Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study Article Swipe
Morris Ogero
,
John Ndiritu
,
Rachel Sarguta
,
Timothy Tuti
,
Samuel Akech
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/hsr2.1433
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1002/hsr2.1433
Background and Aims Prognostic models provide evidence‐based predictions and estimates of future outcomes, facilitating decision‐making, patient care, and research. A few of these models have been externally validated, leading to uncertain reliability and generalizability. This study aims to externally validate four models to assess their transferability and usefulness in clinical practice. The models include the respiratory index of severity in children (RISC)‐Malawi model and three other models by Lowlavaar et al. Methods The study used data from the Clinical Information Network (CIN) to validate the four models where the primary outcome was in‐hospital mortality. 163,329 patients met eligibility criteria. Missing data were imputed, and the logistic function was used to compute predicted risk of in‐hospital mortality. Models' discriminatory ability and calibration were determined using area under the curve (AUC), calibration slope, and intercept. Results The RISC‐Malawi model had 50,669 pneumonia patients who met the eligibility criteria, of which the case‐fatality ratio was 4406 (8.7%). Its AUC was 0.77 (95% CI: 0.77−0.78), whereas the calibration slope was 1.04 (95% CI: 1.00 −1.06), and calibration intercept was 0.81 (95% CI: 0.77−0.84). Regarding the external validation of Lowlavaar et al. models, 10,782 eligible patients were included, with an in‐hospital mortality rate of 5.3%. The primary model's AUC was 0.75 (95% CI: 0.72−0.77), the calibration slope was 0.78 (95% CI: 0.71−0.84), and the calibration intercept was 0.37 (95% CI: 0.28−0.46). All models markedly underestimated the risk of mortality. Conclusion All externally validated models exhibited either underestimation or overestimation of the risk as judged from calibration statistics. Hence, applying these models with confidence in settings other than their original development context may not be advisable. Our findings strongly suggest the need for recalibrating these model to enhance their generalizability.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/hsr2.1433
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433
- OA Status
- gold
- Cited By
- 3
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386225799
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4386225799Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/hsr2.1433Digital Object Identifier
- Title
-
Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation studyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-01Full publication date if available
- Authors
-
Morris Ogero, John Ndiritu, Rachel Sarguta, Timothy Tuti, Samuel AkechList of authors in order
- Landing page
-
https://doi.org/10.1002/hsr2.1433Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433Direct OA link when available
- Concepts
-
Medicine, Generalizability theory, Logistic regression, Calibration, Case fatality rate, Statistics, Emergency medicine, Internal medicine, Epidemiology, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
44Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4386225799 |
|---|---|
| doi | https://doi.org/10.1002/hsr2.1433 |
| ids.doi | https://doi.org/10.1002/hsr2.1433 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/37645032 |
| ids.openalex | https://openalex.org/W4386225799 |
| fwci | 1.62515127 |
| type | article |
| title | Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study |
| biblio.issue | 8 |
| biblio.volume | 6 |
| biblio.last_page | e1433 |
| biblio.first_page | e1433 |
| topics[0].id | https://openalex.org/T11095 |
| topics[0].field.id | https://openalex.org/fields/27 |
| topics[0].field.display_name | Medicine |
| topics[0].score | 0.9993000030517578 |
| topics[0].domain.id | https://openalex.org/domains/4 |
| topics[0].domain.display_name | Health Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2711 |
| topics[0].subfield.display_name | Emergency Medicine |
| topics[0].display_name | Emergency and Acute Care Studies |
| topics[1].id | https://openalex.org/T10218 |
| topics[1].field.id | https://openalex.org/fields/27 |
| topics[1].field.display_name | Medicine |
| topics[1].score | 0.9940999746322632 |
| topics[1].domain.id | https://openalex.org/domains/4 |
| topics[1].domain.display_name | Health Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2713 |
| topics[1].subfield.display_name | Epidemiology |
| topics[1].display_name | Sepsis Diagnosis and Treatment |
| topics[2].id | https://openalex.org/T10654 |
| topics[2].field.id | https://openalex.org/fields/27 |
