Analysis of time delays in imported malaria diagnosis: not only on the patient’s shoulders.

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Nerea Castillo-Fernández, Manuel Jesús Soriano-Pérez, Ana Belén Lozano-Serrano, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3870620/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Nov, 2024 Read the published version in Infection → Version 1 posted 9 You are reading this latest preprint version Abstract Purpose To analyze the diagnostic delay in malaria related to misdiagnosis at first visit medical visit and its association with the risk of severe malaria in non-endemic areas. Methods Retrospective observational study of sub-Saharan migrants with imported malaria from January-2010 to December-2022. Patients were allocated in two groups if they were tested for malaria at first medical visit or not. Time delays in seeking healthcare, medical diagnostic delay and total diagnostic delay were calculated. Results 297 patients were included in the analysis. At first medical visit, malaria was misdiagnosed in 137 patients (46.1%). Medical diagnostic delay and total diagnostic delay were larger for the misdiagnosis group than for those properly diagnosed at first visit (p < 0.001). Although time in seeking healthcare was shorter in the misdiagnosis group, the presence of suggesting symptoms, such as fever, was lower (p < 0.050). Misdiagnosis was more frequent in emergency rooms linked to primary healthcare (p < 0.001). For the overall population (n = 297), total diagnostic delay was mainly due to delay in seeking healthcare. Initial misdiagnosis was associated with a higher risk of severe malaria (adjusted OR 2.23 [1.09–5.10], p = 0.031). Conclusion In a non-endemic area with a high rate of imported malaria, the percentage of patients misdiagnosed is surprisingly high. Misdiagnosis is associated with longer medical and total diagnostic delays and with a higher risk of severe malaria. It seems necessary to redesign training programs to improve knowledge among healthcare professionals and actions targeted to travelers to promote seeking healthcare advice promptly. Imported Malaria diagnostic delay travelers migrants travel medicine Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Malaria, despite being a potentially preventable and treatable disease, ​remains​ a public health challenge that affects approximately 247 million​ people per year in endemic areas, with more than 94%​ of the cases occurring in ​​sub-Saharan Africa [ 1 ]. Spain is the fourth European country with the highest rate of imported malaria [ 2 ]. Almeria is the province of southern Spain where more cases of imported malaria are diagnosed annually, most of them occurring in travelers visiting friends and relatives (VFR)[ 3 ]. This is closely bound to the population profile of the Almeria province, with a 21.7% of foreign residents, many of them (around 45%) being migrants coming from the African continent [ 4 ]. Being a potentially medical emergency, the World Health Organization continues to point out the importance of early diagnosis that allows effective treatment to be initiated within the first 24–48 hours [ 5 ]. However, the diagnosis of malaria depends on clinical suspicion since quite specific techniques, such as immunochromatography (rapid diagnostic test) and/or peripheral blood smear, are needed for its detection [ 6 , 7 ]. In areas where malaria is not endemic, a clinical diagnosis of malaria may be challenging for healthcare providers unfamiliar with the disease. The variable and non-specific nature of the earliest symptoms of malaria, which often overlap with other common viral infections and other banal conditions, difficult early diagnosis [ 5 , 7 ]. Some studies show that up to 40–60% of malaria cases go unnoticed in their initial presentation and alternative erroneous diagnosis are stablished instead [ 8 – 10 ]. Such misdiagnosis contributes to increase morbidity and mortality, especially in the cases of P. falciparum malaria [ 10 – 16 ]. In non-endemic areas, retrospective studies have shown that the time interval from symptom onset to malaria diagnosis ranges from 3–6 days, mostly due to patient's delay in seeking healthcare [ 8 , 12 , 17 – 21 ]. However, few studies have analyzed the delay in diagnosis owning to healthcare providers once the patient has consulted [ 22 ]. In this case, delay is most probably related to the lack of awareness of malaria among such professionals. The objective of this study is to compare, in an European area with a high rate of immigrants from sub-Saharan Africa and universal health coverage, the characteristics of patients with a malaria diagnosis at first visit against those who were initially misdiagnosed. Likewise, analysis of the different time delays according to diagnosis at first visit is made. Finally, the association of misdiagnosis with the risk of severe malaria was also explored. 2. Methods 2.1 Study design and study population A retrospective observational study of malaria cases admitted to the University Poniente hospital (El Ejido, Almeria, Spain) from January 2010 to December 2022 was conducted. Eligible patients were included in the analysis if they fulfilled the following criteria: sub-Saharan origin, older than 14 years of age, stay in endemic area in the last year, and symptomatic malaria admitted to hospital. Patients with submicroscopic malaria were excluded. 2.2 Data collected and definitions Malaria diagnosis was made by means of rapid direct tests (the BinaxNOW® malaria test or SD Bioline® malaria Ag Pf/Pan, Korea) and/or direct microscopic examination of blood thin smear. A conventional Nested Multiplex Malaria PCR (NM-PCR) capable of identifying four human malaria species ( P. vivax, P. falciparum, P. ovale and P. malariae ) was used when a mixed infection was suspected [23]. Data for each malaria episode were obtained retrospectively from the hospital electronic health records. The collection of data included all visits to any public healthcare service or unit after the onset of symptoms. Data collected are reported in Supplementary data. Spain-based migrants traveling to their homeland to visit friends and relatives were considered as VFR travelers whereas those migrants traveling first time to Europe from malaria endemic areas were considered as migrants. Pandemic period of SARS-CoV2 was considered between March 2020 and December 2021. Severe malaria was defined as the combination of one or more severity criteria according to the 2023 World Health Organization definition [6] and requirement of ICU admission. Patients suspected of malaria (and accordingly tested) at the first medical visit were included in the “Malaria diagnosis at first visit” group. The remaining patients, for whom the clinical suspicion of malaria was not established and where not offered a malaria test and received an alternative diagnosis, were included in the “misdiagnosis at first visit” group (figure 1). According to the definitions of Bastaki et al. [22], the following time periods were calculated (figure 1): Time to onset of symptoms, defined as the time between returning from a malaria endemic country and the onset of symptoms for malaria. Patient delay, defined as the time between the onset of symptoms and seeking healthcare advice for the first time or first attending a medical facility. Medical diagnostic delay, defined as the time between first attending a medical facility or seeking healthcare advice and the diagnosis of malaria. Total diagnostic delay, defined as the time between the onset of symptoms and the diagnosis of malaria. To compare groups of similar size, the median value of total diagnostic delay was chosen to define an inappropriate diagnostic delay. All patients were treated at the time of malaria diagnosis so the variable “treatment delay” was not calculated. 2.3 Statistical analysis Continuous variables were expressed as mean, standard deviation, median and interquartile range (IQR), and categorical variables as absolute numbers and percentages. Univariate comparisons were performed by the chi-square or Fisher tests for categorical variables, and the Mann–Whitney U test for continuous variables. A p- value < 0.05 was considered as statistically significant. Univariate analyses of factors potentially associated with severe malaria were performed by univariate logistic regression. Potentially clinically relevant variables and those with a univariate p value less than 0.10 were included in the multivariate logistic regression model to estimate the adjusted OR for severe malaria. Potential interactions were explored and included if they had a significant modifying effect. Variable selection was performed manually using a backward stepwise procedure. The Statistical Package for the Social Sciences (SPSS) version 26.0.0 and the R software v3.0.1 were used for the analysis. 2.4 Ethics statement This study has been approved by the local Ethics Committee of the Coordinating Site (Almería, Spain), code PUB_23_16. 3. Results A flowchart of the study is shown in Figure 2. Two-hundred and ninety-seven patients were included in the analysis. At first medical visit, malaria was suspected or diagnosed in 160 patients (53.9%) (malaria diagnosis at first visit group), while in 137 (46.1%) the initial diagnosis was incorrect (misdiagnosis group). The epidemiological characteristics of the patients included in the study are shown in Table 1. The majority were males (93.3%) with a median age of 35 years (IQR 30 – 41) and 97.6% were VFR travelers. Table 1. General characteristics of the patients included in the study a n d according to diagnosis at first visit a Total (n = 297) Malaria diagnosis at first visit (n = 160) Misdiagnosis at first visit (n = 137) p value Age in years (median, IQR) 35 (30 – 41) 36 (30 – 41) 34 (30 – 40) 0.186 b Male 277 (93.3%) 145 (90.6%) 132 (96.4%) 0.050 Traveler category VFR travelers c 290 (97.6%) 156 (97.5%) 134 (97.8%) 0.585 d Migrants 7 (2.4%) 4 (2.5%) 3 (2.2%) 0.585 d Length of stay in Spain before malaria diagnosis, in months (median, IQR) 120 (84 – 144) 120 (84 – 156) 120 (80 – 144) 0.477 b VFR travelers c 120 (84 – 146) 124 (96 – 156) 120 (84 – 144) 0.229 Migrants 1 (1 – 4) 1 (1 – 1.75) 4 (1 – 4) 0.430 Under specialized medical care before traveling (only apply to VFRs) 26 (8.8%) 12 (7.5%) 14 (10.2%) 0.409 HIV coinfection 13 (4.5%) 8 (5.0%) 5 (3.6%) 0.571 Medical comorbidities e 7 (2.4%) 3 (1.9%) 4 (2.9%) 0.415 d a Except where otherwise specified, data represent numbers (%) of patients. P values were calculated by chi-square test, except where otherwise specified. b Mann-Whitney U -test c One patient was born in Spain d Fisher test e Hypertension (n = 3), diabetes mellitus (n = 3), dyslipidemia (n = 1). Table 2 shows the general features of the first medical visits (when and where they took place) along with several clinical features and laboratory results at hospital admission, and the different types of time delays. For almost two thirds of the patients (n = 191; 64.3%), the first medical visit took place in out-of-hospital public healthcare facilities ( i.e. primary care services: 22.5% primary care attending physician and 77.5% in emergency services linked to primary care). In most cases (99.0%), the infection was caused by the species P. falciparum . Fifty-seven patients (19.2%) had severe malaria. Regarding VFR travelers, 23.8% (n=69) had visited a specialized pre-travel clinic prior to the trip, with no differences between the misdiagnosis and the malaria diagnosis at first visit groups (p=0.757). Of these, 50 patients (72.5%) claimed to have received malaria chemoprophylaxis instructions although they were not followed properly in any case. Twenty - six patients were under specialized care for diverse medical conditions before traveling but most of them (92.3%) did not disclose their traveling plans to their doctors, so no travel - advice could be given. Table 2. Characteristics at hospital admission and according to diagnosis at first visit a Total (n = 297) Malaria diagnosis at first visit (n = 160) Misdiagnosis at first visit (n = 137) p value SARS CoV2 pandemic period 13 (4.4%) 6 (3.8%) 7 (5.1%) 0.586 Medical department at first visit Primary care attending physician 43 (14.5%) 24 (15.0%) 19 (13.9%) 0.782 Emergency rooms linked to primary healthcare 148 (49.8%) 47 (29.4%) 101 (73.7%) < 0.001 Hospital emergency room 106 (35.7%) 89 (54.6%) 17 (12.4%) < 0.001 Symptoms Fever 216 (72.7%) 144 (90.0%) 72 (52.6%) < 0.001 Abdominal pain 51 (17.2%) 37 (23.1%) 14 (10.2%) 0.003 Gastrointestinal tract (other than abdominal pain) 72 (24.2%) 45 (28.1%) 27 (19.7%) 0.092 Headache 171 (57.6%) 108 (67.5%) 63 (46.0%) < 0.001 Respiratory tract 44 (14.8%) 19 (11.9%) 25 (18.2%) 0.123 Arthromyalgia 124 (41.8%) 70 (43.8%) 54 (39.4%) 0.450 ≥ 3 coexisting symptoms 111 (37.4%) 84 (52.5%) 27 (19.7%) < 0.001 Laboratory results (mean, SD) Hemoglobin (g/dL) 13.3 (1.6) 13.4 (1.5) 13.1 (1.7) 0.198 c Platelets (x10 3 /microL) 94.1 (59.1) 106.8 (54.3) 78.7 (61.2) < 0.001 c C-Reactive protein (mg/dL) Reference values (0.0 – 0.5) 10.9 (6.9) 8.7 (6.2) 13.6 (6.6) < 0.001 c Parasitemia (%) (mean, SD) 1.9 (3.2) 1.7 (3.6) 2.2 (2.8) 0.029 c Malaria species Plasmodium falciparum d 294 (99.0%) 158 (98.8%) 136 (99.3%) 0.558 e Non-Plasmodium falciparum f 3 (1.0%) 2 (1.3%) 1 (0.7%) 0.558 e Severe malaria 64 (21.5%) 26 (16.3%) 38 (27.7%) 0.016 Length of hospital stay, in days (median, IQR) 2 (2 – 4) 2 (2 – 3) 2 (2 – 4) 0.221 c Time to onset of symptoms, in days (median, IQR) 4 (1 – 9) 4 (1 – 8) 4 (1.5 – 11.5) 0.224 c Patient delay, in days (median, IQR) 2 (1 – 4) 3 (1.25 – 5) 2 (1 – 3) < 0.001 c Medical diagnostic delay, in days (median, IQR) 0.5 (0 – 2.5) 0 (0 – 0) 2 (2 – 4) < 0.001 c Total diagnostic delay, in days (median, IQR) 4 (2 – 7) 3 (2 – 5) 5 (3 – 8) < 0.001 c a Except where otherwise specified, data represent numbers (%) of patients. P values were calculated by chi-square test, except where otherwise specified. b Univariate comparison between primary healthcare services (primary care attending physician and emergency rooms linked to primary care) and hospital healthcare (hospital emergency room). c Mann-Whitney U -test d Including 5 patients with mixed infection: P. falciparum and P. malariae coinfection (n = 3, 1%); P. falciparum and P. ovale coinfection (n = 2, 0.7%). e P. ovale (n = 2; 0.7%); P. vivax (n = 1; 0.3%). f Fisher test 3.1 Differential characteristics of patients with initial misdiagnosis compared to those with malaria diagnosis at first visit Noteworthy, 46.1% of patients received a wrong diagnosis at the first medical visit (n=137). The characteristics of these patients compared to those who received a correct diagnosis are shown in Tables 1 and 2. No differences in the epidemiological characteristics were found. Respecting the different medical services, initial misdiagnosis was more frequent in the out-of-hospital setting compared to patients treated directly in the hospital emergency room (87.5% vs 12.5%; p<0.001). Within the out-of-hospital setting, initial misdiagnosis was more common for patients treated in the emergency rooms linked to primary care than for those treated by their primary care attending physician (84.2% vs 15.8%, p=0.040). The presence of fever, abdominal pain and headache, as well as the concurrence of 3 or more symptoms at the time of consultation (p<0.001) was associated with an increased likelihood of a correct initial diagnosis of malaria. In relation to the laboratory tests results, patients with initial misdiagnosis had a significantly lower platelet count at the time of malaria final diagnosis (78.7 vs 106.8 x10 3 /microL; p<0.001) and a higher absolute value of C-reactive protein (13.6 vs 8.7 mg/dL; p<0.001). Furthermore, greater levels of parasitization at hospital admission were shown in patients with initial misdiagnosis (2.2 vs 1.7; p=0.015) as well as a higher proportion of severe malaria cases (27.7% vs 16.3%, p=0.016). However, no differences were found regarding the length of hospital stay time between both groups. There were no deaths among the patients included in the study. 3.2 Diagnostic delay in patients diagnosed with malaria Time delays for the total population of the study (n = 297) and according to initial diagnosis groups are shown in table 2 and figure 3, respectively. 3.2.1 Time to onset of symptoms For the total number of patients included in the study (n=297), the median time from arrival to Spain to the onset of symptoms was 4 days (IQR 1 – 9) (table 2). Most patients (n=286, 96.3%) had symptoms within the first 30 days after arrival. Four patients (1.3%) started with malaria symptoms after more than 100 days since leaving the endemic area, with a maximum of 343 days in one patient. The median time to symptom onset was significantly longer in non-VFR patients than in VFR travelers (10 vs 4 days; p=0.022). On the contrary, there were no differences between patients correctly diagnosed at first medical visit versus those misdiagnosed (Figure 3a) 3.2.2 Time to seeking healthcare advice (patient delay) The median time from the onset of symptoms and seeking healthcare advice or first attending a medical facility was 2 days (IQR 1 - 4) (table 2). Thirty-six patients (12.4%) sought medical advice for the first time more than 7 days after the onset of symptoms. This time delay was significantly longer in patients who were correctly diagnosed at first visit (Figure 3b). 3.2.3 Time from first medical visit to diagnosis (medical diagnostic delay) For the 297 patients, the median time from the first healthcare visit to the diagnosis of malaria was 0.5 days (IQR 0 – 2.5) (table 2). Figure 3c shows the median medical diagnostic delay until the correct diagnosis of malaria was reached according to the number of medical visits needed. The medical diagnostic delay of patients with initial misdiagnosis increased with each visit until reaching a median of 13.5 days (IQR 7.25 – 22.0) in those patients who needed up to five visits before getting the right malaria diagnosis. The majority of the 160 patients correctly suspected of malaria at first visit had a confirmatory malaria test done at the same time. However, in 10 of them (6.2%), the malaria blood test was scheduled for later on, with a mean delay time of 9.3 days and a maximum of up to 50 days until blood analysis were finally done. Regarding patients misdiagnosed (n=137), 95 (69.3%) were diagnosed with malaria at the second medical visit. On the other hand, 28 (20.4%), 10 (7.2%) and 4 (2.8%) patients needed three, four and five medical visits, respectively, before getting the right malaria diagnosis. The most frequent alternative misdiagnoses at first visit were: viral disease (35.8%), acute gastroenteritis (14.6%), headache without warning signs (12.4%), pharyngitis (9.5%), and febrile syndrome of undetermined etiology (5.8%). Other less frequent diagnoses were: mechanical lower back pain (2.9%), otitis (0.7%), urinary tract infection (0.7%), and side effect of SARS CoV2 vaccine (0.7%). The diagnosis was not recorded in 21 patients (15.6%). In most cases (n = 118; 86.8%) symptomatic treatment was prescribed, including painkillers and non-steroidal anti-inflammatory drugs. Fifteen patients (11.0%) received antibiotic therapy. 3.2.4 Time between the onset of symptoms and the diagnosis of malaria (total diagnostic delay) Overall, for the whole set of patients (n=297), the total diagnostic delay median was 4 days (IQR 2 – 7) with a mean of 5.9 days (table 2). Delay was significantly greater in patients with initial misdiagnosis as compared to those with correct diagnosis (Figure 3d). One hundred and sixty-three patients (54.9%) had a diagnostic delay≥4 days, considered as an inappropriate. Such inappropriate diagnostic delay was related to first visit having place in primary care services and to the onset of symptoms before arrival to Spain (p<0.05) (supplementary Table 1). Conversely, presenting with fever and headache at first visit was associated with a shorter proportion of inappropriate diagnostic delay (p<0.05). Patients with inappropriate diagnostic delay had significantly lower hemoglobin concentrations and platelet counts and higher C-reactive protein and parasitemia levels (p < 0.05). 3.4 Outcomes The univariate analysis of the variables related to severe malaria is shown in the Supplementary Table 2. Misdiagnosis at first visit was associated with an increased risk of severe malaria (crude OR 1.978 [1.978 – 3.472], p=0.017). SARS CoV2 pandemic period was also associated with an increased risk of severe malaria (crude OR 3.340 [1.018 – 10.318], p=0.036). In the multivariate analysis (Figure 4), after controlling for potential confounders, misdiagnosis (adjusted OR 2.321 [1.090 – 5.104], p=0.031) and SARS CoV2 pandemic period (adjusted OR 3.981 [1.142 – 13.914], p=0.027) remained independently associated with an increased risk of developing severe malaria. 4. Discussion In our study we have observed that almost half of patients with malaria are misdiagnosed at first medical visit, even though the study is carried out in an area with a high proportion of long stablished migrant population from sub-Saharan Africa where a remarkably high number of malaria cases are reported annually. Such initial misdiagnosis is significantly related with an increased risk of developing severe malaria, although it does not lead to a worse outcome for those misdiagnosed in terms of hospital stay and related deaths. Although little is published, the association between initial misdiagnosis and the development of severe malaria has also been demonstrated in other studies [ 9 – 11 ] using the same criteria for severe malaria the WHO severity criteria or the need for ICU admission as our [ 5 ]. Besides, the percentage of patients initially misdiagnosed also changes dramatically depending on the type and level of medical facility where the patient was treated [ 8 – 11 ]. Nevertheless, in our case, the place where the patient is initially diagnosed is not associated with an increased risk of developing severe malaria. Such circumstance may be related to the fact that those patients with milder forms of presentation may be more prone to seek attention in the primary care setting instead of in the hospital emergency room. Inappropriate diagnostic delay, defined in our study as a total diagnostic delay ≥ 4 days, is associated with initial misdiagnosis and this is consistent with previous studies [ 9 , 13 ]. Nonetheless, in our study this delay is not correlated with an increased risk of severe malaria. The available data published about the association between inappropriate diagnostic delay and severe malaria are scarce and heterogeneous, mainly due to the lack of standardization to establish what is considered an acceptable duration to achieve malaria diagnosis from the onset of symptoms [ 8 , 9 , 22 ]. Although there is no clear consensus, in cohorts of patients with severe malaria, the diagnostic delay was longer than 5 days [ 12 , 24 – 26 ]. This disparity could justify that our diagnostic delay ≥ 4 days is not associated with severe malaria. Despite the fact that patients with initial misdiagnosis seemed to consult earlier from the onset of symptoms, the overall diagnosis delay is larger than that of those with malaria diagnosis at first visit. This means that much of the total diagnostic delay in the misdiagnosis group is primarily due to medical diagnostic delay. There are very few studies that specifically assess medical diagnostic delay, with an mean published around 0.5–1.7 days [ 22 , 27 – 30 ]. Even so, when all patients included in the study are analyzed