A novel electronic algorithm using host biomarker point-of-care tests for the management of febrile illnesses in Tanzanian children (e-POCT): A randomized, controlled non-inferiority trial

Background: The management of childhood infections remains inadequate in resource-limited countries, resulting in high mortality and irrational use of antimicrobials. Current disease management tools, such as the Integrated Management of Childhood Illness (IMCI) algorithm, rely solely on clinical signs and have not made use of available point-of-care tests (POCTs) that can help to identify children with severe infections and children in need of antibiotic treatment. e-POCT is a novel electronic algorithm based on current evidence; it guides clinicians through the entire consultation and recommends treatment based on a few clinical signs and POCT results, some performed in all patients (malaria rapid diagnostic test, hemoglobin, oximeter) and others in selected subgroups only (C-reactive protein, procalcitonin, glucometer). The objective of this trial was to determine whether the clinical outcome of febrile children managed by the e-POCT tool was non-inferior to that of febrile children managed by a validated electronic algorithm derived from IMCI (ALMANACH), while reducing the proportion with antibiotic prescription. Methods and findings: We performed a randomized (at patient level, blocks of 4), controlled non-inferiority study among children aged 2–59 months presenting with acute febrile illness to 9 outpatient clinics in Dar es Salaam, Tanzania. In parallel, routine care was documented in 2 health centers. The primary outcome was the proportion of clinical failures (development of severe symptoms, clinical pneumonia on/after day 3, or persistent symptoms at day 7) by day 7 of follow-up. Non-inferiority would be declared if the proportion of clinical failures with e-POCT was no worse than the proportion of clinical failures with ALMANACH, within statistical variability, by a margin of 3%. The secondary outcomes included the proportion with antibiotics prescribed on day 0, primary referrals, and severe adverse events by day 30 (secondary hospitalizations and deaths). We enrolled 3,192 patients between December 2014 and February 2016 into the randomized study; 3,169 patients (e-POCT: 1,586; control [ALMANACH]: 1,583) completed the intervention and day 7 follow-up. Using e-POCT, in the per-protocol population, the absolute proportion of clinical failures was 2.3% (37/1,586), as compared with 4.1% (65/1,583) in the ALMANACH arm (risk difference of clinical failure −1.7, 95% CI −3.0, −0.5), meeting the prespecified criterion for non-inferiority. In a non-prespecified superiority analysis, we observed a 43% reduction in the relative risk of clinical failure when using e-POCT compared to ALMANACH (risk ratio [RR] 0.57, 95% CI 0.38, 0.85, p = 0.005). The proportion of severe adverse events was 0.6% in the e-POCT arm compared with 1.5% in the ALMANACH arm (RR 0.42, 95% CI 0.20, 0.87, p = 0.02). The proportion of antibiotic prescriptions was substantially lower, 11.5% compared to 29.7% (RR 0.39, 95% CI 0.33, 0.45, p < 0.001). Using e-POCT, the most common indication for antibiotic prescription was severe disease (57%, 103/182 prescriptions), while it was non-severe respiratory infections using the control algorithm (ALMANACH) (70%, 330/470 prescriptions). The proportion of clinical failures among the 544 children in the routine care cohort was 4.6% (25/544); 94.9% (516/544) of patients received antibiotics on day 0, and 1.1% (6/544) experienced severe adverse events. e-POCT achieved a 49% reduction in the relative risk of clinical failure compared to routine care (RR 0.51, 95% CI 0.31, 0.84, p = 0.007) and lowered antibiotic prescriptions to 11.5% from 94.9% (p < 0.001). Though this safety study was an important first step to evaluate e-POCT, its true utility should be evaluated through future implementation studies since adherence to the algorithm will be an important factor in making use of e-POCT’s advantages in terms of clinical outcome and antibiotic prescription. Conclusions: e-POCT, an innovative electronic algorithm using host biomarker POCTs, including C-reactive protein and procalcitonin, has the potential to improve the clinical outcome of children with febrile illnesses while reducing antibiotic use