| topics[2].field.display_name | Medicine |
| topics[2].score | 0.9848999977111816 |
| topics[2].domain.id | https://openalex.org/domains/4 |
| topics[2].domain.display_name | Health Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2713 |
| topics[2].subfield.display_name | Epidemiology |
| topics[2].display_name | Pneumonia and Respiratory Infections |
| is_xpac | False |
| apc_list.value | 2200 |
| apc_list.currency | USD |
| apc_list.value_usd | 2200 |
| apc_paid.value | 2200 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2200 |
| concepts[0].id | https://openalex.org/C71924100 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7336297035217285 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q11190 |
| concepts[0].display_name | Medicine |
| concepts[1].id | https://openalex.org/C27158222 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5724728107452393 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q5532422 |
| concepts[1].display_name | Generalizability theory |
| concepts[2].id | https://openalex.org/C151956035 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5633291602134705 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q1132755 |
| concepts[2].display_name | Logistic regression |
| concepts[3].id | https://openalex.org/C165838908 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5441426634788513 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q736777 |
| concepts[3].display_name | Calibration |
| concepts[4].id | https://openalex.org/C187316915 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4336225986480713 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q92307203 |
| concepts[4].display_name | Case fatality rate |
| concepts[5].id | https://openalex.org/C105795698 |
| concepts[5].level | 1 |
| concepts[5].score | 0.3716525137424469 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[5].display_name | Statistics |
| concepts[6].id | https://openalex.org/C194828623 |
| concepts[6].level | 1 |
| concepts[6].score | 0.34711146354675293 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2861470 |
| concepts[6].display_name | Emergency medicine |
| concepts[7].id | https://openalex.org/C126322002 |
| concepts[7].level | 1 |
| concepts[7].score | 0.24479806423187256 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q11180 |
| concepts[7].display_name | Internal medicine |
| concepts[8].id | https://openalex.org/C107130276 |
| concepts[8].level | 2 |
| concepts[8].score | 0.24064528942108154 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q133805 |
| concepts[8].display_name | Epidemiology |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.11222970485687256 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| keywords[0].id | https://openalex.org/keywords/medicine |
| keywords[0].score | 0.7336297035217285 |
| keywords[0].display_name | Medicine |
| keywords[1].id | https://openalex.org/keywords/generalizability-theory |
| keywords[1].score | 0.5724728107452393 |
| keywords[1].display_name | Generalizability theory |
| keywords[2].id | https://openalex.org/keywords/logistic-regression |
| keywords[2].score | 0.5633291602134705 |
| keywords[2].display_name | Logistic regression |
| keywords[3].id | https://openalex.org/keywords/calibration |
| keywords[3].score | 0.5441426634788513 |
| keywords[3].display_name | Calibration |
| keywords[4].id | https://openalex.org/keywords/case-fatality-rate |
| keywords[4].score | 0.4336225986480713 |
| keywords[4].display_name | Case fatality rate |
| keywords[5].id | https://openalex.org/keywords/statistics |
| keywords[5].score | 0.3716525137424469 |
| keywords[5].display_name | Statistics |
| keywords[6].id | https://openalex.org/keywords/emergency-medicine |
| keywords[6].score | 0.34711146354675293 |
| keywords[6].display_name | Emergency medicine |
| keywords[7].id | https://openalex.org/keywords/internal-medicine |
| keywords[7].score | 0.24479806423187256 |
| keywords[7].display_name | Internal medicine |
| keywords[8].id | https://openalex.org/keywords/epidemiology |
| keywords[8].score | 0.24064528942108154 |
| keywords[8].display_name | Epidemiology |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.11222970485687256 |
| keywords[9].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.1002/hsr2.1433 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210188016 |
| locations[0].source.issn | 2398-8835 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2398-8835 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Health Science Reports |
| locations[0].source.host_organization | https://openalex.org/P4310320595 |
| locations[0].source.host_organization_name | Wiley |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320595 |
| locations[0].source.host_organization_lineage_names | Wiley |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Health Science Reports |
