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Enregistrement W3049357420 · doi:10.4103/jacm.jacm_21_20

A survey of practices to diagnose, manage, prevent and control COVID-19 from 28 centres

2020· article· en· W3049357420 sur OpenAlexaboutno aff
Sasmita Hotta

Notice bibliographique

RevueJournal of The Academy of Clinical Microbiologists · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueCOVID-19 diagnosis using AI
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésGovernment (linguistics)Coronavirus disease 2019 (COVID-19)Health careMedicineConversationMedical educationFamily medicinePublic relationsPsychologyPolitical scienceDiseasePathology

Résumé

récupéré en direct d'OpenAlex

Introduction Coronavirus disease (COVID) caused by SARS-CoV-2 has emerged as a major public health problem in India as well globally.[1,2] Many authoritative guidelines and practice recommendations have been published. Despite the presence of multiple guidelines and government advisories, the actual situation or ground reality with regard to policies and practices are not well known. Understanding the real situation at COVID-testing centres and COVID-treating hospitals would give a much-needed insight and may help re-calibration of recommendations and make them more implementable. The objective of this article is to survey the actual practices regarding diagnosis, treatment and prevention of COVID in various healthcare facilities within India. Materials and Methods The survey was conducted in the months of May and June 2020 through an online questionnaire using Google Forms software which provided opportunities to participate in the survey and provide answers. The survey link was emailed to the microbiologists within the organisation, 'The Academy of Clinical Microbiologists', as well as microbiologists outside this organisation. The questions for the survey were selected by a panel of clinical microbiologists representing the editorial board of the Journal of Academy of Clinical Microbiologists. The answers to this survey were collated in an Excel format and duplicate answers, if any, from the same centre was excluded. If there were conflicting answers given by two respondents from the same centre, telephonic conversation was held to clarify ambiguities. Results Types of healthcare facilities and labs Altogether, 28 centres responded to the survey (27 from India and one from Abu Dhabi) [Figure 1]. This included 12/28 (42.86%) from the public sector (government institutions). Central government institutes were 4/28 (14.29%) of the total respondents and 8/28 (28.57%) were from state government medical colleges. Out of 16 private labs, 8 were from medical colleges. The total number of labs participating in the survey from medical college hospitals was 16/28 (57.14%). Eleven out of 28 healthcare facilities (39.29%) had a bed strength >1000; nine out of 28 (32.14%) had bed strength ranging from 200 to 500 beds, whereas, four centres each had bed strength between 0–200 and 500–1000 (14.29%). Ten laboratories out of the 28 (35.71%) had accreditation from the National Accreditation Board for Testing and Calibration Laboratories (NABL) for real-time polymerase chain reaction (RT-PCR) tests on RNA viruses. Out of these ten labs, only three were from the government sector. It was noted that in seven labs out of 28 (25.00%), efforts were on to get NABL accreditation for RT-PCR tests. In total, 17/28 (60.71%) centres were designated as COVID hospitals, out of which eight were from the government sector. Two hospitals were in the process of being designated COVID hospitals. Seven out of the 17 (41.18%) designated COVID hospitals had NABL accreditation for RT-PCR tests. Dedicated COVID unit(s) were present in 25 out of 28 centres (89.29%); among them 15/25 were from the private sector.Figure 1: State-wise distribution of the participantsLaboratory testing practices The survey revealed that COVID RT-PCR was being done in 18/28 labs (64.29%). This included 11 labs from public sector and 7 from private sector. Fifty per cent (9/18) of the labs performing the COVID tests had NABL accreditation. Seventeen out of the 18 (94.44%) healthcare facilities had designated COVID units within their organisation. It was noted that COVID-specific antibody tests were not currently done at any of the centres (0/28), however, five centres were in the process of initiating it. Out of the five, two of the centres responded that they planned to start using chemiluminescence/electro-chemiluminescence-based antibody testing systems (Architect Abbott Laboratories, Chicago; Ortho Clinical Diagnostics, USA; Roche, Switzerland). Cartridge-based nucleic acid amplification test (CBNAAT) for COVID was being done at 6/28 centres (21.43%), with two of them using Cepheid platform, while one mentioned the QIAsymphony 22 respiratory pathogen panel test. The survey showed that conventional PCR was being done at 19/28 centres (67.86%), with a combination of both manual and automated methods being used in 12/19 labs (63.16%); only automation was being used in 5/19 labs (26.32%) and manual method only in 2/19 labs (10.53%). Six of the 19 labs specified the RT-PCR platforms being used, namely Mylab kits at two centres, with others being ALTONA, TRUPCR, SEEGENE. Outsourcing of COVID tests was being carried out by 10/28 labs (35.71%), with two labs sending the samples out only for confirming with reference labs. Twenty-six centres out of 28 (92.86%) used an assay (either from their own lab or from an outsourced lab) that targeted the E gene by RT-PCR, with 21/28 (75.00%) centres using RDRP gene and nine centres using an assay for S gene detection (9/28 or 32.14%). All the three gene targets (E, RDRP and S) were used for detection by 8/28 labs (28.57%), with 19/28 using E and RDRP gene (67.86%) and 8/28 using E & S gene (28.57%). Other gene targets in SARS-CoV-2 used in detection included N2 in 4/28 (14.29% of labs) and ORF1 in 1/28 labs (3.57%). Clinical practices Pre-treatment screening was done at 20/28 centres (71.43%), with 12 centres using RT-PCR and five centres using CBNAAT for COVID screening. All symptomatic staff were being tested for COVID-19 irrespective of history at 8/28 centres (28.57%), with selective testing of staff based on a local policy at 18/28 centres (64.29%). COVID-19 was being tested in only severe acute respiratory illness (SARI) cases at 5 out of 28 centres (17.86%), with 9/28 centres (32.14%) testing in SARI and influenza-like illness (ILI) cases, 2/28 centres (7.14%) in SARI and healthcare-associated infection (HCAI) cases and SARI, ILI and HCAI cases all being tested by 12/28 centres (42.86%). The survey noted that hydroxychloroquine (HCQ) was used at 10/28 centres (35.71%). HCQ prophylaxis was used at 8/28 centres (28.57%), empirical HCQ treatment at 6/28 centres (21.43%), whereas use of HCQ for targeted therapy only in lab-confirmed cases of COVID at 10/28 centres (35.71%). Other anti-COVID drugs were being used at 15/28 centres (53.57%), with Azithromycin at 10/28 centres (35.71%) and Lopinavir-Ritonavir at 13/28 centres (46.43%). Two centres out of the 28 (7.14%) had started plasma therapy for the management of some of their COVID patients. Remdesivir was used in critically ill patients admitted to intensive care unit at only one centre. Infection prevention and control practices COVID test for asymptomatic contacts was done at 24/28 centres (85.71%), with majority (13/24) tested on day five and day 14 (54.17%); four centres (16.67%) tested only on day 14 and 7/24 (29.17%) centres tested only on day five after exposure. Patient isolation rooms were available at 22/28 centres (78.57%), with 12/28 (42.86%) having neutral pressure isolation rooms and 10/28 (35.71%) having negative-pressure isolation rooms [Figure 2]. Designated isolation rooms for sample collection were available at 24/28 centres (85.71%). Personal protective equipment (PPE) was available at all centres although it was in limited supply at two centres. PPEs for eye protective (either goggles or face shield) was available in all labs, gowns were available at 26/28 centres (92.86%) and full body PPE including cap and shoe cover were available at only one centre.Figure 2: Availability of isolation rooms in the participating hospitalsDiscussion A survey of diagnostic, therapeutic and infection prevention and control practices within the country is an essential component of learning, capacity building and review of policies protocols. This article aims to have a collective understanding about COVID-related processes and procedures within India so that individual and institutional practitioners may benefit from the survey report. A study from the Indian Council of Medical Research in the early days of the COVID pandemic reported that: 'Within a week of standardization of the test at National Institute of Virology, Pune, all Viral Research Diagnostic Laboratories could initiate testing for SARS-CoV-2'. The ICMR report also described that the quarantined individuals were tested twice – at days zero and 14.[1,3] In this study, we have not explored the question of capacity of individual labs with regard to maximum numbers that they could process per day by various RT-PCR platforms, but the geographical spread of the respondents suggest that COVID testing capability had expanded to various parts of the country. Surveys to review diagnostic practices in epidemic or pandemic situations are not new. Lee et al. in 2016 in connection with the Middle Eastern respiratory syndrome-associated coronavirus (MERS-CoV) reported from South Korea that most of the specimens sent for diagnosis by RT-PCR were sputum (73.5%). The median turnaround time (TAT) was 5.29 h in the 26 medical institutions covered in the survey.[4] RT-PCR-based techniques can be performed within a working day shift of eight h. This includes two–three h for RNA extraction, about thirty to sixty min for PCR set-up and two–three h for PCR and post-PCR analysis. CBNAAT systems are much faster and can deliver the results in about one hour. To reduce TAT, the following steps may be considered apart from CBNAAT technology: automation of RNA extraction, automation of PCR set up systems (e.g., automated liquid handling systems such as Qiagility, PCR equipment with faster ramp rate; kits with faster PCR cycle parameters, automation of post-PCR analysis and reporting using laboratory information system). It was reported that during the MERS pandemic many laboratories were able to perform tests throughout the whole week.