with HFMD (Fig. 1).

Fig. 1.

Nomogram for the risk prediction of HFMD complicated by encephalitis. (To use the nomogram, locate each predictor on its axis to determine the individual score: for dichotomous variables, assign a point based on presence (1) or absence (0); for continuous variables, read the point corresponding to the value. Then, sum all scores to obtain the total score and project it down to the risk axis to read the final probability estimate. The result is a statistical probability estimate intended to support, not replace, clinical judgment.)

Subsequently, a receiver operating characteristi curve was plotted to assess the predictive model, and the AUC was calculated to evaluate its discriminative ability. A control model was constructed using only clinical risk factors, including fever > 3 days, listlessness, headache, limb myoclonus, and positive neurological signs. The predictive model demonstrated high discriminative ability, with an AUC of 0.902 (95% CI: 0.886–0.917). Its sensitivity was 0.788, specificity was 0.862, and Youden index was 0.650. In comparison, the control model yielded an AUC of 0.878 (95% CI: 0.862–0.895). The sensitivity, specificity, and Youden index for this model were 0.727, 0.864, and 0.591, respectively. These results indicate that the combined predictive model, which incorporates platelet-related indicators, possesses superior discriminative power and higher accuracy compared to the control model (Fig. 2A).

Fig. 2.

Validation of the nomogram model for predicting encephalitis in HFMD. Comparison of model discrimination using receiver operating characteristic curves. The predictive nomogram (integrating clinical risk factors and platelet indices) is shown in red (AUC = 0.902), and the control model (clinical risk factors only) in blue (AUC = 0.878); B. Calibration curve assessing model performance. The black diagonal (Ideal) indicates perfect prediction. The apparent (red) and bias-corrected (blue, from bootstrapping) curves show the original fit and expected new-data performance, respectively. The close alignment of the bias-corrected curve with the ideal line demonstrates good nomogram calibration.)

The calibration of the predictive model was assessed using the Hosmer-Lemeshow goodness-of-fit test, which yielded a chi-square value of 11.172 (P = 0.192). This suggests that the predicted and actual observed values were not significantly different and that the model is well calibrated. Internal validation of the model was further performed using the bootstrap method with 1,000 resamples, and calibration curves were generated accordingly (Fig. 2B). The close agreement between the simulated curve and the actual observed curve indicates that the nomogram model exhibits satisfactory reproducibility and stability.

Discussion

HFMD, a worldwide infectious disease, is caused by enteroviruses, and of these, enterovirus A71 is the primary strain that causes severe infections [5]. Since 1997, several large-scale HFMD epidemics have been reported in the Asia‒Pacific region, particularly in Southeast Asian countries, including cases comllicated by severe neurological complications [6]. Most severe cases of HFMD are observed in children aged less than 3 years, as their immune systems are not yet fully developed. These young children are particularly susceptible to post-infectious immune dysregulation, which can initiate a cascade of systemic inflammatory responses. This may result in severe complications, including neurogenic pulmonary oedema and brainstem encephalitis, which may ultimately lead to death [7].

The clinical progression of HFMD is categorized into five distinct stages: : the initial stage of rash, followed by neurological involvement, precardiorespiratory failure, and cardiorespiratory failure, and finally, recovery. For the diagnosis and treatment of severe cases, it is crucial to identify children with encephalitis in a timely and accurate manner to prevent progression to cardiorespiratory failure [7]. HFMD complicated by encephalitis typically affects children under 3 years of age and can progress rapidly. Compared with adults, infants and young children who present to the clinic are less cooperative during neurological examinations. It is also noteworthy that these young patients frequently present with only some rather than all of the severe symptoms described in the HFMD diagnostic guidelines. Furthermore, they often exhibit nonspecific systemic symptoms, such as poor mental state and vomiting in the presence of high fever, which makes clinical decision-making somewhat challenging. Although a cerebrospinal fluid test remains the definitive diagnostic method for HFMD complicated by encephalitis, it is an invasive procedure. Thus, accurate and early clinical assessment is essential to minimize unnecessary lumbar punctures.

This study novelly incorporated platelet indices into a prediction model for HFMD complicated by encephalitis. The primary function of platelets is the maintenance of blood flow and vascular integrity. However, recent studies have revealed their significant role in mounting immune defenses against infections [8]. Upon infection, platelets are rapidly recruited to the site, where they recognize, bind, and engulf pathogenic microorganisms. This results in the release of diverse proteins with killing effects. Additionally, platelets enhance the function of intrinsic immune cells, such as neutrophils, and stimulate the initiation of the adaptive immune function of T and B lymphocytes. Through these coordinated mechanisms, platelets contribute to the effective clearance of pathogens [9, 10]. Recent studies have also indicated that platelets play a role in the severe progression of HFMD. Li Qianwen et al. [11] identified them as a key factor driving the differentiation and functional regulation of pathogenic CD4 + T cells in HFMD. Jin Yuefei et al. [12] revealed that during EV71 infection, degranulation of platelets releases serotonin and pro-inflammatory mediators, which in turn can disrupt the blood-brain barrier. Furthermore, In mouse models, platelets have been shown to exert proinflammatory effects that promote the development of autoimmune encephalitis [13].