| locations[0].landing_page_url | https://doi.org/10.1002/hsr2.1433 |
| locations[1].id | pmid:37645032 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Health science reports |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/37645032 |
| locations[2].id | pmh:oai:pubmedcentral.nih.gov:10460931 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S2764455111 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | PubMed Central |
| locations[2].source.host_organization | https://openalex.org/I1299303238 |
| locations[2].source.host_organization_name | National Institutes of Health |
| locations[2].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[2].license | cc-by |
| locations[2].pdf_url | https://pmc.ncbi.nlm.nih.gov/articles/PMC10460931/pdf/HSR2-6-e1433.pdf |
| locations[2].version | submittedVersion |
| locations[2].raw_type | Text |
| locations[2].license_id | https://openalex.org/licenses/cc-by |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Health Sci Rep |
| locations[2].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/10460931 |
| locations[3].id | pmh:oai:doaj.org/article:47ab8a1152a7429ea6639104008b12ad |
| locations[3].is_oa | False |
| locations[3].source.id | https://openalex.org/S4306401280 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[3].source.host_organization | |
| locations[3].source.host_organization_name | |
| locations[3].license | |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | article |
| locations[3].license_id | |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Health Science Reports, Vol 6, Iss 8, Pp n/a-n/a (2023) |
| locations[3].landing_page_url | https://doaj.org/article/47ab8a1152a7429ea6639104008b12ad |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5034791930 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-0117-6289 |
| authorships[0].author.display_name | Morris Ogero |
| authorships[0].countries | GB, KE |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210089966 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine London United Kingdom |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I12859529 |
| authorships[0].affiliations[1].raw_affiliation_string | Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[0].institutions[0].id | https://openalex.org/I4210089966 |
| authorships[0].institutions[0].ror | https://ror.org/00a0jsq62 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I124357947, https://openalex.org/I4210089966 |
| authorships[0].institutions[0].country_code | GB |
| authorships[0].institutions[0].display_name | London School of Hygiene & Tropical Medicine |
| authorships[0].institutions[1].id | https://openalex.org/I12859529 |
| authorships[0].institutions[1].ror | https://ror.org/02y9nww90 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I12859529 |
| authorships[0].institutions[1].country_code | KE |
| authorships[0].institutions[1].display_name | University of Nairobi |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Morris Ogero |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine London United Kingdom, Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[1].author.id | https://openalex.org/A5014956602 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-9092-3172 |
| authorships[1].author.display_name | John Ndiritu |
| authorships[1].countries | KE |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I12859529 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[1].institutions[0].id | https://openalex.org/I12859529 |
| authorships[1].institutions[0].ror | https://ror.org/02y9nww90 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I12859529 |
| authorships[1].institutions[0].country_code | KE |
| authorships[1].institutions[0].display_name | University of Nairobi |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | John Ndiritu |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[2].author.id | https://openalex.org/A5071030326 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-7420-7045 |
| authorships[2].author.display_name | Rachel Sarguta |
| authorships[2].countries | KE |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I12859529 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[2].institutions[0].id | https://openalex.org/I12859529 |
| authorships[2].institutions[0].ror | https://ror.org/02y9nww90 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I12859529 |
| authorships[2].institutions[0].country_code | KE |
| authorships[2].institutions[0].display_name | University of Nairobi |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Rachel Sarguta |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Mathematics, University of Nairobi, Nairobi, Kenya |
| authorships[3].author.id | https://openalex.org/A5049810914 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-7915-3004 |