together, patient delay is greater than medical diagnostic delay, confirming what was found in other studies and revealing the importance and consistency of such delay [ 22 , 31 ]. This data could be probably related to the profile of our patients, which VFR travelers predominating. Flateau et al. observed that VFR travelers tended to have a longer delay in seeking healthcare, probably due to a lower perception of the risk of acquiring malaria along with not considering malaria a significant health threat [ 8 , 32 – 34 ]. Moreover, as we have observed in our own study, this group of travelers presented lower rates of attendance to pre-travel clinics and compliance to malaria chemoprophylaxis [ 35 – 37 ]. These data highlight the need to implement training programs aimed to health professionals, but also to broadcast public information campaigns targeted to travelers underlining the value of pre-travel advice and the importance of seeking early medical advice upon return from malaria-endemic areas in the face of any symptoms. Travelers should also be advised to provide recent travel information so to help in the diagnostic pathway, specially when presenting with vague symptoms or mild clinical conditions. It is noteworthy that up to 30.9% of patients wrongly diagnosed at first visit (14.1% of the total patients included in the study) needed to be evaluated more than twice before a malaria diagnosis was reached, with a median diagnostic delay of almost two weeks. Moreover, in some cases, the attending physicians did not consider suspected malaria as a potential medical emergency and diagnostic tests were requested as part of a routine analysis. In these cases, the diagnostic delay reached up to 50 days. These data are far from the WHO recommendations that stress the need for an urgent evaluation of all patients suspected of having malaria [ 5 ]. It should also be noted that patients with a failed initial diagnosis presented more undifferentiated syndromes, with a lower proportion of fever, abdominal pain or headache and a lower concurrence of more than three symptoms. It is important to remember that malaria can cause several and diverse symptoms and should not only be suspected in patients with febrile syndromes [ 5 , 7 ]. Surely, the most definitive clue is the history of traveling to a malaria endemic area, a decisive information that should always be registered in the clinical history of these patients. Regarding laboratory tests, patients with initial misdiagnosis presented, when finally diagnosed, worse results, compatible with a more advanced stage of the disease, such as greater thrombocytopenia, higher parasite loads and higher levels of CRP. The period of the SARS CoV2 pandemic seems to be related to a higher probability of serious cases but not to a greater diagnostic delay, although due to the small number of patients treated during this period, data should be interpreted with caution. Other studies including a higher proportion of patients diagnosed during this pandemic period have also shown higher rates of severe malaria cases and longer diagnostic delays, but data are heterogeneous [ 7 , 8 , 38 – 40 ]. Such findings could be due to underdiagnosis of milder malaria cases as a result of the saturation of the healthcare systems, as well as to a lower diagnostic offer. The limitations of the study derive, first of all, from its retrospective nature, as it is likely that some relevant clinical data were not properly recorded in the medical records. Secondly, extrapolation of the results to other types of population is not guaranteed since only patients from sub-Saharan Africa, mostly VFR and largely infected by P. falciparum , have been included. On the other hand, the large number of patients included in the study strengthens our results. Furthermore, it should also be noted that this is one of the few studies published so far addressing specifically medical diagnostic delay in patients with imported malaria once they have sought medical advice. It could be the starting point for a deeper analysis of such delay and the implementation of measures to shorten it. 5. Conclusion In conclusion, the data from this study reveal a situation of concern, since even in an area with a high rate of patients diagnosed annually with malaria and where specific training activities aimed to both hospital and out-of-hospital healthcare personnel are periodically carried out, the number of patients with initial misdiagnosis is surprisingly high. Misdiagnosis leads to a larger number of medical visits, a larger medical diagnostic delay, and larger proportion of severe malaria cases; it also may contribute to increase healthcare expenses. Misdiagnosis could be an even more serious problem in those non-endemic areas where malaria cases are not as frequent and healthcare personnel is not as familiar with the disease. It seems necessary to redesign the educational and training strategies aimed at improving knowledge in the field of imported diseases among healthcare professionals, specially for those working in the out-of-hospital setting. Finally, we must not forget the actions targeted at travelers in relation to the prevention of malaria, with special attention to VFR travelers. Declarations Funding statement: This work was supported by the Red de Investigación de Centros de Enfermedades Tropicales – RICET (Project RD16/0027/0013 of the PN de I+D+I, ISCIII-Subdirección General de Redes y Centros de Investigación Cooperativa RETICS, co-financed with FEDER funds -European Regional Development Fund- "A way to make Europe”/”Investing in your future”), Ministry of Health and Consumption, Madrid; and by the research group PAIDI CTS582 of the regional Ministry of Health and Families of the Government of Andalusia. Conflict of interest: All authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Acknowledgements: We thank Adrián Aparicio Mota, technician in Research Methodology and Biostatistics from FIBAO, for providing invaluable support for the statistical analysis of the data. Author contributions: N.C.F: Conceptualization, Writing–Original Draft, Methodology, Formal Analysis, Investigation, Data curation, Writing–Review & Editing. MJ.S.P: Investigation, Data curation, Writing–Review & Editing. AB.L.S: Formal Analysis, Investigation, Writing–Review & Editing. J.V.V: Investigation, Data curation, Writing–Review & Editing. MP.L.G: Investigation, Data curation, Writing–Review & Editing. MI.C.B: Investigation, Data curation, Writing–Review & Editing. C.O.L: Investigation, Data curation, Writing–Review & Editing. R.P.M: Investigation, Writing–Review & Editing. J.S.C: Conceptualization, Methodology, Investigation, Data curation, Writing–Review & Editing, Supervision. All authors have read and agreed to the published version of the manuscript. Credit Author Statement: The present version of this paper has met the approval of all authors and they accept full responsibility for the content. The authors declare that this manuscript has not been simultaneously submitted for publication in any other journal, nor have the findings been partially disclosed in any other publication. References World Health Organization. World malaria report 2022. Geneva: World Health Organization; 2022. Licence: CC BY-NC-SA 3.0 IGO European Centre for Disease Prevention and Control (ECDC). Malaria; Annual Epidemiological Report for 2021. Stockholm: ECDC; 2023. Pousibet-Puerto J, Lozano-Serrano AB, Soriano-Pérez MJ et al. Migration-associated malaria from Africa in southern Spain. Parasit Vectors. 2021 Dec 1;14(1). https://doi.org/10.1186/s13071-021-04727-0. Instituto Nacional de España - Padrón Municipal. 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Avoiding misdiagnosis of imported malaria: screening of emergency department samples with thrombocytopenia detects clinically unsuspected cases. J Travel Med. 2003 May-Jun;10(3):155-9. Dorsey G, Gandhi M, Oyugi JH, Rosenthal PJ. Difficulties in the prevention, diagnosis, and treatment of imported malaria. Arch Intern Med. 2000 Sep 11;160(16):2505-10. Jordane L, Bruno M, Nicolas A et al. Changes in the clinical presentation and outcomes of patients treated for severe malaria in a referral French university intensive care unit from 2004 to 2017. Ann Intensive Care. 2020 Dec 1;10(1). Bruneel F, Tubach F, Mira JP et al. Imported falciparum malaria in adults: host- and parasite-related factors associated with severity. The French prospective multicenter PALUREA cohort study. Intensive Care Med. 2016 Oct 1;42(10):1588–96. Stȩpień M, Rosińska M. Imported malaria in Poland 2003 to 2011: Implications of different travel patterns. J Travel Med. 2014;21(3):189–94. Briand V, Bouchaud O, Tourret J et al. Hospitalization criteria in imported falciparum malaria. J Travel Med. 2007 Sep;14(5):306–11. Fernández López M, Ruiz Giardín JM, San Martín López JV et al. Imported malaria including HIV and pregnant woman risk groups: Overview of the case of a Spanish city 2004-2014. Malar J. 2015 Sep 17;14(1). Bastaki H, Carter J, Marston L et al. Time delays in the diagnosis and treatment of malaria in non-endemic countries: A systematic review. Travel Med Infect Dis. 2018 Jan-Feb;21:21-27. Rubio JM, Post RJ, van Leeuwen WM et al. Alternative polymerase chain reaction method to identify Plasmodium species in human blood samples: the semi-nested multiplex malaria PCR (SnM-PCR). Trans R Soc Trop Med Hyg. 2002 Apr;96 Suppl 1:S199-204. Checkley AM, Smith A, Smith V, et al. Risk factors for mortality from imported falciparum malaria in the United Kingdom over 20 years: An observational study. BMJ. 2012 Apr 27;344(7854). Valls ME, Nicolás JM, González A et al. Severe Imported Malaria in Adults: Retrospective Study of 20 Cases. Am J Trop Med Hyg. 2009 Oct 1;81(4):595–9. Christen D, Steffen R, Schlagenhauf P. Deaths caused by malaria in Switzerland 1988-2002. American Journal of Tropical Medicine and Hygiene. 2006;75(6):1188–94. Higa F, Tateyama M, Tasato D et al. Imported malaria cases in Okinawa Prefecture, Japan. Jpn J Infect Dis. 2013;66(1):32-5. McCarthy AE, Morgan C, Prematunge C, Geduld J. Severe malaria in Canada, 2001-2013. Malar J. 2015 Dec 1;14(1). Nakayama K, Shimizu T. Reducing the delay in initiation of treatment improved clinical outcomes in patients with imported malaria. Jpn J Infect Dis. 2014;67(1):27-32. Chalumeau M, Holvoet L, Chéron G et al. Delay in diagnosis of imported Plasmodium falciparum malaria in children. European Journal of Clinical Microbiology and Infectious Diseases. 2006 Mar;25(3):186–9. Färnert A, Wyss K, Dashti S, Naucler P. Duration of residency in a non-endemic area and risk of severe malaria in African immigrants. Clinical Microbiology and Infection. 2015 May 1;21(5):494–501. De Gier B, Suryapranata FST, Croughs M et al. Increase in imported malaria in the Netherlands in asylum seekers and VFR travellers. Malar J. 2017 Feb 2;16(1):1–8. Kendjo E, Houzé S, Mouri O et al. Epidemiologic Trends in Malaria Incidence Among Travelers Returning to Metropolitan France, 1996-2016. JAMA Netw Open. 2019 Apr 5;2(4):e191691. Smith AD, Bradley DJ, Smith V et al. Imported malaria and high risk groups: Observational study using UK surveillance data 1987-2006. BMJ. 2008 Jul 12;337(7661):103–6. Angelo KM, Libman M, Caumes E et al. Malaria after international travel: A GeoSentinel analysis, 2003-2016. Malar J. 2017 Jul 20;16(1). Ferrara P, Masuet-Aumatell C, Ramon-Torrell JM. Pre-travel health care attendance among migrant travellers visiting friends and relatives (VFR): A 10-year retrospective analysis. BMC Public Health. 