What is the clinical evidence from this study?

Study design: Observational. Population: General surgical admissions (n=11263). Intervention: Risk-stratified models using routine clinical data. Primary outcome: Mortality at discharge.

July 31, 2003British journal of surgeryOpen Access

Towards a national clinical minimum data set for general surgery

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Key result

Risk-stratified models using routine clinical data successfully stratified mortality risk into five or more bands for general surgical admissions.

Why the study?

Can effective risk-stratified models of mortality for general surgical admissions be constructed from routine clinical data?

Population

11,263 general surgical admissions

Design

Cohort

Follow-up

until discharge

Authors

DPDavid PrytherchUniversity of Portsmouth JSJ.S. SirlUniversity of Portsmouth PWP C WeaverUniversity of Portsmouth

Discussion

Member takes

Implication

Routine data-derived models enable surgical performance monitoring; leaves open prospective validation before widespread adoption.

Study Design

Type

Observational (n=11,263)

Structured PICO

Can effective risk-stratified models of mortality for general surgical admissions be constructed from routine clinical data?

Population

11,263 general surgical admissions over 2 years were used to generate mortality risk models, which were then applied prospectively to 3 years of subsequent data.

Exposure

Risk stratification models using routine clinical data (urea, haemoglobin, white blood cell count, sodium, potassium, age on admission, sex, BUPA Operative Severity Score)

Outcome

Mortality at dischargehard clinical

Effective mortality risk models for general surgical admissions can be constructed using routine clinical data, minimizing data collection burden.

Cite This Study

Prytherch et al. (2003) conducted an observational in General surgical admissions (n=11,263). Risk-stratified models using routine clinical data was evaluated on Mortality at discharge. Risk-stratified models using routine clinical data successfully stratified mortality risk into five or more bands for general surgical admissions.

synapsesocial.com/papers/6a6231a4cd947529a989bb86 https://doi.org/10.1002/bjs.4274

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July 31, 2003British journal of surgeryOpen Access

Towards a national clinical minimum data set for general surgery

View Full Paper

Ask AI

Bookmark

Key result

Risk-stratified models using routine clinical data successfully stratified mortality risk into five or more bands for general surgical admissions.

Why the study?

Can effective risk-stratified models of mortality for general surgical admissions be constructed from routine clinical data?

Population

11,263 general surgical admissions

Design

Cohort

Follow-up

until discharge

Authors

DPDavid PrytherchUniversity of Portsmouth JSJ.S. SirlUniversity of Portsmouth PWP C WeaverUniversity of Portsmouth

Discussion

Member takes

Implication

Routine data-derived models enable surgical performance monitoring; leaves open prospective validation before widespread adoption.

Study Design

Type

Observational (n=11,263)

Structured PICO

Can effective risk-stratified models of mortality for general surgical admissions be constructed from routine clinical data?

Population

11,263 general surgical admissions over 2 years were used to generate mortality risk models, which were then applied prospectively to 3 years of subsequent data.

Exposure

Risk stratification models using routine clinical data (urea, haemoglobin, white blood cell count, sodium, potassium, age on admission, sex, BUPA Operative Severity Score)

Outcome

Mortality at dischargehard clinical

Effective mortality risk models for general surgical admissions can be constructed using routine clinical data, minimizing data collection burden.

Cite This Study

synapsesocial.com/papers/6a6231a4cd947529a989bb86 https://doi.org/10.1002/bjs.4274

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

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