| authorships[3].author.display_name | Timothy Tuti |
| authorships[3].countries | KE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I2841861 |
| authorships[3].affiliations[0].raw_affiliation_string | Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Nairobi, Kenya |
| authorships[3].institutions[0].id | https://openalex.org/I2841861 |
| authorships[3].institutions[0].ror | https://ror.org/04r1cxt79 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I2841861, https://openalex.org/I87048295 |
| authorships[3].institutions[0].country_code | KE |
| authorships[3].institutions[0].display_name | Kenya Medical Research Institute |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Timothy Tuti |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Nairobi, Kenya |
| authorships[4].author.id | https://openalex.org/A5040869237 |
| authorships[4].author.orcid | https://orcid.org/0000-0001-5126-1225 |
| authorships[4].author.display_name | Samuel Akech |
| authorships[4].countries | KE |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I2841861 |
| authorships[4].affiliations[0].raw_affiliation_string | Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Nairobi, Kenya |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I12859529 |
| authorships[4].affiliations[1].raw_affiliation_string | School of Medicine, University of Nairobi, Nairobi, Kenya |
| authorships[4].institutions[0].id | https://openalex.org/I2841861 |
| authorships[4].institutions[0].ror | https://ror.org/04r1cxt79 |
| authorships[4].institutions[0].type | facility |
| authorships[4].institutions[0].lineage | https://openalex.org/I2841861, https://openalex.org/I87048295 |
| authorships[4].institutions[0].country_code | KE |
| authorships[4].institutions[0].display_name | Kenya Medical Research Institute |
| authorships[4].institutions[1].id | https://openalex.org/I12859529 |
| authorships[4].institutions[1].ror | https://ror.org/02y9nww90 |
| authorships[4].institutions[1].type | education |
| authorships[4].institutions[1].lineage | https://openalex.org/I12859529 |
| authorships[4].institutions[1].country_code | KE |
| authorships[4].institutions[1].display_name | University of Nairobi |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Samuel Akech |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme, Nairobi, Kenya, School of Medicine, University of Nairobi, Nairobi, Kenya |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11095 |
| primary_topic.field.id | https://openalex.org/fields/27 |
| primary_topic.field.display_name | Medicine |
| primary_topic.score | 0.9993000030517578 |
| primary_topic.domain.id | https://openalex.org/domains/4 |
| primary_topic.domain.display_name | Health Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2711 |
| primary_topic.subfield.display_name | Emergency Medicine |
| primary_topic.display_name | Emergency and Acute Care Studies |
| related_works | https://openalex.org/W2118717649, https://openalex.org/W410723623, https://openalex.org/W2413243053, https://openalex.org/W2015341305, https://openalex.org/W4225593417, https://openalex.org/W2035068594, https://openalex.org/W2059783833, https://openalex.org/W2573498121, https://openalex.org/W3160494304, https://openalex.org/W3039825081 |
| cited_by_count | 3 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 4 |
| best_oa_location.id | doi:10.1002/hsr2.1433 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210188016 |
| best_oa_location.source.issn | 2398-8835 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2398-8835 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Health Science Reports |
| best_oa_location.source.host_organization | https://openalex.org/P4310320595 |
| best_oa_location.source.host_organization_name | Wiley |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320595 |
| best_oa_location.source.host_organization_lineage_names | Wiley |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Health Science Reports |
| best_oa_location.landing_page_url | https://doi.org/10.1002/hsr2.1433 |
| primary_location.id | doi:10.1002/hsr2.1433 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210188016 |
| primary_location.source.issn | 2398-8835 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2398-8835 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Health Science Reports |
| primary_location.source.host_organization | https://openalex.org/P4310320595 |
| primary_location.source.host_organization_name | Wiley |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320595 |
| primary_location.source.host_organization_lineage_names | Wiley |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hsr2.1433 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Health Science Reports |