Given the increasing recognition of the immune status of platelets, platelet indices have been increasingly used in the evaluation of infectious diseases. For example, indices such as the PLT, MPV, PDW, and PLR are useful for diagnosing bloodstream infections, influenza, and urinary tract infections, as well as for assessing their severity [14–16]. In this study, children in the HFMD complicated by encephalitis group had significantly higher PLTs, PDWs, and PLRs than did those in the control group. These indices were identified as independent risk factors for HFMD complicated by encephalitis. To date, few studies have explored the predictive value of platelet indices in HFMD complicated by encephalitis. Li Miao et al. [17] reported that the PLT was independently associated with HFMD progression in a nonlinear manner. Li Qianwen et al. [11] reported that the PLT and PDW were positively associated with the severity of HFMD. These studies support some of the conclusions of our research. Moreover, our study involved a larger sample size than previous studies.

Moreover, this study found that the peripheral blood leukocyte counts in children diagnosed with HFMD complicated by encephalitis were lower than those in the control group. A subsequent review of the literature demonstrated that the significance of an elevated WBC in HFMD complicated by encephalitis remains controversial and unclear, and requires further validation [2, 18].

In this study, a nomogram prediction model for HFMD complicated by encephalitis was constructed using clinical features and platelet indices. The model is simple, cost-effective, and highly suitable for clinical use in resource-limited settings. Compared to the control model based solely on clinical features, the platelet-enhanced prediction model demonstrated a larger AUC and improved discriminatory power. Furthermore, the platelet indices offer objective measures unaffected by subjective interpretation. Bootstrap internal validation was performed to ensure the reliability of the nomogram prediction model, which confirmed its stability. The Hosmer–Lemeshow goodness-of-fit test yielded a P value of 0.192, indicating satisfactory calibration.

A routine blood examination is a common laboratory investigation. In this study, we utilized routine blood test data from patients with HFMD to extract novel insights and evaluate the predictive utility of platelet indices. We subsequently developed a nomogram prediction model for HFMD complicated by encephalitis, which may assist clinicians in assessing patient condition and facilitating clinical decision-making. Furthermore, our findings provide a basis for further exploration of the role of platelets in this disease. Despite these contributions, this study has several limitations. As a single-center investigation conducted in Suzhou, the findings may reflect local epidemiological patterns, circulating viral strains, and clinical practices, which could limit direct applicability to other regions. Additionally, by focusing on hospitalized children, the model’s performance in identifying at-risk cases among milder outpatient presentations requires further assessment. Future development should therefore follow two main paths: prospective, multi-regional validation to confirm generalizability, and evaluation in outpatient populations to establish its role in early clinical decision-making.

Conclusions

In summary, this study demonstrated that platelet indices including PLT, PDW, and PLR serve as significant predictors for HFMD complicated by encephalitis in children. The constructed nomogram model integrates platelet indices and clinical features to provide a practical tool for early risk stratification. With strong predictive accuracy (AUC = 0.902), along with reliable calibration and stability, this model offers a valuable resource for clinicians in resource-limited settings to facilitate timely diagnosis and intervention, potentially improving outcomes in severe HFMD cases.

Abbreviations

PLT

Platelet

MPV

Mean platelet volume

PDW

Platelet distribution width

PLR

Platelet-to-lymphocyte ratio

HFMD

Hand, foot and mouth disease

AUC

Area under the curve

WBC

White blood cell

CRP

C-reactive protein

Author contributions

Conception and design: FF Cheng, SH Zhan, WH Yan; Administrative support: JM Tian; Provision of study materials or patients: FF Cheng, SH Zhan, K Wang, MLu Cao, ZF Hui, WX Shi; Collection and assembly of data: All authors; Data analysis and interpretation: FF Cheng, SH Zhan. Manuscript writing: All authors; Final approval of manuscript: All authors.

Funding

This study was supported by the Medical Research Project of Jiangsu Provincial Health Commission (K2023049).

Data availability

All analysed datasets are available from the corresponding author upon request.

Declarations

Ethics approval and consent to participate

All study procedures adhered to the principles outlined in the Declaration of Helsinki and received approval from the Medical Ethics Committee of Children’s Hospital of Soochow University (Approval No. 2022CS148). Participation in the study was voluntary, and informed consent was obtained from the parents, who acted as legal guardians, to ensure compliance with ethical standards for participants under 16.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.