2019 Oct 28;19(1). Paudel P, Raina C, Zwar N et al. Risk activities and pre-travel health seeking practices of notified cases of imported infectious diseases in Australia. J Travel Med. 2017 Sep 1;24(5). De Laval F, Maugey N, Bonet D’Oleon A at al. Increased risk of severe malaria in travellers during the COVID-19 pandemic. J Travel Med. 2021 Aug 1;28(6). Robben PM, Dunbar CR, Akin EH et al. Late-presenting Plasmodium falciparum Malaria in a Non-Endemic Setting During COVID-19 Travel Restrictions. Mil Med. 2023 May 16;188(5–6):e1335–7. Norman FF, Treviño-Maruri B, Ruiz Giardín JM et al. Trends in imported malaria during the COVID-19 pandemic, Spain (+Redivi Collaborative Network). J Travel Med. 2022 Aug 1;29(6). Additional Declarations No competing interests reported. Supplementary Files Supplementaryfile.docx Cite Share Download PDF Status: Published Journal Publication published 18 Nov, 2024 Read the published version in Infection → Version 1 posted Editorial decision: Revision requested 08 Jul, 2024 Reviews received at journal 07 Jul, 2024 Reviewers agreed at journal 18 May, 2024 Reviews received at journal 29 Feb, 2024 Reviewers agreed at journal 15 Feb, 2024 Reviewers invited by journal 14 Feb, 2024 Editor assigned by journal 17 Jan, 2024 Submission checks completed at journal 17 Jan, 2024 First submitted to journal 16 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3870620","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267683095,"identity":"bb15516b-cd46-4fde-a400-ad12b9353696","order_by":0,"name":"Nerea Castillo-Fernández","email":"data:image/png;base64,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","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":true,"prefix":"","firstName":"Nerea","middleName":"","lastName":"Castillo-Fernández","suffix":""},{"id":267683096,"identity":"e7da8fb5-8eb2-4a6d-a04a-92948bc1fbe2","order_by":1,"name":"Manuel Jesús Soriano-Pérez","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"Jesús","lastName":"Soriano-Pérez","suffix":""},{"id":267683097,"identity":"be8a8f70-63e4-40f4-b011-e4acf59a3f62","order_by":2,"name":"Ana Belén Lozano-Serrano","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"Ana","middleName":"Belén","lastName":"Lozano-Serrano","suffix":""},{"id":267683098,"identity":"75f14d1d-4a84-44aa-8921-19d51b41c83b","order_by":3,"name":"José Vázquez-Villegas","email":"","orcid":"","institution":"Tropical Medicine Unit, Distrito sanitario Poniente","correspondingAuthor":false,"prefix":"","firstName":"José","middleName":"","lastName":"Vázquez-Villegas","suffix":""},{"id":267683099,"identity":"32e3f9be-733c-4516-b887-df493a4739ae","order_by":4,"name":"María Pilar Luzón-García","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Pilar","lastName":"Luzón-García","suffix":""},{"id":267683100,"identity":"35d33ad2-0fa7-4122-bad3-c9075e60a877","order_by":5,"name":"María Isabel Cabeza-Barrera","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"María","middleName":"Isabel","lastName":"Cabeza-Barrera","suffix":""},{"id":267683101,"identity":"e30030cc-d575-4819-b305-0ab80bde1f9e","order_by":6,"name":"Cristina Ocaña-Losada","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"Cristina","middleName":"","lastName":"Ocaña-Losada","suffix":""},{"id":267683102,"identity":"53c039ad-5ce0-4c2a-98f7-484da1a4f4fc","order_by":7,"name":"Rosario Pérez-Moyano","email":"","orcid":"","institution":"Hematology Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"Rosario","middleName":"","lastName":"Pérez-Moyano","suffix":""},{"id":267683103,"identity":"0e64525c-d25e-45cd-9599-01fa725dedeb","order_by":8,"name":"Joaquín Salas-Coronas","email":"","orcid":"","institution":"Tropical Medicine Unit, Hospital Universitario de Poniente","correspondingAuthor":false,"prefix":"","firstName":"Joaquín","middleName":"","lastName":"Salas-Coronas","suffix":""}],"badges":[],"createdAt":"2024-01-16 17:59:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3870620/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3870620/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s15010-024-02436-1","type":"published","date":"2024-11-18T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49894700,"identity":"00a17a5e-fbdc-4509-8495-5a92c6a0e42c","added_by":"auto","created_at":"2024-01-19 21:33:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":27894,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDefinitions of the time periods calculated in the study and group allocation according to diagnosis at first medical visit\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eFootnote figure 1: \u003csup\u003ea\u003c/sup\u003eAdapted from Bastaki et al.\u003c/p\u003e\n\u003cp\u003e[22]\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/23e5779835d669d3aff46606.png"},{"id":49894701,"identity":"056d739b-60eb-4cda-9603-f686331c1228","added_by":"auto","created_at":"2024-01-19 21:33:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":29443,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of the study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/cec5053569b98321867743c2.png"},{"id":49894703,"identity":"96985faf-d535-4d67-8702-dfd86dbe3ff0","added_by":"auto","created_at":"2024-01-19 21:33:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":233115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferent time delays according to diagnosis at first medical visit.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFootnote figure 3: \u003c/strong\u003eFigure 3a shows the time to onset of symptoms since arrival to Spain. Figure 3b shows patient delay time according to diagnosis at first medical visit. Figure 3c shows medical diagnosis delay defined as the time between the first medical visit and the malaria diagnosis. Patients were classified into different categories according to the number of visits needed to reach the malaria diagnosis. In this case, the first visit category concerns to patients with accurate diagnosis and the other categories belong to patients with misdiagnosis. Figure 3d shows total diagnostic delay time according to diagnosis at first medical visit. \u003cem\u003eP\u003c/em\u003e value was calculated between the malaria diagnosis and the misdiagnosis at first visit group by Mann-Whitney \u003cem\u003eU\u003c/em\u003e-test. All data are presented in box-and-whisker plots. The whiskers indicate the range, the top and bottom of the boxes indicate the inter-quartile range, and the horizontal line within each box indicates the median.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/f8e34d1a1f567ae0dec076ca.png"},{"id":49894702,"identity":"696d95be-73b8-4e7a-b34a-abbeccbeded3","added_by":"auto","created_at":"2024-01-19 21:33:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":57635,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdjusted analysis for factors associated with severe malaria\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003ea\u003c/strong\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eFootnote figure 4: \u003csup\u003ea \u003c/sup\u003eMultivariate logistic regression analysis for misdiagnosis on severe malaria. We included variables with a univariate \u003cem\u003ep\u003c/em\u003e value of 0.2 or smaller for severe malaria and those clinically relevant. The model showed a \u003cem\u003ep\u003c/em\u003e value of 0.435 for the Hosmer-Lemeshow goodness-of-fit test. All variance inflation factor values of the variables included in the final multivariate model were less than 1.5.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb \u003c/sup\u003ePrimary healthcare services includes primary care attending physicians and emergency rooms liked to primary care.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/308031ddcce241400849dc38.png"},{"id":69834999,"identity":"36967c13-11bb-4851-8842-e31cc46d5b9c","added_by":"auto","created_at":"2024-11-25 16:11:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1105654,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/f42bc4ff-38dc-4fb0-bfba-41e0086cab3f.pdf"},{"id":49894704,"identity":"e1344dff-bdd5-4933-b8d1-07f9190108d5","added_by":"auto","created_at":"2024-01-19 21:33:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23132,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile.docx","url":"https://assets-eu.researchsquare.com/files/rs-3870620/v1/54f7a4f40eedc4056af8e8e6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of time delays in imported malaria diagnosis: not only on the patient’s shoulders.","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMalaria, despite being a potentially preventable and treatable disease, ​remains​ a public health challenge that affects approximately 247 million​ people per year in endemic areas, with more than 94%​ of the cases occurring in ​​sub-Saharan Africa [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Spain is the fourth European country with the highest rate of imported malaria [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Almeria is the province of southern Spain where more cases of imported malaria are diagnosed annually, most of them occurring in travelers visiting friends and relatives (VFR)[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This is closely bound to the population profile of the Almeria province, with a 21.7% of foreign residents, many of them (around 45%) being migrants coming from the African continent [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeing a potentially medical emergency, the World Health Organization continues to point out the importance of early diagnosis that allows effective treatment to be initiated within the first 24\u0026ndash;48 hours [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the diagnosis of malaria depends on clinical suspicion since quite specific techniques, such as immunochromatography (rapid diagnostic test) and/or peripheral blood smear, are needed for its detection [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In areas where malaria is not endemic, a clinical diagnosis of malaria may be challenging for healthcare providers unfamiliar with the disease. The variable and non-specific nature of the earliest symptoms of malaria, which often overlap with other common viral infections and other banal conditions, difficult early diagnosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Some studies show that up to 40\u0026ndash;60% of malaria cases go unnoticed in their initial presentation and alternative erroneous diagnosis are stablished instead [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Such misdiagnosis contributes to increase morbidity and mortality, especially in the cases of \u003cem\u003eP. falciparum\u003c/em\u003e malaria [\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn non-endemic areas, retrospective studies have shown that the time interval from symptom onset to malaria diagnosis ranges from 3\u0026ndash;6 days, mostly due to patient's delay in seeking healthcare [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18 CR19 CR20\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, few studies have analyzed the delay in diagnosis owning to healthcare providers once the patient has consulted [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In this case, delay is most probably related to the lack of awareness of malaria among such professionals.\u003c/p\u003e \u003cp\u003eThe objective of this study is to compare, in an European area with a high rate of immigrants from sub-Saharan Africa and universal health coverage, the characteristics of patients with a malaria diagnosis at first visit against those who were initially misdiagnosed. Likewise, analysis of the different time delays according to diagnosis at first visit is made. Finally, the association of misdiagnosis with the risk of severe malaria was also explored.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study design and study population\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective observational study of malaria cases admitted to the University Poniente hospital (El Ejido, Almeria, Spain) from January 2010 to December 2022 was conducted. Eligible patients were included in the analysis if they fulfilled the following criteria: sub-Saharan origin, older than 14 years of age, stay in endemic area in the last year, and symptomatic malaria admitted to hospital. Patients with submicroscopic malaria were excluded.