| primary_location.landing_page_url | https://doi.org/10.1002/hsr2.1433 |
| publication_date | 2023-08-01 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2196983317, https://openalex.org/W4206811881, https://openalex.org/W4200293663, https://openalex.org/W2146080983, https://openalex.org/W3032387069, https://openalex.org/W3092992705, https://openalex.org/W2154286581, https://openalex.org/W2019694480, https://openalex.org/W1994682257, https://openalex.org/W2106546096, https://openalex.org/W2126436234, https://openalex.org/W3014535943, https://openalex.org/W2082376914, https://openalex.org/W154377515, https://openalex.org/W1985002022, https://openalex.org/W2002504925, https://openalex.org/W1947115500, https://openalex.org/W2118798331, https://openalex.org/W2105800119, https://openalex.org/W2115013670, https://openalex.org/W2565595203, https://openalex.org/W2295243070, https://openalex.org/W2093274439, https://openalex.org/W2932020605, https://openalex.org/W2971016842, https://openalex.org/W2492762296, https://openalex.org/W2118953259, https://openalex.org/W2996480032, https://openalex.org/W2065974896, https://openalex.org/W2134843796, https://openalex.org/W2115098571, https://openalex.org/W2747990130, https://openalex.org/W2346747043, https://openalex.org/W3209694143, https://openalex.org/W2018195004, https://openalex.org/W2165139489, https://openalex.org/W6669451516, https://openalex.org/W621403667, https://openalex.org/W4386225799, https://openalex.org/W4207070571, https://openalex.org/W4225987334, https://openalex.org/W2074932800, https://openalex.org/W2605975631, https://openalex.org/W2318487091 |
| referenced_works_count | 44 |
| abstract_inverted_index.A | 20 |
| abstract_inverted_index.an | 195 |
| abstract_inverted_index.as | 248 |
| abstract_inverted_index.be | 269 |
| abstract_inverted_index.by | 68 |
| abstract_inverted_index.et | 70, 186 |
| abstract_inverted_index.in | 49, 60, 259 |
| abstract_inverted_index.of | 11, 22, 58, 114, 147, 184, 199, 233, 245 |
| abstract_inverted_index.or | 243 |
| abstract_inverted_index.to | 30, 38, 43, 83, 110, 281 |
| abstract_inverted_index.AUC | 156, 204 |
| abstract_inverted_index.All | 227, 236 |
| abstract_inverted_index.CI: | 160, 169, 178, 208, 216, 225 |
| abstract_inverted_index.Its | 155 |
| abstract_inverted_index.Our | 271 |
| abstract_inverted_index.The | 52, 73, 135, 201 |
| abstract_inverted_index.al. | 71, 187 |
| abstract_inverted_index.and | 2, 9, 18, 33, 47, 64, 104, 120, 132, 172, 218 |
| abstract_inverted_index.few | 21 |
| abstract_inverted_index.for | 277 |
| abstract_inverted_index.had | 138 |
| abstract_inverted_index.may | 267 |
| abstract_inverted_index.met | 97, 143 |
| abstract_inverted_index.not | 268 |
| abstract_inverted_index.the | 55, 78, 85, 89, 105, 127, 144, 149, 163, 181, 210, 219, 231, 246, 275 |
| abstract_inverted_index.was | 92, 108, 152, 157, 166, 175, 205, 213, 222 |
| abstract_inverted_index.who | 142 |
| abstract_inverted_index.(95% | 159, 168, 177, 207, 215, 224 |
| abstract_inverted_index.0.37 | 223 |
| abstract_inverted_index.0.75 | 206 |
| abstract_inverted_index.0.77 | 158 |
| abstract_inverted_index.0.78 | 214 |
| abstract_inverted_index.0.81 | 176 |
| abstract_inverted_index.1.00 | 170 |
| abstract_inverted_index.1.04 | 167 |
| abstract_inverted_index.4406 | 153 |
| abstract_inverted_index.Aims | 3 |
| abstract_inverted_index.This | 35 |
| abstract_inverted_index.aims | 37 |
| abstract_inverted_index.area | 125 |
| abstract_inverted_index.been | 26 |
| abstract_inverted_index.data | 76, 101 |
| abstract_inverted_index.four | 41, 86 |
| abstract_inverted_index.from | 77, 250 |
| abstract_inverted_index.have | 25 |
| abstract_inverted_index.need | 276 |
| abstract_inverted_index.rate | 198 |
| abstract_inverted_index.risk | 113, 232, 247 |
| abstract_inverted_index.than | 262 |
| abstract_inverted_index.used | 75, 109 |
| abstract_inverted_index.were | 102, 122, 192 |
| abstract_inverted_index.with | 194, 257 |
| abstract_inverted_index.(CIN) | 82 |
| abstract_inverted_index.5.3%. | 200 |
| abstract_inverted_index.care, | 17 |
| abstract_inverted_index.curve | 128 |
| abstract_inverted_index.index | 57 |
| abstract_inverted_index.model | 63, 137, 280 |
| abstract_inverted_index.other | 66, 261 |
| abstract_inverted_index.ratio | 151 |
| abstract_inverted_index.slope | 165, 212 |
| abstract_inverted_index.study | 36, 74 |
| abstract_inverted_index.their | 45, 263, 283 |
| abstract_inverted_index.these | 23, 255, 279 |
| abstract_inverted_index.three | 65 |
| abstract_inverted_index.under | 126 |
| abstract_inverted_index.using | 124 |
| abstract_inverted_index.where | 88 |
| abstract_inverted_index.which | 148 |
| abstract_inverted_index.(AUC), | 129 |
| abstract_inverted_index.10,782 | 189 |
| abstract_inverted_index.50,669 | 139 |
| abstract_inverted_index.Hence, | 253 |