through improved identification of children with severe infections, and better targeting of children in need of antibiotic prescription. The study protocol and related documents were approved by the institutional review boards of the Ifakara Health Institute and the National Institute for Medical Research in Tanzania, by the Ethikkommission Beider Basel in Switzerland, and the Boston Children’s Hospital ethical review board. An independent data and safety monitoring board oversaw the study. The trial was registered in ClinicalTrials.gov, identifier {"type":"clinical-trial","attrs":{"text":"NCT02225769","term_id":"NCT02225769"}}NCT02225769. This was a randomized (at patient level), open controlled trial to investigate whether a novel electronic algorithm using point-of-care (POC) testing, e-POCT, was not inferior in terms of clinical outcome to a validated electronic algorithm derived from IMCI (ALMANACH) when treating febrile infections in children under 5 years of age. In parallel to the randomized study, a small cohort of children managed per routine care was observed, and their clinical outcomes were compared to those of the children treated using e-POCT. The protocol for this trial, the statistical analysis plan, and supporting CONSORT checklist are available as supporting information (S1 and S2 Texts; S1 Table). This study was conducted in the city of Dar es Salaam, Tanzania. Malaria endemicity in this region is relatively low, with about 10% of fever patients positive for malaria; transmission is perennial with a peak in the post-rainy season [15]. Consecutive patients presenting for acute care during normal business hours at the outpatient departments of 3 district hospitals and at 6 health centers in Dar es Salaam were screened for eligibility. Recruitment sites were chosen to represent the pediatric outpatient population in Dar es Salaam. Inclusion criteria were age 2 to 59 months, history of fever for 7 days or less, and axillary temperature ≥ 37.5°C at presentation. Exclusion criteria were weight less than 2.5 kg, main complaint being an injury or acute poisoning, or previous medical care for the present illness. Children satisfying the inclusion and exclusion criteria were enrolled if the parent or guardian had received full information on the study and signed written informed consent. For the main comparison between e-POCT and ALMANACH, patients were enrolled by the study clinicians and then randomized to 1 of the 2 management arms. They were individually randomized in blocks of 4 according to a computer-generated randomization list provided by an independent, off-site researcher. Sealed, opaque forms were used for allocation concealment and were opened only after the patient’s enrollment. Patients in the routine care cohort were enrolled by a research assistant and directed to a routine clinician at the corresponding health center. The intervention consisted in having study clinicians use the e-POCT algorithm (e-POCT arm) or ALMANACH algorithm (control arm) during the consultation to manage the patient. The development, rationale, and content of the e-POCT algorithm are detailed in S1 Text. In brief, we performed a structured literature review focusing on (i) the identification of children with severe infections requiring referral, (ii) the identification of children with serious bacterial infections, including using CRP and PCT to predict the need for antibiotic treatment, and (iii) the identification of children with dehydration (S2 Table; S1 Fig). The evidence retrieved is described in detail in S3 Text. It was used to design the novel e-POCT electronic algorithm (Figs ​(Figs11 and ​and22). Example of input and output screens, sensor input, and background algorithm calculations. An example of a consultation with respective input and output screens is shown on the left; the background calculations of the algorithm are displayed on the right in black; input of information from POCTs is displayed in orange. CRP, C-reactive protein; F/u, follow-up; HIV, human immunodeficiency virus; PCT, procalcitonin; POCT, point-of-care test; mRDT, malaria rapid diagnostic test; RR, respiratory rate; SaO2, oxygen saturation. The main content (algorithm) of e-POCT is displayed. Questions and information requested by the algorithm are shown on the left side, the respective disease classifications and treatment recommendations on the right. 1Heart rate ≥ 90th percentile for age and temperature [19]. 2Blood glucose < 3.3 mmol/l. 3Respiratory rate ≥ 97th percentile for age and temperature [20]. 4Children ≥ 6 months only. 5Weight-for-age z-score < 3, per WHO 2006 growth charts, and/or mid-upper arm circumference < 11.5 cm and age > 6 months. 6Clouding of cornea or severe mouth ulcers or cough and tachypnea (respiratory rate ≥ 75th percentile for age and temperature [20]). 7Hb < 90 g/l (2–6 months), < 100 g/l (7–24 months), < 110 g/l (25–59 months). 8Measured for patients with negative mRDT only. 9Respiratory rate ≥ 75th percentile for age and temperature [20]. 10>5 loose stools over past 24 hours or ≥3 loose stools over past 24 hours and emesis or >3 emeses over past 24 hours. CNS, central nervous system; Hb, hemoglobin; IM, intramuscular; INH, inhaled; IR, intrarectal; mRDT, malaria rapid diagnostic test; ORS, oral rehydration solution; PMTCT, prevention of mother-to-child transmission; PO, per os; resp., respiratory; SaO2, oxygen saturation. e-POCT differs from the 2014 version of IMCI in the following ways: (i) use of pulse oximetry to identify children with hypoxemia and severe tachycardia, (ii) use of Hb testing to detect children with severe anemia, (iii) construction of a “severe respiratory distress” classification, (iv) refinement of criteria for severe malnutrition, (v) use of a 2-step approach including temperature- and age-corrected respiratory rate and CRP for diagnosing bacterial pneumonia, and (vi) use of CRP and PCT to decide on antibiotic prescription for children with fever without localizing symptoms. The main differences between the e-POCT and ALMANACH algorithms, as well as IMCI, are summarized in Table 1. We constructed a novel electronic algorithm, e-POCT, that was programmed into an Android-based mobile tool. The electronic version allowed integrating a greater amount of data, more elaborate calculations, and direct connection to the oximeter, without increasing the complexity of the consultation process for the clinician. The conjunctions “and” or “or” are to be read across columns. 1Severe respiratory distress: Speaks only single words or grunts or speaks short phrases only or short cries and lower chest wall indrawing. 2Severe tachypnea: respiratory rate ≥ 97th percentile for age and temperature [20]. 3Severe tachycardia: heart rate ≥ 90th percentile for age and temperature [19]. 4WFA z-score < −3 and/or MUAC < 11.5 cm and age > 6 months. 5WFH z-score < −3 and/or MUAC < 11.5 cm and age > 6 months; complications defined as feeding problem or medical problem. Please note that ALMANACH was developed based on the 2008 version of IMCI, which used only clinical signs for the identification of malnutrition. 6Very fast breathing: respiratory rate ≥ 50/min, regardless of age. 7Fast breathing: respiratory rate ≥ 50/min and age < 12 months or RR ≥ 40/min and age ≥ 12 months. 8Tachypnea: respiratory rate ≥ 75th percentile for age and temperature. 9>5 loose stools over past 24 hours or ≥3 loose stools over past 24 hours and emesis or >3 emeses over past 24 hours. 10Algorithm provides diagnoses and specific treatment recommendations for 13 common skin diseases (abscess, cellulitis, impetigo/pyoderma, tinea corporis, pityriasis versicolor, candidiasis, tinea capitis, scabies, chicken pox, herpes, larva migrans, eczema, urticarial). CNS, central nervous system; CRP, C-reactive protein; IMCI, Integrated Management of Childhood Illness; LRTI, lower respiratory tract infection; mRDT, rapid test for malaria; MUAC, mid-upper arm circumference; PCT, procalcitonin; POCT, point-of-care test, SaO2, oxygen saturation, HIV, human immunodeficiency virus; WFA, weight-for-age; WFH, weight-for-length/height. Children enrolled in the intervention arm were assigned to study clinicians using e-POCT (Figs ​(Figs1,1, ​,22 and S1) during 2 weeks, while children enrolled in the control arm were managed by other study clinicians using ALMANACH (S2 Fig). In order to minimize a cluster effect at clinician level, clinicians then switched arms, and thus algorithms, every 2 weeks. Based on their assignment, enrolled children were directed either to the e-POCT or ALMANACH clinician. Compared to the IMCI-based algorithm (ALMANACH) used by study clinicians in the control arm, e-POCT uses fewer clinical symptoms and