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Data collected and definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMalaria diagnosis was made by means of rapid direct tests (the BinaxNOW\u0026reg; malaria test or\u0026nbsp;SD Bioline\u0026reg;\u0026nbsp;malaria Ag Pf/Pan, Korea) and/or direct microscopic examination of blood thin smear. A conventional Nested Multiplex Malaria PCR (NM-PCR) capable of identifying four human malaria species (\u003cem\u003eP. vivax, P. falciparum, P. ovale\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;P. malariae\u003c/em\u003e)\u0026nbsp;was used when a mixed infection was suspected [23].\u003c/p\u003e\n\u003cp\u003eData for each malaria episode were obtained retrospectively from the hospital electronic health records. The collection of data included all visits to any public healthcare service or unit after the onset of symptoms. Data collected are reported in Supplementary data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpain-based migrants traveling to their homeland to visit friends and relatives were considered as VFR travelers whereas those migrants traveling first time to Europe from malaria endemic areas were considered as migrants. Pandemic period of SARS-CoV2 was considered between March 2020 and December 2021. Severe malaria was defined as the combination of one or more severity criteria according to the 2023 World Health Organization definition [6] and requirement of ICU admission. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients suspected of malaria (and accordingly tested) at the first medical visit were included in the \u0026ldquo;Malaria diagnosis at first visit\u0026rdquo; group. The remaining patients, for whom the clinical suspicion of malaria was not established and where not offered a malaria test and received an alternative diagnosis, were included in the \u0026ldquo;misdiagnosis at first visit\u0026rdquo; group (figure 1).\u003c/p\u003e\n\u003cp\u003eAccording to the definitions of Bastaki et al. [22], the following time periods were calculated (figure 1):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eTime to onset of symptoms, defined as the time between returning from a malaria endemic country and the onset of symptoms for malaria.\u003c/li\u003e\n \u003cli\u003ePatient delay, defined as the time between the onset of symptoms and seeking healthcare advice for the first time or first attending a medical facility.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMedical diagnostic delay, defined as the time between first attending a medical facility or seeking healthcare advice and the diagnosis of malaria. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTotal diagnostic delay, defined as the time between the onset of symptoms and the diagnosis of malaria.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u0026nbsp;To compare groups of similar size, the median value of total diagnostic delay was chosen to define an inappropriate diagnostic delay. All patients were treated at the time of malaria diagnosis so the variable \u0026ldquo;treatment delay\u0026rdquo; was not calculated. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were expressed as mean, standard deviation, median and interquartile range (IQR), and categorical variables as absolute numbers and percentages. Univariate comparisons were performed by the chi-square or Fisher tests for categorical variables, and the Mann\u0026ndash;Whitney \u003cem\u003eU\u003c/em\u003e test for continuous variables. A \u003cem\u003ep-\u003c/em\u003evalue \u0026lt; 0.05 was considered as statistically significant. Univariate analyses of factors potentially associated with severe malaria were performed by univariate logistic regression. Potentially clinically relevant variables and those with a univariate \u003cem\u003ep\u003c/em\u003e value less than 0.10 were included in the multivariate logistic regression model to estimate the adjusted OR for severe malaria. Potential interactions were explored and included if they had a significant modifying effect. Variable selection was performed manually using a backward stepwise procedure. The Statistical Package for the Social Sciences (SPSS) version 26.0.0 and the R software v3.0.1 were used for the analysis. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Ethics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been approved by the local Ethics Committee of the Coordinating Site (Almer\u0026iacute;a, Spain), code PUB_23_16.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eA flowchart of the study is shown in Figure 2. Two-hundred and ninety-seven patients were included in the analysis. At first medical visit, malaria was suspected or diagnosed in 160 patients (53.9%) (malaria diagnosis at first visit group), while in 137 (46.1%) the initial diagnosis was incorrect (misdiagnosis group).\u003c/p\u003e\n\u003cp\u003eThe epidemiological characteristics of the patients included in the study are shown in Table 1. The majority were males (93.3%) with a median age of 35 years (IQR 30 \u0026ndash; 41) and 97.6% were VFR travelers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. General characteristics of the patients included in the study a\u003c/strong\u003e\u003cstrong\u003en\u003c/strong\u003e\u003cstrong\u003ed according to diagnosis at first visit\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n = 297)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003eMalaria diagnosis at first visit\u003c/p\u003e\n \u003cp\u003e(n = 160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003eMisdiagnosis at first visit\u003c/p\u003e\n \u003cp\u003e(n = 137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAge in years (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e35 (30 \u0026ndash; 41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e36 (30 \u0026ndash; 41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e34 (30 \u0026ndash; 40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.186\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e277 (93.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e145 (90.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e132 (96.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTraveler category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.1164021164021163%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.1005291005291%\" valign=\"top\"\u003e\n \u003cp\u003eVFR travelers\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.81305114638448%\" valign=\"top\"\u003e\n \u003cp\u003e290 (97.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.164021164021165%\" valign=\"top\"\u003e\n \u003cp\u003e156 (97.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e134 (97.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e0.585\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.1164021164021163%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.1005291005291%\" valign=\"top\"\u003e\n \u003cp\u003eMigrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.81305114638448%\" valign=\"top\"\u003e\n \u003cp\u003e7 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.164021164021165%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e0.585\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eLength of stay in Spain before malaria\u0026nbsp;diagnosis,\u0026nbsp;in months (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e120 (84 \u0026ndash; 144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e120 (84 \u0026ndash; 156)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e120 (80 \u0026ndash; 144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.477\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.1164021164021163%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.1005291005291%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;VFR travelers\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.81305114638448%\" valign=\"top\"\u003e\n \u003cp\u003e120 (84 \u0026ndash; 146)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.164021164021165%\" valign=\"top\"\u003e\n \u003cp\u003e124 (96 \u0026ndash; 156)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e120 (84 \u0026ndash; 144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.1164021164021163%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.1005291005291%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Migrants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.81305114638448%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.164021164021165%\" valign=\"top\"\u003e\n \u003cp\u003e1 (1 \u0026ndash; 1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.576719576719576%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.229276895943563%\" valign=\"top\"\u003e\n \u003cp\u003e0.430\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUnder specialized medical care before traveling (only apply to VFRs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e26 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e12 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e14 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHIV coinfection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e13 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e8 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e5 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"31.09540636042403%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMedical comorbidities\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.84452296819788%\" valign=\"top\"\u003e\n \u003cp\u003e7 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.20141342756184%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.6113074204947%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.247349823321555%\" valign=\"top\"\u003e\n \u003cp\u003e0.415\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eExcept where otherwise specified, data represent numbers (%) of patients. \u003cem\u003eP\u0026nbsp;\u003c/em\u003evalues were calculated by chi-square test, except where otherwise specified.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Mann-Whitney \u003cem\u003eU\u003c/em\u003e-test\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e One patient was born in Spain\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u0026nbsp;\u003c/sup\u003eFisher test\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ee\u003c/sup\u003e Hypertension (n = 3), diabetes mellitus (n = 3), dyslipidemia (n = 1).\u003c/p\u003e\n\u003cp\u003eTable 2 shows the general features of the first medical visits (when and where they took place) along with several clinical features and laboratory results at hospital admission, and the different types of time delays. For almost two thirds of the patients (n = 191; 64.3%), the first medical visit took place in out-of-hospital public healthcare facilities (\u003cem\u003ei.e.\u003c/em\u003e primary care services: 22.5% primary care attending physician and 77.5% in emergency services linked to primary care). In most cases (99.0%), the infection was caused by the species \u003cem\u003eP. falciparum\u003c/em\u003e. Fifty-seven patients (19.2%) had severe malaria.\u003c/p\u003e\n\u003cp\u003eRegarding VFR travelers, 23.8% (n=69) had visited a specialized pre-travel clinic prior to the trip, with no differences between the misdiagnosis and the malaria diagnosis at first visit groups (p=0.757). Of these, 50 patients (72.5%) claimed to have received malaria chemoprophylaxis instructions although they were not followed properly in any case. Twenty - six patients were under specialized care for diverse medical conditions before traveling but most of them (92.3%) did not disclose their traveling plans to their doctors, so no travel - advice could be given.