| abstract_inverted_index.assess | 44 |
| abstract_inverted_index.either | 241 |
| abstract_inverted_index.future | 12 |
| abstract_inverted_index.judged | 249 |
| abstract_inverted_index.models | 5, 24, 42, 53, 67, 87, 228, 239, 256 |
| abstract_inverted_index.slope, | 131 |
| abstract_inverted_index.(8.7%). | 154 |
| abstract_inverted_index.163,329 | 95 |
| abstract_inverted_index.Methods | 72 |
| abstract_inverted_index.Missing | 100 |
| abstract_inverted_index.Models' | 117 |
| abstract_inverted_index.Network | 81 |
| abstract_inverted_index.Results | 134 |
| abstract_inverted_index.ability | 119 |
| abstract_inverted_index.compute | 111 |
| abstract_inverted_index.context | 266 |
| abstract_inverted_index.enhance | 282 |
| abstract_inverted_index.include | 54 |
| abstract_inverted_index.leading | 29 |
| abstract_inverted_index.model's | 203 |
| abstract_inverted_index.models, | 188 |
| abstract_inverted_index.outcome | 91 |
| abstract_inverted_index.patient | 16 |
| abstract_inverted_index.primary | 90, 202 |
| abstract_inverted_index.provide | 6 |
| abstract_inverted_index.suggest | 274 |
| abstract_inverted_index.whereas | 162 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Clinical | 79 |
| abstract_inverted_index.applying | 254 |
| abstract_inverted_index.children | 61 |
| abstract_inverted_index.clinical | 50 |
| abstract_inverted_index.eligible | 190 |
| abstract_inverted_index.external | 182 |
| abstract_inverted_index.findings | 272 |
| abstract_inverted_index.function | 107 |
| abstract_inverted_index.imputed, | 103 |
| abstract_inverted_index.logistic | 106 |
| abstract_inverted_index.markedly | 229 |
| abstract_inverted_index.original | 264 |
| abstract_inverted_index.patients | 96, 141, 191 |
| abstract_inverted_index.settings | 260 |
| abstract_inverted_index.severity | 59 |
| abstract_inverted_index.strongly | 273 |
| abstract_inverted_index.validate | 40, 84 |
| abstract_inverted_index.Lowlavaar | 69, 185 |
| abstract_inverted_index.Regarding | 180 |
| abstract_inverted_index.criteria, | 146 |
| abstract_inverted_index.criteria. | 99 |
| abstract_inverted_index.estimates | 10 |
| abstract_inverted_index.exhibited | 240 |
| abstract_inverted_index.included, | 193 |
| abstract_inverted_index.intercept | 174, 221 |
| abstract_inverted_index.mortality | 197 |
| abstract_inverted_index.outcomes, | 13 |
| abstract_inverted_index.pneumonia | 140 |
| abstract_inverted_index.practice. | 51 |
| abstract_inverted_index.predicted | 112 |
| abstract_inverted_index.research. | 19 |
| abstract_inverted_index.uncertain | 31 |
| abstract_inverted_index.validated | 238 |
| abstract_inverted_index.−1.06), | 171 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Conclusion | 235 |
| abstract_inverted_index.Prognostic | 4 |
| abstract_inverted_index.advisable. | 270 |
| abstract_inverted_index.confidence | 258 |
| abstract_inverted_index.determined | 123 |
| abstract_inverted_index.externally | 27, 39, 237 |
| abstract_inverted_index.intercept. | 133 |
| abstract_inverted_index.mortality. | 94, 116, 234 |
| abstract_inverted_index.usefulness | 48 |
| abstract_inverted_index.validated, | 28 |
| abstract_inverted_index.validation | 183 |
| abstract_inverted_index.Information | 80 |
| abstract_inverted_index.calibration | 121, 130, 164, 173, 211, 220, 251 |
| abstract_inverted_index.development | 265 |
| abstract_inverted_index.eligibility | 98, 145 |
| abstract_inverted_index.predictions | 8 |
| abstract_inverted_index.reliability | 32 |
| abstract_inverted_index.respiratory | 56 |
| abstract_inverted_index.statistics. | 252 |
| abstract_inverted_index.facilitating | 14 |
| abstract_inverted_index.0.28−0.46). | 226 |
| abstract_inverted_index.0.71−0.84), | 217 |
| abstract_inverted_index.0.72−0.77), | 209 |
| abstract_inverted_index.0.77−0.78), | 161 |
| abstract_inverted_index.0.77−0.84). | 179 |
| abstract_inverted_index.RISC‐Malawi | 136 |
| abstract_inverted_index.in‐hospital | 93, 115, 196 |
| abstract_inverted_index.recalibrating | 278 |
| abstract_inverted_index.discriminatory | 118 |
| abstract_inverted_index.overestimation | 244 |
| abstract_inverted_index.underestimated | 230 |
| abstract_inverted_index.(RISC)‐Malawi | 62 |
| abstract_inverted_index.case‐fatality | 150 |
| abstract_inverted_index.transferability | 46 |
| abstract_inverted_index.underestimation | 242 |
| abstract_inverted_index.evidence‐based | 7 |
| abstract_inverted_index.generalizability. | 34, 284 |
| abstract_inverted_index.decision‐making, | 15 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5034791930 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I12859529, https://openalex.org/I4210089966 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile.value | 0.79010239 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |