跳至主要内容
临床试验/CTRI/2025/08/093506
CTRI/2025/08/093506尚未招募不适用

Intensivist Involvement in Indian ICU and Impact on outcome (5 I study)

Indian Society of Critical Care Medicine1 个研究点 分布在 1 个国家目标入组 1,000 人开始时间: 2025年9月10日最近更新:

试验速览

阶段
不适用
状态
尚未招募
入组人数
1,000
试验地点
1
主要终点
1. Quantification of Intensivist’s involvement in multiple ICUs at national level

研究概览

简要总结

Intensivist Involvement in Indian ICU and Impact on outcome 5 I study

 Background: Since “Leapfrog initiative” intensivist driven critical care with 7 days of the week, with

no other clinical duties in the ICU resulted in improved outcome.  Thereafter, most of the

published literature from developed world favored the intensivist based care and

multidisciplinary care in managing critically ill patients. However, some of the reports

challenged this school of thoughts. Some of the results are difficult to compare being

diversity bias in definition used. Often used are the three traditional models – open, transitional

or mandatory ICU consult and Closed. Variations like semi-closed or semi-open also exist but

are not well defined

Intent: Diversity in intensive care in India is higher than rest of the high middle- income and

developed world in many aspects. There are medical, surgical, mixed and super specialty ICU

with various degree intensivist involvement. How to best organize and deliver intensive care

with CCM as super specialty and scarcity of resources is a matter of debate. Patients

characteristics, infection pattern, infrastructure, intensivist’s involvement and role, processes and

standard of care are variable in various set ups.

Need of the study

Since inception of ICU in about 1950s, ICU bed strength over decades is going on increasing and

currently, due to increasing life expectancy and resources, the bed-strength is increasing to about

20 percent of the total hospital beds and is expected to rise to 50 percent in next decade. There are reports in

literature that suggest that trained intensivist coverage was associated with lower in-hospital and

1 year mortality rates. There are questions like type of critical care model focusing on

patient safety, cost effectiveness and utility, ICU beds per population density, proving high

quality care at the lowest costs etc.

Secondly, there is scarcity of resources to match the demand, even in the developed world, which

was very obvious during the COVID pandemic. Intensive care is highly demanding in terms

of both kinds of resources, man and material. ICU is a complex model of health care system

where most of resource utilization and expenditure takes place. So, we need to have the best

cost-effective or cost-utilization model. Health economic evaluations are increasingly common

in the critical care literature, and include highly qualified professional assistance, costly

equipment and economical gains are represented by patient outcome, as life and years saved.

In this national study, we hypothesize that intensivist based care leads to improved mortality and

other clinical outcome parameters and at the same time to find the best care model.

 Aims: To determine the effect of different levels of intensivist involvement models on clinical

outcomes for critically ill patients in Indian ICUs and to determine impact of the different

models of intensivist involvement on patient outcome and resource utilization.

 Primary objectives

  1. Quantification of Intensivist’s involvement in multiple ICUs at national level

  2. Impact on ICU discharge and hospital mortality with different degree of intensivist

involvement

Secondary objectives

  1. Life adjusted gain years

  2. LAMA patients’ characteristics analysis based on different ICU care model

Inclusion:

  1. Interested hospitals with minimal bed capacity of 10 ICU beds

  2. ICUs that routinely record mortality and nosocomial infection rates

Exclusion: Nil

Methodology

Design- Prospective, observational, multicenter

Duration of study: Discharge or death of the enrolled patients

Recruitment: Two-point recruitment one month apart for 5 specified days in each

session

Sample Size calculation

Risk reduction by 5 percent

Data collection: Data will be collected for minimum of 20 patients from each center. Two

random periods of 5 days will be selected in two successive months. Existing10 patients in each

session will be enrolled. APACHE II score and risk of mortality will be calculated within the 24

hours after ICU admission

Note: In India presently, there are more than 500 PG, DM and DNB seats in CCM and IDCCM, in

approximately 100 institutes. Even if we enroll 50percent, 50 institutes all over the country, 1000 patients.

 Data will be collected on pre-structured CRF that will be divide into 4 sections National survey

will be done through ICU Research Net or ISCCM portal for infrastructure and processes as

follows.

Part I- Personal information, once at the time of enrollment of Centre

 Part II- Infrastructure,once at the time of enrollment of Centre

Part III- Patient data, disease severity, APACHE-II score, procedures performed

Part IV- Outcome, number of deaths, number of LAMA, etc

Part B secondary objectives

All hospitals or institutes including teaching and nonteaching where DM, Dr NB, and ISCCM conducted

courses in Critical Care, will be approached via ICU Research Net. Administrative level of

involvement, care involvement, services level, consultant or resident based or mandatory or lead

type or service type.

Critical Nursing standards

Accreditation with national and international agencies. ICUs that are willing to

participate for outcome analysis will be enrolled further.

For this analysis, all included ICUs will be categorized into three groups.

Group I Closed ICU patient admitted under the ICU team and all decisions made by the ICU

team.

Group II Mandatory Critical Care Consultation patient remains admitted under primary

specialty but all patients in ICU are seen by the ICU team

Group III Open ICU or ICU managed by non-intensivist ICU physician and intensivist call on

SOS basis and decision given by primary consultant most of the times or no intensivist

involvement at all.

Subgroup analysis

Subgroup analyses of clinical outcomes will be also conducted.

Stratification into subgroups by

  1. Age

  2. Surgical Vs Non-Surgical

  3. SOFA Scores

  4. Super specialty vs Broad specialty eg A patient admitted under a physician for stroke

is broad specialty MD physician or super specialty,Neuro problem

  1. Type of hospital: Private vs General or University Affiliated vs non

The ICU discharge, mortality rates and in-hospital mortality rates, will be compared according to

these subgroups.

研究设计

研究类型
Observational

入排标准

年龄范围
18.00 Year(s) 至 90.00 Year(s)(—)
性别
All

入选标准

  • Hospitals with minimal 10 ICU bed capacity
  • ICUs that routinely record mortality and nosocomial infection rates.

排除标准

  • 未提供

结局指标

主要结局

1. Quantification of Intensivist’s involvement in multiple ICUs at national level

时间窗: Two-point recruitment one month apart for 5 specified days in each | session

2. Impact on ICU discharge and hospital mortality with different degree of intensivist

时间窗: Two-point recruitment one month apart for 5 specified days in each | session

involvement

时间窗: Two-point recruitment one month apart for 5 specified days in each | session

次要结局

  • 1. Life adjusted gain years(2. LAMA patients’ characteristics analysis based on different ICU care model)

研究者

申办方类型
Other [Non profit organization of experts in field of Critical Crae]
责任方
Principal Investigator
主要研究者

Dr Parshotam Lal Gautam

Dayanand Medical College and Hospital, Ludhiana

研究点 (1)

Loading locations...

相似试验