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Characteristics at hospital admission and according to diagnosis at first visit\u003c/strong\u003e\u003csup\u003ea\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"581\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n = 297)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003eMalaria diagnosis at first visit\u003c/p\u003e\n \u003cp\u003e(n = 160)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003eMisdiagnosis at first visit\u003c/p\u003e\n \u003cp\u003e(n = 137)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ep\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSARS CoV2 pandemic period\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e13 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e6 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e7 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMedical department at first visit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Primary care attending physician\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e43 (14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e24 (15.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e19 (13.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Emergency rooms linked to primary healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e148 (49.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e47 (29.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e101 (73.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;Hospital emergency room\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e106 (35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e89 (54.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e17 (12.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSymptoms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eFever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e216 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e144 (90.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e72 (52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eAbdominal pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e51 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e37 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e14 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eGastrointestinal tract (other than abdominal pain)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e72 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e45 (28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e27 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e171 (57.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e108 (67.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e63 (46.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eRespiratory tract\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e44 (14.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e19 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e25 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eArthromyalgia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e124 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e70 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e54 (39.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 3 coexisting symptoms\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e111 (37.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e84 (52.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e27 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eLaboratory results (mean, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e13.3 (1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e13.4 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e13.1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.198\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003ePlatelets (x10\u003csup\u003e3\u003c/sup\u003e/microL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e94.1 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e106.8 (54.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e78.7 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003eC-Reactive protein (mg/dL)\u003c/p\u003e\n \u003cp\u003eReference values (0.0 \u0026ndash; 0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e10.9 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e8.7 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e13.6 (6.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eParasitemia (%) (mean, SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e1.9 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e1.7 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e2.2 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.029\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMalaria species\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ePlasmodium falciparum\u003c/em\u003e\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e294 (99.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e158 (98.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e136 (99.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.558\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"2.0654044750430294%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30.292598967297764%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eNon-Plasmodium falciparum\u003c/em\u003e\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.558\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSevere malaria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e64 (21.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e26 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e38 (27.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eLength of hospital stay, in days (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.221\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTime to onset of symptoms, in days (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1 \u0026ndash; 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1 \u0026ndash; 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e4 (1.5 \u0026ndash; 11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e0.224\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePatient delay, in days (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e3 (1.25 \u0026ndash; 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1 \u0026ndash; 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMedical diagnostic delay, in days (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e0.5 (0 \u0026ndash; 2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e0 (0 \u0026ndash; 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e2 (2 \u0026ndash; 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.358003442340795%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal diagnostic delay, in days (median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.146299483648882%\" valign=\"top\"\u003e\n \u003cp\u003e4 (2 \u0026ndash; 7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.17039586919105%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2 \u0026ndash; 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.588640275387263%\" valign=\"top\"\u003e\n \u003cp\u003e5 (3 \u0026ndash; 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.736660929432015%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eExcept where otherwise specified, data represent numbers (%) of patients. \u003cem\u003eP\u0026nbsp;\u003c/em\u003evalues were calculated by chi-square test, except where otherwise specified.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Univariate comparison between primary healthcare services (primary care attending physician and emergency rooms linked to primary care) and hospital healthcare (hospital emergency room).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ec\u003c/sup\u003e Mann-Whitney \u003cem\u003eU\u003c/em\u003e-test\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ed\u0026nbsp;\u003c/sup\u003eIncluding 5 patients with mixed infection: \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. malariae\u0026nbsp;\u003c/em\u003ecoinfection (n = 3, 1%); \u003cem\u003eP. falciparum\u003c/em\u003e and \u003cem\u003eP. ovale\u0026nbsp;\u003c/em\u003ecoinfection (n = 2, 0.7%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ee\u0026nbsp;\u003c/sup\u003e\u003cem\u003eP. ovale\u003c/em\u003e (n = 2; 0.7%); \u003cem\u003eP. vivax\u003c/em\u003e (n = 1; 0.3%).\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ef\u0026nbsp;\u003c/sup\u003eFisher test\u003cstrong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 Differential characteristics of patients with initial misdiagnosis compared to those with malaria diagnosis at first visit\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNoteworthy, 46.1% of patients received a wrong diagnosis at the first medical visit (n=137). The characteristics of these patients compared to those who received a correct diagnosis are shown in Tables 1 and 2. No differences in the epidemiological characteristics were found. Respecting the different medical services, initial misdiagnosis was more frequent in the out-of-hospital setting compared to patients treated directly in the hospital emergency room (87.5% vs 12.5%; p\u0026lt;0.001). Within the out-of-hospital setting, initial misdiagnosis was more common for patients treated in the emergency rooms linked to primary care than for those treated by their primary care attending physician (84.2% vs 15.8%, p=0.040). The presence of fever, abdominal pain and headache, as well as the concurrence of 3 or more symptoms at the time of consultation (p\u0026lt;0.001) was associated with an increased likelihood of a correct initial diagnosis of malaria.\u003c/p\u003e\n\u003cp\u003eIn relation to the laboratory tests results, patients with initial misdiagnosis had a significantly lower platelet count at the time of malaria final diagnosis (78.7 vs 106.8 x10\u003csup\u003e3\u003c/sup\u003e/microL; p\u0026lt;0.001) and a higher absolute value of C-reactive protein (13.6 vs 8.7 mg/dL; p\u0026lt;0.001). Furthermore, greater levels of parasitization at hospital admission were shown in patients with initial misdiagnosis (2.2 vs 1.7; p=0.015) as well as a higher proportion of severe malaria cases (27.7% vs 16.3%, p=0.016). However, no differences were found regarding the length of hospital stay time between both groups. There were no deaths among the patients included in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Diagnostic delay in patients diagnosed with malaria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTime delays for the total population of the study (n = 297) and according to initial diagnosis groups are shown in table 2 and figure 3, respectively. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.1 Time to onset of symptoms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the total number of patients included in the study (n=297), the median time from arrival to Spain to the onset of symptoms was 4 days (IQR 1 \u0026ndash; 9) (table 2). Most patients (n=286, 96.3%) had symptoms within the first 30 days after arrival. Four patients (1.3%) started with malaria symptoms after more than 100 days since leaving the endemic area, with a maximum of 343 days in one patient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe median time to symptom onset was significantly longer in non-VFR patients than in VFR travelers (10 vs 4 days; p=0.022). On the contrary, there were no differences between patients correctly diagnosed at first medical visit versus those misdiagnosed (Figure 3a)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2 Time to seeking healthcare advice (patient delay)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median time from the onset of symptoms and seeking healthcare advice or first attending a medical facility\u0026nbsp;was 2 days (IQR 1 - 4) (table 2). Thirty-six patients (12.4%) sought medical advice for the first time more than 7 days after the onset of symptoms. This time delay was significantly longer in patients who were correctly diagnosed at first visit (Figure 3b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.3 Time from first medical visit to diagnosis (medical diagnostic delay)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor the 297 patients, the median time from the first healthcare visit to the diagnosis of malaria was 0.5 days (IQR 0 \u0026ndash; 2.5) (table 2). Figure 3c shows the median medical diagnostic delay until the correct diagnosis of malaria was reached according to the number of medical visits needed. The medical diagnostic delay of patients with initial misdiagnosis increased with each visit until reaching a median of 13.5 days (IQR 7.25 \u0026ndash; 22.0) in those patients who needed up to five visits before getting the right malaria diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe majority of the 160 patients correctly suspected of malaria at first visit had a confirmatory malaria test done at the same time. However, in 10 of them (6.2%), the malaria blood test was scheduled for later on, with a mean delay time of 9.3 days and a maximum of up to 50 days until blood analysis were finally done.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding patients misdiagnosed (n=137), 95 (69.3%) were diagnosed with malaria at the second medical visit. On the other hand, 28 (20.4%), 10 (7.2%) and 4 (2.8%) patients needed three, four and five medical visits, respectively, before getting the right malaria diagnosis. The most frequent alternative misdiagnoses at first visit were: viral disease (35.8%), acute gastroenteritis (14.6%), headache without warning signs (12.4%), pharyngitis (9.5%), and febrile syndrome of undetermined etiology (5.8%). Other less frequent diagnoses were: mechanical lower back pain (2.9%), otitis (0.7%), urinary tract infection (0.7%), and side effect of SARS CoV2 vaccine (0.7%). The diagnosis was not recorded in 21 patients (15.6%). In most cases (n = 118; 86.8%) symptomatic treatment was prescribed, including painkillers and non-steroidal anti-inflammatory drugs. Fifteen patients (11.0%) received antibiotic therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.4 Time between the onset of symptoms and the diagnosis of malaria (total diagnostic delay)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, for the whole set of patients (n=297), the total diagnostic delay median was 4 days (IQR 2 \u0026ndash; 7) with a mean of 5.9 days (table 2). Delay was significantly greater in patients with initial misdiagnosis as compared to those with correct diagnosis (Figure 3d).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne hundred and sixty-three patients (54.9%) had a diagnostic delay\u0026ge;4 days, considered as an inappropriate. Such inappropriate diagnostic delay was related to first visit having place in primary care services and to the onset of symptoms before arrival to Spain (p\u0026lt;0.05) (supplementary Table 1). Conversely, presenting with fever and headache at first visit was associated with a shorter proportion of inappropriate diagnostic delay (p\u0026lt;0.05). Patients with inappropriate diagnostic delay had significantly lower hemoglobin concentrations and platelet counts and higher C-reactive protein and parasitemia levels (p \u0026lt; 0.05). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe univariate analysis of the variables related to severe malaria is shown in the Supplementary Table 2. Misdiagnosis at first visit was associated with an increased risk of severe malaria (crude OR 1.978 [1.978 \u0026ndash; 3.472], p=0.017). SARS CoV2 pandemic period was also associated with an increased risk of severe malaria (crude OR 3.340 [1.018 \u0026ndash; 10.318], p=0.036). In the multivariate analysis (Figure 4), after controlling for potential confounders, misdiagnosis (adjusted OR 2.321 [1.090 \u0026ndash; 5.104], p=0.031) and SARS CoV2 pandemic period (adjusted OR 3.981 [1.142 \u0026ndash; 13.914], p=0.027) remained independently associated with an increased risk of developing severe malaria.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn our study we have observed that almost half of patients with malaria are misdiagnosed at first medical visit, even though the study is carried out in an area with a high proportion of long stablished migrant population from sub-Saharan Africa where a remarkably high number of malaria cases are reported annually. Such initial misdiagnosis is significantly related with an increased risk of developing severe malaria, although it does not lead to a worse outcome for those misdiagnosed in terms of hospital stay and related deaths.\u003c/p\u003e \u003cp\u003eAlthough little is published, the association between initial misdiagnosis and the development of severe malaria has also been demonstrated in other studies [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] using the same criteria for severe malaria the WHO severity criteria or the need for ICU admission as our [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Besides, the percentage of patients initially misdiagnosed also changes dramatically depending on the type and level of medical facility where the patient was treated [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Nevertheless, in our case, the place where the patient is initially diagnosed is not associated with an increased risk of developing severe malaria. Such circumstance may be related to the fact that those patients with milder forms of presentation may be more prone to seek attention in the primary care setting instead of in the hospital emergency room.\u003c/p\u003e \u003cp\u003eInappropriate diagnostic delay, defined in our study as a total diagnostic delay\u0026thinsp;\u0026ge;\u0026thinsp;4 days, is associated with initial misdiagnosis and this is consistent with previous studies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Nonetheless, in our study this delay is not correlated with an increased risk of severe malaria. The available data published about the association between inappropriate diagnostic delay and severe malaria are scarce and heterogeneous, mainly due to the lack of standardization to establish what is considered an acceptable duration to achieve malaria diagnosis from the onset of symptoms [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Although there is no clear consensus, in cohorts of patients with severe malaria, the diagnostic delay was longer than 5 days [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This disparity could justify that our diagnostic delay\u0026thinsp;\u0026ge;\u0026thinsp;4 days is not associated with severe malaria.\u003c/p\u003e \u003cp\u003eDespite the fact that patients with initial misdiagnosis seemed to consult earlier from the onset of symptoms, the overall diagnosis delay is larger than that of those with malaria diagnosis at first visit. This means that much of the total diagnostic delay in the misdiagnosis group is primarily due to medical diagnostic delay. There are very few studies that specifically assess medical diagnostic delay, with an mean published around 0.5\u0026ndash;1.7 days [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Even so, when all patients included in the study are analyzed together, patient delay is greater than medical diagnostic delay, confirming what was found in other studies and revealing the importance and consistency of such delay [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This data could be probably related to the profile of our patients, which VFR travelers predominating. Flateau et al. observed that VFR travelers tended to have a longer delay in seeking healthcare, probably due to a lower perception of the risk of acquiring malaria along with not considering malaria a significant health threat [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Moreover, as we have observed in our own study, this group of travelers presented lower rates of attendance to pre-travel clinics and compliance to malaria chemoprophylaxis [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These data highlight the need to implement training programs aimed to health professionals, but also to broadcast public information campaigns targeted to travelers underlining the value of pre-travel advice and the importance of seeking early medical advice upon return from malaria-endemic areas in the face of any symptoms. Travelers should also be advised to provide recent travel information so to help in the diagnostic pathway, specially when presenting with vague symptoms or mild clinical conditions.\u003c/p\u003e \u003cp\u003eIt is noteworthy that up to 30.9% of patients wrongly diagnosed at first visit (14.1% of the total patients included in the study) needed to be evaluated more than twice before a malaria diagnosis was reached, with a median diagnostic delay of almost two weeks. Moreover, in some cases, the attending physicians did not consider suspected malaria as a potential medical emergency and diagnostic tests were requested as part of a routine analysis. In these cases, the diagnostic delay reached up to 50 days. These data are far from the WHO recommendations that stress the need for an urgent evaluation of all patients suspected of having malaria [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt should also be noted that patients with a failed initial diagnosis presented more undifferentiated syndromes, with a lower proportion of fever, abdominal pain or headache and a lower concurrence of more than three symptoms. It is important to remember that malaria can cause several and diverse symptoms and should not only be suspected in patients with febrile syndromes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Surely, the most definitive clue is the history of traveling to a malaria endemic area, a decisive information that should always be registered in the clinical history of these patients. Regarding laboratory tests, patients with initial misdiagnosis presented, when finally diagnosed, worse results, compatible with a more advanced stage of the disease, such as greater thrombocytopenia, higher parasite loads and higher levels of CRP.\u003c/p\u003e \u003cp\u003eThe period of the SARS CoV2 pandemic seems to be related to a higher probability of serious cases but not to a greater diagnostic delay, although due to the small number of patients treated during this period, data should be interpreted with caution. Other studies including a higher proportion of patients diagnosed during this pandemic period have also shown higher rates of severe malaria cases and longer diagnostic delays, but data are heterogeneous [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Such findings could be due to underdiagnosis of milder malaria cases as a result of the saturation of the healthcare systems, as well as to a lower diagnostic offer.\u003c/p\u003e \u003cp\u003eThe limitations of the study derive, first of all, from its retrospective nature, as it is likely that some relevant clinical data were not properly recorded in the medical records. Secondly, extrapolation of the results to other types of population is not guaranteed since only patients from sub-Saharan Africa, mostly VFR and largely infected by \u003cem\u003eP. falciparum\u003c/em\u003e, have been included. On the other hand, the large number of patients included in the study strengthens our results. Furthermore, it should also be noted that this is one of the few studies published so far addressing specifically medical diagnostic delay in patients with imported malaria once they have sought medical advice. It could be the starting point for a deeper analysis of such delay and the implementation of measures to shorten it.