signs. Rather, it relies on signs that can be measured objectively: hypoxemia and severe tachycardia (oximeter), severe anemia (POC hemoglobinometer), hypoglycemia (POC glucometer), as well as host biomarkers of inflammation predictive of bacterial infection (elevated CRP using a rapid semi-quantitative lateral-flow test and elevated PCT using a POC immunoassay system). We chose ALMANACH, instead of the paper IMCI, as a control group, since ALMANACH is also built into an Android support tool: we were interested in comparing the impact related to the content of the algorithms rather than the format and technological features. In addition, since our goal was to reduce antibiotic prescription while ensuring optimal clinical patient outcome, and since a reduction in both antibiotic prescriptions and clinical failures using ALMANACH versus routine care has already been demonstrated, we regarded ALMANACH as the current gold standard in terms of antibiotic prescription and used it for the reference control arm [2]. In order to monitor routine care practice during the study, children were included in a routine care cohort in 2 participating health centers. After enrollment, patients were managed by routine clinicians. There was no intervention done, but we assured that essential laboratory tests and medicines were available at the health center. Rapid diagnostic testing for malaria was done for all patients (including in the routine care cohort) using either the SD BIOLINE Malaria Ag P.f/Pan (Standard Diagnostics) or CareStart Malaria HRP2 (Access Bio) assay. Other POCTs were performed on site as recommended by the algorithms (Figs ​(Figs1,1, ​,22 and S2; Table 1). Following Tanzanian national guidelines, voluntary screening for human immunodeficiency virus (HIV) antibodies using the Determine HIV-1/2 (Alere) was offered to all patients when HIV test kits were available at the health facilities. In the routine care cohort, voluntary screening was offered at the routine clinician’s discretion per standard practice. In the e-POCT arm, Hb measurement (HemoCue 201+ photometer) and oximetry (NONIN XPod with pediatric probe) were done in all patients. Children with clinical signs of lower respiratory tract infection (LRTI) (Table 1) underwent CRP testing to decide on antibiotic prescription for pneumonia. For children with FWS, the e-POCT algorithm uses combined CRP and PCT testing (Table 1). For CRP testing, we used a POC semi-quantitative assay (bioNexia CRPplus, Biomérieux). PCT values were determined on site using the B.R.A.H.M.S PCT assay on the miniVIDAS platform (Biomérieux, Thermo Scientific). Using ALMANACH, children less than 2 years with FWS underwent urine dipstick testing, as well as older children with dysuria (Table 1). Children 2 years or older with FWS were tested for typhoid using the Typhidot assay (Reszon Diagnostics International). All caregivers were asked to return with the child for scheduled visits on days 3 and 7, or at any time if the parent was concerned about the child’s condition. Patients cured at day 3 were followed up by phone only on day 7. Field workers traced patients missing the day 7 follow-up. For admitted patients, the scheduled visits were done in the hospital. Patients not cured (see definition below under “Outcomes”) before day 7 were treated again per the assigned algorithm, i.e., the e-POCT algorithm if they were part of the e-POCT arm or ALMANACH if in the control arm. Patients not cured before day 7 in the routine care cohort were treated at the routine clinician’s discretion. Patients not cured at day 7 were treated per the study clinician’s judgment, and another follow-up visit was performed at day 14 to assure that the child was cured. All patients were called by phone at day 30 to assess for severe adverse events (secondary outcome measure, see below). When the algorithm recommended referral (or a routine clinician decided to refer a patient), a field worker escorted the patient to the nearest referral hospital. Patients were then admitted (or discharged home) and managed at the discretion of the responsible medical doctor in the referral hospital. The primary outcome measure was the risk of clinical failure (Table 2) by day 7. At follow-up, clinicians recorded the variables that were used to calculate the criteria for clinical failure per Table 2 (the