[4] This is important from a public health point of view but requires reorganisation of human resources. Laboratory biosafety preparedness in MERS-CoV and SARS-CoV included Biosafety Level- 2 laboratories with class II biosafety cabinets. Generally, a separated pre-PCR, PCR, MasterMix preparation rooms are required for conventional real-time PCR systems; however, these requirements are changing because of CBNAAT technology.[4] Like MERS CoV, SARS CoV-2 requires ideally a negative pressure sample pre-treatment room for RNA extraction and ideally a negative pressure sputum/nose-throat swab sample collection room. Surveys on diagnostic practices in COVID also reveal interesting facts. A Canadian study reported that there was a wide variety of PCR instruments, reagents, PCR targets and reaction conditions used between the different diagnostic and commercial RT-PCR methods for the identification of SARS-CoV-2. Despite this variability, the limit of detection or analytical sensitivity of the PCR assay of the various laboratory-developed tests (LDTs) or home brew assays were between 3.4 and 4.5 log10 copies/mL (2511–31,622 copies/mL). Most commercial assays surveyed were equivalent to the home brew assays. This shows that with good quality control, it is possible for individual labs or reference labs with good molecular biology expertise to develop reliable diagnostic assays.[5] Similarly, a European consortium representing 87 labs from 23 countries reported that 45% of the surveyed labs had a test in place by 26 March, which is well into the first wave of the pandemic in most countries. Positive and negative controls (specificity panels) are essential for the development of home brew assays (LDTs). The European survey reported that the main implementation barriers for introduction of a SARS-CoV-2 molecular assay in European diagnostic laboratories were non-availability of positive controls and a specificity panel.[6] Our study revealed that more labs use imported kits than made-in-India kits. This reflects an urgent need to develop indigenous technology and make adequate provisions for seamless transfer of technology to the manufacturing companies. There is also a need to develop repository for quality control strains of viruses within India which are commercially available (e.g., National Institute for Biological Standards and Control, UK).[7] Knowledge, attitude and practice (KAP) are essential for any disease management, and COVID is not an exception. In India's neighbourhood, a study from Pakistan showed that healthcare workers had good knowledge (93%), a positive attitude (mean 8.43) and good practice (89%) regarding COVID-19. The attitude section in this study was assessed using responses to seven questions in a 5-point Likert scale (1, strongly agree; 2, agree; 3, undecided; 4, disagree; 5, strongly disagree). In addition, a study on healthcare workers in Pakistan perceived that limited infection control material and poor knowledge regarding transmission were the major barriers to infection control.[8] In a questionnaire-based survey, the awareness among healthcare students and professionals in Mumbai metropolitan region was assessed. It was noted that <50% of the total survey participants could correctly define 'close contact'. More than 75% of the responders were aware of the various infection control measures such as rapid triage, respiratory hygiene and cough etiquette and having a separate, well-ventilated waiting area for suspected COVID-19 patients. However, only 45% of the responders were aware of the correct sequence for the application of PPEs such as a mask/respirator, and only 53% of the responders were aware of the preferred hand hygiene method for visibly soiled hands.[9] For any capacity-building activity, emphasis on KAP is essential. The NABL accreditation of the labs, which was the requirement by the government for private labs for permission to provide COVID PCR services, ensures that staff are recruited after a proper assessment of qualification, skills, knowledge through interview, competency assessed periodically and standard operating procedures to ensure uniformity of practice are in place. In our study, 35% of the labs had NABL accreditation. A study from China, which covered 1070 specimens collected from 205 patients, reported virus detection from a variety of clinical specimens. In this survey, we did not elaborate on the sample types processed. Nose swab and throat swab in viral transport medium is the overwhelmingly common sample types processed. Bronchoalveolar lavage fluid specimens showed the highest positive rates (14 of 15; 93%) in this Chinese study, followed by sputum (72 of 104; 72%), nasal swabs (5 of 8; 63%), fibrobronchoscope brush biopsy (6 of 13; 46%), pharyngeal swabs (126 of 398; 32%), faeces (44 of 153; 29%) and blood (3 of 307; 1%). Interestingly, none of the 72 urine specimens tested positive for SARS-CoV-2. The mean cycle threshold (Ct) values of all specimen types were more than 30 (<2.6 × 104 copies/mL) except for nasal swabs with a mean Ct value of 24.3 (1.4 × 106 copies/mL), indicating higher viral loads in nasopharyngeal samples. Live SARS-CoV-2 was observed in the stool sample from two patients who did not have diarrhoea.