The Use of Wireless, Smartphone App–Assisted Home Blood Pressure Monitoring Among Hypertensive Patients in Singapore: Pilot Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Reliable home blood pressure monitoring (HBPM) is essential to effective hypertension management; however, manual recording is subject to underreporting and inaccuracies. Mobile health technologies hold great potential as HBPM tools, but the fidelity of a smartphone app in HBPM has not been adequately assessed. OBJECTIVE: The primary aim of the trial was to compare the fidelity of a smartphone app to that of a handwritten logbook in making HBPM data available to clinicians at follow-up visits. Fidelity was defined as the percentage of scheduled blood pressure (BP) recordings over a 3-week period that were properly recorded and reported to the clinic. The secondary aims were to investigate patient factors associated with HBPM fidelity and to explore the effect of time on the fidelity. METHODS: A 2-arm, parallel, unblinded, randomized controlled pilot trial was conducted in a government polyclinic in Singapore. Hypertensive adults, aged 40 to 70 years, who were on antihypertensive medication and owned a smartphone were recruited and randomized by a computer-generated randomization schedule to 3 weeks of either semiautomated HBPM utilizing a Bluetooth-enabled BP monitor and a smartphone app or a fully manual process utilizing a conventional handwritten logbook. The primary outcome was home BP recording fidelity. RESULTS: Of the 80 patients randomized, 79 (smartphone app: 38 and logbook: 41) were included in the final analysis. Although fidelity was higher among the app users, it did not differ significantly between study arms (smartphone app: 66.7% and logbook: 52.4%; P=.21). Chinese and Indian ethnicities were associated with higher fidelity (absolute percent and 95% CI) by 35.6% (4.27 to 66.9) and 45.0% (8.69 to 81.3), respectively, in comparison with other ethnicities (P=.03); longer smartphone ownership increased fidelity on an average of 10.5% (0.83 to 20.2) per year (P=.03); the number of apps on the smartphone decreased fidelity at a rate of -0.32% (-0.58 to -0.05) per app (P=.02); years of hypertension morbidity increased fidelity at a rate of 1.56% (0.03 to 3.09) per year (P=.046); and the number of people working in the household decreased fidelity at a rate of -8.18% (-16.3 to -0.08) per additional working person (P=.048). The fidelity of the app was significantly higher in the first week (64.4%) than the second (55.1%, P=.001) and third (58.2%, P=.03) weeks of monitoring. CONCLUSIONS: Amid the increasing integration of health technologies into clinical practice, our study demonstrates the feasibility of smartphone app-assisted HBPM in hypertensive adults of Singapore. Our pilot study found no statistically significant difference in mean BP recording fidelity between a smartphone app and conventional handwritten logbook. However, the small sample size precludes definitive conclusions and highlights the need for a larger, adequately powered trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03209024; https://clinicaltrials.gov/ct2/show/NCT03209024 (Archived by WebCite at http://www.webcitation.org/78EVWBg0T).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».