variables were either already part of the electronic algorithm assessment or otherwise recorded on paper forms). However, the clinicians were unaware of the study criteria for clinical failure and how the variables recorded were used to calculate study outcomes. The study outcomes were not used to decide on patient management. To guarantee equal assessments of the primary outcome in both arms, the following additional definition was applied: Patients were considered “not cured” and were treated again using the respective algorithm (or per the routine clinician) if either (i) the caregiver considered that the child was still ill or (ii) the child still had fever when assessed by trained field workers who did not know the content of the algorithms nor the criteria for clinical failure. The secondary outcome measures were the proportion of antibiotic prescriptions at day 0 and between day 1 and day 6, the proportion of primary referrals at day 0, and the proportion of severe adverse events (secondary hospitalizations and death) by day 30. 1Respiratory rate ≥ 97th percentile for age and temperature [20]. 2Heart rate ≥ 90th percentile for age and temperature [19]. 3Respiratory rate ≥ 60/min and age < 12 months or respiratory rate ≥ 50/min and age ≥ 12 months. 4Dehydration requiring facility-based treatment. 5≥3 liquid stools per day. 6Skin infection requiring systemic antibiotic treatment and/or facility-based treatment. SaO2, oxygen saturation. The sample size was computed for the primary analysis based on a 97.5% (1-sided) confidence interval (CI). To prove non-inferiority, the upper limit of this CI was to be within 3%. This non-inferiority margin was chosen because 3% was considered a clinically meaningful difference in clinical failure by day 7. The proportion of clinical failures by day 7 was estimated to be 10% in both arms based on prior studies using ALMANACH in the same area [2]. Assuming 80% statistical power, 3,140 patients were needed to show whether the difference in clinical failure by day 7 between the e-POCT and ALMANACH arms was within 3%. Interim analyses of clinical failure rates were performed after inclusion of the first 200 and 1,000 patients. A stopping rule was predefined for an absolute difference in clinical failure by day 7 of more than 5% between e-POCT and ALMANACH. Both intention-to-treat (ITT) and per-protocol (PP) study populations were defined. The ITT population comprised all randomized patients (or patients recruited into the routine care cohort); per definition, patients who were lost to follow-up were treated as clinical failures. The PP population included all randomized patients (or patients recruited into the routine care cohort) who received the intervention (or were attended by the routine clinician) and completed the day 7 assessment (Fig 3). “Not eligible” refers to patients who did not meet inclusion criteria or met exclusion criteria. Since this was a non-inferiority trial, and bias towards the null would tend to favor non-inferiority, we used a PP analysis as our primary analysis. Accordingly, all results are displayed according to PP analyses if not stated otherwise. Risk difference (RD) and risk ratio (RR) values with 95% CIs were calculated to estimate the intervention effects on the main study outcomes using the Stata cs procedure; associations between the interventions and outcomes were checked using the chi-squared test. Stratified analyses with Mantel–Haenszel estimates for RR were performed to explore the statistical heterogeneity of effect between health centers and clinicians [21]. For the primary outcome, mixed effects logistic regression was used to adjust for possible confounding covariates. Health center was modeled as a random effect, and clinician as a fixed effect. Additional predictors (age in months, weight-for-age z-score, body temperature, respiratory rate, heart rate, past medical history, and maternal education) were chosen based on clinical reasoning and were introduced into the model in a stepwise forward selection process. Predictors that were either a confounder or significantly related to the outcome were kept in the final model. Changes in odds ratio (OR) were used as approximated changes in RR since the primary outcome was rare. Kaplan–Meier survival analysis was used to compare the duration of fever between the 2 study arms.