[10] The above findings are important as they show that various samples have different positivity rates and viral loads. While we deal with samples from COVID positive patients be it for other microbiology investigations (bacteriology or mycology) or for other lab investigations (haematology, chemistry and cytology), the possibility of non-respiratory samples having SARS-CoV-2 needs to be remembered and appropriate measures taken to mitigate the risk. The evidence regarding the efficacy of HCQ in COVID has been equivocal at best and negative in recent meta-analyses. In the meta-analysis by Sarma et al. it was reported that treatment with HCQ resulted in a smaller number of cases, showing the radiological progression of lung disease. No difference was observed in virological cure or death, and safety, when compared with the control/conventional treatment. However, the meta-analysis by Singh et al. reported no benefit on viral clearance but a significant increase in mortality with HCQ-treated group compared to control in patients with COVID-19.[11,12] A recent review by the Oxford Centre for evidence-based medicine concluded that as HCQ and macrolide antibiotics can prolong the QT interval in electrocardiogram, combining these treatments increases this risk and the combination should be used with extreme caution and only when the advantages outweigh the disadvantages.[13] In our study, we found that HCQ was used as an empirical treatment at 21% of the centres and for targeted therapy at 35% of the centres. Only 28% of the centres used HCQ for prophylactic purposes. This shows that majority of the centres are not using HCQ for therapeutic reasons. This could be a reflection of the facts till date from the meta-analysis. Remdesivir was recently issued the Emergency Use Authorization (EUA) on one May 2020, by the Food and Drug Administration for its compassionate use in critically ill COVID-19 patients. Pre-clinical studies showed significant reduction in viral load in both prophylactic and therapeutic use against SARS-CoV, making it a viable option for therapy in the future. Studies and case reports show varying response to its use, in both virological and clinical cure, although there were fewer adverse effects and better tolerability to the dosage regimen. The major for its use to clinical studies is the limited and which needs to be to its In our study, only one centre reported the use of Remdesivir in critically ill patients. The of this which was 200 on day followed by for a total of ten has been as one of the significant effects of The of Remdesivir is for a of RT-PCR is essential for the detection of the of in COVID diagnosis is being A meta-analysis by et al. which and antibody tests on samples tests based on assay and the provided important about the of assays in the detection of to SARS-CoV-2. The study at studies from The meta-analysis concluded that the tests using the S were more than assays. tests performed better than tests in of when samples were taken antibody was five to days for and days for at the of and antibody it was that a test was a better in of sensitivity than antibody All methods specificity with and having to clinical the by the two participating centres to start SARS-CoV-2 using these and methods performed better in of sensitivity followed by and with ranging from to In our study, of the centres were the possibility of the antibody tests. This is in view of its and value in the clinical tests not tests. It value to diagnosis through some information in of exposure. In this we have through a questionnaire-based survey the different practices in the management of COVID pandemic from 28 centres spread 11 of India as well as one from Abu [Figure 1]. The major findings of the survey have use of the conventional RT-PCR as the main for COVID testing with as the most preferred RT-PCR centres antibody tests for assessment of COVID majority of the centres not using HCQ for treatment of majority of the centres not using HCQ as a against majority of the centres did not have a negative-pressure isolation room for COVID patients. have noted of diagnostic practices and facilities for isolation [Figure 2]. have also the to the this we that clinical laboratory and infection control would get an about that this and capacity NABL accreditation to labs to initiate SARS-CoV-2 (either by molecular the to facilities and equipment during such and between laboratory and clinical are essential in and this COVID management requires and at the and There is a need to to quality control of testing processes and clinical and infection control policies in the of changing clinical evidence and government This study shows that the there is a of uniformity and of It is that this is because of the of by government and 1: from 28 individual laboratories – coronavirus disease and and of There are no of

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,026

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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.

Tête enseignante Opus0,215
Tête enseignante GPT0,480
Écart entre enseignants0,266 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

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Publié2020
Routes d'admission1
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Même revueJournal of The Academy of Clinical MicrobiologistsMême sujetCOVID-19 diagnosis using AITravaux en français237 207