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, the data from this study reveal a situation of concern, since even in an area with a high rate of patients diagnosed annually with malaria and where specific training activities aimed to both hospital and out-of-hospital healthcare personnel are periodically carried out, the number of patients with initial misdiagnosis is surprisingly high. Misdiagnosis leads to a larger number of medical visits, a larger medical diagnostic delay, and larger proportion of severe malaria cases; it also may contribute to increase healthcare expenses. Misdiagnosis could be an even more serious problem in those non-endemic areas where malaria cases are not as frequent and healthcare personnel is not as familiar with the disease. It seems necessary to redesign the educational and training strategies aimed at improving knowledge in the field of imported diseases among healthcare professionals, specially for those working in the out-of-hospital setting. Finally, we must not forget the actions targeted at travelers in relation to the prevention of malaria, with special attention to VFR travelers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding statement:\u0026nbsp;\u003c/strong\u003eThis work was supported by the Red de Investigaci\u0026oacute;n de Centros de Enfermedades Tropicales \u0026ndash;\u0026nbsp;RICET (Project RD16/0027/0013 of the PN de I+D+I, ISCIII-Subdirecci\u0026oacute;n General de Redes y Centros de Investigaci\u0026oacute;n Cooperativa RETICS, co-financed with FEDER funds -European Regional Development Fund- \u0026quot;A way to make Europe\u0026rdquo;/\u0026rdquo;Investing in your future\u0026rdquo;), Ministry of Health and Consumption, Madrid; and by the research group PAIDI CTS582 of the regional Ministry of Health and Families of the Government of Andalusia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eAll authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe thank Adri\u0026aacute;n Aparicio Mota, technician in Research Methodology and Biostatistics from FIBAO, for providing invaluable support for the statistical analysis of the data.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eN.C.F: Conceptualization, Writing\u0026ndash;Original Draft, Methodology, Formal Analysis, Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. MJ.S.P: Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. AB.L.S: Formal Analysis, Investigation, Writing\u0026ndash;Review \u0026amp; Editing. J.V.V: Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. MP.L.G: Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. MI.C.B: Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. C.O.L: Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing. R.P.M: Investigation, Writing\u0026ndash;Review \u0026amp; Editing. J.S.C:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Investigation, Data curation, Writing\u0026ndash;Review \u0026amp; Editing, Supervision. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit Author Statement:\u0026nbsp;\u003c/strong\u003eThe present version of this paper has met the approval of all authors and they accept full responsibility for the content. The authors declare that this manuscript has not been simultaneously submitted for publication in any other journal, nor have the findings been partially disclosed in any other publication.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. World malaria report 2022. Geneva: World Health Organization; 2022. 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Alternative polymerase chain reaction method to identify Plasmodium species in human blood samples: the semi-nested multiplex malaria PCR (SnM-PCR). Trans R Soc Trop Med Hyg. 2002 Apr;96 Suppl 1:S199-204.\u003c/li\u003e\n\u003cli\u003eCheckley AM, Smith A, Smith V, et al. Risk factors for mortality from imported falciparum malaria in the United Kingdom over 20 years: An observational study. BMJ. 2012 Apr 27;344(7854).\u003c/li\u003e\n\u003cli\u003eValls ME, Nicol\u0026aacute;s JM, Gonz\u0026aacute;lez A et al. Severe Imported Malaria in Adults: Retrospective Study of 20 Cases. Am J Trop Med Hyg. 2009 Oct 1;81(4):595\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eChristen D, Steffen R, Schlagenhauf P. Deaths caused by malaria in Switzerland 1988-2002. American Journal of Tropical Medicine and Hygiene. 2006;75(6):1188\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eHiga F, Tateyama M, Tasato D et al. Imported malaria cases in Okinawa Prefecture, Japan. Jpn J Infect Dis. 2013;66(1):32-5.\u003c/li\u003e\n\u003cli\u003eMcCarthy AE, Morgan C, Prematunge C, Geduld J. Severe malaria in Canada, 2001-2013. Malar J. 2015 Dec 1;14(1).\u003c/li\u003e\n\u003cli\u003eNakayama K, Shimizu T. Reducing the delay in initiation of treatment improved clinical outcomes in patients with imported malaria. Jpn J Infect Dis. 2014;67(1):27-32.\u003c/li\u003e\n\u003cli\u003eChalumeau M, Holvoet L, Ch\u0026eacute;ron G et al. Delay in diagnosis of imported Plasmodium falciparum malaria in children. European Journal of Clinical Microbiology and Infectious Diseases. 2006 Mar;25(3):186\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eF\u0026auml;rnert A, Wyss K, Dashti S, Naucler P. Duration of residency in a non-endemic area and risk of severe malaria in African immigrants. Clinical Microbiology and Infection. 2015 May 1;21(5):494\u0026ndash;501.\u003c/li\u003e\n\u003cli\u003eDe Gier B, Suryapranata FST, Croughs M et al. Increase in imported malaria in the Netherlands in asylum seekers and VFR travellers. Malar J. 2017 Feb 2;16(1):1\u0026ndash;8.\u003c/li\u003e\n\u003cli\u003eKendjo E, Houz\u0026eacute; S, Mouri O et al. Epidemiologic Trends in Malaria Incidence Among Travelers Returning to Metropolitan France, 1996-2016. JAMA Netw Open. 2019 Apr 5;2(4):e191691.\u003c/li\u003e\n\u003cli\u003eSmith AD, Bradley DJ, Smith V et al. Imported malaria and high risk groups: Observational study using UK surveillance data 1987-2006. BMJ. 2008 Jul 12;337(7661):103\u0026ndash;6.\u003c/li\u003e\n\u003cli\u003eAngelo KM, Libman M, Caumes E et al. Malaria after international travel: A GeoSentinel analysis, 2003-2016. Malar J. 2017 Jul 20;16(1).\u003c/li\u003e\n\u003cli\u003eFerrara P, Masuet-Aumatell C, Ramon-Torrell JM. Pre-travel health care attendance among migrant travellers visiting friends and relatives (VFR): A 10-year retrospective analysis. BMC Public Health. 2019 Oct 28;19(1).\u003c/li\u003e\n\u003cli\u003ePaudel P, Raina C, Zwar N et al. Risk activities and pre-travel health seeking practices of notified cases of imported infectious diseases in Australia. J Travel Med. 2017 Sep 1;24(5).\u003c/li\u003e\n\u003cli\u003eDe Laval F, Maugey N, Bonet D\u0026rsquo;Oleon A at al. Increased risk of severe malaria in travellers during the COVID-19 pandemic. J Travel Med. 2021 Aug 1;28(6).\u003c/li\u003e\n\u003cli\u003eRobben PM, Dunbar CR, Akin EH et al. Late-presenting Plasmodium falciparum Malaria in a Non-Endemic Setting During COVID-19 Travel Restrictions. Mil Med. 2023 May 16;188(5\u0026ndash;6):e1335\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eNorman FF, Trevi\u0026ntilde;o-Maruri B, Ruiz Giard\u0026iacute;n JM et al. Trends in imported malaria during the COVID-19 pandemic, Spain (+Redivi Collaborative Network). J Travel Med. 2022 Aug 1;29(6).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Imported Malaria, diagnostic delay, travelers, migrants, travel medicine","lastPublishedDoi":"10.21203/rs.3.rs-3870620/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3870620/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eTo analyze the diagnostic delay in malaria related to misdiagnosis at first visit medical visit and its association with the risk of severe malaria in non-endemic areas.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective observational study of sub-Saharan migrants with imported malaria from January-2010 to December-2022. Patients were allocated in two groups if they were tested for malaria at first medical visit or not. Time delays in seeking healthcare, medical diagnostic delay and total diagnostic delay were calculated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e297 patients were included in the analysis. At first medical visit, malaria was misdiagnosed in 137 patients (46.1%). Medical diagnostic delay and total diagnostic delay were larger for the misdiagnosis group than for those properly diagnosed at first visit (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Although time in seeking healthcare was shorter in the misdiagnosis group, the presence of suggesting symptoms, such as fever, was lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.050). Misdiagnosis was more frequent in emergency rooms linked to primary healthcare (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). For the overall population (n\u0026thinsp;=\u0026thinsp;297), total diagnostic delay was mainly due to delay in seeking healthcare. Initial misdiagnosis was associated with a higher risk of severe malaria (adjusted OR 2.23 [1.09\u0026ndash;5.10], p\u0026thinsp;=\u0026thinsp;0.031).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn a non-endemic area with a high rate of imported malaria, the percentage of patients misdiagnosed is surprisingly high. Misdiagnosis is associated with longer medical and total diagnostic delays and with a higher risk of severe malaria. It seems necessary to redesign training programs to improve knowledge among healthcare professionals and actions targeted to travelers to promote seeking healthcare advice promptly.\u003c/p\u003e","manuscriptTitle":"Analysis of time delays in imported malaria diagnosis: not only on the patient’s shoulders.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-19 21:33:27","doi":"10.21203/rs.3.rs-3870620/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T09:21:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-07T20:25:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269568389351228962851992546035891622683","date":"2024-05-18T20:23:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-02-29T18:59:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9ba54a1a-9ec5-49e9-8137-c677e362b7cd","date":"2024-02-15T18:18:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-02-14T22:31:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-17T17:13:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-17T06:16:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Infection","date":"2024-01-16T17:49:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"infection","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infe","sideBox":"Learn more about [Infection](http://link.springer.com/journal/15010)","snPcode":"15010","submissionUrl":"https://submission.nature.com/new-submission/15010/3","title":"Infection","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1c89c18f-e130-41f3-b540-6354f242feaf","owner":[],"postedDate":"January 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-25T16:03:36+00:00","versionOfRecord":{"articleIdentity":"rs-3870620","link":"https://doi.org/10.1007/s15010-024-02436-1","journal":{"identity":"infection","isVorOnly":false,"title":"Infection"},"publishedOn":"2024-11-18 15:57:57","publishedOnDateReadable":"November 18th, 2024"},"versionCreatedAt":"2024-01-19 21:33:27","video":"","vorDoi":"10.1007/s15010-024-02436-1","vorDoiUrl":"https://doi.org/10.1007/s15010-024-02436-1","workflowStages":[]},"version":"v1","identity":"rs-3870620","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3870620","identity":"rs-3870620","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}